attached
This is a more interactive assignment that requires you to do some hands on interaction.
1. Using the internet, find examples of various sensory phenomena.
Find one picture or more that demonstrates each of the following:
· use of complementary colours to increase contrast
· colour aftereffects used correctly
· colour aftereffects used incorrectly
Copy and paste the picture(s) into your assignment and write a brief explanation of what is demonstrated in each.
2. Find a painting (or paintings) that illustrates the use of monocular/pictorial depth cues. If it is a well-known painting, identify it by name and artist. Otherwise, scan a picture of it or provide a link in your assignment. Point out all the different cues the artist used. The more examples you can find within your painting, the better you will do.
3. Draw a picture and trace the path a sound stimulus has to take as it travels through the outer ear, middle ear, and inner ear.
4. Follow the instructions for Aristotle’s Illusion from ISLE 1.5. Describe your experience. Why do you think this illusion occurs?
5. Get four friends and a minimum of four different flavours of juices, such as grape, orange, cranberry, and others. You will also need an eyedropper and cups that do not allow the juice to be seen through the cup. Have the friend close their nose, place a drop of the juice on their tongue, and ask them to identify it. Then repeat the task with their nose open and again ask them to identify the juice. Keep careful track of whether they are correct or not. Are they better with their nose open or closed? Are there juices that are identified more easily with their nose closed?
See if you can explain your results.
Repeat the same experiment, but this time find a minimum of four different foods and spices with distinct smells (e.g., banana, apple, strawberry, chocolate, garlic, cinnamon, cheese, ginger, vinegar) making sure your friends don’t know which smells you will expose them to ahead of time.
Make sure they are blindfolded and can’t see what is being put in front of them. Keep track of their guesses (and what they are saying), but also keep track of the facial expressions they make and how long it takes them to guess.
Write up your results in report form and briefly discuss our ability to recognize tastes and smells without any visual stimuli to help. Feel free to use references/resources to back up your answer.
See the Assignment Schedule for the due date.
Submit using the Dropbox.
https://isle.hanover.edu/isle2/Ch01Intro/Ch01Aristotle.html
2. Follow the instructions for Aristotle’s Illusion from ISLE 1.5. Describe your experience. Why do you think this illusion occurs?
Praise for
“This book gives students the advantage of
having access to a lot of resources and
ENGAGING ACTIVITIES that will help them
understand the concepts as they read each
chapter in the text.”
—Nicha K. Otero, University of Arkansas—Fort Smith
“This is an EXCELLENT TEXTBOOK for an
undergraduate class in sensation and
perception. The textbook covers all the
important topics in the field. The authors
include a good mix of classic research and
recent research. The chapters are well
written and well organized. Students will
enjoy learning from this book.”
—Robert Hines, University of Arkansas, Little Rock
“The CLARITY OF WRITING makes this product
very reader friendly.”
—T. C. Sim, Sam Houston State University
“The application sections are interesting and
allow students to see how what they are
learning is RELEVANT TO THE REAL WORLD.”
—Alexis Grosofsky, Beloit College
“This text is EASY TO READ, includes examples
that are relevant to your life, covers all the
essential information for a course in
sensation and perception.”
—Jennifer L. Thomson, Messiah College
“The INTERACTIVE NATURE of these [ISLE]
activities is great for student learning. The
function of emailing themselves their action
plan is also useful for student organization.
Flashcards are great for revision and
checking on knowledge. I think these
resources will be used a lot by the students.”
—Sue Wilkinson, Cardiff Metropolitan University
Sara Miller McCune founded SAGE Publishing in 1965 to support
the dissemination of usable knowledge and educate a global
community. SAGE publishes more than 1000 journals and over
800 new books each year, spanning a wide range of subject areas.
Our growing selection of library products includes archives, data,
case studies and video. SAGE remains majority owned by our
founder and after her lifetime will become owned by a charitable
trust that secures the company’s continued independence.
Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne
Florida International University Hanover College
Copyright © 2019 by SAGE Publications, Inc.
All rights reserved. No part of this book may be reproduced or utilized in any form or
by any means, electronic or mechanical, including photocopying, recording, or by
any information storage and retrieval system, without permission in writing from the
publisher.
Illustrations provided by Auburn Associates and Body Scientific International, LLC.
Special thanks to Carolina Hrejsa, Senior Medical Illustrator of Body Scientific
International.
Printed in the United States of America
Library of Congress Cataloging-in-Publication Data
Names: Schwartz, Bennett L., author. | Krantz, John H., author.
Title: Sensation and perception / Bennett L. Schwartz, Florida International University,
John H. Krantz, Hanover College.
Description: Los Angeles : SAGE, [2019] | Includes bibliographical references and index.
Identifiers: LCCN 2017040166 | ISBN 9781506383910 (hardcover : alk. paper)
Subjects: LCSH: Senses and sensation. | Perception.
Classification: LCC QP430 .S334 2019 | DDC 612.8—dc23
LC record available at https://lccn.loc.gov/2017040166
This book is printed on acid-free paper.
18 19 20 21 22 10 9 8 7 6 5 4 3 2 1
FOR INFORMATION:
SAGE Publications, Inc.
2455 Teller Road
Thousand Oaks, California 91320
E-mail: order@sagepub.com
SAGE Publications Ltd.
1 Oliver’s Yard
55 City Road
London EC1Y 1SP
United Kingdom
SAGE Publications India Pvt. Ltd.
B 1/I 1 Mohan Cooperative Industrial Area
Mathura Road, New Delhi 110 044
India
SAGE Publications Asia-Pacific Pte. Ltd.
3 Church Street
#10-04 Samsung Hub
Singapore 049483
Acquisitions Editor: Abbie Rickard
Content Development Editor: Emma Newsom
Editorial Assistant: Jennifer Cline
Production Editor: Jane Haenel
Copy Editor: Colleen Brennan
Typesetter: C&M Digitals (P) Ltd.
Proofreader: Scott Oney
Indexer: Sheila Bodell
Cover and Interior Designer: Scott Van Atta
Marketing Manager: Jenna Retana
ISLE Activities xvi
Preface xxii
Acknowledgments xxvii
About the Authors xxix
1 WHAT IS PERCEPTION? …………………………………………………1
2 RESEARCH METHODOLOGY ………………………………………….27
3 VISUAL SYSTEM: THE EYE ……………………………………………53
4 VISUAL SYSTEM: THE BRAIN ………………………………………..91
5 OBJECT PERCEPTION ………………………………………………..123
6 COLOR PERCEPTION ………………………………………………….151
7 DEPTH AND SIZE PERCEPTION …………………………………….187
8 MOVEMENT AND ACTION …………………………………………..227
9 VISUAL ATTENTION ………………………………………………….255
10 THE AUDITORY SYSTEM …………………………………………….289
11 THE AUDITORY BRAIN AND SOUND LOCALIZATION ………….317
12 SPEECH PERCEPTION ………………………………………………..341
13 MUSIC PERCEPTION ………………………………………………….371
BRIEF CONTENTS
istockphoto.com
14 TOUCH AND PAIN …………………………………………………….401
15 OLFACTION AND TASTE ……………………………………………..435
Glossary 461
References 475
Author Index 493
Subject Index 500
DETAILED CONTENTS
ISLE Activities, xvi
Preface, xxii
Acknowledgments, xxvii
About the Authors, xxix
1 WHAT IS PERCEPTION? …………………….. 1
Introduction, 1
Why Is This Psychology? 3
The Myth of Five Senses, 4
The Basics of Perception, 5
Action, 8
The Nature of Experience
and Phenomenology, 8
The History of Sensation and Perception, 9
The Beginnings, 10
Helmholtz Versus Hering, 11
Weber, Fechner, and the Birth
of Psychophysics, 12
The 20th Century and the Study
of Perception: Cognitive
Psychology Approaches, 13
Gestalt Psychology, 13
Direct Perception (The Gibsonian
Approach), 15
Information-Processing Approach, 15
Computational Approach, 16
Neuroscience in Sensation and Perception, 17
Exploration: Cognitive Penetration, 19
Application: Avoiding Collisions, 21
Chapter Summary, 23
Review Questions, 23
Ponder Further, 24
Key Terms, 24
2 RESEARCH METHODOLOGY ……………… 27
Introduction, 27
The Measures and Methods
of Psychophysics, 29
Method of Limits, 29
Method of Constant Stimuli, 32
Method of Adjustment, 33
Magnitude Estimation, 34
Catch Trials and Their Use, 35
Signal Detection Theory, 36
Neuroimaging Techniques, 42
Exploration: Intersensory
Perception, 44
Application: Psychophysics in
Assessment: Hearing Tests
and Vision Tests, 45
Chapter Summary, 49
Review Questions, 50
Ponder Further, 50
Key Terms, 50
3 VISUAL SYSTEM: THE EYE ………………. 53
Introduction, 53
Light, 55
The Eye and Its Role in
the Visual System, 57
Field of View, 58
Anatomy of the Eye, 58
The Cornea, 59
The Lens, 60
Development: The Emerging
and Aging Eye, 61
The Retina, 62
Anatomy of the Retina, 63
The Receptors: Rods
and Cones, 64
Retinal Physiology, 65
Transduction of Light, 66
Classes of Receptors, 68
The Duplex Theory of Vision, 68
Spectral Sensitivity and the
Purkinje Shift, 69
Spatial Summation and Acuity, 70
Dark and Light Adaptation, 70
Development: Infant Acuity, 72
Retinal Ganglion Cells and
Receptive Fields, 73
Refractive Errors and Diseases
of the Eye, 77
Myopia (Nearsightedness), 78
Hyperopia (Farsightedness) and
Presbyopia (Old-Sightedness), 78
Astigmatism, 79
Cataracts, 80
Macular Degeneration, 80
Retinitis Pigmentosa, 80
Exploration: Animal Eyes, 82
Cats, 82
Nautiluses, 83
Application: Vision Prostheses, 85
Chapter Summary, 86
Review Questions, 87
Ponder Further, 88
Key Terms, 88
4 VISUAL SYSTEM: THE BRAIN …………… 91
Introduction, 91
The Optic Nerve and Chiasm, 92
The Lateral Geniculate Nucleus, 94
Processing in the LGN, 97
The Superior Colliculus, 98
The Primary Visual Cortex, 99
Mapping the Eye on the Brain, 101
Receptive Fields of V1 Cells, 102
Simple Cells, 103
Complex Cells and V1 Responses
to Visual Features, 103
The Organization of V1, 104
V2 and Beyond, 106
V2, 106
Functional Pathways in the
Visual Cortex, 107
The Ventral Pathway, 109
The Dorsal Pathway, 110
Where Does Vision Come Together? 111
Development of the Visual System, 111
Exploration: Blindsight, 113
Application: Conjugate Gaze Palsy, 116
Chapter Summary, 117
Review Questions, 119
Ponder Further, 119
Key Terms, 119
5 OBJECT PERCEPTION …………………….. 123
Introduction, 123
Introduction to Object Perception, 124
Top-Down Processing and Bottom-Up
Processing, 126
Recognition and Representation, 127
Perceptual Organization, 128
Gestalt Psychology and Perceptual
Organization, 128
Figure–Ground Organization, 129
A Few Rules That Govern What
We See as Figure and What
We See as Ground, 131
Gestalt Laws of Perceptual
Grouping, 132
Perceptual Interpolation, 134
Recognition by Components, 136
The Neuroanatomy and Physiology
of Object Perception, 137
Representation of Shapes in Area V4, 137
Object Recognition in the
Inferotemporal Area, 137
The Fusiform Face Area and
Face Recognition, 138
Prosopagnosia, 139
Other Inferotemporal Cortex
Areas With Specific Object
Recognition Functions, 140
Grandmother Cells and Specific Coding
in the Inferotemporal Cortex, 140
Exploration: Vision and Animacy: How
Do We Tell a Who From a What? 143
Application: The Science of
Airport Screening, 145
Chapter Summary, 147
Review Questions, 148
Ponder Further, 148
Key Terms, 148
6 COLOR PERCEPTION …………………….. 151
Introduction, 151
Wavelengths of Light and Color, 153
Hue, Saturation, Lightness,
and Brightness, 155
Additive and Subtractive Color Mixing, 156
Additive Color Mixing (Mixing Lights), 157
Subtractive Color Mixing
(Mixing Paints), 158
Color-Matching Experiments, 158
The Retina and Color, 160
Univariance, or Why More Than
One Receptor Is Necessary
to See in Color, 161
The Trichromatic Theory of Color Vision, 162
The Opponent-Process Theory
of Color Perception, 163
Findings That Support Opponent-
Process Theory, 164
Hue Cancellation, 165
Opponent Cells in the LGN and V1, 166
The Development of Color Perception, 168
Color Perception in Infancy, 168
Aging and Color Perception, 169
Color Deficiency, 169
Rod Monochromacy, 171
Cone Monochromacy, 171
Dichromacy, 172
Protanopia, 172
Deuteranopia, 172
Tritanopia, 173
Cortical Achromatopsia, 174
Constancy: Lightness and
Color Constancy, 175
Color Constancy, 175
Lightness Constancy, 177
Exploration: The Color Purple, 178
Application: Color Deficiency and
Our Colorful Information, 180
Chapter Summary, 181
Review Questions, 182
Ponder Further, 183
Key Terms, 183
7 DEPTH AND SIZE PERCEPTION ……….. 187
Introduction, 187
Monocular Depth Cues, 189
Occlusion (or Interposition), 190
Relative Height, 191
Relative Size, 191
Familiar Size, 192
Linear Perspective, 193
Texture Gradients, 194
Atmospheric Perspective, 194
Shadows and Shading, 195
Motion Cues, 196
Motion Parallax, 196
Deletion and Accretion, 197
Optic Flow, 198
Oculomotor Cues, 199
Accommodation, 199
Vergence (or Convergence), 199
Binocular Cues to Depth, 200
Binocular Disparity, 201
Corresponding and
Noncorresponding Points, 202
The Correspondence
Problem, 206
Stereograms, 207
Random-Dot Stereograms, 208
The Anatomy and Physiology
of Binocular Perception, 209
Developmental Issues in
Stereopsis, 210
Size Perception, 211
Size Constancy, 212
Visual Illusions of Size
and Depth, 213
The Müller–Lyer Illusion, 214
The Ponzo Illusion, 215
The Ames Room Illusion, 215
The Moon Illusion, 216
Exploration: Stereopsis and Sports: Do We
Need Binocular Vision in Sports? 218
Application: Virtual Reality
and Therapy, 219
Chapter Summary, 222
Review Questions, 223
Ponder Further, 223
Key Terms, 223
8 MOVEMENT AND ACTION ……………… 227
Introduction, 227
How Do We Perceive Motion? 228
Motion Thresholds: How Slow
and How Fast? 228
Real and Apparent Motion, 230
The Neuroscience of Vision
and Motion, 232
Motion Detection in the Retina, 232
The Complexity of Motion, 232
Corollary Discharge Theory, 234
Eye Movements, 235
Saccades, 236
Smooth-Pursuit Eye Movements, 236
MT: The Movement Area of
the Brain, 236
Motion Aftereffects, 239
Form Perception and Biological
Motion, 241
Action, 242
Visually Guided Eye Movements, 244
Visually Guided Grasping, 245
Exploration: Motion Illusions, 246
Illusion 1: Rotating Snakes, 247
Illusion 2: Illusory Rotation, 248
Illusion 3: The Furrow Illusion, 248
Application: Motion Perception
in Airplane Pilots, 249
Chapter Summary, 251
Review Questions, 251
Ponder Further, 252
Key Terms, 252
9 VISUAL ATTENTION ……………………… 255
Introduction, 255
Selective Attention, 258
Spatial Limits of Attention, 259
Attention and the Direction of
Gaze in Space, 259
Inattentional Blindness, 262
Stimulus Features That Draw Attention, 264
Stimulus Salience, 265
Visual Search, 266
Feature Integration Theory, 267
Attention Over Time, 268
Change Blindness, 268
Attentional Blink and Rapid Serial
Visual Presentation, 270
The Anatomy and Physiology
of Attention, 272
The Orienting Attention Network, 273
The Executive Attention Network, 273
How Attention Affects the
Visual Brain, 274
The Neuropsychology of Attention, 275
Bálint’s Syndrome, 277
Developmental Aspects of
Visual Attention, 278
Exploration: Awareness and
Visual Consciousness, 279
Perceptual Bistability, 280
Blindsight, 281
Application: Distracted Driving, 282
Chapter Summary, 284
Review Questions, 285
Ponder Further, 285
Key Terms, 286
10 THE AUDITORY SYSTEM ……………….. 289
Introduction, 289
Sound as Stimulus, 290
The Relation of Physical and Perceptual
Attributes of Sound, 292
Amplitude and Loudness, 292
Frequency and Pitch, 294
Waveform and Timbre, 295
Phase, 297
Anatomy of the Ear, 298
The Outer Ear, 298
The Middle Ear, 299
The Inner Ear, 301
The Basilar Membrane of the Cochlea, 302
The Organ of Corti, 304
Exploration: Hearing Loss, 306
Conductive Hearing Loss, 307
Sensorineural Hearing Loss, 307
Tinnitus, 308
Application: The Science of Hearing
Aids and Cochlear Implants, 308
Hearing Aids, 308
Cochlear Implants, 310
Chapter Summary, 311
Review Questions, 312
Ponder Further, 313
Key Terms, 313
11 THE AUDITORY BRAIN AND SOUND
LOCALIZATION …………………………..317
Introduction, 317
Brain Anatomy and the Pathway
of Hearing, 318
Auditory Nerve Fibers, 318
Auditory Cortex, 320
Localizing Sound, 321
Interaural Time Difference, 322
Interaural Level Difference, 324
The Cone of Confusion, 324
Elevation Perception, 325
Detecting Distance, 325
Auditory Scene Analysis, 326
Temporal Segregation, 328
Spatial Segregation, 329
Spectral Segregation, 329
Auditory Development, 330
Exploration: Biosonar in Bats
and Dolphins, 331
Application: Concert Hall
Acoustics and Hearing, 335
Chapter Summary, 336
Review Questions, 337
Ponder Further, 337
Key Terms, 338
12 SPEECH PERCEPTION ……………………. 341
Introduction, 341
The Human Voice as Stimulus, 342
Vowels and Consonants, 343
Speech, 344
Variability in the Acoustics of Phonemes, 347
Coarticulation, 348
Categorical Perception, 349
The Effect of Vision on Speech Perception
and the McGurk Effect, 351
Top-Down Processing and
Speech Perception, 352
The Phonemic Restoration Effect, 353
Theories of Speech Perception, 355
The Development of Phoneme
Perception, 357
Speech Perception and the Brain, 358
Exploration: Hearing Loss and
Speech Perception, 362
Application: Hey Siri, or Are You Cortana?
Computer Speech Recognition, 364
Chapter Summary, 366
Review Questions, 367
Ponder Further, 367
Key Terms, 367
13 MUSIC PERCEPTION …………………….. 371
Introduction, 371
The Acoustics of Music, 373
Pitch, Chroma, and the Octave, 373
The Octave, 375
Consonance and Dissonance, 376
Dynamics and Rhythm, 377
Timbre, 378
Melody, 380
Scales and Keys and Their
Relation to Melody, 380
Gestalt Principles of Melody, 381
The Neuroscience of Music, 383
The Neuroanatomy of Music, 384
Synesthesia, 385
The Neuropsychology of Music, 386
Learning, Culture, and Music
Perception, 388
Music and Language, 388
Culture and Music Perception, 389
Exploration: Musical Illusions, 391
Shepard Tones, 392
The Octave Illusion, 392
The Scale Illusion, 393
The Tritone Paradox, 394
Application: Music Perception in
Hearing-Impaired Listeners, 394
Chapter Summary, 396
Review Questions, 397
Ponder Further, 398
Key Terms, 398
14 TOUCH AND PAIN ………………………… 401
Introduction, 401
The Skin and Its Receptors, 403
Mechanoreception, 404
SAI Mechanoreceptors, 405
SAII Mechanoreceptors, 405
FAI Mechanoreceptors, 405
FAII Mechanoreceptors, 406
Proprioception: Perceiving
Limb Position, 406
Thermoreception, 407
Nociception and the
Perception of Pain, 409
Neural Pathways, 410
Somatosensory Cortex, 413
Suborganization of the
Somatosensory Cortex, 414
Pathways for Pain, 415
The Neurochemistry of Pain:
Endogenous Opioids, 417
The Perception of Itch, 418
Haptic Perception, 419
Reading Braille, 420
Tactile Agnosia, 421
The Development of Haptic
Perception, 422
The Vestibular System: The
Perception of Balance, 423
Exploration: Electroreception in Fish, 425
Application: Phantom Limbs and
Phantom Limb Pain, 427
Chapter Summary, 429
Review Questions, 430
Ponder Further, 431
Key Terms, 431
15 OLFACTION AND TASTE ………………… 435
Introduction, 435
Olfaction, 436
The Anatomy and Physiology of
the Olfactory System, 437
The Nose, 437
Genes and Olfaction, 439
The Trigeminal Nerve, 440
The Pathway to the Brain, 440
Representation Within the
Piriform Cortex, 442
The Orbitofrontal Cortex, 443
Olfactory Perception, 443
Detection, 443
Identifying Odors, 444
Odor Imagery, 445
Olfactory Illusions, 445
Taste Perception, 447
Anatomy of the Tongue and
Taste Coding, 448
Taste and Flavor, 451
Individual Differences in Taste
Perception, 451
The Wonderful World of
Chili Peppers, 452
Development of Taste
Perception, 453
Exploration: Anosmia, 453
Application: Artificial Sweeteners
and Taste Perception, 455
Chapter Summary, 457
Review Questions, 458
Ponder Further, 459
Key Terms, 459
Glossary, 461
References, 475
Author Index, 493
Subject Index, 500
xvi Sensation and Perception
ISLE ACTIVITIES
ISLE 1.1 Sequence of Sensory Events
ISLE 1.2 Illustration of Action
ISLE 1.3 Bach’s Violin Partita No. 2 in D minor
ISLE 1.4 Column Taper Illusion
ISLE 1.5 Aristotle’s Illusion
ISLE 1.6 Motion Aftereffect
Chapter 1
ISLE 1.7 Fechner’s Colors and Benham’s Top
ISLE 1.8 Kanizsa Triangle
ISLE 1.9 Optic Flow
ISLE 1.10 Kuffler and Single-Cell Recording
ISLE 1.11 Size–Arrival Effect
Preface
ISLE P.1 Obtaining or Creating Anaglyph Glasses
ISLE 2.1
North Carolina Hot Sauce Contest
Link | Proceed to Quiz
ISLE 2.2 Method of Limits
ISLE 2.2a Dot Threshold
ISLE 2.2b Frequency Discrimination
ISLE 2.3 Method of Constant Stimuli
ISLE 2.3a Dot Threshold
ISLE 2.3b Frequency Discrimination
ISLE 2.4 Method of Adjustment
ISLE 2.4a Dot Threshold
ISLE 2.4b Frequency Discrimination
ISLE 2.5 Point of Subjective Equality
ISLE 2.6 Magnitude Estimation
ISLE 2.6a Dot Brightness
ISLE 2.6b Tone Loudness
ISLE 2.6c Line Length
Chapter 2
ISLE 2.7 Stevens’s Power Law
ISLE 2.8 Forced-Choice Method
ISLE 2.8a Dot Brightness
ISLE 2.8b Frequency Discrimination
ISLE 2.9 Signal Detection Experiment
ISLE 2.10 Signal Detection Theory
ISLE 2.10a
Basics of Signal
Detection Theory
ISLE 2.10b Visualizing Signal Detection Theory
ISLE 2.10c
Decision Making in Signal
Detection Theory
ISLE 2.11
Signal Detection Theory and the
Receiver-Operating Characteristic
(ROC) Curve
ISLE 2.12 Masking Demonstration
ISLE 2.13
Seeing With Myopia and
Presbyopia
Experiment Interactive Link Video Audio illustration
ISLE Activities xvii
ISLE 3.1 The Basics of Waves
ISLE 3.2 Accommodation
ISLE 3.3 Presbyopia
ISLE 3.4 Letters and the Fovea
ISLE 3.5 Map Your Blind Spot
ISLE 3.6 Photopic vs. Scotopic Vision
ISLE 3.7 Purkinje Shift
ISLE 3.8 Convergence
ISLE 3.9 Dark Adaptation Function
ISLE 3.9a Illustrating Dark Adaptation
ISLE 3.10
Automatic Light Adjustment in
Cockpits
Chapter 3
ISLE 3.11 Center-Surround Receptive Fields
ISLE 3.11a Simulating Kuffler’s Experiment
ISLE 3.11b
Center-Surround Receptive Fields
as Contrast Detectors
ISLE 3.12 Mach Bands
ISLE 3.13 Correcting Myopia and Hyperopia
ISLE 3.14 Astigmatism
ISLE 3.15
Living With Macular Degeneration
and Retinitis Pigmentosa
ISLE 3.16 Compound Eyes
ISLE 3.17 Vision Prostheses
ISLE 4.1 From Eye to LGN
ISLE 4.2 Simple Cells
ISLE 4.3 Complex Cells
Chapter 4
ISLE 4.4 Hypercolumns
ISLE 4.5 Navigation in Blindsight
ISLE 5.1 Segregation and Grouping
ISLE 5.2
Ambiguous Figure–Ground
Perception
ISLE 5.3 Figure–Ground Symmetry
ISLE 5.4 Gestalt Laws
ISLE 5.4a Law of Good Continuation
ISLE 5.4b Laws of Proximity and Similarity
ISLE 5.4c Law of Symmetry
Chapter 5
ISLE 5.4d Law of Closure
ISLE 5.4e Law of Common Fate
ISLE 5.5 Necker Cube
ISLE 5.6 Illusory Contours
ISLE 5.7 Geons
ISLE 5.8
Facial Responses in the Brain
(Inferotemporal Region)
ISLE 6.1 Different Types of White Lights
ISLE 6.2 Dimensions of Color
ISLE 6.3 Newton’s Prism Experiment
Chapter 6
ISLE 6.4 Color Mixing
ISLE 6.4a Additive Color Mixing
ISLE 6.4b Subtractive Color Mixing
ISLE 6.4c
Additive and Subtractive Color
Mixing
xviii Sensation and Perception
ISLE 6.5
Color-Matching Experiment:
Metameric Matches
ISLE 6.6
Trichromatic Theory and Cone
Responses
ISLE 6.7
Univariance and Color Matching
in Monochromat or During
Scotopic Vision
ISLE 6.8 Color Aftereffect
ISLE 6.8a
Color Aftereffect Using
Photographs
ISLE 6.9 Simultaneous Color Contrast
ISLE 6.10 Hue Cancellation
ISLE 6.11
Single- and Double-Opponent
Cells
ISLE 6.12 Color-Deficiency Tests
ISLE 6.13 Rod Monochromat Vision
ISLE 6.14 Dichromacy
ISLE 6.14a Cones Missing in Dichromacy
ISLE 6.14b Color Matching in Dichromats
ISLE 6.14c Simulating Dichromacy
ISLE 6.15 Illumination and Color Constancy
ISLE 6.16 Lightness Constancy
ISLE 6.17 Gelb Effect
ISLE 6.18
Color Camouflage and
Dichromacy
ISLE 7.1
Depth Perception and Adanson’s
Jumping Spider
ISLE 7.2 Monocular Depth Cues
ISLE 7.2a Relative Size
ISLE 7.2b Size Constancy
ISLE 7.2b.1 Size Constancy Illustration
ISLE 7.2b.2 Size Constancy Experiment
ISLE 7.3 Motion Depth Cues
ISLE 7.3a Motion Parallax
ISLE 7.3a1 Motion Parallax Illustrated
ISLE 7.3a2 Motion Parallax Explained
ISLE 7.3b Deletion and Accretion
ISLE 7.3c Optic Flow
ISLE 7.4 Accommodation
ISLE 7.5 Vergence
ISLE 7.6 Stereopsis
Chapter 7
ISLE 7.7 Binocular Disparity
ISLE 7.8
The Construction of Visual Depth With
Binocular Disparity
ISLE 7.8a The Horopter
ISLE 7.8b Panum’s area of fusion
ISLE 7.8c Crossed vs. Uncrossed Disparities
ISLE 7.9 Anaglyph Stereograms
ISLE 7.9a
Stereo Jitter (Does not Need
Glasses)
ISLE 7.10 Random-Dot Stereograms
ISLE 7.11 Retinal Image Size and Distance
ISLE 7.12 Müller–Lyer Illusion
ISLE 7.13 Ponzo Illusion
ISLE 7.14 Ames Room
ISLE 7.15 Moon Illusion
ISLE 7.16 Virtual Reality Photographs
ISLE 7.17 Virtual Reality and Therapy
ISLE 8.1 Relative Motion
ISLE 8.1a
Relative Motion and Frame of
Reference
ISLE 8.2 Time-Lapse Motion
ISLE 8.3 Motion Thresholds
Chapter 8
ISLE 8.4 Apparent Motion
ISLE 8.5
Correspondence Problem in Motion
(Wagon Wheel Effect)
ISLE 8.6 Induced Motion
ISLE 8.7 Reichardt Detectors
xix ISLE Activities
ISLE 8.8 Corollary Discharge
ISLE 8.8a
Corrollary Discharge
Demonstration
ISLE 8.8b Moving Afterimages
ISLE 8.9 Eye Movements
ISLE 8.10 Correlated Motion
ISLE 8.11 Motion Aftereffect
ISLE 8.11a Waterfall Illusion
ISLE 8.11b Spiral Aftereffect
ISLE 8.12 Structure From Motion
ISLE 8.13 Biological Motion
ISLE 8.13a Examples of it Working
ISLE 8.13b
Examples of the Breakdown of
Biological Motion
ISLE 8.14 Cat and Laser Pointer
ISLE 8.15 Optic Flow
ISLE 8.16 Rotating Snakes
ISLE 8.17 Spiral Staircase
ISLE 8.18 Illusory Rotation
ISLE 8.19 The Furrow Illusion
ISLE 9.1 The Stroop Effect
ISLE 9.2 Scanning
ISLE 9.3 Spatial Cuing
ISLE 9.4 Inattentional Blindness Examples
ISLE 9.5 Stimulus Salience
ISLE 9.6 Feature vs. Conjunction Search
ISLE 9.7 Change Blindness
ISLE 9.8 RSVP
ISLE 9.9
Attentional Blink and Repetition
Blindness
ISLE 9.9a
Attentional Blink and Repetition
Blindness : Demonstration
ISLE 9.9b
Attentional Blink and Repetition
Blindness : Experiment
Chapter 9
ISLE 9.10 Hemifield or Unilateral Neglect
ISLE 9.11 Bálint’s Syndrome
ISLE 9.12 Perceptual Bistability
ISLE 9.12a Necker Cube
ISLE 9.12b Vase/Face
ISLE 9.13 Navigation in Blindsight
ISLE 10.1 The Sound Stimulus
ISLE 10.1a Sound and Air Pressure
ISLE 10.1b The Sound Wave and Distance
ISLE 10.1c Pure Tones
ISLE 10.2
The Speed of Sound and the
Sonic Boom
ISLE 10.3 The Decibel Scale
Chapter 10
ISLE 10.4 Frequency and Pitch on a Piano
ISLE 10.5 Frequency Response of the Ear
ISLE 10.6 Timbre and Musical Instruments
ISLE 10.7 Fourier Analysis in Audition
ISLE 10.8 Missing Fundamental
ISLE 10.9 Timbre and Overtones
xx Sensation and Perception
ISLE 11.1 Sound Localization Experiment
ISLE 11.2 Interaural Time Differences
ISLE 11.2a
Auditory Illustration (Needs
Headphones)
ISLE 11.2b Interactive Diagram
ISLE 11.3 Interaural Level Differences
ISLE 11.3a
Auditory Illustration (Needs
Headphones)
ISLE 11.3b Interactive Diagram
Chapter 11
ISLE 11.4 Auditory Scene Analysis
ISLE 11.5 Doppler Shift
ISLE 11.6 Architectural Space and Echoes
ISLE 11.7 Testing a Concert Hall
ISLE 12.1 Coarticulation
ISLE 12.2 Voicing-Onset Time
ISLE 12.3 McGurk Effect
ISLE 12.4 Familiar vs. Unfamiliar Languages
Chapter 12
ISLE 12.5 Phonemic Restoration Effect
ISLE 12.6 Genie
ISLE 12.7 Broca’s and Wernicke’s Aphasia
ISLE 13.1 Kurdish Music Example
ISLE 13.2
Javanese Gamelan Music
Example
ISLE 13.3 Ancient Greek Music
ISLE 13.4 35,000-Year-Old Flute
ISLE 13.5 Is This Music?
ISLE 13.6 The Octave and Tone Similarity
ISLE 13.7 Pentatonic Music
ISLE 13.8 Meter and Beat
ISLE 13.9 Bolero Clip
Chapter 13
ISLE 13.10 Attack and Decay
ISLE 13.11 Examples of Melody
ISLE 13.12 Types of Scales
ISLE 13.12a Play Scales
ISLE 13.12b Natural vs. Equal Tempered
ISLE 13.13 Gestalt Principles Review
ISLE 13.13a Proximity and Similarity
ISLE 13.13b Closure
ISLE 13.13c Good Continuation
ISLE 13.14
Gestalt Principle: Proximity:
Bach’s Partita No. 3 in E major
ISLE 10.10 Phase and Cancellation
ISLE 10.11 The Middle Ear
ISLE 10.12
The Basilar Membrane and Sound
Stimuli
ISLE 10.13 The Traveling Wave
ISLE 10.14 Place Code Theory
ISLE 10.15
The Basilar Membrane and
Fourier Analysis
ISLE 10.16 Transduction and Hair Cells
ISLE 10.17 Temporal Code Theory
xxi ISLE Activities
ISLE 14.1 Action of Mechanoreceptors
ISLE 14.2
Mechanoreceptors and Aristotle’s
Illusion
ISLE 14.3 Heat Grille
ISLE 14.4 Somatosensory Pathways
Chapter 14
ISLE 14.5
Melzack and Wall’s Gate Control
Theory
ISLE 14.6
Professor Ramachandran and
Phantom Limb Syndrome
ISLE 14.7 Treatment of Phantom Limb Pain
ISLE 15.1 Brain Area for Olfactory Bulbs
Chapter 15
ISLE 15.2 Posterior Piriform Cortex
ISLE 13.15 A Shave and a Haircut
ISLE 13.16
Cross-Modal Matchings as a
Simulation of Synesthesia
ISLE 13.17 Indian Raga Music Example
ISLE 13.18
Bach’s Violin Partita No. 2 in D
minor
ISLE 13.19 Shepard Tones
ISLE 13.20 Octave Illusion
ISLE 13.21 Scale Illusion
ISLE 13.22 Tritone Paradox
Bonus Illustrations
Shifting Melody: Ratio or Constant
Musical Stroop: A Part of Cognition
Laboratory Experiments
PREFACE
Everything we do as human beings starts with our ability to perceive the world. We
wake up in the morning to the jarring sound of an alarm clock prompting us to turn
on the light in the room so we can see. A few minutes later, the aroma of the coffee
lifts our mood and gets us ready to face the day. We feel inside our pocketbooks and
briefcases to make sure we have our keys. Then we listen to the radio as we watch for
traffic on the busy streets in our cars. Thus, nearly everything we do over the course of
our waking hours involves sensation and perception. Think of the obstacles faced by
a person missing one or more of these sensory systems. The famous Helen Keller was
completely dependent on her sense of touch in the absence of vision and hearing. For
this reason, the study of sensation and perception has been important to psychologists
from the very beginnings of psychology.
Sensation and Perception is designed to be a primary textbook for undergraduate
courses in sensation and perception or, as in some universities, simply perception. We
have written it primarily with students in mind but also so that professors will find it
useful as a supplement and guide to their teaching. The two authors come from very
different settings: One is a professor at a large public university, the other at a small
private college. We have tried to meld our experiences into a textbook that will be
useful in both the large lecture typical of the public university and the small seminar
of the private college.
When we teach sensation and perception, one of the most common questions we
receive from students is the following: How is this material relevant to my life and
to my future as a psychologist? Sensation and perception textbooks seldom address
this topic. Students learn about theories, physiology, anatomy, and experiments, and
they get to see some curious illusions. These are all important to the understand-
ing of sensation and perception, and these issues are well covered in our book. But
Sensation and Perception also instructs students in how to apply these concepts to
their everyday lives and how sensation and perception research is valuable in the real
world. For example, we discuss applications of sensation and perception research
to driving cars, to playing sports, and to evaluating risk in the military. Moreover,
we discuss numerous medical applications, including extended discussion of such
topics as macular degeneration, retinitis pigmentosa, color blindness, hearing aids
and cochlear implants, and neuropsychological conditions such as prosopagnosia.
For each chapter, we finish with Exploration and Application sections. The Application
sections deal directly with applications of sensation and perception research.
The higher education classroom has changed dramatically in the past decade.
Many students take some, if not all, of their classes online without ever having to
come to a university building. Classes now usually have companion websites, and
students have been “googling” interesting topics since they first could read. A mod-
ern textbook needs to adjust to the easy availability of information. What a mod-
ern textbook offers that distinguishes it from online sources of information is its
accuracy at presenting the most relevant information in an engaging, well-written
manner. Of course, we wrote our textbook to be approachable and readable, but
fundamentally what we offer our students is the guarantee that what they read here
is an accurate reflection of what is relevant in the field of sensation and perception.
Having said that, Sensation and Perception is written with the current state of
technology in mind. First and foremost, we have prepared the Interactive Sensation
Laboratory Exercises (ISLE) website, the companion website for the textbook. The
ISLE website provides opportunities to view and hear many of the phenomena we dis-
cuss in the book, including anatomical diagrams, visual illusions, auditory illusions,
xxiii Preface
and musical selections. It provides simulations of experiments and neurological pro-
cesses, and it provides exercises to help students understand how models such as
signal detection actually work. A book cannot present sound or motion, important
components of sensation and perception. But a click on an ISLE link will bridge the
gap, bringing these phenomena to your attention. Both teacher and student will find
ISLE an invaluable resource.
We also hope that student and professor alike will find our pedagogical resources
to be helpful. To help students learn, we start each chapter with a list of learning
objectives, which should help the reader organize the material and therefore learn
it better. After each major section, we have “test your knowledge” questions. These
open-ended questions promote thinking about the material broadly and linking con-
cepts together. Key terms with must-be-learned definitions are clearly marked off
in the margins, and illustrations throughout the text reinforce what is written in
the text. At the end of each chapter is a carefully organized chapter summary, a set
of review questions, “ponder further” questions for those who want to delve even
deeper into the topic, and a list of the key terms presented in the chapter.
Sensation and Perception emphasizes science. It describes experiments, patients
with neurological disorders, the areas of the brain involved in sensation and per-
ception, and the theory that links this research together. We wrote this book with
students in mind—their concerns, interests, and curiosity. This book not only empha-
sizes the science of sensation and perception but also tells a story about our search to
understand our own minds and how we can benefit from that understanding.
WHAT IS NEW IN THIS EDITION
So why a new edition? There are several reasons: We have included new science that
has emerged, we have learned from the feedback of reviewers and users, and we have
drawn on our own experience in the classroom. We have reviewed, revised, and updated
each and every chapter. Every chapter has been thoroughly reviewed and edited. This
process has been helped extensively by several rounds of reviews on each chapter to
which we are indebted to the reviewers who have so kindly lent their critique. As we
have gone through the chapters and feedback, we have made several changes that need
to be explicitly mentioned.
We have expanded the coverage of perceptual development in this text. In addi-
tion, we have made sure that our developmental topics always are clearly identified
in the chapter headings to make sure that that material can be found. So, in almost
every chapter, there is a section titled “Development.” We also added some new sec-
tions to chapters that did not have developmental sections. For example, we added
a section on infant acuity in Chapter 3; a section on the development of color per-
ception, including both infants and aging adults, in Chapter 6; and a section on the
development of haptic perception in Chapter 14.
In the first edition, we had an In Depth section that either examined a research
topic of interest or an application. In this edition, we have created two sections to
replace the In Depth section. The Exploration section examines a current research
topic, and the Application section discusses one of the many applications of sensa-
tion and perception. In some chapters, the former In Depth section has become an
Exploration and in other chapters an Application section, and in one case, Chapter 10,
the material was divided to make both sections and to limit both sections to a more
feasible length. Table P.1 lists these sections with their titles. There were many rea-
sons for this change, but perhaps the most compelling was the fact that research
in this field is ongoing in many interesting and exciting ways, and the Exploration
xxiv Sensation and Perception
section allows us to give a taste of this excitement. It could be argued that there are
more applications of sensation and perception than any other field of psychology; the
Application section allows us to help students see a few of the ways that they interact
with this field every day.
In addition to the content changes, we have expanded and refined the pedagogi-
cal features of this text. The learning objectives have been revised to make sure that
each major heading has a learning objective, and they have been reworked to take
into account Bloom’s taxonomy. At the end of each major section, we have increased
the number of Test Your Knowledge questions. Finally, at the end of each chapter are
Ponder Further questions, which ask students to take the material of the chapter and
consider the implications beyond the confines of the material presented. In addition,
the video links in the text have all been converted to ISLE activities to make is eas-
ier for students to access these illustrations. Beyond that, there are many new ISLE
activities that enhance the coverage of existing material and cover the new material
as well.
TABLE P.1 Exploration and Application Sections at the End of Each Chapter
Chapter Exploration Application
1 Cognitive Penetration Avoiding Collisions
2 Intersensory Perception Psychophysics in Assessment:
Hearing Tests and Vision Tests
3 Animal Eyes Vision Prostheses
4 Blindsight Conjugate Gaze Palsy
5 Vision and Animacy: How Do We
Tell a Who From a What?
The Science of Airport Screening
6 The Color Purple Color Deficiency and Our Colorful
Information
7 Stereopsis and Sports: Do We
Need Binocular Vision in Sports?
Virtual Reality and Therapy
8 Motion Illusions Motion Perception in Airplane
Pilots
9 Awareness and Visual
Consciousness
Distracted Driving
10 Hearing Loss The Science of Hearing Aids and
Cochlear Implants
11 Biosonar in Bats and Dolphins Concert Hall Acoustics and
Hearing
12 Hearing Loss and Speech
Perception
Hey Siri, or Are You Cortana?
Computer Speech Recognition
13 Musical Illusions Music Perception in Hearing-
Impaired Listeners
14 Electroreception in Fish Phantom Limbs and Phantom
Limb Pain
15 Anosmia Artificial Sweeteners and Taste
Perception
xxv Preface
ANAGLYPH GLASSES
Some of the photographic figures in the text and on ISLE are anaglyphic stereograms,
and they will require special glasses to be seen properly. (See Chapter 7 for more infor-
mation about stereograms.) We provide these glasses with this edition of the text.
However, if you lose them or buy a used copy of the text without these glasses, they are
easy to make, or, if you prefer, cheap to buy, individually or in bulk. Please note that you
will need red/cyan anaglyph glasses. Consult ISLE P.1 for specific information about
either making or ordering these glasses.
DIGITAL RESOURCES
SAGE edge offers a robust online environment featuring an impressive array of
tools and resources for review, study, and further exploration, keeping both instructors
and students on the cutting edge of teaching and learning. Go to edge.sagepub.com/
schwartz2e to access the companion site.
SAGE edge for Instructors
SAGE edge for Instructors, a password-protected instructor resource site, supports
teaching by making it easy to integrate quality content and create a rich learning envi-
ronment for students. The following chapter-specific assets are available on the teach-
ing site:
• Author-created test banks provide a diverse range of questions as well as the
opportunity to edit any question and/or insert personalized questions to effec-
tively assess students’ progress and understanding.
• Lecture notes summarize key concepts by chapter to assist in the preparation of
lectures and class discussions.
• Sample course syllabi for semester and quarter courses provide suggested models
for structuring a course.
• Editable, chapter-specific PowerPoint slides offer complete flexibility for creating
a multimedia presentation for the course.
• Lively and stimulating ideas for class assignments can be used in class to reinforce
active learning. The creative assignments apply to individual or group projects.
• Chapter-specific discussion questions help launch classroom interaction by
prompting students to engage with the material and by reinforcing important
content.
• Multimedia content includes audio and video resources that appeal to students
with different learning styles.
SAGE edge for Students
SAGE edge for Students provides a personalized approach to help students accomplish
their coursework goals in an easy-to-use learning environment. The open-access study
site includes the following:
• Interactive Sensation Laboratory Exercises (ISLE) provide opportunities to view
and hear many of the phenomena discussed in the book, including anatomical
diagrams, visual illusions, auditory illusions, and musical selections.
• Learning objectives reinforce the most important material.
ISLE P.1
Obtaining or Creating
Anaglyph Glasses
xxvi Sensation and Perception
• Mobile-friendly eFlashcards strengthen understanding of key terms and concepts.
• Multimedia content includes audio and video resources that appeal to students
with different learning styles.
• EXCLUSIVE! Access to full-text SAGE journal articles that have been carefully
selected to support and expand on the concepts presented in each chapter.
ACKNOWLEDGMENTS
We need to thank many people for their contributions to this book. Although the cover
lists Bennett and John as the authors, a multitude of people made invaluable contribu-
tions to ensuring that this book came together. First, we must thank many people at
SAGE Publishing for their help with the development, art program, and production of
Sensation and Perception. We continue to thank those people who worked on the first
edition, for without their work we would not be working on a second edition. Reid
Hester initiated the project, brought us together, guided the book to the finish line, and
saw it published in a timely manner. Lucy Berbeo, Nathan Davidson, Laura Barrett
and her staff in Production, Sarita Sarak, and Jim Kelly rounded out the team for the
first edition. We gratefully acknowledge all of their work. As is so often the case, teams
change over time. We had a mostly new team for this edition, but they have really been
wonderful additions to the project. Abbie Rickard stepped in as editor and was tireless
in making the process clear and serving as a constant support for the book. We are
grateful for her insight and hard work. Lucy Berbeo, Morgan Shannon, Jennifer Cline,
Alexander Helmintoller, Emma Newsom, and Nathan Davidson all provided much-
needed support in the technical aspects of the text, which are too numerous to mention.
We also thank the people who reviewed earlier drafts of chapters or the whole
book and generously gave us their feedback:
First Edition
Benoit-Antoine Bacon, Bishop’s
University
Mark E. Berg, The Richard Stockton
College of New Jersey
Michael D. Biderman, The University
of Tennessee at Chattanooga
Bryan R. Burnham, The University of
Scranton
Beatrice M. de Oca, California State
University Channel Islands
Robert Dippner, University of
Nevada, Las Vegas
Susan E. Dutch, Westfield State
University
Jim Dykes, University of
Texas at San Antonio
John H. Flowers, University of
Nebraska–Lincoln
Gina A. Glanc, Texas A&M
University Corpus Christi
Paula Goolkasian,
UNC Charlotte
Billy R. Hammond Jr., The
University of Georgia
Cheryl-Ann Hardy, Columbia
College
C. Eric Jones, Regent University
Eric Laws, Longwood
University
Fabio Leite, The Ohio State
University at Lima
Poornima Madhavan,
Old Dominion University
Sara J. Margolin, The College at
Brockport, State University of
New York
Daniel S. McConnell, University of
Central Florida
John Philbeck, The
George Washington University
Elisabeth J. Ploran, Hofstra
University
Jamie Prowse Turner,
Red Deer College
Jennifer S. Queen, Rollins College
Jason A. Rogers, State University of
New York Institute of Technology
xxviii Sensation and Perception
Tom Sanocki, University of South
Florida
Matthew Schlesinger, Southern
Illinois University Carbondale
Carl W. Scott, University of
St. Thomas
T. C. Sim, Sam Houston State
University
Sherril M. Stone, Northwestern
Oklahoma State University
Albert K. Toh, University of
Arkansas–Pine Bluff
Erik C. Tracy, University of North
Carolina at Pembroke
Emily A. Wickelgren, California State
University, Sacramento
Robert J. Woll, Siena College
Takashi Yamauchi,
Texas A&M University
Lonnie Yandell,
Belmont University
Diana L. Young, Georgia College &
State University
Second Edition
Karla M. Batres, Caldwell University
Tifani Fletcher, West Liberty
University
Alexis Grosofsky, Beloit College
Robert J. Hines, University of
Arkansas, Little Rock
Sara J. Margolin, The College at
Brockport, State University of
New York
Nicha K. Otero, University of
Arkansas, Fort Smith
Dennis Rodriguez, Indiana
University South Bend
T. C. Sim, Sam Houston University
Jennifer L. Thomson, Messiah
College
Sue Wilkinson, Cardiff
Metropolitan University
We must also thank many colleagues and students who read drafts of chapters or
who gave us advice on the important questions for a particular topic. These people
include, but are not limited to, Chaz Firestone, Matthew Schulkind, Pat Delucia,
Zehra Peynircioglu, Scott Pearl, Randy Blake, Adrien Chopin, Thomas Sanocki,
Brian Pasley, and Todd Kahan. And thanks to Julia Overton, who sent us information
on chili pepper eating contests.
We thank Hanover College for hosting the ISLE website for the first edition.
Finally, we thank the various individuals who helped out with the art program for
this textbook. Photographs, musical contributions, and likenesses were freely con-
tributed by Margaret Krantz, Leslie Frazier, Sarina Schwartz, Erin Hunter, Jonathan
Altman, Scott Pearl, Robert Kirkpatrick, and Todd Kahan.
Bennett L. Schwartz & John H. Krantz
December 2017
ABOUT THE AUTHORS
Bennett L. Schwartz received his PhD in 1993 from Dartmouth College in New
Hampshire. Since then he has been at Florida International University (FIU) in Miami,
Florida, where he is currently professor of psychology. He is author or editor of 10
published books as well as over 70 journal articles and chapters. His textbook Memory:
Foundations and Applications, 3rd Edition (SAGE), was published in 2017. He has won
several teaching awards at FIU and currently teaches courses in memory, cognition, and
sensation and perception. His main research area is metacognition and memory, but he
has also conducted research in diverse areas that range from visual perception to evolu-
tionary psychology, to the language of thought, and to memory in nonhuman primates.
Schwartz currently serves as the editor-in-chief of New Ideas in Psychology.
John H. Krantz received his psychology PhD from the University of Florida. After grad-
uate school, he worked in industry at Honeywell on visual factors related to cockpit
displays. In 1990, he returned to academia, taking a position at Hanover College. John
has done extensive research in vision, human factors, computers in psychology, and the
use of the Web as a medium for psychological research. He has been program chair and
president of the Society for Computers in Psychology and editor of the journal Behavior
Research Methods. John was the first to develop Web experiments in psychological sci-
ence and led the way on techniques for sending multimedia via the Web. He has served
as a faculty associate for The Psychology Place, developing interactive learning activi-
ties, and created psychology’s first global website for the Association for Psychological
Science (APS). In addition, he is an author for both the Cognitive Toolkit and PsychSim 6.
John is well known for his widely used online psychological experiments related to
sensation, perception, and cognition. His current research is focused on using the Web
for psychological research and modeling the visual system.
1What Is Perception?
Barry Downard/Alamy Stock Photo
LEARNING OBJECTIVES
1.1 Discuss why understanding sensation and perception is important.
1.2 Assess why there are actually more than five senses.
1.3 Describe how transduction transforms a physical signal into a neural signal.
1.4 Illustrate the history of the study of sensation and perception.
1.5 Explain the theory of cognitive penetration, and apply
sensation and perception research to collisions.
INTRODUCTION
Try to imagine the last concert you attended. It does not matter what kind of music you
like—rap, country, even the opera. Most likely, your experience at the concert was thrill-
ing—an experience initiated by the pleasure that auditory perception can bring. The
sounds of the singer’s voice and the guitarist’s riffs stir your emotions. The music pulses
into your ears. Despite your distance from the stage, and the assortment of voices and
instruments, you correctly sort out the lead singer’s voice from
the guitar, the bass, the keyboard, and the drums. Moreover,
even though there is a disconnect between the source of the
sound (the loudspeakers) and the location of the musicians (the
stage), you correctly attribute the sound to the stage. But in
almost all cases, in all varieties of music, a concert is more than
just sound. The flashy clothes and the elaborate video screens
fill your eyes with color and movement. This mixture of sight
and sound is not unique to pop concerts. The same is true for
opera (Figure 1.1). Because opera incorporates drama as well
as music, costumes and visual appearance are as much a part
of the art form as is the music itself. Our enjoyment of a live
concert comes from this coordinated combination of sensory
stimulation.
We tend to take our amazing sensory abilities for granted,
even when we are specifically engaging in activities such as
concerts or visits to art museums, in which we are deliberately
ISLE EXERCISES
1.1 Sequence of Sensory
Events
1.2 Illustration of Action
1.3 Bach’s Violin Partita
No. 2 in D minor
1.4 Column Taper Illusion
1.5 Aristotle’s Illusion
1.6 Motion Aftereffect
1.7 Fechner’s Colors and
Benham’s Top
1.8 Kanizsa Triangle
1.9 Optic Flow
1.10 Kuffler and Single-
Cell Recording
1.11 Size–Arrival Effect
FIGURE 1.1 Chinese Opera
In Chinese opera, elaborate and colorful costumes make
the performance as much a visual experience as it is a
musical one.
©
iStockphoto.com
/xiao-m
ing
2 Sensation and Perception
challenging our sensory systems. In general, we seldom think
about the manner in which we see, hear, touch, taste, and smell
the world, and how we become aware of our own internal
states as well. Perceptual abilities work fast, and they provide
us, during every waking moment, with an ongoing update of
the state of the world around us. We may attend to only cer-
tain aspects of the world at any given moment, but a wealth of
potential information exists around us. Consider the simple act
of reading this paragraph. Unless you are blind and using either
touch or audition to read these words, you are looking at a pat-
tern of black squiggles on a white background. Your attentional
focus is on decoding these squiggles from an intricate pattern
of visual stimulation into meaningful concepts. However, even
if you are in a quiet room, you are surrounded by myriad other
sources of sensory stimulation. Just a slight break of concentra-
tion, and you may become aware of the slight hum of the heat-
ing system, voices from upstairs chatting about campus events,
the pulse of the refrigerator, the Escalade with the deafening
bass line driving by outside, and maybe the plaintive cooing of
a mourning dove in a tree outside the window. Look up from
your text and you can see the flowers your mother sent you, the
leftover dinner that needs to be cleaned up, or your relaxed cat
sleeping by your feet. An inadvertent sniff, smelling the cookies baking in the kitchen,
breaks your concentration (Figure 1.2). Feel free to put “Schwartz and Krantz” down
for a moment and have one of those cookies before you continue reading. And don’t
worry about the vase.
The fact of the matter is that each of these sensory processes, from reading words
in a book to smelling cookies baking in an oven, is incredibly complicated; each one
is completed by exquisitely fine-tuned processes in our brains. By and large, however,
we become conscious only of the finished product—the words on the screen, the
music of the Black Eyed Peas gradually getting louder, then softer, as the car with the
loud stereo passes by outside, the brush of your cat’s soft fur against your skin, and
the taste of the warm chocolate mixing with the sugary cookie dough. The incredible
computing power of the human brain is focused on processing each of these sensory
inputs and allowing your conscious mind to pick and choose among them. Indeed,
sensory systems have evolved to accomplish these processes quickly and efficiently.
This textbook is an introduction to the science of sensory processes. We will
address the issue of sensation and perception from the perspectives of both psychol-
ogy and neuroscience. We will discuss both the neural underpinnings of sensation
and perception and the psychological processes based on those neural processes.
The study of sensation and perception began at the very beginning of scientific psy-
chology, and science has made progress on how sensory processes work. Granted,
there are many questions still unanswered about how sensory experience occurs,
but there is a broad consensus on the general pattern, from how information is
perceived by sensory neurons to the areas of the brain responsible for each sen-
sory system to the cognitive processes whereby we recognize common objects. This
textbook is written to help you understand the complex processes that go into sen-
sory perception. We hold that the study of sensation and perception is a fascinating
area that sheds light on the basic nature of what it is to be human. We hope you find
this journey interesting.
However, at the outset, we find it necessary to inform the reader: Understanding
sensory processes is not easy. No matter how clearly we describe each topic in
©
iS
to
ck
ph
ot
o.
co
m
/S
Co
ut
ts
FIGURE 1.2 Chocolate Chip Cookies
Just seeing chocolate chip cookies may make you hungry.
However, most people cannot make a taste image. Try to
imagine what chocolate chip cookies taste like (not look
like) with nothing actual to taste. Most people cannot
do it. However, when we smell the cookies, we get a
sensation very distinct from what they look like.
3 Chapter 1: What Is Perception?
this book or how well your professor explains the material, understanding this
material takes hard work and patience. The human mind and brain are complex;
therefore, to understand how they work and create our ability to sense and perceive
is also a complex task. Thus, read your text slowly and repeatedly, consult the
online resources, experience the illusions and demonstrations provided on ISLE,
answer the review questions, test yourself repeatedly, and give yourself the time to
learn about sensation and perception. Moreover, the terminology is often complex
and certainly requires ample memorizing. Make sure to learn the key terms, because
they are important in understanding the concepts (and presumably doing well
in your class). Do not get frustrated—it is likely that other students need just as
much time to learn the terms and help understanding sensation and perception as
you do. We think it is worth the time—we hope you will find the incredible designs
and abilities nature has evolved in our sensory systems to be inspiring, interesting,
and important.
WHY IS THIS PSYCHOLOGY?
1.1 Discuss why understanding sensation and perception is important.
You may wonder why sensation and perception are part of the psychology curriculum and
not, say, the biology curriculum. This is a fair question given that much of what you will
read in this book concerns anatomy and physiology, with a little bit of cognitive science
thrown in. The answer, however, is simple: The goal is to understand perceptual experi-
ence, that is, how our brains make sense of the sensory world around us. Understanding
how our minds, through our brains, interpret the world around us is an inherently psycho-
logical goal. We will see, as well, that psychological processes, such as attention, intention,
emotion, and biases, influence the ways in which we perceive the world. Consider the
sensory experience of pain. Every marathon runner, whether an amateur or an Olympic
medalist, crosses the finish line in intense bodily discomfort (Figure 1.3). Body tempera-
ture is at fever levels, muscles are filled with lactic acid,
sunburn covers the skin, dehydration is present, and sores
are opening on the feet. But despite the pain and discom-
fort, the marathon runner is likely ecstatic—he or she
has completed an incredibly challenging goal. The pain
is interpreted in the context of completing a long-sought
objective—to demonstrate that the marathon can be run.
If the same physical conditions were duplicated in a prison
setting, it could be interpreted as torture.
Consider, too, how our personal biases can influence
perception. Think about two friends from Los Angeles
watching a basketball game between the Los Angeles
Clippers and the Los Angeles Lakers. Each person is
watching the same game from the same vantage point in
the stands. That is, both friends are receiving the same
perceptual input. However, each person perceives dif-
ferent things. The Clippers fan sees Lakers star Lonzo
Ball “charging,” that is, committing an offensive foul.
The Lakers fan sees the same play as a blocking foul
on Clippers star DeAndre Jordan, maybe even a flagrant
©
iStockphoto.com
/bytepark
FIGURE 1.3 Runner Overcoming Pain
Marathon runners must overcome intense pain by the end of
the race. Our bodies have a number of ways of easing the pain.
The marathon runner may value the sense of accomplishment of
finishing the race. But pain is still an intense sensory experience.
4 Sensation and Perception
foul. The same sensory input results in two different perceptual outputs. Research has
shown that even when participants are instructed to be totally objective, they cannot
overcome the kinds of biases that are created by being a fan of one team or another
(e.g., Hastorf & Cantril, 1954). That is, even when trying to be totally objective, Lakers
fans cannot see the game from a Clippers perspective, and Clippers fans cannot see the
game from a Lakers perspective. For this reason, referees who grew up as Lakers fans
are seldom assigned the job of refereeing games involving Los Angeles teams. The hope
is that a referee from Seattle can see a game in an unbiased way (or at least a less biased
way) compared with a referee from Los Angeles. However, because of the biases of the
Clippers fans and the Lakers fans, they will never see what the referee sees. Thus, the
fairest of referees may often be scolded by fans of both teams as being biased toward
one or the other team—in the very same game.
Knowledge can influence perception in more subtle ways than occur among
biased sports fans. Consider seeing a small dot on the horizon of the ocean. Because
you know that it is a cruise ship out there, you tend to see it as such. That the object
could be an alien spaceship is considered far less likely, so you do not see it as such.
Indeed, we use our knowledge of objects to help us perceive them even in relatively
simple and static scenes.
TEST YOUR KNOWLEDGE
1. Why are sensation and perception studied by psychologists?
2. How do personal biases influence perception? Do such biases influence what
we see and hear, or do they bias what decisions we make about what we see
and hear?
THE MYTH OF FIVE SENSES
1.2 Assess why there are actually more than five senses.
Most of us were taught in elementary school about the five
senses—vision, hearing, touch, smell, and taste. This standard
taxonomy is not a simplified classification system, though it
goes all the way back to Aristotle. It is wrong! We certainly
have more than five senses. For example, in addition to these
sensory systems, we have a vestibular system to help keep our
balance and a proprioception system to allow us to monitor the
position of our bodies. Our sense of touch is composed of mul-
tiple physiological systems designed to sense different features
of the environment. Heat, cold, pain, itchiness, and soft touch
are all implemented by separable systems. Indeed, the receptors
for the “itch” experience are a unique kind of receptor different
from those that sense touch and those that sense pain. Thus,
depending on how the different touch systems are counted, it is
more realistic to say that human beings have anywhere from 7
to 12 different sensory systems (Table 1.1). Indeed, some have
even argued that hunger and thirst should be counted as senses.
We leave them out, as they deal strictly with internal states that
are not directly linked to perception of the external world.
TABLE 1.1 Senses of the Human Body
This table shows that there are more sensory systems than the
traditional five.
Function Organ
External
or Internal
Stimuli
Vision Eyes External
Hearing Ears External
Smell Nose External
Taste Tongue External
Light touch Skin External
Pressure Skin External
Cold Skin External
Heat Skin External
Pain Skin/viscera External/internal
Itch Skin External
Vestibular Inner ear External
Proprioception Muscles Internal
5 Chapter 1: What Is Perception?
The standard five-sense approach also fails if you think of the sensory systems as
hierarchically organized. For example, our perception of the flavors of foods is a com-
plex interaction of smell and taste, and it is something we feel is quite different from
smell itself. Flavor may also take into account other sensory modalities, such as vision.
For example, if you have ever tried to eat green eggs and ham, you know what we are
saying. However, because smell and taste are so bound together, it makes sense to group
these two senses in the same way that soft touch, pain, and temperature are grouped
together as the sense of touch or as a somatosensory system. Nonetheless, old habits are
hard to break, and this book is roughly organized according to the traditional five-sense
taxonomy. This is merely a bow to convention, not an endorsement of any scientific truth
behind it. In Chapter 14 we cover the skin senses (touch, pain, and temperature). You
will see that the various senses that make up this group are different both perceptually
and anatomically. Indeed, even the sensation of “hotness” and the sensation of “cold-
ness” are brought about by different receptor systems, not a differential response from a
“temperature” receptor. The classic “burn” sensation of feeling liquid nitrogen on one’s
skin is an example of this (removing of warts and moles with freezing liquid nitrogen is
a common dermatological procedure).
It makes scientific sense to discuss the visual system and the auditory system as
discrete sensory systems. And given the centrality of these two systems to human
sensory processing, much of this book is devoted to them. Indeed, all but the last two
chapters are about vision and audition. Increasingly, however, how sensory systems
interact is becoming an important topic of study known as multisensory processing,
studies of which address how one sense can affect perception in another (Alvarado,
Vaughan, Stanford, & Stein, 2007).
TEST YOUR KNOWLEDGE
1. What is meant by the myth of five senses?
2. What is the difference between internal and external senses? Can you give an
example of each?
THE BASICS OF PERCEPTION
1.3 Describe how transduction transforms a physical signal into a neural signal.
Sensation refers to the registering of a physical stimulus on our sensory receptors.
That is, sensation is the earliest stage of a process that starts off in the eyes, ears, or
skin and ends in the higher centers of the brain. Sensation changes physical stimuli,
such as light, sound waves, and mechanical vibrations, into information in our nervous
systems. Perception, by contrast, refers to the later aspects of the perceptual process.
To be specific, perception involves turning the sensory input into meaningful conscious
experience. In this sense, perception means the translation of that neural signal into
usable information.
Sensation and perception are usually thought of as distinct processes, one refer-
ring to the basic process of converting external information into a neural signal
and the other concerned with interpreting what that signal means. Other research-
ers think that the dichotomy between sensation and perception is a false one (e.g.,
Gibson, 1979). We will begin with the standard model, in which sensation occurs in
the sensory organs. For audition, sensation occurs in the ear, in particular, the hair
1.3
Sensation: the registration
of physical stimuli on sensory
receptors
Stimulus: an element of the
world around us that impinges
on our sensory systems
Perception: the process of
creating conscious perceptual
experience from sensory input
6 Sensation and Perception
cells of the cochlea. For our sense of touch, sensation occurs along the surface of the
skin. Perception occurs after cognitive processing begins, typically in the cerebral
cortex of the brain. Sensation is about stimuli; perception is about interpretation.
To perceive the world, we need both. We cannot perceive the Russian doll on the
coffee table as a Russian doll on the coffee table without both ends of the process
(Figure 1.4). The image of the doll must fall on the retina in order for us to perceive,
but equally important is the parsing of the perceptual environment, that is, knowing
where the doll ends and the table begins. Perception also involves knowing what you
are looking at.
So let’s take a look at the perceptual process, that is, the sequence of mental
operations that bring us from the initial sensory input to our understanding of our
conscious experience (ISLE 1.1).
Stimuli reflect light, produce sounds and vibrations, have surface texture, and
produce volatile chemicals (which we can smell). The job of our perceptual processes
is to determine what is out there in the world around us. We want our perceptual
processes to produce a veridical (truthful) representation of what surrounds us and
allow us to focus on those stimuli that are most important to us. Veridicality is
important because we want our sensory systems to be guiding us in adaptive ways.
For example, if we perceive an object as being farther away than it actually is, we
may bump into it and injure ourselves.
Because there are many potential stimuli in our world, we must be able to focus on
potential stimuli that are important or interesting. Such stimuli are called the attended
stimuli. When most of us listen to a song, our attention is drawn to the voice of the
singer or the melody of an instrumental tune. We can pick out different parts of the
music, say, the drums or the bass, by switching the attended stimulus from the lead
singer to the bass line, but usually our attention is focused on the melody. With vision,
we may be looking at a beautiful beach, but our attended stimulus may be the beer
bottle a previous beachgoer left behind.
Through our senses, we are presented with an incredibly rich and varied experi-
ence of the world, including the aroma of roasting coffee, the texture of fine silk, the
taste of dark chocolate, the sound of our favorite musician, and the sight of a glorious
sunset. Not all sensory experiences are pleasant and lovely,
of course. We have all smelled rotting garbage, felt a painful
pinprick, placed our fingers on a hot stovetop, tasted foods
we detest, heard fingernails screeching on the blackboard, and
seen images in movies that have made us close our eyes. The
senses unflinchingly bring to us an immense range of experi-
ences from the world around us, positive and negative alike.
Yet the next question we can ask is how do stimuli in
the outside world become perceptual experiences? How do
our sensory systems, such as our eyes, ears, and skin, trans-
late light, sound, and surface textures into perceptions? For
example, how does our nose turn the volatile chemicals of
coffee into the tantalizing aroma of coffee (Figure 1.5)? We
need to explore how physical stimuli are converted into a
sensory representation. So we now introduce the concepts of
transduction and neural responses.
For each of our sensory systems, we have specialized
neural cells called receptors, which transduce (transform)
a physical stimulus into an electrochemical signal, called a
neural response, which then can be sent to the brain. For
FIGURE 1.4
Seeing: A Complex Process
To understand this photograph,
you must sense the colors and
images, but cognitive processes
aid in understanding what it
is you are looking at. Without
some cultural knowledge, the
sensation makes little sense.
However, to our conscious
selves, the process of perceiving
the Russian dolls is seamless.
©
iS
to
ck
ph
ot
o.
co
m
/S
yl
vi
eB
ou
ch
ar
d
ISLE 1.1
Sequence of Sensory Events
FIGURE 1.5 The Smell of Coffee
The smell of coffee comes from molecules in the air that
rise from the coffee. Special cells in our noses must convert
the presence of those molecules into neural signals, which
we interpret as the wonderful aroma of coffee.
©
S
hu
tt
er
st
oc
k/
Ra
ch
at
a
Te
yp
ar
si
t
7 Chapter 1: What Is Perception?
FIGURE 1.6 Converting Energy Into a Neural Signal
Perception is the process of converting physical stimuli, such as light and sound energy, into neural signals within our sensory organs.
(a) Light is reflected off the petals of the flowers and into the eyes. The eyes then transduce this light into a neural signal to be sent to
the brain. (b) Sound is produced by the bird and reaches our ears. Special hair cells in the cochlea of the ear transduce the sound into
a neural signal to be sent to the brain.
vision, these specialized cells are called rods and cones, and they are located on the
retina of the eye. For hearing, these specialized cells are called the hair cells, and
they are found in the cochlea in the inner ear. For our sense of taste, we have cells
in our taste buds, which create neural signals when they come into contact with
certain chemicals in our food. Rods and cones transduce the physical energy of light
into an electrochemical signal, which is then transmitted to the brain via the optic
nerve. Hair cells convert the vibrating of the cochlear membrane (which vibrates in
response to physical sound) into a neural response, which is then transmitted to the
brain via the auditory (or cochlear) nerve. Taste bud cells convert the presence of a
particular chemical (such as sugars) into a neural response transmitted to the brain
by gustatory nerves (Figure 1.6).
Once a neural signal is transduced by the receptors, it is transmitted to the brain
for processing. Though the neural signal contains much information, it is necessary
for the brain to process that information in order to extract relevant information,
such as color for vision and pitch for sound. It is for this reason that we find it useful
to distinguish between sensation and perception. Sensation refers to the process of
transduction, in which receptors convert physical signals into neural responses, and
perception refers to the process of taking that signal and processing it into a usable
image or experience. For example, when we hear orchestral music, the hair cells in
our cochleae convert the sound waves into neural signals, but it is our brains that
convert that neural signal into the experience of the music we hear, the rich sound of
Transduction: the process of
converting a physical stimulus
into an electrochemical signal
Receptors: specialized sensory
neurons that convert physical
stimuli into neural responses
Neural response: the signal
produced by receptor cells that
can then be sent to the brain
(a) (b)
8 Sensation and Perception
the violins contrasting with the sharp tones of the trumpets, and
the underlying low tones of the basses and bassoons. Sensation
enables us to take in the sounds, but perception allows us to
appreciate the music.
Action
The goal of sensation and perception is to guide us through our
environment. We use visual information to avoid obstacles while
walking around campus or driving on the highway. When it is
completely dark, we avoid obstacles by touch. We feel our way by
touching the obstacles in front of us. In this way, most of us can
negotiate our own homes at night with the lights off just using
touch. We use auditory information to determine what people are
saying and whether the phone is ringing. We use olfactory (smell)
information to determine if we want to eat something or avoid
any contact with it. We use information about temperature on our
skin to determine if we want to wear a sweater or a T-shirt. Thus,
perceiving what is around us guides us to action. We can define action as any motor
activity. Thus, action includes moving one’s eyes along the page of a book as well as a
baseball player’s swinging his bat at an incoming fastball (Figure 1.7). It includes turning
your head when you hear the voice of a friend or a concert pianist’s fingers darting across
her piano keyboard. Thus, any movement we make can qualify as action. If that move-
ment is directed by something we perceive in the environment, then we can see that it is
perception-guided action. In sum, one of the chief goals, if not the
goal itself, is to guide functional action. (There are some interesting
illustrations of this on ISLE 1.2.)
The Nature of Experience
and Phenomenology
Think about the experience of listening to very beautiful music. For
example, think of a violin virtuoso playing Bach’s Violin Partita
No. 2 in D minor. If you are not familiar with this piece of music,
you can listen to an excerpt of it (ISLE 1.3). If you do not like this
style of music, imagine a piece of music that you think is very sad
but also very beautiful. In the Bach partita, our ears are respond-
ing to differences in frequency, tempo, rhythm, and loudness as we
hear the sound of the lone violin. Our toes may move in time to
the music, and our eyes may cloud with tears at the poignancy of
the music. These movements may be considered action. But
why does the piece affect us emotionally? Why do we find music beautiful in the first
place? How is it that we feel Bach’s grief at losing his wife through his music nearly 300
years after the piece was written? If you are a music theorist, this speaks to the power
of Bach’s music. But for our purposes, it introduces us to the issue of phenomenology.
Phenomenology is our subjective experience of perception. Phenomenology refers to our
internal experience of the world around us. Phenomenology is the beauty of the lone vio-
lin, the aromatic smell of coffee in the morning, and the wonder of seeing the colors of
the sunset in the west of an evening sky (Figure 1.8). By the same token, phenomenology
can refer to the annoying cacophony of the neighbor’s lawnmower, the stink of an airplane
ISLE 1.2
Illustration of Action
FIGURE 1.7 Perception and Action
The baseball player’s swing is guided by the perception
of the approaching baseball. Opposing pitchers may
throw curveballs, which change direction at the last
moment, to confuse batters’ perceptions.
©
iS
to
ck
ph
ot
o.
co
m
/R
BF
rie
d
FIGURE 1.8 Phenomenology
When we see a beautiful sunset, we notice the colors
and the landscape. The experience of all this is
considered its phenomenology. Issues of phenomenology
interest psychologists and philosophers alike.
©
iS
to
ck
ph
ot
o.
co
m
/t
om
of
bl
ue
sp
rin
gs
Action: any motor activity
Phenomenology: our
subjective experience of
perception
9 Chapter 1: What Is Perception?
bathroom, and an up-close look at a stranger’s nose hairs. Regardless of the effects they
induce in us, perception induces these internal mental experiences in each of us.
Phenomenology distinguishes us from computer-driven robots. Robots have
microphones to capture sound and internal computer processing units to decode
the messages into something that can drive the robots to follow certain courses of
action. But computer devices do not have internal experiences (as best we know).
Phenomenology appears to be a unique creation of the living brain. Philosophers
have argued about what purpose it serves, whether people share common phenom-
enology, how widespread it is among nonhuman animals, and if it is possible in
nonliving systems. The discussion of these questions is largely outside the scope of
this book, but there is a lively debate in philosophy concerning how we would know
if animals or artificially intelligent devices experience phenomenology when they
process the external world.
An interesting issue in phenomenology is that it is a private experience. Each of us
has sensory experiences, and we agree on common terminology for them, but because
phenomenology is private, philosophers often wonder if this means that we share phe-
nomenology. For example, scientists know what frequencies of light elicit an experi-
ence of blue, and people all across the world agree on what constitutes blue (regardless
of language). We may also share common cultural referents to blue, which we all agree
on (blue jeans, blue moods, blue states, etc.). However, is our internal experience of
blue the same? Do you and I have the same phenomenology of blue? This conundrum
is often referred to as the inverted-rainbow question. We all agree on the relation of
frequency to color name when we see a rainbow, but what if our internal experiences
were different? By and large, this question takes us out of the domain of scientific psy-
chology, as it cannot be answered empirically. But philosophers take these questions
quite seriously. At sagepub.com, you can find some approachable readings on the phi-
losophy of phenomenology.
TEST YOUR KNOWLEDGE
1. What is transduction? How might it differ from one sensory system to the next?
2. What is phenomenology? Why do you think it is so difficult to study by
experimental psychologists?
THE HISTORY OF SENSATION
AND PERCEPTION
1.4 Illustrate the history of the study of sensation and perception.
To understand any field of study, it is helpful to understand its history. Often the ques-
tions asked in the past and the way they were posed influence modern research. Therefore,
knowing the history can often help us understand why issues are framed the way they are
and why our knowledge has both the strengths and the weaknesses that it does. It can
also help us understand our own assumptions about the nature of the world by seeing
ideas from different epochs, when ideas and technology were different. Sometimes a field
does not even make sense until its history is considered. In this section, a short history of
the field of the study of sensation and perception is covered to give some context to the
material in this chapter and throughout the book.
ISLE 1.3
Bach’s Violin Partita
No. 2 in D minor
10 Sensation and Perception
The Beginnings
Thinking about our senses probably predates any written record. We
would like to think that even in prehistoric times, people marveled at
the beauty of a rainbow or a sunset. The formal study of sensation
and perception goes nearly as far back as written records exist. The
Ramesseum medical papyri date back to approximately 1800 BCE.
That’s nearly 4,000 years ago! The unknown authors describe disrup-
tions in visual perception and their connection to diseases of the eye
(Weitzmann, 1970). Interestingly, the papyri recommend hemp as a
treatment for eye disorders, much as doctors now prescribe medical
marijuana for glaucoma. In ancient Greece (some 1,500 years after the Ramesseum
medical papyri), Greek architects were aware of how perception could be distorted by
visual illusions (Coren & Girgus, 1978). Indeed, the Parthenon was built to appear as if
it had straight columns, though in order to do so, the architects had to design columns
that were not perfectly vertical. Elsewhere, Greek architects built perfectly straight col-
umns, but these appear bent (ISLE 1.4).
Aristotle (384–322 BCE) conducted conceptual work and observations in the field
of sensation and perception. He clearly distinguished between sensory and motor
functions; he described the sensory organs and their functions; he even gave us our
prototypical list of five senses: sight, hearing, smell, taste, and touch (Murphy &
Kovach, 1972). In addition to these basic ideas, Aristotle was a keen
observer and is the first to have recorded two very interesting sensory
phenomena, which we describe here, as they are relevant to topics we
discuss in later chapters.
The first is an illusion of touch that still bears his name, the Aristotle
illusion (Benedetti, 1985). In this illusion, a single touch between the tips
of two crossed fingers, say with a pen, will be experienced as if there were
two touches, as if there were two pens and not a single one (ISLE 1.5).
You can experience the illusion very simply by crossing your index and
middle finger (Figure 1.9). Then pick up a pencil and touch the place just
where the two fingers meet. You probably experience two touches (as
there is one touch to each finger) that feel like two pencils. The Aristotle
illusion is relevant to material discussed in Chapter 14.
The second illusion discussed by Aristotle is known as the motion
aftereffect, also known as the waterfall illusion (Verstraten, 1996; Wade,
1996). A motion aftereffect is a sensory experience that occurs after
prolonged experience of visual motion in one particular direction (ISLE
1.6). So if we think of a waterfall, the water is all moving in the same
direction: down. That is the only way real waterfalls actually occur.
After staring at a waterfall for some time, if you move your eyes to a
solid stationary object, you may get the sense that the stationary object
is moving upward, that is, in the direction opposite the one in which the
waterfall was moving. Another way to observe this illusion at home is to
watch the credits at the end of a movie without taking your eyes off the
television screen. After watching the credits for 2 minutes, have a friend
or family member hit the pause button. You will see an illusion of the
movie credits’ moving up the screen, even though you know the video is
now stopped. Aristotle observed this by looking at nonmoving surfaces
after watching the downward motion of waterfalls (Figure 1.10).
Many philosophers and scientists prior to the 19th century devel-
oped ideas about perception, some of which still influence our thinking
ISLE 1.5
Aristotle’s Illusion
ISLE 1.6
Motion Aftereffect
FIGURE 1.9 The Aristotle Illusion
In the illustration, we see two crossed fingers and
a pencil touching in the middle. In this illusion, we
feel as if we have been touched by two pencils
rather than one.
FIGURE 1.10 Waterfall Illusion
After watching the constant downward motion
of a waterfall, the motion detectors in our brains
adapt or tire in response to the downward
motion. When we look away from the waterfall,
upward motion detectors become active, and we
experience the illusion that whatever stationary
object we are looking at is moving upward.
©
iS
to
ck
ph
ot
o.
co
m
/M
ax
le
vo
yo
u
ISLE 1.4
Column Taper Illusion
11 Chapter 1: What Is Perception?
today. For example, the astronomer Robert Hooke (1635–1703) developed the first
acuity test for vision (Grüsser, 1993). However, it is with the 19th century that we
see the beginnings of a real science of sensation and perception. The contributions
came from people in many different disciplines. Physicist Thomas Young (1773–1829)
argued that light is a wave and that color is detected by three kinds of nerve fibers,
an idea elaborated on later by Hermann von Helmholtz. Biologist Johannes Mueller
(1801–1858) developed the doctrine of the specific nerve energies. The doctrine of
specific nerve energies argues that it is the specific neurons activated that determine
the particular type of experience. That is, activation of the optic nerve leads to visual
experiences, whereas activation of the auditory nerve leads to auditory experiences.
This seemingly obvious conception was controversial at the time because one of the
confusing findings of that time period was how similar the electrical activity was in all
of the neurons, regardless of the sensory modality. This led Mueller and others to won-
der how the brain could distinguish between seeing an apple and hearing a song, for
example. Those neurons involved in seeing will cause the impression of seeing regard-
less of how they are stimulated. So if a sound stimulates the neurons involved in vision,
you will still have a visual experience. Some early evidence for this view is the visual
experience we have when we manually stimulate the retina. Try pushing at the side of
your eye, and you will see that pushing on the eye can cause shifts of color and shading.
Helmholtz Versus Hering
One of Mueller’s students was Hermann von Helmholtz (1821–1894) (Figure 1.11).
Helmholtz was born in Potsdam in what was then the Kingdom of Prussia (now part
of Germany). He was a professor for many years at the University of Berlin. Helmholtz
was trained in medicine and physiology but became famous for his work in both sen-
sory perception and physics. His work in physics includes the formulation of the law
of the conservation of energy, an important landmark in physics. He was also a pioneer
in thermodynamics and electrodynamics. In biology, Helmholtz was the first person to
determine the speed of the neural impulse (or action potential). He also contributed
greatly to the beginnings of sensory physiology and the scientific study of perception.
Indeed, Helmholtz wrote a three-volume study of physiological optics and also wrote a
book on music perception. In particular, he elaborated on the work of Thomas Young
and developed the concept of the trichromatic theory of color vision. For this reason,
the trichromatic theory of color vision is often called the Young–Helmholtz theory of
color perception. Helmholtz thought of our color vision as being based on the percep-
tion of three primary colors, red, green, and blue, even though he was not certain that
there were three cone types in the retina (this was not known for certain until much
later). By and large, his color theory is still relevant today.
Helmholtz developed a general theory of how our senses work, which is mostly
still held today by most researchers within the field of sensation and perception. In his
constructivist approach, Helmholtz argued that the information from the sensory sig-
nal itself is inadequate to explain the richness of our experiences. That is, the sensory
signal needs to be interpreted by active cognitive processes. For example, recognizing
the face or voice of a loved one is more than basic sensations. Your auditory system
must integrate the sound of the voice with your knowledge of your sister and the
knowledge of what she usually talks to you about in order to fully perceive the speech
directed at you. Thus, we must incorporate information from our existing knowledge
to completely perceive the world around us. According to Helmholtz, because our
senses do not produce sufficient information about the world, we must use a form
of reason, unconsciously, to make an educated guess about what we actually per-
ceive. Helmholtz called this an unconscious inference (Turner, 1977). This type of
Aftereffect: a sensory
experience that occurs after
prolonged experience of visual
motion in one particular direction
Doctrine of specific nerve
energies: the argument that it
is the specific neurons activated
that determine the particular
type of experience
Constructivist approach:
the idea that perceptions are
constructed using information
from our senses and cognitive
processes
Unconscious inference:
perception is not adequately
determined by sensory
information, so an inference
or educated guess is part of
the process; this inference
is not the result of active
problem solving but rather of a
nonconscious cognitive process
FIGURE 1.11
Hermann von Helmholtz
Hermann Ludwig Ferdinand von
Helmholtz (1821–1894) was a
German physician, physicist,
and sensory physiologist. He
is credited with developing
a theory of color vision and
promoting the constructivist view
of sensory perception.
©
G
L A
rchive/A
lam
y
12 Sensation and Perception
theory is useful for explaining the occurrences of auditory and visual illusions, such
as the waterfall illusion. In this way, Helmholtz’s work foreshadowed the cognitive
approaches known as information processing and the computational approach.
Helmholtz’s colleague and rival was Ewald Hering (1834–1918) (Figure 1.12).
Hering was born in Saxony, in what is now Germany, but he was a professor in
Prague in what is now the Czech Republic and Leipzig in Germany. Hering dis-
agreed with Helmholtz both on the specifics of color vision and on a general model
of how sensory processes worked. With respect to color vision, Hering did not see
color vision as being based on three primary colors but as being based on color
opponency (Turner, 1993). He saw two major pairs of color opponents, green–red
and blue–yellow. Any receptor excited by green turns off red, and any receptor
excited by red turns off green. Modern research suggests that both Helmholtz and
Hering were correct to some extent. Trichromacy seems to best explain the work-
ings of the retina, whereas opponency can account for how areas of the visual brain
(occipital cortex) treat color. That they were both right would have displeased both
of these proud scientists, who deeply respected each other but were also fiercely
competitive with one another. This controversy is discussed at length in the chapter
on color perception (Chapter 6). Look ahead to the demonstration on this issue in
that chapter.
Hering also disagreed with Helmholtz’s theory of unconscious inference. Hering
viewed environmental inputs and our sensory apparatus as sufficient for us to grasp
the structure of the perceived world, without the need for internal unconscious
inferences. That is, stimuli contain adequate information for viewers to perceive
the world. In Hering’s view, the perceptual processes in the brain do not need to
make sense of the perceptual world; the brain simply needs to register it. Whereas
Helmholtz’s view is more popular with most experimental psychologists as well as
physiologists, Hering’s view influenced the development of gestalt psychology and,
later, direct perception theory (also known as the Gibsonian view).
Weber, Fechner, and the Birth of Psychophysics
Helmholtz and Hering both approached sensation and perception from the perspective
of physiology. Around the same time as Helmholtz and Hering were looking at the
relation of physiology and perception, other German scientists were doing work with a
more psychological perspective. Ernst Heinrich Weber (1795–1878) discovered Weber’s
law (though it was Gustav Fechner, another German scientist, who named the law after
Weber). Weber’s law states that a just-noticeable difference (JND) between two stimuli
is related to the magnitude or strength of the stimuli. What does this mean? Well, it con-
cerns two stimuli that are very similar. Can we detect the difference between two very
close red colors, or can we detect the difference between 1.44 mg of sugar dissolved in
a cup of water and 1.48 mg of sugar dissolved in a cup of water? Thus, Weber’s law
concerns the perception of difference between two stimuli. For more examples, do we
hear the difference between a 1,000-Hz tone and one of 1,005 Hz? Another example
is whether we see the difference in length between a line 466 mm long and one that is
467 mm long. Weber’s law suggests that we might not be able to detect a 1-mm dif-
ference when we are looking at lines 466 and 467 mm in length, but we may be able
to detect a 1-mm difference when we are comparing a line 2 mm long with one 3 mm
long. Another example of this principle is that we can detect 1 candle when it is lit in
an otherwise dark room. But when 1 candle is lit in a room in which 100 candles are
already burning, we may not notice the light from this candle. The JND is greater for
very loud noises than it is for much more quiet sounds. When a sound is very weak, we
can tell that another sound is louder, even if it is barely louder. When a sound is very
loud, to tell that another sound is even louder, it has to be much louder. Thus, Weber’s
Weber’s law: a just-noticeable
difference between two stimuli
is related to the magnitude or
strength of the stimuli
FIGURE 1.13
Gustav Fechner
Gustav Fechner (1801–1887)
is considered the “father of
psychophysics.” His landmark
work on the relation between
physical stimuli and perception
established sensory psychology as
a unique discipline separate from
physiology. His work inspired the
beginning of scientific psychology.
D
ig
ita
l L
ib
ra
ry
–
S
m
ith
so
ni
an
In
st
itu
tio
n
Li
br
ar
ie
s
FIGURE 1.12
Ewald Hering
Karl Ewald Kostantin Hering
(1834–1918) was a German
physiologist who introduced
the opponent theory of color
vision. He was also interested
in binocular vision. He
disagreed with Helmholtz on
constructivism. Hering argued
that stimuli themselves had
sufficient information to allow for
direct perception.
U
.S
. N
at
io
na
l L
ib
ra
ry
o
f M
ed
ic
in
e,
H
is
to
ry
o
f M
ed
ic
in
e
D
iv
is
io
n
13 Chapter 1: What Is Perception?
law means that it is harder to distinguish between two samples when those
samples are larger or stronger levels of the stimuli. To repeat, Weber’s law
states that a “just-noticeable difference” (JND) between two stimuli is related
to the magnitude or strength of the stimuli.
Gustav Fechner (1801–1887) is generally considered the founder of
psychophysics, the study of the relation between physical stimuli and
perception (Figure 1.13). Fechner’s (1860/1966) book Elements of
Psychophysics is often considered the beginning of the psychological study
of sensation and perception. Fechner discovered the illusion known as
the Fechner color effect, whereby moving black-and-white figures create
an illusion of color (ISLE 1.7). This illusion is also known as Benham’s
top (Figure 1.14). Fechner also developed Fechner’s law, which states that
sensation is a logarithmic function of physical intensity. This means that
our sensory experience changes at a lower rate than does the physical
intensity. That is, our perception of the intensity of a stimulus increases at
a lower rate than does the actual intensity of the stimulus. For example,
his law is captured in the decibel scale that we use to measure loudness, on
which 20 dB is 100 times louder than 10 dB in terms of the physical stim-
ulus. But in psychological studies, we hear 20 dB as only twice as loud as
10 dB, not 100 times. In vision, the psychological concept of brightness is
a function of the intensity of a light. But to perceive a doubling of bright-
ness, the intensity of the light must increase 10-fold. Fechner’s book and
his view on the relation between physical stimuli and psychological per-
ception influenced many early psychological scientists, including Wilhelm
Wundt, Hermann Ebbinghaus, and William James.
The 20th Century and the Study of
Perception: Cognitive Psychology Approaches
The 20th century brought a burst of interest and research in the study of sensation and
perception. First, sensation and perception research spread from Germany to many
other countries across the world, and a number of perspectives emerged, including
gestalt psychology, direct perception (or the Gibsonian approach), the information-pro-
cessing approach, and the computational approach. These latter two, information
processing and the computational approach, can be considered cognitive psychology
approaches. We briefly describe each approach here.
Gestalt Psychology
Gestalt psychology in general and sensation and perception in particular argued that
we view the world in terms of general patterns and well-organized structures rather than
separable individual elements (Schultz & Schultz, 1992). Consider Figure 1.15. In this
figure, we see the A only when we order the smaller elements together. In another exam-
ple, gestalt psychologists were interested in apparent motion, which can be explained
only by reference to the interaction between parts, not the individual parts themselves.
Gestalt psychologists were also interested in how edges are perceived, an interest that
has continued in both computational and neuroscience approaches to sensation and
perception. Gestalt psychologists considered the visual perception of edges as critical
to determining what objects were. They also identified several situations in which we
see illusory edges on the basis of gestalt principles. One of these is the famous Kanizsa
triangle, depicted in Figure 1.16 (ISLE 1.8). In the Kanizsa triangle, we see illusory
contours, which are suggested by the overall pattern of the figure but are not physically
there. The gestalt psychologists established a number of laws, which they argued were
ISLE 1.7
Fechner Colors and Benham’s Top
Psychophysics: the study of
the relation between physical
stimuli and perception events
Gestalt psychology: a school
of thought claiming that we view
the world in terms of general
patterns and well-organized
structures rather than separable
individual elements
FIGURE 1.14 Benham’s Top
This illusion was discovered by Fechner. Copy
the image shown here. Or look up Benham’s
tops on the Internet and print out a copy of the
above image. Put a pin or needle through the
very center of the image. Then spin the image
as fast as you can. While the image is moving,
you may see colors. Stop the movement and
look at the image again. The colors will be gone.
FIGURE 1.15
Gestalt Psychology
To see the A, one must order the
individual elements into a pattern.
By examining only the individual
elements, we would never see
the A. Gestalt psychologists
considered patterns such as these
the rule rather than the exception.
X X
X
X X
X X
X X
X X X X X X
X X
X X
X X
14 Sensation and Perception
constants in visual perception. These laws were devised to explain how patterns are
seen from individual elements (Figure 1.17).
Gestalt psychology flourished in Europe in the early 20th century. However, during
the same time period, American psychology was under the influence of behaviorism,
which had a very different perspective than did gestalt psychology. Behaviorists were
firm believers in the importance of “nurture” when it came to developmental issues
in psychology, whereas gestalt psychologists were firmly in the “nature” camp; that
is, they believed that these perceptual laws and other principles of human behavior
were genetically wired. Thus, gestalt psychology did not take hold in the United States.
However, when the Nazis came to power in Germany, many gestalt psychologists came
to the United States and Canada, where they influenced the development of the direct
perception view of perception, which we discuss shortly.
ISLE 1.8
Kanizsa Triangle
FIGURE 1.16
Kanizsa Triangle
When most people look at
this figure, they see a bright
white triangle lying on top of a
background consisting of a less
bright triangle and some odd-
shaped “Pac-Man” figures. The
bright white triangle is illusory.
The triangle is suggested by
the pattern of figures, and our
perceptual systems enhance
the perceived brightness of the
figure, but close inspection of the
figure will convince you that there
is no actual change in brightness.
Ka
ni
zs
a
Tr
ia
ng
le
FIGURE 1.17 The Laws of Gestalt Psychology
a. The law of proximity. You will see this
arrangement as a set of columns–not a set
of rows. Items that are near each other are
grouped together. Now notice the typing in
this book. You see rows of letters rather than
columns because a letter is closer to the
letters to the right and left than it is to the
letters above and below.
c. The law of good continuation. You will see
a zigzag line with a curved line running
through it, so that each line continues in the
same direction it was going prior to intersection.
Notice that you do not see the �gures as being
composed of the two elements below.
d. The law of closure. You will see a circle
here, even though it is not perfectly closed. A
complete �gure is simply more tempting than
a curved line! Now close this book and put
your �nger across one edge, focusing on the
shape of the outline of your book. You should
still see your book as complete, but with a
�nger in front of it.
e. The law of common fate. If dots 1, 3, and 5
suddenly move up and dots 2, 4, and 6—at
the same time—suddenly move down, the
dots moving in the same direction will be
perceived as belonging together. The next
time you look at automobile traf�c on a
moderately busy street, notice how clearly
the cars moving in one direction form one group
and the cars moving in the opposite direction
form another group.
Look out the window at the branches of a
tree, and focus on two branches that form a
cross. You clearly perceive two straight lines,
rather than two right angles touching each
other.
b. The law of similarity. You will see this
arrangement as a set of rows rather than
columns. Items that are similar to each other
are grouped together. Now look at the two
words at the end of this sentence that are in
boldface type. Notice how these two words
in heavier print cling together in a group,
whereas the words in regular, lighter print
form their own separate groups.
+ + + + + + +
+ + + + + + +
+ + + + + + +
15 Chapter 1: What Is Perception?
One prominent gestalt psychologist was Wolfgang Köhler (1887–1967). Köhler
was a patriotic, aristocratic German, who nonetheless vehemently opposed the Nazis
(Figure 1.18). In 1933, he was the last person in Germany to publish an article
critical of the Nazis during their regime. Soon afterward, he escaped to the United
States. Once there, he became a successful professor first at Swarthmore College in
Pennsylvania and then at Dartmouth College in New Hampshire. While at Dartmouth,
he was also president of the American Psychological Association. Early in his career,
Köhler applied gestalt psychology to auditory perception but then expanded gestalt
psychology into other domains of psychology, including his famous study of problem
solving in chimpanzees.
Direct Perception (The Gibsonian Approach)
The direct perception view was developed by the American husband-and-wife team
J. J. and Eleanor Gibson, who were professors at Smith College in Northampton,
Massachusetts, and later at Cornell University in Ithaca, New York (Gibson, 2001). The
Gibsons emphasized that the information in the sensory world is complex and abun-
dant, and therefore the perceptual systems need only directly perceive such complexity.
In this view, the senses do not send to the brain incomplete and inaccurate informa-
tion about the world that needs to be reasoned about to generate a perception. Thus,
the direct perception view is diametrically opposed to Helmholtz’s concept of uncon-
scious inference. Rather, in the direct perception view (Gibsonian approach), the world
generates rich sources of information that the senses merely need to pick up directly.
The direct perception view also emphasized ecological realism in experiments. This
means that rather than showing simple displays to participants in experiments, direct
perception theorists advocated using more naturalistic stimuli. Indeed, J. J. Gibson
(1979) criticized much work in perception because the stimuli used by researchers were
just points of light, tones, or stimuli that otherwise would not normally be encoun-
tered in everyday life. He emphasized that researchers should study real-world stimuli.
For this reason, the direct perception view is often called the ecological approach to
perception. For a demonstration of optic flow, one of the key contributions of this
approach, see ISLE 1.9.
Information-Processing Approach
The information-processing approach postulates that perceptual and cognitive sys-
tems can be viewed as the flow of information from one process to another. Information
is collected by sensory processes and then flows to a variety of modules that decode the
information, interpret it, and then allow the organism to act on it. Consider the pro-
cessing of visual information. Information flows from the eyes to various units in the
brain that extract color, motion, figure–ground, and object information and then pass
that information to cognitive systems that extract meaning and then pass it to other
cognitive systems that determine actions that should be implemented on the basis of
the visual information. The information-processing view stipulates that each of these
stages or processes takes a finite amount of time, even if they are very fast, and therefore
these processes can be observed or measured by recording reaction times as observers
do various tasks (Figure 1.19).
The information-processing view greatly influenced cognitive psychology. During
the 1960s and 1970s, information-processing models were used in both perception
research and memory research. The approach continues to influence both of these
fields, though contemporary researchers realize that the brain is massively “parallel”
and many processes can be occurring simultaneously.
FIGURE 1.18
Wolfgang Köhler
Wolfgang Köhler (1887–1967) was
a major theorist in the gestalt
psychology movement. Köhler
immigrated to the United States
prior to World War II. He expanded
the use of gestalt psychology
beyond its traditional domain of
sensation and perception to other
areas of psychology, such as
problem solving.
©
IN
TERFO
TO
/A
lam
y
ISLE 1.9
Optic Flow
Direct perception
(Gibsonian approach): the
approach to perception that
claims that information in the
sensory world is complex
and abundant, and therefore
the perceptual systems need
only directly perceive such
complexity
Ecological approach to
perception: another name for
the direct perception view
Information-processing
approach: the view that
perceptual and cognitive
systems can be viewed as the
flow of information from one
process to another
16 Sensation and Perception
The information-processing
view is different from Gibson’s
direct perception view because,
like Helmholtz’s view, the informa-
tion-processing view requires inter-
nal cognitive processes to interpret
the perceptual image, whereas the
direct perception view asserts that
the sensory input is sufficient in
and of itself. The information-pro-
cessing view is similar to the gestalt
view in the specification of internal
processes that extract information.
However, the gestalt view emphasizes
patterns and organization, whereas the
information-processing view empha-
sizes the analysis of information and
its flow from one system to another.
Computational Approach
The computational approach stud-
ies perception by trying to specify
the necessary computations the
brain would need to carry out to
perceive the world. Originally devel-
oped by David Marr (1982), it was
heavily influenced by the growth of
computer science and, in particular,
early theory in artificial intelligence.
Marr attempted to specify perception
in terms of what computations the brain would need to perform the task of perception.
He conceived of the brain as an incredibly complicated computer and sought a math-
ematical explanation for perceptual processes, especially vision. The computational
approach built on the information-processing approach but acknowledged from the
beginning that many perceptual processes may occur in parallel in the brain. Using the
approach’s modern form, researchers attempt to develop mathematical models that pre-
dict perceptual phenomena. Many of these mathematical models are based on neural
networks, computer simulations of how nervous systems work (Venrooij et al., 2013).
Many who value the computational approach try to get computers to “see” in
ways that make sense given our knowledge of the brain. In this way, the computa-
tional approach is often more theoretical, focusing on modeling perception in com-
puter simulations, whereas the information-processing approach is more directly
linked to observations in behavioral experiments. In computational models, if the
computer can “see,” theoretically so should the brain, and it is quite possible that the
brain will also use many of the same computations as the computer. Studies using
this approach often attempt to simulate perception on computers. A researcher will
give a computer some visual task. The task may be to see a real object, and the com-
puter has some form of electronic “eye,” such as a video camera, attached. It might
also involve simply a computer-generated world. In either case, the computer may
be given the task of identifying an object, perhaps partially hidden by another object
(e.g., Doerschner, Kersten, & Schrater, 2009). If the computer can do the task and
also tends to make the same types of mistakes humans do, then those doing research
FIGURE 1.19 An Information-Processing Model
Information processing means that information flows from one process or stage to
another during perception. Thus, in the diagram, we see an early sensory stage in which
transduction takes place. Information then flows to a series of perceptual modules,
eventually leading to final percept, which drives action.
Visual Image Storage
Long-Term Memory
Cognitive Processor
Movement Response
(arms, legs, mouth, eyes, etc.)
Motor
Subsystem
Cognitive
Subsystem
Perceptual
Subsystem
Senses
Perceptual Processor
Auditory Image Storage
Working Memory
Motor Processor
Computational approach:
an approach to the study
of perception in which the
necessary computations the
brain would need to carry out to
perceive the world are specified
17 Chapter 1: What Is Perception?
according to the computational approach have some
confidence that they have made progress in their goal.
Neuroscience in Sensation
and Perception
The goal of neuroscience is to understand sensation and
perception in terms of the structures and processes in
the nervous system that produce it. Thus, the neurosci-
ence approach starts with examining the physiological
processes whereby a physical signal is transduced into a
neural signal. Neuroscience then continues to investigate
sensation and perception by looking at connections from
the sensory organs to the brain and then at regions in
the brain itself that are involved in perceptual processes.
Neuroscience research can span the gamut from work
on single cells within the brain to examining connections
among differing regions in the brain.
Neuroscience is interested in the cellular level, nec-
essary to understand how individual neurons convert
physical stimuli into electrochemical signals (Figure 1.20). At the cellular level, neu-
roscientists can look at the actions of individual cells and how they respond to
particular signals. Neuroscience is also interested in what processes occur in the
brain to process and interpret sensory information. Here, neuroscientists can look at
larger units in the brain and attempt to correlate those regions with particular per-
ceptual functions. For example, studies show activity in an area of the brain, known
as MT (middle temporal) or V5, in the occipital lobe, when people are watching
moving stimuli.
One of the most important developments in neuroscience was the development of
the microelectrode in the 1940s and 1950s. A microelectrode is a device so small that
it can penetrate a single neuron in the mammalian central nervous system without
destroying the cell. Once in the cell, it can record the electrical activity there or even
stimulate the cell by carrying electrical current to the cell from an electrical source at
the command of the scientist. Thus, this method allows the recording of the behavior
of single neurons in the mammalian brain. It was first used in the sensory systems
by Kuffler (1953) (ISLE 1.10). In this way, it can be used to determine what kind of
stimuli a particular cell responds to. Thus, for example, a cell in area V1 (also known
as the primary visual cortex) of the brain may respond to visually seen lines of dif-
ferent orientations. Another cell might respond only to stimuli in the left visual field.
This technique led to some profound breakthroughs in our understanding of how the
brain processes sensory information.
Hubel and Wiesel (1959, 1962, 1965) are probably the names most associated
with this technique. Their Nobel Prize–winning work not only helped us understand
the behavior of individual cells but uncovered unexpected levels of organization in
the brain (Hubel & Wiesel, 1965) and information on how the brain develops (e.g.,
Hubel & Wiesel, 1962). For example, they found cells in the brains of cats and
monkeys that were selective to one eye or the other and other cells that responded
only when both eyes were able to see the same objects in the visual world. Single-
cell recording made major contributions to neuroscience with animal models, but it
is used less often nowadays because it is difficult to do with humans and we have
increased concerns about animal welfare.
ISLE 1.10
Kuffler and Single-Cell Recording
FIGURE 1.20 A Sensory Neuron
Bipolar cells, such as the one depicted in this image, connect the
receptor cells to the tracts that lead information from the sensory
organ to the brain. Bipolar cells in vision, for example, connect
rods and cones to the cells that lead information out of the eye and
through the optic nerve.
©
The Science Picture Com
pany/A
lam
y
Neuroscience: the study of the
structures and processes in the
nervous system and brain
Microelectrode: a device so
small that it can penetrate a
single neuron in the mammalian
central nervous system without
destroying the cell
18 Sensation and Perception
The neuroscience approach also includes the field of neuropsychology.
Neuropsychology is the study of the relation of brain damage to changes in behavior.
In neuropsychological research, scientists know what part of a person’s brain is dam-
aged and then look for behavioral changes in that individual. Behavioral changes
may include problems with language, memory, or perception. They may also include
difficulties in decision making, action, or emotion. Brain damage may arise from
a variety of tragedies and accidents, including strokes, tumors, aneurysms, loss of
blood during surgery, auto accidents, blows to the head, bullet wounds, concus-
sions, and near drowning. The origins of neuropsychology arise from such tragedies.
Indeed, the study of neuropsychology began in earnest in the 1870s in Europe, as
antiseptic procedures allowed soldiers in the Franco-Prussian war to survive gun-
shot wounds that would previously have been fatal. Antiseptics arrived too late for
American soldiers in the Civil War, many of whom died from infections that would
have been curable a few years later. Neuropsychologists continue to learn from and
help individuals returning from war (Vasterling et al., 2006).
Consider a particular case in which brain damage resulted from lifesaving sur-
gery. A patient called D.B. had part of his occipital lobe removed as treatment for
a malignant tumor. The tumor was causing seizures and could have threatened his
life, were it to have spread to other regions of his brain and body. Thus, surgeons
removed it as carefully as possible but also had to excise a great deal of tissue within
the V1 area of his occipital lobe. Medically, the operation was a tremendous success.
The tumor removal allowed D.B. to return to his job as a computer programmer and
lead a normal life, with few or no side effects. However, as a result of the loss of area
V1 tissue, D.B. developed partial blindness in one area of his visual field (Weiskrantz,
1996). This sounds more serious than it actually was. D.B. had no difficulties mov-
ing his eyes, so his eye movements quickly compensated for this patch of blindness.
However, it allowed D.B. to be an interesting research participant. The researchers
could correlate the brain damage (known to be in a particular area of the occipi-
tal lobe) and the behavioral deficits (partial blindness). As such, it was possible to
correlate the area of the occipital lobe that was removed with being responsible for
seeing in a certain part of the visual field. D.B. was also an important patient in the
study of the phenomenon of blindsight, a topic that is covered in depth in Chapter 4.
One form of brain damage affecting perception is known as agnosia. Agnosia is
a deficit in some aspect of perception as a result of brain damage. For example, there
is a form of agnosia caused by damage to an area of the temporal lobe known as the
fusiform face area (prosopagnosia, or face agnosia). Damage to this area results in
a deficit in recognizing faces. Damage to certain areas of the right temporal lobe can
result in a person’s loss of appreciation of music. This condition, known as amusia,
a form of agnosia, is covered in Chapter 13. Thus, neuropsychological methods are
effective at relating areas of the brain to particular perceptual functions.
Neuroscience research also includes the neuroimaging techniques. Neuroimaging
involves technologies that allow us to map living intact brains as they engage in
ongoing tasks. Neuroimaging allows us to observe an intact living brain as it per-
ceives, learns, and thinks. This is the newest technology used in neuroscience, with
the first magnetic resonance imaging (MRI) research not beginning until the 1990s.
Since then, however, neuroimaging research has become a major force in under-
standing both the brain and cognition and perception. One method is functional
MRI (fMRI). This technique can image the blood levels in different areas of the brain,
which correlate with activity levels in those regions, allowing activity in the human
brain to be correlated with our actual sensory abilities (Tremblay, Dick, & Small,
2011). Figure 1.21 shows what an fMRI scan looks like.
The fMRI technique is thought of as a hemodynamic technique because it mea-
sures the blood flow to the brain. The technique starts with the reasonable assumption
Neuropsychology: the study
of the relation of brain damage
to changes in behavior
Agnosia: a deficit in some
aspect of perception as a result
of brain damage
Prosopagnosia: face
agnosia, resulting in a deficit in
perceiving faces
Amusia: a condition in which
brain damage interferes with
the perception of music but
does not interfere with other
aspects of auditory processing
Neuroimaging: technologies
that allow us to map living
intact brains as they engage in
ongoing tasks
Functional magnetic
resonance imaging (fMRI):
a neuroimaging technique that
generates an image of the brain
on the basis of the blood levels
in different areas of the brain,
which correlate with activity
levels in those regions
19 Chapter 1: What Is Perception?
that because the brain is a biological organ, it requires oxy-
gen. Moreover, the areas of the brain that are active require
more oxygen and therefore more blood than other areas of
the brain. Thus, a person talking will need oxygen delivered
to the parts of his or her brain that are responsible for speech
production. A person listening to music will require a greater
oxygen supply to areas that are responsible for music percep-
tion. Thus, if you can trace the flow of blood in the brain, you
will know what areas of the brain are currently in use. For
example, Kau et al. (2013) recorded the neural activity in the
brains of participants tracking moving dots across a screen.
When the participants were attending to the motion, there
was activity in an area of the brain known as V3, located in
the occipital lobe. Other studies have associated area V3 with
movement perception.
Neuroimaging may very well be the fastest growing area in
scientific psychology. It offers us the opportunity to watch the
human brain as it does its work, certainly a fascinating propo-
sition. In this way, it can tell us a great deal about the structure
and function of the human brain and the nature of sensation
and perception. But neuroimaging can also be misleading. For
example, small differences in methodology between studies
can sometimes lead to big differences in the neural patterns.
Moreover, because fMRI researchers may do many statistical
tests per scan, there is a risk that neural activity in some regions may exceed a cri-
terion level simply by chance (Bennett, Wolford, & Miller, 2009). It is also true that
neuroimaging, at present, is still looking at vast groupings of cells. So neuroimaging
technology still cannot bridge the gap from gross anatomy to the fine-tuned results
of single-cell studies. Thus, it is still worthwhile to cast a critical eye at data that
come from fMRI studies, as they are not immune to such methodological problems.
Nonetheless, neuroimaging is a useful tool and one that has definitely broadened the
scope of the neuroscience of perception.
TEST YOUR KNOWLEDGE
1. What was at the center of the difference in viewpoints of Helmholtz and Hering?
Does this difference in view still have resonance for today’s science?
2. What is the difference between the views of gestalt psychology, direct
perception, the information-processing view, and the computational approach?
1.5
Explain the theory of cognitive penetration, and apply
sensation and perception research to collisions.
FIGURE 1.21 fMRI
This functional magnetic resonance image shows
the areas of the brain that are active when an odor is
presented to an individual. The areas depicted in color
include areas of the brain critical in odor perception, such
as the piriform cortex in the temporal lobe.
©
BSIP SA
/A
lam
y
EXPLORATION: Cognitive Penetration
Basketball players will sometimes say that the basket-
ball rim looks wider when they are doing well and looks
narrower when they are not making their shots. Golfers
report similar experiences with their putting. Tired hikers
may say the mountain looks steeper when they are tired
than when they are fresh. Many of us will report colors
being brighter when we are in good moods than when
we are depressed. Most of us agree that food tastes better
when we are hungry. Is this really true? Do factors such
as our success, our physical state, and our emotional state
20 Sensation and Perception
really affect how we perceive? Does our state of hunger
really affect what our taste buds are reporting?
The view that cognitive and emotional factors influence
the phenomenology of perception is known as cognitive
penetration (Marchi & Newen, 2015). Cognitive pen-
etration means that nonperceptual factors affect what
we see, hear, taste, and feel. The opposing view is that
perception is not affected by cognitive factors and that
only our reporting of perception is. This view is called
cognitive impenetrability (Firestone & Scholl, 2016).
Impenetrability implies that our perception remains the
same, regardless of our cognitive and emotional state.
What changes instead is attention, expectation, or our
mood state, which is different than our perceptual state.
The dominant view in the field is that perception is cog-
nitive impenetrable. However, recent research supports
some instances in which cognitive or emotional factors
influence the phenomenology of the perceived world.
Delk and Fillenbaum (1965) asked participants to match
the color of figures with the color of their background.
Some of the figures depicted objects associated with a par-
ticular color. These included typically red objects such as
an apple, lips, and a symbolic heart. Other objects were
presented that are not typically associated with red, such
as a mushroom or a bell. However, all the figures were
made out of the same red–orange cardboard. Participants
then had to match the figure to a background varying from
dark to light red. They had to make the background color
the same as the color of the figures. Delk and Fillenbaum
found that red-associated objects (e.g., the apple) required
more red in the background to be judged a match than
did the objects that were not associated with the color red.
This suggests that the knowledge of the objects was influ-
encing people to perceive them as being more red than
other objects (Figure 1.22). Hansen, Olkkonen, Walter,
and Gegenfurtner (2006) replicated this basic finding.
They presented participants with photographs of fruit
such as bananas and simple patches of colors. Participants
were asked to adjust the color of the object (banana or
patch) to the uniform gray background. Hansen et al.
found that participants adjusted the fruits differently than
the patches of equivalent color. For example, participants
added more blue to the banana in order to cancel out the
more perceived yellowness of it (we will discuss color
cancellation more in Chapter 6). Hansen and colleagues
suggest that this implies that the cognitive association of
objects to color influences how we perceive that color.
There may be cognitive penetration in other sensory
domains as well. For example, in research on pain, there
have been many studies documenting the placebo effect,
which is the finding that when people expect reduced
pain from a medicine, they experience less pain, even if
the medicine is essentially inert (Miller & Miller, 2015).
Freeman and colleagues (2015) gave three identical
creams to three different groups of participants before
presenting a somewhat painful stimulus. In the first con-
dition, they told participants that the cream was “lido-
caine” and would reduce pain (i.e., an analgesic). In the
second condition, they told participants that the cream
was “capsaicin” and might increase the pain (i.e., hyper-
algesia). In the third condition, participants were told
the cream was “neutral”; that is, it would not affect their
pain levels at all. The belief that the cream was an anal-
gesic led to less pain experienced relative to the control
condition. The belief that the cream was hyperalgesic
(leading to greater pain) led to more reported pain rela-
tive to the control. These results suggest that our expec-
tations actually influence the pain we experience (but see
Gatzia & Schwartz, 2016).
Despite the evidence, cognitive penetration is a tricky
issue. There are lots of alternate explanations for why
the results might be the way they are instead of the
Cognitive penetration: the view that cognitive and
emotional factors influence the phenomenology of perception
Cognitive impenetrability: perception is not affected by
cognitive factors; only our reporting of perception is
FIGURE 1.22 Cognitive Penetration Experiment
(Delk & Fillenbaum, 1965)
Red-associated objects (e.g., the apple) required more red in the
background to be judged a match than did the objects that were
not associated with the color red.
©
iS
to
ck
ph
ot
o.
co
m
/A
le
xB
ry
lo
v
21 Chapter 1: What Is Perception?
view that perceptual phenomenology actually changes
(Firestone & Scholl, 2016). For example, in one study,
participants judged a hill to be steeper when they were
wearing heavy backpacks (Bhalla & Proffitt, 1999).
Firestone and Scholl point out that many factors other
than perception may go into such judgments, such
as the expectation that a mountain must be climbed.
When participants had to match the hill they saw with
a test incline, they did not show different choices based
on the heaviness of the backpack. Thus, Firestone and
Scholl think that nonperceptual factors influenced their
decisions, not their perceptions. Indeed, the idea of cog-
nitive penetration is now one generating much interest
and controversy in the field of perception. Keep an eye
on this field, as we suspect there will be some very inter-
esting findings to come yet ahead.
APPLICATION: Avoiding Collisions
There is probably no field of psychology in which there
have been greater applications of psychological work than
the area of sensation and perception. It is also likely that
applications of this research area will continue to grow in
the future. We use our perceptions of the world around us
in nearly everything we do in our lives, with the possible
exception of daydreaming. Every practical aspect of life
involves looking, listening, touching, and tasting. Thus,
if you are considering a career in applied psychology or
human factors, you should pay very close attention to the
topics in this book and to your course in sensation and
perception. Understanding the basics of sensation and
perception is critical for any human factors psychologist
working in industry or government. Understanding the
basics of sensation and perception is important for civil
engineers who are designing safer roads.
Just consider a few of our technological horizons. Think
of designing the face of a modern smartphone. The size
of text and icons must be large enough for the human eye
to distinguish, and buttons must be positioned so that
human fingers can distinguish between the button for the
phone and the button for the music player. Companies
such as Apple and Samsung hire many human factors
psychologists to help them design these products in ways
that are consistent with human perception. Moreover,
consider the console of a modern jet plane. Warning
lights and controls must be positioned so that they
quickly demand the attention of the pilot if there is a
problem with a particular system in the airplane.
Sensory systems are also important in developing new
technologies. A major technological innovation that
many car companies are working toward is functional
self-driving cars. What goes into engineering such a
system? Cameras and computers have to be wired like
eyes and brains (only without blinking, falling asleep,
or experiencing road rage). Understanding the cues the
human eye attends to while driving is critical in design-
ing safe self-driving cars (Brett, 2016). Consider also
computerized voice recognition systems. The engineers
who design these systems must first understand the pro-
cesses by which humans recognize one another’s voices
and interpret meaning. Thus, several of our major tech-
nological fronts involve a role for understanding human
perception.
Returning to cars, it may be many years before self-driv-
ing cars are widespread, but road safety is a major issue
both in the United States and throughout the world.
According to U.S. government statistics, there are more
than 32,000 fatalities per year in car accidents in the
United States alone. This translates into more than
2,600 deaths per month on American roads. That means
that approximately the same number of Americans die
in car accidents every month as did in the tragic attacks
of September 11, 2001. It is estimated that there were
5.5 million automobile accidents in the United States in
2010 (Keane, 2011). Thus, there is still much that can
be done to improve road safety outcomes. Sensation and
perception research has much to offer here.
Many sensation and perception researchers study the
visually guided action associated with driving cars or
flying planes. Some of this research concerns the effects
of distraction on driving, a topic we discuss in depth
later (Chapter 5). Other research considers the effect
of fatigue on perception and driving ability. In this
Application section, we consider the perceptual pro-
cesses that drivers use to avoid automobile accidents.
Think about driving (assuming that you are a driver).
It is a visual task: We look in front of us to see where
we are going, and we check our rearview mirrors often
for potential dangers coming from behind us. We use
this visual information for simple tasks, such as noticing
22 Sensation and Perception
when our exit is coming and moving to the right or seeing
a swerving car and quickly applying the brakes. In this
way, avoiding impending collisions involves perceptually
guided action. When people see approaching objects, their
visual systems rely on their perception of depth, that is,
how far away the oncoming objects are, and judgments of
time to collision. These judgments need to be very accu-
rate in order to make good driving decisions.
However, research shows that people have systematic
biases in making these decisions. People estimate that
a large but farther away approaching object will collide
with them sooner than a smaller but closer approach-
ing object (DeLucia, 2013; DeLucia et al., 2016). That
is, people estimate accurately the likelihood that a truck
will strike them but underestimate the likelihood that
a smaller object such as a motorcycle will enter their
path. Motorcyclists often complain about how cars “cut
them off.” This may not always be the result of reck-
lessness or rudeness but rather a poor estimate on the
part of the car’s driver of how close the motorcycle
actually is (Figure 1.23). We now consider the research
of Dr. Patricia DeLucia of Texas Tech University, who
has devoted her career to understanding the factors that
affect our perceptual decisions in collision situations
(DeLucia, 2013; DeLucia et al., 2016).
Why is this? DeLucia’s research shows that the human
visual system uses two cues to make judgments about
impending collisions. The first is called time to collision.
This means that, in theory, your visual system estimates
the time it will take for an object to collide with you
by dividing the object’s optical size at a given point in
time by the object’s rate of expansion within the visual
field. That is, time to collision is determined by the
object’s optical size per unit time. In simpler language,
approaching objects increase in size, and more rap-
idly approaching objects increase in size more as they
approach you. Think of a baseball player judging when
to swing his bat. A fastball increases in optical size as it
approaches him more so than does a changeup (a pitch
thrown deliberately slow). Or think of a pilot guid-
ing a plane to touchdown on a runway. As the plane
approaches the ground, the runway increases in optical
size for the pilot. There is ample evidence that people
attend to this aspect of looming objects in a variety of
situations (Hecht & Savelsbergh, 2004).
However, people also use another cue to determine
time to collision. The second cue is the size of the
object. Larger objects are judged to be closer than
smaller objects. This is known as the size–arrival effect
(DeLucia, 2013). Numerous studies have shown that
perception of collision is
affected by the relative
sizes of objects (Brendel,
DeLucia, Hecht, Stacy, &
Larsen, 2012; DeLucia, 2013; Hahnel & Hecht, 2012).
You can see an illustration of this effect in ISLE 1.11.
The size–arrival effect results in the illusion that smaller
objects are less likely to collide with the viewer. This has
a number of unfortunate consequences for driving and
transportation safety. For example, drivers may under-
estimate the likelihood of collision when turning when
a smaller oncoming vehicle is approaching because it is
perceived as being farther away. Indeed, data from both
actual accidents and experimental simulations show
that a crash between a motorcycle and a car can occur
when the car intrudes on the motorcycle’s path, with
the car’s driver thinking the motorcycle is farther away
(Brendel et al., 2012; DeLucia, 2013; DeLucia et al.,
2016). In one simulated study, participants were asked
to press a button when they thought an approaching
vehicle would arrive at a particular location (Horswill,
Helman, Ardiles, & Wann, 2005). The experiment-
ers varied the sizes of the vehicles (motorcycle, car, or
van) and their speeds (30 or 40 mph). Time-to-collision
estimates were greater for motorcycles than for cars
and vans, consistent with the size–arrival effect. Thus,
DeLucia and others have recommended that roads and
motorcycle design should consider this factor in order
to make transportation safer. It is also possible that
ISLE 1.11 Size–Arrival Effect
©
iS
to
ck
ph
ot
o.
co
m
/p
al
in
ch
ak
jr
FIGURE 1.23 Avoiding Collisions
The automobile driver must estimate the time to collision with the
bicyclist. If the driver determines that a collision is imminent, he
or she must apply the brakes immediately, in this case, to spare
the bicyclist major injury.
Time to collision: the estimate of the time it will take for an
approaching object to contact another
Size–arrival effect: bigger approaching objects are seen
as being more likely to collide with the viewer than smaller
approaching objects
23 Chapter 1: What Is Perception?
education can be directed at drivers to help them realize
that they often underestimate the likelihood of collision
with smaller objects. Motorcycles designed to look big-
ger may also be safer for motorcyclists to ride. Thus,
this first Application section introduces the concept of
applications of sensation and perception research and
describes a particular area, research on time to collision
and its implications.
CHAPTER SUMMARY
1.1
Discuss why understanding sensation and per-
ception is important.
The study of sensation and perception sheds light on the
basic nature of what it is to be human. Sensation is the
registration of physical stimuli on sensory receptors, and
perception is the process of creating conscious perceptual
experience from sensory input. In this textbook, we discuss
the science and applications of research on sensation and
perception. In this chapter, we have discussed the nature of
physical stimuli, whether they be light for vision on the retina
or sound waves for the auditory system.
1.2
Assess why there are actually more than five
senses.
In addition to vision, hearing, touch, smell, and taste, we
have a vestibular system to help keep our balance and a pro-
prioception system to allow us to monitor the position of our
bodies. Our sense of touch is composed of multiple systems
designed to sense different features of the environment. Heat,
coldness, pain, itchiness, and soft touch are all implemented
by separable sensory systems.
1.3
Describe how transduction transforms a physi-
cal signal into a neural signal.
Sensory systems transduce physical signals into neural
responses, which are sent to the brain for processing. The
brain processes the signals, determines their meaning, and
decides on appropriate actions. Perception also produces a
characteristic phenomenology, which is the purely subjec-
tive experience we get when perceiving the world.
1.4
Illustrate the history of the study of sensation
and perception.
Writings on disorders of sensation and perception go back all
the way to the ancient Egyptians. Aristotle theorized extensively
about perception and its causes. Later, in the 19th century, German
physiologists began experimenting on the neural processes that
underlie sensation, and others started the field of psychophysics,
which studies the relation of physical stimuli to the psychologi-
cal experience. Later influences in the development of sensation
and perception research include gestalt psychology, Gibsonian
direct perception, information processing, and the computational
approach. Neuroscience also addresses issues of sensation and
perception. Neuroscience research includes single-cell record-
ing, neuropsychology, and neuroimaging.
1.5
Explain the theory of cognitive penetration, and apply
sensation and perception research to collisions.
Cognitive penetration means that nonperceptual factors affect
what we see, hear, taste, and feel. The opposing view is that
perception is not affected by cognitive factors and that only
our reporting of the perception is. This view is called cognitive
impenetrability. Impenetrability implies that our perception
remains the same, regardless of our cognitive and emotional
state. In the last section, we took one topic in depth as a case
study in applications of sensation and perception research.
This research concerns the visual perception of imminent col-
lisions. The research shows that people use both the rates of
expansion of approaching objects and the sizes of the objects
to estimate time to collision. The use of the sizes of objects
to estimate time to collision results in errors, in that smaller
objects are judged to impact later than they actually do.
REVIEW QUESTIONS
1. What is the myth of five senses? Can you list eight
different human sensory systems?
2. What do the terms sensation and perception mean?
What is the difference between the two?
3. What is the process of transduction? Why is it
important to perception?
4. What is phenomenology? Why is it so difficult to
address in science?
Sensation and Perception24
5. Who was Hermann von Helmholtz? What was his view of
color vision? How did it differ from that of Ewald Hering?
6. What is an unconscious inference in perception?
Why is it important to the constructivist approach?
7. What is a JND? Can you give a real-world example of
a JND?
8. What is the direct perception view? How does it dif-
fer from the information-processing view?
9. What is cognitive impenetrability? How does it differ
from cognitive penetration?
10. What is meant by the term time to collision? How is it
that the size–arrival effect changes our judgments of
collision times? What practical suggestions could you
make to improve transportation safety on the basis of
these findings?
PONDER FURTHER
1. Our perceptual abilities are shaped by natural evo-
lution. Weber’s law states that a just-noticeable
difference between two stimuli is related to the
magnitude or strength of the stimuli. Why might it
be adaptive to have a system that has this kind of
varied sensitivity as a function of the magnitude of
the stimuli? That is, why can we tell the difference
in weight between a 1-gram weight and 2-gram
weight, but not between a 2,000-gram weight and a
2,001-gram weight?
2. Most likely, you have a piece of art on your wall.
Maybe it is something original, perhaps a poster of a
famous work of art. Look at it now. Can you see if the
artist applied any gestalt principles in constructing the
visual image? Does knowing about the gestalt princi-
ples change the way you appreciate the art?
KEY TERMS
Action, 8
Aftereffect, 10
Agnosia, 18
Amusia, 18
Cognitive impenetrability, 20
Cognitive penetration, 20
Computational approach, 16
Constructivist approach, 11
Direct perception
(Gibsonian approach), 15
Doctrine of specific nerve energies, 11
Ecological approach to perception, 15
Functional magnetic resonance
imaging (fMRI), 18
Gestalt psychology, 13
Information-processing approach, 15
Microelectrode, 17
Neural response, 6
Neuroimaging, 18
Neuropsychology, 18
Neuroscience, 17
Perception, 5
Phenomenology, 8
Prosopagnosia, 18
Psychophysics, 13
Receptors, 6
Sensation, 5
Size–arrival effect, 22
Stimulus, 5
Time to collision, 22
Transduction, 6
Unconscious inference, 11
Weber’s law, 12
Chapter 1: What Is Perception? 25
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
1.1 Discuss why understanding sensation and perception is
important.
Wishful Seeing: How Preferences Shape Visual Perception
David Eagleman: Can We Create New Senses for Humans?
A Virtual Arm That Talks With the Brain
1.2 Assess why there are actually more than five senses. We Have Far More Than Five Senses
1.3 Describe how transduction transforms a physical signal into a
neural signal.
Perception and Health
Bright Lights, Big Headache: A Study Explains
1.4 Illustrate the history of the study of sensation and perception. Gestalt Illusion
Waterfall Illusion
Artwork of Bev Doolittle
1.5 Explain the theory of cognitive penetration, and apply sensation
and perception research to collisions.
Effects of Size on Collision Perception and Implications for
Perceptual Theory and Transportation Safety
Box Shape Influences the Size-Weight Illusion During
Individual and Team Lifting
Research Methodology
Jon Berkeley/Ikon Images/Getty Images
LEARNING OBJECTIVES
2.1 Explain the nature of psychophysical scales and how they measure the
relations between real-world stimuli and our perceptions of them.
2.2 Demonstrate an understanding of signal detection theory.
2.3 Evaluate neuroscience methods and what they tell
us about sensation and perception.
INTRODUCTION
In 2016, the Trinidad Moruga Scorpion blend was ranked the world’s second hottest
chili pepper after the Carolina Reaper (Bannister, 2016). According to the Chile Pepper
Institute at New Mexico State University, the Trinidad Moruga Scorpion rates close to
3 million on the Scoville scale. That puts this pepper in roughly the same range on the
Scoville scale as law enforcement–grade pepper spray. By contrast, Scotch bonnet peppers
and habanero peppers score from 100,000 to 300,000 Scoville units. Scotch bonnets and
habaneros are usually the hottest peppers most people eat. The first question we can ask is
why would anyone ever want to eat a Trinidad Moruga Scorpion? And the next question
we can ask is how do we determine hotness and how people experience it?
The Scoville scale measures our detection of the amount of an ingredient called
capsaicin in chili peppers. Capsaicin is a chemical present in peppers that directly
stimulates the somatosensory system, especially heat and pain receptors in our
mouths, and our eyes (which is why pepper spray irritates the eyes). It presumably
evolved to be present in wild chili peppers to prevent mammals from consuming their
fruit. Capsaicin, in general, repels mammals but does not affect birds, as the birds are
necessary to disperse the seeds. However, many people acquire a taste for capsaicin,
as the heat and pain felt in the mouth interact with smell and taste to create inter-
esting, if acquired, flavors, known as piquancy. Indeed, worldwide, the chili pepper
has become an important ingredient in cooking. Moreover, some chili pepper enthu-
siasts “compete” in competitions to see who can eat the hottest pepper. For example,
there is a chili pepper–eating contest at the North Carolina Hot Sauce Contest. To
win, contestants must eat an entire orange habanero chili (300,000 Scoville units)
(Figure 2.1). In the competition, contestants start off with milder peppers and work
their way up to the really spicy stuff. To find out more about this competition, see
the link on ISLE 2.1.
ISLE EXERCISES
2.1 North Carolina Hot
Sauce Contest Link
2.2 Method of Limits
2.3 Method of Constant
Stimuli
2.4 Method of
Adjustment
2.5 Point of Subjective
Equality
2.6 Magnitude Estimation
2.7 Stevens’s Power Law
2.8 Forced-Choice Method
2.9 Signal Detection
Experiment
2.10 Signal Detection
Theory
2.11 Signal Detection
Theory and the Receiver-
Operating Characteristic
(ROC) Curve
2.12 Masking
Demonstration
2.13 Seeing With
Myopia and Presbyopia
2
Scoville scale: a measure of
our detection of the amount of
an ingredient called capsaicin in
chili peppers
Capsaicin: the active
ingredient in chili peppers that
provides the experience of
hotness, piquancy, or spiciness
28 Sensation and Perception
The Scoville scale is a psychophysical scale, meaning that it relates psychological
experience to some aspect of the physical world. A psychophysical scale is one in
which people rate their psychological experiences as a function of the level of a phys-
ical stimulus. In this case, the Scoville scale measures our experience of piquancy or
“hotness” at different concentrations of capsaicin. Thus, the concentration of cap-
saicin in a particular food or drink is the physical dimension, whereas our experi-
ence of piquancy is the psychological correlate of that physical dimension. We will
encounter numerous instances of psychophysical scales throughout this textbook.
For example, the decibel scale measures the psychological construct of loudness as a
function of the intensity of a sound stimulus.
The Scoville scale is named after a chemist named Wilbur Scoville, who developed
the scale more than 100 years ago, in 1912. He derived the scale before chemists
could accurately measure the amount of capsaicin in a particular pepper, which labs
can do routinely now. In Scoville’s time, having a reliable scale to measure the “hot-
ness” of foods was important in the development of commercial foods. To measure
the piquancy, Scoville recruited brave volunteers from the company he worked for to
evaluate chili peppers. Once he had willing volunteers, Scoville adjusted the level of
chili peppers in a liquid solution that he had his observers taste. Obviously, the greater
the concentration of chili peppers, the hotter would be the taster’s experience, but
Scoville wanted to quantify this relation. He measured when the observers first start-
ing experiencing heat when tasting the pepper solution and how much more capsaicin
he needed to add to get people to notice a difference in the hotness of the solution. If a
taster did not notice any difference as a function of more chili peppers, Scoville added
more until that taster did notice the difference. In this way, Scoville was measuring a
characteristic known in psychophysics as the just-noticeable difference (JND). A JND
is the smallest amount of physical change observers notice as a perceptual change.
The Scoville scale, then, measures people’s perceived sense of hotness as a func-
tion of the amount of capsaicin in the sample solution. This scale was critical for
the development of commercial products that contained capsaicin. The scale is now
widely used in the food industry. The production of commercial hot sauces is a world-
wide business, and companies will report the Scoville ratings of their sauces. Tabasco
sauce, spicy to many of us, rates only about 2,000 on the Scoville scale, far less than
the piquancy of a Scotch bonnet pepper, let alone a Trinidad Moruga Scorpion. So, if
you know that Tabasco sauce is relatively mild on the Scoville scale, you might try it
on your tofu. However, if someone is offering you Trinidad Moruga Scorpion sauce,
you might want to think twice before dousing your dinner. For our purposes here,
the perception of piquancy and the Scoville scale serve as an excellent introduction
to the research methods used in sensation and perception and in understanding the
concepts of psychophysics.
This chapter covers basic questions, techniques, and research methods used by
researchers to discover how human sensory systems work. This information will set
the stage for later chapters that cover specific sensory systems, how they work, and
what we perceive. In terms of methods, in some cases, participants are asked to rate
a stimulus on a numerical scale, whereas in other situations, they may be asked to
decide only whether a stimulus is present (see the various demonstrations on ISLE).
In the latter case, a researcher can quantify on the basis of the percentage of correct
responses at each level of the stimulus.
The study of human sensory systems starts with psychophysics, the study of the
relation between physical stimuli and perception events, much as we just saw with
the Scoville scale for chili pepper hotness. Psychophysical methods involve presenting
a carefully controlled stimulus to a participant and asking a question directly of the
participant that allows the answer to be quantified, that is, turned into a number. From
©
iS
to
ck
ph
ot
o.
co
m
/D
N
Y5
9
FIGURE 2.1
Eat at Your Own Risk
These are orange habaneros,
which rate about 300,000 on
the Scoville scale. The Scoville
scale is a psychophysical scale
that measures our experience
of piquancy or “hotness.” The
more capsaicin is present in a
particular food, the spicier it will
taste.
ISLE 2.1
North Carolina Hot
Sauce Contest Link
Psychophysical scale: a
scale on which people rate
their psychological experiences
as a function of the level of a
physical stimulus
29 Chapter 2: Research Methodology
these direct questions, we hope to understand the way
the mind works to accomplish sensation and perception.
Thus, the psychophysical approach focuses on the relation
between physical properties (e.g., the amount of capsaicin
present) and perception (the experience of hotness).
However, the actual questions asked of participants may
vary depending on the research focus. Participants may be
asked to do a detection task (“Is there any hotness in the
taste?”), a comparison task (“Which is hotter, Stimulus A
or Stimulus B?”), or a magnitude task (“How hot is the
stimulus?”). Moreover, the scale might be a preference
scale (“Which level of hotness is preferable?”). Researchers
need to be clear about which methods they use, because
sometimes different methods may reveal different patterns.
As such, it is important to detail the research methods of
sensation and perception in this chapter, before we delve
into individual sensory systems in the remaining chapters.
THE MEASURES AND
METHODS OF PSYCHOPHYSICS
2.1
Explain the nature of psychophysical scales and how they measure
the relations between real-world stimuli and our perceptions of them.
When you go to an optometrist to get your vision tested or to an audiologist to get your
hearing tested, you essentially perform a series of psychophysical tests. At the optom-
etrist, you are asked questions such as “Can you distinguish the d’s from the b’s and
the o’s from the q’s?” If you can, great; if you cannot, you may need to start wearing
glasses (Figure 2.2). At the audiologist, you are asked questions such as “In which ear
do you hear the tone?” If you can’t identify whether the sound is coming from the left
or the right, it may be time to consider hearing aids. But for our purposes, it is the basic
methods of psychophysics that allow us to start studying the processes of perception.
Many of the methods go back to Gustav Fechner in the 19th century.
Method of Limits
In the method of limits, stimuli are presented on a graduated scale, and participants
must judge the stimuli along a certain property that goes up or down. For example,
a participant may be presented with an increasingly dimmer set of lights. The par-
ticipant is asked to tell the experimenter when the lights are no longer visible. The
researcher will then present the participant with lights so dim that they cannot be seen
and then present increasingly intense lights until the participant detects them (Figure
2.3). Similarly, one could present a series of tones, starting at a volume so soft that one
cannot hear them and gradually increasing the loudness until the participant can hear
the tones. We illustrate the method of limits with ISLE 2.2. In the first screen of this
experiment, you will find a window in which you can set up the values that will adjust
how your method of limits experiment will run. The first item asks you to determine
the number of levels to test. The number of levels refers to the number of intensity steps
in the independent variable that will be tested. In the method of limits, the researcher
FIGURE 2.2 Woman Undergoing
a Routine Eye Exam at an Optometrist’s Office
People should have these exams annually to determine the
health of their eyes. Many of the tests an optometrist runs are
similar to psychophysical tests.
©
iStockphoto.com
/M
achineH
eadz
Method of limits: stimuli are
presented in a graduated scale,
and participants must judge the
stimuli along a certain property
that goes up or down
30 Sensation and Perception
hopes to pick an extreme value that is readily detected and a level that is never detected
and then several levels between these.
The method of limits is often used to determine both absolute and difference
thresholds. An absolute threshold is the smallest amount of a stimulus necessary to
allow an observer to detect its presence. For example, the smallest amount of light
energy at any particular wavelength of light that we can detect is its absolute thresh-
old. Similarly, the least amount of sound that we can hear at any particular frequency
is its absolute threshold. The smallest amount of capsaicin that we can detect as
hotness is its absolute threshold. Indeed, a bell pepper has such a small amount of
capsaicin that it earns a zero on the Scoville scale. For a final example, the smallest
amount of salt that your taste buds can detect is also its absolute threshold.
The method of limits can also be used to determine the difference threshold
(the JND mentioned earlier), which is the smallest difference between two stimuli
that can be detected. Thus, one might hold two weights and attempt to determine
if their masses are the same or different. The smallest difference in weight that can
be detected is the difference threshold, equal to 1 JND. Similarly, an observer might
see two green lights and be asked if the lights are the same or not in terms of expe-
rienced greenness. The smallest difference in the wavelengths of the lights that can
be detected is the difference threshold, or 1 JND. Similarly, the smallest increase of
capsaicin that can be detected as a difference in piquancy is also a 1 JND difference.
Returning to the concept of absolute thresholds, it turns out that detecting abso-
lute thresholds is harder than simply finding the softest sound a person can hear or
the dimmest light a person can see. For example, if you are just leaving the firing
range and have been hearing loud percussions for the past hour, detecting a very soft
tone might be difficult. If you have been studying in the library for the past hour, that
same tone might be quite audible. Similarly, it may be easier to detect a dim light in
the dark of night than it is to detect the same light on a bright summer day. If you
have just eaten a large and satisfying meal, the taste of another piece of lasagna may
not be as satisfying as the first. That is, absolute thresholds are not so absolute—they
depend on many internal and external conditions. In fact, our sensory systems are
constantly adapting to local conditions. On one hand, this makes assessing absolute
thresholds difficult, but on the other hand, it is an adaptive feature of our sensory
systems, as it allows us to perceive under a wide range of conditions. On a bright
sunny day at the beach, we want our sensitivity to light to be less than when we are
FIGURE 2.3
The Method of Limits
The participant must decide if a
stimulus is present at a number
of different levels of intensity.
The stimulus is increased in even
trials and decreased in odd trials.
A Y indicates that the participant
detects the stimulus, whereas an
N indicates that the participant
does not detect the stimulus.
The estimate of the threshold
is considered to be the mean
crossover point.
Intensity Trial Number
10 Y Y Y Y Y
9 Y Y Y Y Y
8 Y Y Y Y Y
7 Y Y Y Y Y
6 Y Y N Y Y
5 Y N Y Y Y Y
4 N Y N N Y Y N
3 N N N N N
2 N N N N
1 N N N N
Crossover 4.5 3.5 5.5 4.5 6.5 4.5 3.5 3.5 4.5
Threshold = mean crossover = 4.5
ISLE 2.2
Method of Limits
Absolute threshold: the
smallest amount of a stimulus
necessary to allow an observer
to detect its presence
Difference threshold (JND):
the smallest difference between
two stimuli that can be reliably
detected
31 Chapter 2: Research Methodology
trying to find our way around a forest campground on
a dark, moonless night.
In assessing thresholds, we often need to estimate
the threshold and try to compensate for any sensory
adaptation that is occurring, such as whether we have
just eaten. Thus, to determine an absolute threshold
with the method of limits, a researcher must use both
an ascending series and a descending series. An ascend-
ing series (or an ascending staircase) is one in which
a stimulus gets increasingly larger along a physical
dimension. Thus, the intensity of light might increase,
the amplitude of sound might increase, or the amount of capsaicin in a taste capsule
might increase. By contrast, a descending series (or a descending staircase) is one in
which the stimulus gets increasingly smaller along a physical dimension. Thus, the
researcher starts with a clearly visible light and lowers the amount of light on each
successive trial (Figure 2.4).
Consider a light detection experiment. We want to determine
a person’s absolute threshold for a red light in an otherwise dark
environment. In the ascending method, we start off with a level of
red light that is known to be below the threshold. The participant
should respond that he or she does not see it. The experimenter then
gradually increases the intensity of the light until the person can
detect the light. In the descending method, we start off with a bright
level of red light that the person can obviously detect and then lower
the intensity of the light until the person can no longer see it. The
point at which people change from detecting to not detecting or
vice versa is known as the crossover point. Typically, the threshold
will be different when measured by the ascending method versus
by the descending method. In general, with ascending series, people
are likely to claim that they can detect a stimulus when in fact the
stimulus is below the threshold. With descending series, people are
likely to claim that they cannot detect a stimulus when it actually
is above the threshold. Researchers will typically average over sev-
eral descending and ascending series to get their best estimate of the
absolute threshold (see ISLE 2.2).
Consider some common absolute thresholds in the natural world. Think of look-
ing up at the stars on a clear night (Figure 2.5). Think of the faintest star you can
possibly see—this star may be at or around your visual threshold. And for the audi-
tory system, consider hearing the faintest drone of a conversation from an upstairs
dorm room. You cannot make out the content of what they are saying, but you can
just barely hear their voices. In the domain of taste, consider how much sugar you
must put in your iced tea before it has the slightest hint of sweet. And think of the
faintest hint of a distant odor—perhaps a faraway smell of coffee. Thus, in real life,
we do encounter at-threshold stimuli from time to time.
In Chapter 1, we mentioned the work of Ernst Heinrich Weber, who did some
of the earliest work on thresholds in the 19th century. One area he investigated was
threshold in touch along the surface of the skin. He was interested in the two-point
touch threshold, which is the minimum distance along the skin at which two touches
are perceived as two touches and not one. In this case, two needles can be brought
gently to touch a person’s skin close to one another. If a person feels only one touch,
then it is below the threshold, but if the person feels two touches, then they are above
the threshold. Our two-point touch thresholds vary across our skin. Our fingers can
Ascending series: a series
in which a stimulus gets
increasingly larger along a
physical dimension
Descending series: a series
in which a stimulus gets
increasingly smaller along a
physical dimension
Crossover point: the point at
which a person changes from
detecting to not detecting a
stimulus or vice versa
Two-point touch threshold:
the minimum distance at which
two touches are perceived as
two touches and not one
FIGURE 2.4 Absolute Threshold
Illustration of the detection of absolute thresholds through the
method of descending limits. Each light is dimmer than the one to
its left.
©
iStockphoto.com
/Baltskars
FIGURE 2.5 Stars on a Clear Night
Many stars are easy to see, but some may lie just at
our thresholds. When we look at these stars straight
on, we may miss them, but we see them again “out
of the corner of our eye,” or at our periphery, which
is more light sensitive.
32 Sensation and Perception
detect two touches even when the needles are extremely close to each other. However,
the skin of our backs requires greater distance to feel two touches. Areas on the face
and mouth have small two-point thresholds, but not as good as the fingers. Other
areas, such as the arms and legs, require larger distances to perceive two touches, but
not as great distances as the skin of the back. The two-point threshold is an absolute
threshold. The size of the absolute threshold differs on different parts of the body,
just as acuity changes across the surface of the eye’s retina. Table 2.1 lists a few
everyday absolute thresholds.
TEST YOUR KNOWLEDGE
1. What is the difference between an absolute threshold and a difference
threshold? When might you want to use one and when might you want to use
the other?
2. Why would the method of limits not be a good method to test piquancy of hot
peppers?
Method of Constant Stimuli
In the method of constant stimuli, the threshold is determined by presenting the
observer with a set of stimuli, some of which are above the threshold and some of
which are below it; the stimuli are presented in a random order. This differs from the
method of limits. In the method of limits, the stimuli are changed to focus on a par-
ticular observer’s threshold. In the method of constant stimuli, all stimuli are always
presented, and all are selected beforehand. In the method of constant stimuli, the pre-
sentation of stimuli is given in a random order rather than zeroing in on the threshold.
This technique prevents the observer from being able to predict or anticipate what the
next stimulus will be. This reduces errors that may result from habituation or fluctua-
tions in perception due to attention or other factors. However, the method of constant
stimuli is often quite time-consuming, as it requires pretesting to gauge the general
region of the threshold for each participant. Moreover, it requires many trials to detect
a statistically determined threshold. In the method of constant stimuli, the stimulus that
is detected 50% of the time and not detected 50% of the time is considered to be the
threshold (Figure 2.6). You can see a demonstration of the method of constant stimuli
on ISLE 2.3.
The method of constant stimuli is used by audiologists when testing patients for
hearing thresholds (Gelfand, 2009). For each frequency of sound, the audiologist will
present the patient with an assortment of louder and softer tones to detect (see ISLE
2.3b). In this way, the audiologist can determine the threshold of hearing at each fre-
quency and, in some cases, if that threshold is higher than it should be, whether the
Method of constant stimuli:
a method whereby the threshold
is determined by presenting the
observer with a set of stimuli,
some above threshold and some
below it, in a random order
Sense Threshold
Vision A candle 30 miles away on a dark night
Audition A ticking watch 20 feet away in an otherwise silent location
Taste A teaspoon of sugar in 2 gallons of water
Smell A drop of perfume in three rooms
TABLE 2.1 Everyday Absolute Thresholds
Source: Adapted from Galanter (1962).
ISLE 2.3
Method of Constant Stimuli
33 Chapter 2: Research Methodology
person might be a candidate for hearing aids. Typically, hearing loss varies as a func-
tion of sound frequency, meaning that for some sound frequencies, a person may be
impaired but for others have normal hearing. An audiologist needs to know the
profile of hearing loss to properly program a patient’s hearing aids. For this reason,
as we will see later in the chapter, audiology starts with psychophysics.
Method of Adjustment
In the method of adjustment, the observer controls the level of the stimulus and
“adjusts” it to be at the perceptual threshold. The participant does so by increasing
or decreasing the level of the stimulus until it feels as if it is just at the detectable
level. Typically, the participant will do so by continuously adjusting a knob to control
the level of the stimulus. This is an intuitive measure for most participants because it
mirrors many normal activities, such as adjusting the volume control on a radio or a
dimmer switch on a light. In a light threshold study, the method of adjustment would
require the observer to adjust the light source to the dimmest light the participant can
detect. Adjusting the knob any lower would render the stimulus invisible. The advan-
tage of this technique is that it can quickly yield a threshold for each participant, but
a disadvantage is that it leads to great variance from one participant to the next and
between successive trials for each participant.
The method of adjustment is very useful for matching one stimulus to another to
determine the point of subjective equality (PSE). The PSE designates the settings of
two stimuli at which the observer experiences them as identical. For example, con-
sider a researcher who is interested in the JND in the detection of pitch differences
as a function of sound frequency. The observer hears a constant sample tone at, for
example, 1,000 Hz. The observer would then adjust a second tone until it matched
perceptually the sample tone. The experimenter could then look at the frequency
selected by the observer and see just how closely he or she actually matched the
sample tone. In vision research, the experimenter may present a stimulus of particu-
lar brightness. The participant would have to adjust another stimulus to be equally
bright to the first one. And, returning to our chili pepper example, an experimenter
might present a chili pepper sauce as the sample taste. Then a participant would have
to adjust the level of capsaicin in a second sample to match the level of hotness in
the first. To see and experience an auditory example of the method of adjustment, see
ISLE 2.4 and try a PSE in ISLE 2.5.
Stimulus level
100
75
50
25
0
5 10
Threshold
P
e
rc
e
n
ta
g
e
r
e
p
o
rt
e
d
“
S
e
e
n
”
15 20
100
75
50
25
0
5 10
I see it
I don’t see it
Stimulus level
P
e
rc
e
n
ta
g
e
r
e
p
o
rt
e
d
“
S
e
e
n
”
15 20
(a) (b) FIGURE 2.6
Measuring Threshold
These graphs illustrate how
we measure the threshold in
psychophysical experiments. In
Figure 2.6a, we see a hypothetical
cutoff at a particular level of
intensity that separates the stimulus
level at which we see the stimulus
and the stimulus level at which
we do not see the stimulus. Figure
2.6b illustrates that in most cases,
thresholds vary from trial to trial,
and we must estimate the threshold
from the point at which participants
are 50% likely to say “saw it” and
50% likely to say “didn’t see it.”
Method of adjustment: a
method whereby the observer
controls the level of the stimulus
and “adjusts” it to be at the
perceptual threshold
Point of subjective equality
(PSE): the settings of two
stimuli at which the observer
experiences them as identical
ISLE 2.4
Method of Adjustment
ISLE 2.5
Point of Subjective Equality
34 Sensation and Perception
Closely related to the concept of threshold is the concept of sensitivity. Sensitivity
is the ability to perceive a particular stimulus. It is inversely related to threshold.
As the threshold goes down, the observer is deemed to be more sensitive. That is,
lower thresholds mean higher sensitivity. This makes sense when one considers that
threshold refers to the ability to perceive a stimulus at smaller and smaller levels
of that quantity. Thus, a person who can hear a sound at 10 decibels (dB) is more
sensitive than a person who can hear the sound only at 15 dB. A person who can
smell a perfume at smaller concentrations in the air is more sensitive to that odor
than someone who requires larger concentrations. Sensitivity may vary across situa-
tions. For example, one may be more sensitive to changes in the intensity of light in
a room when one has just been in a dark room than when one has just come out of
the brilliant sunshine.
Magnitude Estimation
Magnitude estimation is a psychophysical method in which participants judge and
assign numerical estimates to the perceived strength of a stimulus. This technique was
developed by S. S. Stevens in the 1950s (e.g., Stevens, 1956). Magnitude estimation usu-
ally works in the following way. An experimenter presents a standard tone and assigns
it a particular loudness value, say 20. Then the participant must judge subsequent tones
and give them numerical values, in comparison with the standard. So if the participant
thinks the new tone is twice as loud as the standard, it should be assigned a 40. If the
next tone is just a bit softer than the standard, it may be assigned a 15. If the tone is
heard to be much softer than the standard, it might receive a 5 on this hypothetical
scale of loudness.
Magnitude estimation can also be used for visual experiments. It follows the same
principle: In brightness estimation, a sample light might be given a standard value,
and then other samples are judged in relation to the standard. Magnitude estimation
can be adapted to just about any perceptual dimension. Participants may be asked to
judge the brightness of light, the lengths of lines, or the sizes of circles on a numerical
scale. For visual and auditory examples of magnitude adjustment, go to ISLE 2.6.
As experimenters in a psychophysics experiment, we can control the stimulus. For
example, we can have people taste and make judgments of the sweetness of a sample
with a known quantity of sugar, say 1 teaspoon per gallon. We then present them
with a sample of a solution of sugar water calibrated to 2 teaspoons per gallon. The
new stimulus has twice as much sugar in it per unit of water, but is it perceived as
twice as sweet? In all sensory systems, there is a phenomenon called response com-
pression. Response compression means that as the strength of a stimulus increases,
so, too, does the perceptual response, but the perceptual response does not increase
by as much as the strength of the stimulus increases. That is, if you judge the first
sugar-water solution as a 5 on the sweetness scale, doubling the sugar in the solution
will cause an increase in your sweetness judgment but not a doubling of the perceived
sweetness. In fact, you will likely judge the 2-teaspoon solution as a 7 or an 8 on the
sweetness scale.
There is an exception to the response compression rule for sensory perception,
and that involves pain perception. In pain perception, there is response expansion
instead of response compression. Response expansion means that as the strength
of a stimulus increases, the perceptual response increases even more. In this case,
if a person receives an electric shock of physical intensity 10 and judges it to be
5 on a pain scale, increasing the physical intensity to 20 will lead to a more than
doubling of the judgment, to perhaps 15 on the pain scale. That is, smaller incre-
ments of increase in the physical dimension (e.g., electric shock) lead to greater
ISLE 2.6
Magnitude Estimation
Sensitivity: the ability to
perceive a particular stimulus; it
is inversely related to threshold
Magnitude estimation: a
psychophysical method in which
participants judge and assign
numerical estimates to the
perceived strength of a stimulus
Response compression:
as the strength of a stimulus
increases, so does the
perceptual response, but the
perceptual response does not
increase by as much as the
stimulus increases
Response expansion: as
the strength of a stimulus
increases, the perceptual
response increases even more
Stevens’s power law: a
mathematical formula that
describes the relationship
between stimulus intensity and
our perception; it allows for
both response compression
and response expansion
35 Chapter 2: Research Methodology
increments in the perception of the perceptual characteristic (e.g.,
the perception of pain).
Stevens (1957, 1961) developed an equation to try to encapsu-
late both types of data sets (this is one of just a few mathematical
equations that will be presented in this book). It is called Stevens’s
power law, and it is as follows:
P = cIb
In this equation, P is equal to the perceived magnitude of a stim-
ulus, that is, how bright we perceive a light to be or how sweet we
perceive a sugar solution to be. I is equal to the intensity of the actual
stimulus. Thus, at the simplest level, our perception is a function of
the physical intensity of the stimulus. However, there are two other
parts of the equation that explain the relation between perception
and the physical stimulus. The letter c represents a constant, which
will be different for each sensory modality or for each sensory dimen-
sion. The constant also allows you to scale your measure appropri-
ately. For example, both Fahrenheit and Celsius temperature scales
measure the same underlying property, but they do so with different
scales. The exponent b equals the power to which the intensity is
raised. It is this exponent b that allows response compression and
response expansion. Response compression occurs when b is less
than 1, and response expansion occurs when b is greater than 1.
Thus, Stevens’s power law equation can account for both types of
subjective responses. This is depicted in Figure 2.7. For a graphical
demonstration of how this works, go to ISLE 2.7.
To give an example, let us return to the Scoville scale. We could
present a chili sauce with 1 milligram of capsaicin per kilogram
of other substances. We tell people that this is a 1 on the piquancy scale. We then
increase the dosage to 2 mg/kg. Thus, we have doubled the active “hot” ingredient.
Applying Stevens’s law, we need to know the constant and the exponent to determine
a person’s perceptual response. Because capsaicin stimulates pain receptors, we can
expect an exponent of greater than 1 (and hence response expan-
sion). Thus, the hotness judgment should be more than double
the baseline, leading to a hotness judgment of greater than 2. We
must know the psychological response in order to apply Stevens’s
law. That is, knowing the amount of capsaicin in a food would
not have allowed Scoville to measure piquancy. He needed the psy-
chophysical measure to map response expansion. A few exponents
for Stevens’s power law are given for different sensory domains
in Table 2.2. A value greater than 1 indicates response expansion,
whereas a value less than 1 indicates response compression.
Catch Trials and Their Use
One of the potential difficulties that arise with the traditional methods
of limits, constant stimuli, and adjustment is that the participant might
be willingly or unwillingly misinforming the experimenter about perceptual experience.
For example, a participant may indicate that he heard a sound when he was not sure
or perhaps because he thinks a sound should have occurred even though he did not
perceive one. Or worse, perhaps the participant wants to impress the experimenter with
100
75
50
25
0
Electric shock
Bar length
Brightness
Physical intensity of
stimulus
P
e
rc
e
iv
e
d
i
n
te
n
si
ty
o
f
st
im
u
lu
s
FIGURE 2.7 Comparison of the Physical
Intensity of a Stimulus and Its Perceptual
Correlate
In response compression, as the physical intensity
of a stimulus increases, its perceptual correlate
increases as well, but not by as much. In response
expansion, as the physical intensity of a stimulus
increases, its perceptual correlate increases even
more. The curve for brightness illustrates response
compression, whereas the curve for electric shock
illustrates response expansion
ISLE 2.7
Stevens’s Power Law
Sense Perception Exponent
Vision Brightness 0.3
Audition Loudness 0.5
Taste Sweetness 0.8
Vision Apparent length 1.0
Touch Pain 3.5
TABLE 2.2
Stevens’s Power Law Exponents
Source: Adapted from Stevens (1961).
36 Sensation and Perception
his extraordinary sensory abilities. In all of the methods described so
far, it would be easy to do; you could simply report that you see or hear
the stimulus when you do not. Because the stimulus is always present,
even at a very soft volume or at a very low brightness, the experimenter
cannot know if the participant is being truthful or not. One technique
to counter this strategy is to use catch trials. A catch trial is a trial in
which the stimulus is not presented. It is easy to insert these trials as
checks on the participant’s accuracy and honesty. Thus, in catch trials,
the correct answer is “No, I didn’t hear it” or “No, I didn’t see it.” If a
participant reliably says that she saw the stimulus in a catch trial, we
can dismiss this participant as an unreliable observer.
Another method that circumvents problems of false reporting is
the forced-choice method (Blackwell, 1953; Jones, 1956). In every
trial, the subject is asked to report either when the stimulus occurred
or where it occurred. Thus, instead of determining whether a light
was present or not, the participant must decide if a light was present
in one location or another or at one time slot or another time slot.
Instead of determining whether the participant heard a sound or not,
the participant must determine in which of two time intervals there
was a sound or not. This technique prevents the need for catch trials
because the observer cannot simply say “yes” in every trial, regard-
less of the presence of a stimulus in that trial. But it also allows the
determination of thresholds, because if a stimulus cannot be detected, performance
will be at chance (50% if there are two choices). Threshold can be determined by
finding a level of performance that is significantly above chance. See ISLE 2.8 for an
illustration of the forced-choice method (also see Figure 2.8).
TEST YOUR KNOWLEDGE
1. What is the point of subjective equality (PSE)? Why is it critical when using the
method of adjustment?
2. How can the equation to represent Stevens’s power law explain both response
compression and response expansion?
2.2 Demonstrate an understanding of signal detection theory.
Signal Detection Theory
On July 3, 1988, Iran Air Flight 655 was shot down by a U.S. missile from the
Navy vessel U.S.S. Vincennes (Figure 2.9). All 290 passengers and crew, including
66 children, were killed. Although the United States has never apologized to Iran,
the U.S. government gave $61 million to the relatives of the victims of the attack.
The incident took place at a time when there was heavy tension between the United
States and Iran, and Iranian jets had previously attacked U.S. Navy vessels. However,
in this case, the radar operators on the Vincennes mistakenly judged the civilian
airplane, an Airbus 300, to be an incoming Iranian F-14 fighter, with the horrify-
ing consequences described here. How had the Navy made such a terrible mistake?
We will couch an explanation of how this disaster occurred in terms of one of the
most influential theories in the history of sensation and perception research, namely,
signal detection theory.
Consider the radar specialist examining the screen that depicted incoming objects.
He or she had to decide, on the basis of the information available on the radar screen,
ISLE 2.8
Forced-Choice Method
Catch trial: a trial in which the
stimulus is not presented
Forced-choice method: a
psychophysical method in which
a participant is required to
report when or where a stimulus
occurs instead of whether it
was perceived
Signal detection theory: the
theory that in every sensory
detection or discrimination,
there is both sensory sensitivity
to the stimulus and a criterion
used to make a cognitive
decision
FIGURE 2.8 Illustration of the
Forced-Choice Method
The participant in this experiment is engaged in
a psychophysical task using the forced-choice
method, pressing the right or left button to
indicate where a light displays on the screen.
37 Chapter 2: Research Methodology
whether the incoming object was an enemy warplane (an
Iranian F-14) or a harmless jetliner (an Airbus 300). In
1988, this involved examining a radar screen and making
a judgment as to the nature of the incoming airplane. The
United States had (and has) complicated procedures to dif-
ferentiate military and civilian airplanes on incoming radar.
But in a war zone with an object approaching you at 600
mph, decisions must be made quickly.
From the U.S. Navy’s standpoint, there are two types
of errors. The Navy could mistake a civilian airplane for
a military jet, or it could mistake a military jet for a civil-
ian airplane. Both of these errors could have fatal conse-
quences for innocent people, as indeed they did in this case.
In the Vincennes case, the mistake that arose is called a
false alarm. A false alarm, in psychophysical terms, occurs
when the observer mistakes a harmless or null signal for
a dangerous or an active signal. The other type of error
is called a miss, in which a harmful signal is perceived as
harmless. In one case, the danger is to innocent civilians aboard the aircraft, whereas
in the other case, the danger is to equally innocent personnel aboard the Navy vessel.
Thus, in this situation, everything must be done to avoid both errors (Table 2.3).
In such a situation, there are also two potential correct responses. A correct rejection
occurs when a harmless signal is perceived as harmless, and a hit occurs when a
harmful signal is correctly perceived as harmful. In the case of the Vincennes, the
correct response should have been a correct rejection. The plane was a civilian jet-
liner that offered no threat to the Navy. In this example, a hit would have occurred if
the radar had correctly identified an incoming military warplane as a threat. Military
action must optimize hits and correct rejections in order to achieve strategic objec-
tives and minimize civilian casualties. Thus, one of the goals of any military surveil-
lance equipment is to maximize hits and correct rejections while minimizing false
alarms and misses.
Consider a radar operator examining the signal on his or her radar screen. Such
an operator may be more likely to define a signal as “dangerous” if the signal is
coming from an aircraft over the Strait of Hormuz, especially after recent attacks on
the U.S. Navy, than if he or she is monitoring aircraft flying over the skies of central
Nebraska. This differing judgment on the basis of situation is called the criterion. In
Nebraska, the radar specialist will select a very high criterion, so as to avoid false
alarms, and misses are less of a concern. However, when a Navy vessel is patrolling
the Strait of Hormuz, near a highly hostile Iranian government, which has recently
launched attacks against U.S. ships, the criterion will be lower, as there are more
risks in the environment and the Navy does not want to miss an actual attack; thus,
False alarm: in signal detection
analysis, a false alarm is an
error that occurs when a
nonsignal is mistaken for a
target signal
Miss: in signal detection
analysis, a miss is an error that
occurs when an incoming signal
is not detected
Correct rejection: in signal
detection analysis, a correct
rejection occurs when a
nonsignal is dismissed as not
present
Hit: in signal detection analysis,
a hit occurs when a signal is
detected when the signal is
present
Criterion: a bias that can
affect the rate of hits and false
alarms
Incoming Signal
Response Is a Fighter Jet Is a Civilian Plane
Think it is a fighter jet Shoot down enemy plane Innocent civilians killed
Think it is a civilian plane Innocent sailors killed No hostile interactions
TABLE 2.3 Signal Detection Theory: Is It a Threat?
FIGURE 2.9 The U.S.S. Vincennes
The U.S.S. Vincennes, seen here in 2005, was a guided-missile
cruiser. In 1988, its crew mistakenly shot down a civilian
aircraft. This error, called a false alarm in psychophysical
terminology, had devastating consequences.
A
P Photo/G
reg English
ISLE 2.9
Signal Detection Experiment
38 Sensation and Perception
there is greater risk for more false alarms. This is exactly what happened off the
coast of Iran in 1988. Thus, this military tragedy fits into the logic of signal detection
theory, as we will shortly see (Green & Swets, 1966). See ISLE 2.9 to play such a
war game yourself.
Here’s another way of thinking about signal detection theory (Figure 2.10).
Consider the following situation: You are driving down the road, and you think
you hear a noise from the engine that sounds like a clunk. However, with your
stereo playing and the sounds of the road, you are not sure exactly what the clunk
is. If your car is relatively new and has a history of smooth running, perhaps you
will decide that you didn’t really hear anything (high criterion). Your hearing is
“playing tricks” on you. However, if you are driving an old car that has a history
of spending nearly as much time in the shop as on the road, you might decide
that you did hear something and head to the nearest service center (low criterion).
What is important in this example is that even in this very basic sensory discrim-
ination, there is a cognitive decision-making element that needs to be taken into
account. This is another practical example of the situations for which signal detec-
tion accounts.
So let us look at a model of signal detection starting with a visual detection
example (Table 2.4). Signal detection assumes that there is “noise” in any system.
On occasion, this noise may be mistaken for an actual signal. In these examples,
what should have been seen as noise, in the military sense, was mistaken for a mili-
tary signal by the crew of the Vincennes. This noise may occur because of distortion
on the screen or a wobble on the radar caused by atmospheric conditions. Similarly, if
we have an old car, we may hear
“clunks” even when the car is
operating effectively. This noise
in the system may be other sounds
from the road, tinnitus in our
ear, or something rustling in
the trunk. Thus, the task for
the observer is to distinguish
an actual signal from the back-
ground noise. In a vision thresh-
old experiment, this might be
the actual dim light in the noise
produced by random firing of
retinal receptors.
So consider first the case in
which there is a faint signal. We
can detect it (hit) or not detect it
(miss). But there is also the case
in which the signal is absent. In
that case, we may detect some-
thing (false alarm) or correctly
realize that there is no signal
(correct rejection). Signal detec-
tion theory states that we must
consider all four possibilities to
successfully measure thresholds.
FIGURE 2.10
Old Car/New Car
When we think we hear a noise
associated with an engine
malfunction, we adopt different
criteria, depending on the situation.
If we are driving the old clunker
(a), we may adopt a more liberal
criterion for hearing an engine
problem. This will help us catch
engine trouble (hits) but may also
increase the rate of bringing the
car to the shop when there is no
problem (false alarm). If we are
driving the shiny new sports car (b),
we may adopt a more conservative
criterion for hearing an engine
problem. This will increase the
likelihood of correctly dismissing
a sound as noise rather than a
mechanical problem (correct
rejection) but may increase the
likelihood that we do not hear a
problem when there is one (miss).
©
iS
to
ck
Ph
ot
o.
co
m
/n
w
in
te
r
©
iS
to
ck
Ph
ot
o.
co
m
/R
aw
pi
xe
l
(a)
(b)
39 Chapter 2: Research Methodology
Consider a situation in which there is little noise in the system. Imagine if the
captain of the Vincennes in 1988 had access to 2018 satellite imaging (perhaps cour-
tesy of Dr. Who, the fictional time-traveling British superhero). In this case, there
is little noise in the system. He could watch the video feed from the satellite and
see that the incoming plane is an Airbus rather than an F-14. In this case, there
would be few false alarms and few misses, only hits and correct rejections. But in
1988, the radar technology had noise in the system, presumably generated by any
number of atmospheric conditions. Thus, the noise introduces the potential for error
in the system.
These differences are represented graphically in Figure 2.11. In the figure, we con-
sider a common psychophysical task, detecting a soft sound in a quiet environment.
The Signal Is
Response Present Absent
Perceived it Hit False alarm
Did not perceive it Miss Correct rejection
The Clunk
Response Actual Did Not Happen
Think it happened You get needed service You make an unneeded
service visit
Think it did not happen You break down You go happily on your way
FIGURE 2.11
Signal Detection Theory
Illustrated Graphically
Figure 2.11a shows the
continuum of neurons firing
in response to a soft or an
absent sound. Figure 2.11b
shows a potential distribution
for perceiving the soft sound or
misperceiving the absent sound.
Figure 2.11c adds the criterion.
Figures 2.11d through 2.11g show
correct rejections, hits, false
alarms, and misses.
N
u
m
b
e
r
o
f
in
st
a
n
ce
s
N
u
m
b
e
r
o
f
in
st
a
n
ce
s
Less More
Your perception
Less More
Sounds like phone
Less More
Sounds like phone
NO YESCriterion
NO YESCriterionNO YESCriterionNO YESCriterionNO YESCriterion
(d) Correct rejection (e) Hit (f) False alarm (g)
(a) (b) (c)
Miss
Less More
Sounds like phone
Less More
Sounds like phone
Less More
Sounds like phone
Less More
Sounds like phone
Shower “noise” alone
Ring + noise
TABLE 2.4A Signal Detection Theory: Possible Situations
TABLE 2.4B Signal Detection Theory: Possible Situations
40 Sensation and Perception
Noise here can be defined as random neuronal firing—think of the odd “sound” you
experience but are not sure if it is for real. Thus, a hit occurs when we detect a soft
sound when present, and a false alarm represents when we think we heard a soft
sound when one was not present. A correct rejection occurs when we say that no
sound was present when no sound was present, but a miss occurs when we say that
no sound was present when in fact there was a soft sound. Each of these situations
is represented in the figure.
Let’s return now to an idea introduced in comparing the threat in the Strait of
Hormuz and the threat in Nebraska, that is, the idea of a criterion in signal detec-
tion theory. The criterion is an internal cutoff determined by the observer, above
which the observer makes one response and below which the observer makes another
response. Translated into technical terms, then, the criterion is a bias that can affect
the rate of hits and false alarms. Thus, in the Strait of Hormuz, we adopt a criterion
or an internal cutoff to respond at a lower threat level than we do in Nebraska. After
all, we assume that the danger of an incoming enemy aircraft is much higher off the
coast of a hostile nation than in the safety of the middle of our own. In our other
example, if the clunking sound is above a certain level of loudness, we decide that
there really is a clunk, and there is a problem with the car. If it is below that level
of loudness, we decide that there is no reason to worry. This cutoff point may be
different depending on whether we have a new car or that old clunker. Similarly, in
a psychophysical study, the criterion determines the level of stimulation above which
we decide a light is present and below which we decide not to indicate the presence
of the light.
However, criteria vary depending on the situation. You might adopt a lax crite-
rion for hearing the clunk if your car is old and has a history of engine problems.
That is, you are more likely to attribute the clunk to the car than to random road
sounds. This means you will risk more false alarms to catch all hits—you don’t want
your car to fall apart at 70 mph on the highway. But there is little cost to taking it
the shop one more time. Alternatively, if your car is new and has just been checked
by a mechanic, you may adopt a stricter strategy. This means that you are more likely
to attribute the noise to the road and not to the car. In signal detection terms, this
means a greater desire to avoid false alarms (not
paying extra money to the mechanic) and risking
missing hits (i.e., a breakdown, which you think
is unlikely).
Thus, a criterion is a value set by the observer
depending on circumstances that only he or she
knows. If the stimulus is above the criterion, the
observer will say “yes” or “present,” but if the
stimulus is below the criterion, the observer will
say “no” or “absent.” Consider how the concept
of a criterion might apply to real-world decisions.
A radiologist screening for breast cancer must
weigh the risks of unnecessary testing against the
risk for cancer in evaluating a mammogram. If
the woman is young and has no family history
of breast cancer, the radiologist might adopt a
stricter criterion, not wanting to risk a false alarm
and put the woman through the pain of taking a
FIGURE 2.12 Sensitivity
Sensitivity is the ability to distinguish a noise signal from an actual signal,
such as the difference between random noise and the clunking sound in
your car. Figure 2.12a shows an example of when the perceiver has no
sensitivity—it is impossible to tell the difference between signal and noise.
Figure 2.12b shows when the perceiver is somewhat better at distinguishing
signal from noise, and Figure 2.12c shows much higher sensitivity.
N
u
m
b
e
r
o
f
in
st
a
n
ce
s
N
u
m
b
e
r
o
f
in
st
a
n
ce
s
N
u
m
b
e
r
o
f
in
st
a
n
ce
s
Less More Less More
Sounds like phone
d’ = ∼4d’ = ∼1d’ = ∼0
Sounds like phoneSounds like phone
Less More
(a) (b) (c)No sensitivity Moderate sensitivity High sensitivity
Shower “noise” alone
Ring + noise
Sensitivity (signal detection
theory): the ease or difficulty
with which an observer can
distinguish signal from noise
d′ (d-prime): a mathematical
measure of sensitivity
Receiver-operating
characteristic (ROC) curve: in
signal detection theory, a plot of
false alarms versus hits for any
given sensitivity, indicating all
possible outcomes for a given
sensitivity
41 Chapter 2: Research Methodology
tissue sample. However, if the woman is older or
has a family history of breast cancer, the radiolo-
gist may adopt a more lax criterion, not wanting
to make a miss, and recommend further testing.
Mammographic screening is very effective, but
there are still misses and false alarms to be con-
cerned about.
There is one last piece to understand in sig-
nal detection theory. Sensitivity, as used in sig-
nal detection theory, is the ease or difficulty with
which the observer can distinguish the signal
from noise. That is, sensitivity measures how
easy it is to tell if a signal is present or absent
(Figure 2.12). Thus, one can imagine a radar
operator with 1948 technology and one with
2018 technology. The older system has lower sen-
sitivity, so it is harder to determine the nature of
the incoming threat. The 2018 version has higher
sensitivity, so it is easier to tell the difference between a harmless
passenger plane and a dangerous enemy fighter jet. Similarly, if
you have had a “clunking” problem before, you may know exactly
what to listen for. Therefore, it will be easy to distinguish between
noise and the clunk.
An observer with high sensitivity will be able to make mostly
hits and correct rejections. But, as you can see in Figure 2.12,
as sensitivity decreases, more false alarms and misses occur.
As sensitivity increases, the observer has more hits and correct
rejections. Thus, when you know what distinguishes between
noise and clunks, you will make few mistakes and catch the
car if it is on the brink of breaking down and ignore the
sound if you know that it is just random noise. In psychophysics,
if you know the relation of hits to false alarms, you can
determine d′ (d-prime), which is a mathematical measure of
sensitivity.
Sensitivity and criterion interact in interesting ways.
Sensitivity may be high, but if the criterion is relatively low,
there still might be many false alarms. Even if sensitivity is
high, if the criterion is very loose, there still might be many
false alarms. That is, even if our radar system is very good at
detecting enemy aircraft, a trigger-happy officer might still be
making too many false alarms. This is illustrated in Figure 2.13.
You can also review all of the issues related to signal detection
theory in ISLE 2.10.
For any given sensitivity d′, there is a range of possible out-
comes according to signal detection theory. To simplify seeing all of the possible out-
comes for a given signal strength, researchers have developed a way to summarize all
of the possible outcomes for this situation across all possible criteria. This summary
is called the receiver-operating characteristic (ROC) curve (Figure 2.14). The ROC
curve is a graphical plot of how often false alarms occur versus how often hits occur
FIGURE 2.13 Hits and False Alarms
When sensitivity is kept constant, there can still be differences in the ratio
of hits to false alarms, depending on the criterion. Figure 2.13a shows a lax
criterion, which allows many false alarms but maximizes hits. Figure 2.13b
shows a medium criterion, and Figure 2.13c shows a strict criterion, which
minimizes false alarms but also reduces the detection of hits.
Shower “noise” alone
Ring + noise
N
u
m
b
e
r
o
f
in
st
a
n
ce
s
N
u
m
b
e
r
o
f
in
st
a
n
ce
s
N
u
m
b
e
r
o
f
in
st
a
n
ce
s
Less More Less More
Sounds like phoneSounds like phoneSounds like phone
Less More
(a) (b) (c)“Gotta get that call!” “Is that the phone?” “What phone?”
FIGURE 2.14 Receiver-Operating
Characteristic (ROC) Curves for Different Values
of d′ (Sensitivity)
When d′ = 0, sensitivity is zero, and the perceiver
cannot discriminate between signal and noise. As d′
increases, hits and correct rejections increase, and
misses and false alarms decrease. If d′ were perfect,
we would get only hits and correct rejections, but in
the real world, d′ is never perfect.
Correct rejection Pr (N/n)
False alarm Pr (S/n)
1.0
1.00
0
1.0 0
01.0
H
it
P
r
(S
/s
)
M
iss P
r (N
/s)
d’ = 2
d’ = 1.5
d’ = 0.75
d’ = 0
Ch
an
ce
d
ia
go
na
l
ISLE 2.10
Signal Detection Theory
42 Sensation and Perception
for any level of sensitivity. See ISLE 2.11, in which you can adjust the criterion and
the sensitivity and see what the ROC curve looks like.
The advantage of ROC curves is that they capture all aspects of signal detec-
tion theory in one graph. Sensitivity, or d′, is captured by the “bow” in the curve.
The more the curve bends up to the right, the better the sensitivity. Moving
along the bow captures the criterion. As one moves up any individual level
of sensitivity, the higher you go, the more loosely you are setting your criterion,
thus opening the possibility of more hits but also more false alarms. Regarding
Figure 2.14, the blue line indicates the highest d′. This observer can set her crite-
rion low and still catch many hits while minimizing false alarms. For the observer
represented by the green line to make as many hits, he risks more false alarms.
If the blue line and green line were radar operators, we would prefer to have Blue
line making decisions, as she has a higher sensitivity. Depending on circumstances,
she can set her criterion low or high and achieve the accuracies indicated on the
ROC curve.
ROC curves are also important in evaluating medical decision making.
Consider radiologists evaluating computerized tomographic (CT) scans looking for
brain tumors. They want to be able to detect as many brain tumors as possible but
also minimize the risk for false alarms, as false alarms can be quite dangerous—one
does not want to initiate brain surgery if there is
nothing wrong with the patient’s brain. So in eval-
uating radiologists, we want those with the highest
values of d′, that is, those who can best distinguish
real tumors from false alarms in the CT scans. And
we may also want them to set intermediate crite-
ria, because false alarms also come with risk (Xue,
Peng, Yang, Ding, & Cheng, 2013).
TEST YOUR KNOWLEDGE
1. What is signal detection theory? How does it
differentiate between accurate perception and
errors?
2. What is d′ in signal detection theory? Why is it
important in graphing ROC curves?
2.3
Evaluate neuroscience methods and
what they tell us about
sensation and perception.
Neuroimaging Techniques
Neuroimaging techniques are technologies that permit visual examination of living
human brains. These techniques allow scientists to correlate perception with brain
activity. Neuroimaging techniques are also used to investigate memory, attention,
problem solving, and emotion. Two goals of neuroimaging are to reveal where per-
ception happens in the brain and how perception unfolds through the brain over
time. To reveal the particular area(s) in the brain where a specific process occurs,
scientists use these methods to develop spatial maps of the brain, which show the
FIGURE 2.16 Magnetoencephalography (MEG)
In MEG, magnetic sensors detect magnetic fields produced by the
electrical activity in the brain. MEG has better spatial resolution than EEG.
Th
e
Sy
dn
ey
M
or
ni
ng
H
er
al
d/
Fa
irf
ax
M
ed
ia
/G
et
ty
Im
ag
es
FIGURE 2.15
Electroencephalography (EEG)
In EEG, electrodes monitor the
electrical output of large numbers
of neurons in the brain. The more
electrodes that are placed on the
scalp, the better the ability will
be of the EEG to specify spatial
locations in the brain.
©
iS
to
ck
ph
ot
o.
co
m
/f
ot
og
ra
fix
x
Electroencephalography
(EEG): using electrodes to
measure the electrical output of
the brain by recording electric
current at the scalp
ISLE 2.11
Signal Detection Theory
and the Receiver-Operating
Characteristic (ROC) Curve
43 Chapter 2: Research Methodology
areas that are active during perceptual tasks. To ascertain
changes in activity in the brain over time, scientists use
neuroimaging pictures in quick succession to find the time
course of perceptual processes. The field of neuroimag-
ing is changing quickly, but we review four of the main
techniques.
1. Electroencephalography (EEG). In EEG, up to 128
electrodes are positioned on a person’s scalp (Figure
2.15). The electrodes detect electrical signals created
by the brain. Areas of the brain that are active gener-
ate faster changing electrical signals than those that
are not active, and thus, by comparing electrical out-
put across electrodes, we can approximate where a
perceptual process is coming from in the brain. EEG
picks up a continuous electric signal, which allows
for measurements to be made every millisecond.
Thus, EEG allows for determining the time course of
perceptual processes in the brain.
2. Magnetoencephalography (MEG). In MEG, magnetic sensors detect small mag-
netic fields produced by the electrical activity in the brain (Figure 2.16). MEG
detects rapid changes in the brain, although at a less precise time scale than
does EEG. However, MEG produces better spatial maps of the brain than EEG,
though not as good as fMRI, discussed next.
3. Magnetic resonance imaging (MRI) and functional magnetic resonance
imaging (fMRI). In this technique, large magnetic fields align the oxygen
molecules within our brains (Figure 2.17). Then, as blood flows into
areas of the brain, the molecules’ organization is disrupted, which can be
detected by sensors in the MRI machine. The fMRI scanners take a pic-
ture approximately every 30 milliseconds, which allows scientists to
pinpoint both where and over what time course perceptual processes
are happening in the brain. Such fMRI scans are incredibly important
right now in determining the areas of the brain responsible for various
perceptual processes and the connections in the brain that link different
areas involved in the complex process of turning sensory stimulation into
experiences.
4. Transmagnetic Stimulation (TMS). We include a number of technologies
that can be grouped together under the general label of TMS (Figure 2.18).
These techniques stimulate the brain via electric current, but the specifics
of the technique and what kind of current use varies from one technique to
another. In TMS, researchers place a magnetic field generator (or coil) on the
head of participants. The coil induces an electric current in the particular
brain region beneath the coil, which induces changes in how this region func-
tions, which may be either perceptual or behavioral. In research, these changes
are temporary, but they permit the experimental analyses of brain region and
function. Indeed, a TMS pulse to the occipital lobe can induce temporary
blindness.
Magnetoencephalography
(MEG): using a magnetic
sensor to detect the small
magnetic fields produced by
electrical activity in the brain
Transmagnetic stimulation
(TMS): a procedure in which
a magnetic coil is used to
stimulate electrically a specific
region of the brain
FIGURE 2.17 Magnetic Resonance Imaging (MRI)
Large magnetic fields align the oxygen molecules within
our brains. Then, as blood flows into areas of the brain, the
molecules’ organization is disrupted, which can be detected by
sensors in the MRI machine.
BSIP/U
niversal Im
ages G
roup/G
etty Im
ages
FIGURE 2.18
Transmagnetic Stimulation
(TMS)
TMS techniques stimulate
the brain via electric current.
Researchers can see if perception
or behavior changes in a particular
domain as a function of that
stimulation, allowing researchers
to draw causal relations between
that brain region and perception.
G
aro/Phanie/Science Source
44 Sensation and Perception
EXPLORATION: Intersensory Perception
The chapters in this textbook cover vision, audition, the skin
senses, and the chemical senses. In these chapters, we discuss
the underlying neuroanatomy, the physiology, and the psy-
chological science of each area. However, real people mov-
ing and acting in the world are processing all of these senses
simultaneously. In many domains, understanding what is
going on in the world involves co-perceiving across two
modalities. For example, when we talk with someone, we
both listen to their words and watch their faces. When we eat
our dinner, we simultaneously taste our food, smell our food,
look at our food, feel the texture of the food in our mouths,
and, as discussed at the beginning of the chapter, feel the pain
caused by certain chemicals in our food. A natural question
arises as to whether or not one sensory system affects other
sensory systems, and, if so, how? This Exploration section
looks at some research that uses psychophysical measures to
address how olfaction (sense of smell) affects visual thresh-
olds (Robinson, Laning, Reinhard, & Mattingley, 2016).
In order to work through the work examining the effects
of odor on visual thresholds, a short digression is needed
concerning the nature of visual masking. Masking refers
to the difficulty in seeing one stimulus when it is quickly
replaced by a second stimulus that occupies the same or
adjacent spatial locations. In masking, a briefly shown
and to-be-detected stimulus that would normally be visi-
ble is rendered invisible by the presence of a second stim-
ulus that occurs in the same location immediately after
it or by stimuli that surround the test stimuli and per-
sist after the test stimulus disappears (Enns & Di Lollo,
1997). Because masking is not easy to imagine, please
take a moment to log onto ISLE and view the demon-
stration provided there (ISLE 2.12).
In a masking experiment, a to-be-detected stimulus is pre-
sented to participants somewhere in their visual field. The
stimulus may be a simple dot, a photograph of a face,
or even a word. The
to-be-detected stimulus
is presented for a very
short time span, perhaps
50 milliseconds. This is
long enough that if the stimulus is presented by itself, most
people will report seeing it. However, if the stimulus is
immediately replaced by another stimulus in the same area,
the person will not consciously detect the to-be-detected
stimulus. This is a phenomenon known as backward
masking (Breitmeyer & Hanif, 2008). Masking can also
occur if the to-be-detected stimulus is surrounded by other
stimuli that are presented at the same time and persist a
bit longer than the to-be-detected stimulus. If the masking
stimuli disappear at the same time as the to-be-detected
stimulus, the to-be-detected stimulus will be detected.
However, if the masking stimuli persist after the to-be-
detected stimulus, then it will be masked and consciously
invisible. This form of masking is called object-substitu-
tion masking (Enns & Di Lollo, 1997).
Because masking experiments require participants to
make decisions about whether a visual target is present
or not, they lend themselves to signal detection analyses.
In signal detection analyses, how good a person is at
detecting the stimuli is a measure of sensitivity. Indeed,
studies using masking usually report participants’ sensi-
tivity in terms of d′ analyses, which we covered in this
chapter. A high d′ means that participants are good at
detecting the stimulus when it is present but also good
at rejecting a trial when the stimulus is not present. This
brings us back to the topic of this section: Does the
presence of stimuli from another sensory domain affect
visual sensitivity? We can answer this question by look-
ing at the sensitivity of participants in a masking exper-
iment when stimuli from another sensory domain are
present or not. This question means presenting stimuli
from another sensory domain such as audition or olfac-
tion before or during a masking trial and determining if
the presence of the second sensory modality influences
the d′ of the participant in the masking task.
Robinson et al. (2016) were interested in whether olfaction
interacts with vision. To investigate this topic, they used
object-substitution masking. In the study, participants were
presented with images such as pictures of a leaf of mint, an
orange, or a rose flower. These were called “target” images
because, in some conditions, they would be accompa-
nied by the odors associated with each plant. Participants
were also presented with “nontarget images,” which were
images, such as those of a hat or a telephone, for which cor-
responding odors would not be presented. The odor that
was presented just before each trial either corresponded to
a target (i.e., the smell of a rose before an image of a rose
was flashed) or did not correspond to the target (i.e., the
smell of mint was presented just before an image of a rose
was flashed). In some conditions, the stimulus was masked
with the object-substitution masking, whereas in other
conditions, the target and nontarget images were presented
ISLE 2.12
Masking Demonstration
45 Chapter 2: Research Methodology
without masks and could be more easily seen. The ques-
tion that Robinson et al. were interested in was whether or
not the presence of a corresponding odor would lower the
threshold (or raise the sensitivity) of detecting masked stim-
uli. See Figure 2.19 for an illustration of their methodology.
Here is a summary of Robinson and colleagues’ (2016)
results. First, the masking manipulation worked. For
the masked trials, sensitivity was higher than for the
unmasked trials. On catch trials (where no target was
present), participants mostly claimed they could not see
anything. Thus, these results suggest that the object-
substitution masking manipulation was successful at
reducing the visibility of masked trials. Having established
that the masking worked, we can now look at whether
the presence of odors influenced performance on the
visual task. Note that if odors either strengthen the effect
of the masking or make the participants more sensitive to
the target stimuli, we can say that there is an odor–vision
interaction. Only if the odors have no effect on masking
can we reject the idea of an odor–vision interaction, at
least in this type of study. The results here are mixed. For
men, there was no effect of odor on the masking variable.
Men showed the same sensitivity in conditions in which a
congruent odor (mint–mint), an incongruent odor (mint–
orange), or no odor was presented. However, there was a
very strong effect with women. Women showed a much
stronger sensitivity to targets when there was a congruent
odor, but also showed a weakened sensitivity to targets
when the odor was incongruent relative to the no-odor
condition. Thus, for women, smelling the same odor as
the masked stimulus made that stimulus easier to visually
detect. But also, for women, when they smelled an odor
that did not match the visual stimulus, detecting the stim-
ulus was harder.
These results are consistent with the general advantage
women have over men with respect to their sense of
smell (Zucco, Aiello, Turuani, & Koster, 2012). However,
beyond that, Robinson et al. (2016) show a greater inte-
gration between vision and olfaction in women than
in men. This greater integration helps women, relative
to men, when the odor and the image match, but hurts
women, relative to men, when there is a mismatch. If you
are interested, you can read Robinson’s paper to explore
neurological explanations for the effect. We present their
results here to show you that psychophysical methods
such as threshold detection, sensitivity, and the signal
detection approach are alive and well in the contempo-
rary field of sensation and perception.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
MaleFemale
Congruent No Odor Incongruent
FIGURE 2.19 Sensitivity of Detection
The y-axis represents sensitivity. Lower values represent better
detection of the masked stimuli. Sensitivity in females was
helped by congruent odors, but sensitivity was also hurt by
incongruent odors. In men, however, odor had no effect at all,
either positive or negative.
APPLICATION: Psychophysics in
Assessment: Hearing Tests and Vision Tests
Our sensory capabilities are critical to living our lives in the
manner that we choose. One’s ability to make a livelihood,
attend school, and enjoy various recreational opportunities
is directly related to one’s ability to perceive the world accu-
rately. Take, for example, the everyday activity of driving a
car. Most of us have to drive to work or school. Driving
Masking: refers to the difficulty in seeing one stimulus when
it is quickly replaced by a second stimulus that occupies the
same or adjacent spatial locations
46 Sensation and Perception
is completely dependent on being visually competent. If
you become visually impaired, your ability to drive safely
decreases, and if you lose your eyesight, driving is no longer
an option. Once you get to school, you are also dependent
on your senses. You have to read a textbook and listen to
lectures. These require both vision and audition. Having
a conversation with anyone requires that your hearing
allow you to understand what others are saying. Even pain
allows us to recognize health issues that threaten us. Many
people will endorse the statement that eating delicious food
is one of life’s great pleasures.
But now, consider a student who is visually impaired or has
a hearing deficit. If you do not think you know any, you are
not paying attention. These impairments can range from
mild nearsightedness, requiring glasses or contact lenses,
to much more severe impairments. Being visually impaired
presents a number of obstacles that a sighted person cannot
even imagine. Even in a technological world that can offer
the visually impaired many ways of compensating for their
deficit and competing against normally sighted individuals,
being blind obviously creates obstacles. Blind students now
can use technology that automatically reads text aloud, but
text readers proceed more slowly than do sighted people
who typically can read while looking at text. Blind readers
who use Braille type can read silently, but this process is
also typically slower than reading by vision. So even with
the best technology, blind students work much harder and
longer to keep up with their sighted classmates. Auditory
impairment can be equally challenging. Those of us with
normal hearing take spoken language for granted. But deaf
individuals rely on sign language to communicate, which
renders reading and writing essentially the same as learning
a second language. Even less severe auditory impairment
can be challenging. Hearing aids may amplify sounds, but
it is often tricky to get them to amplify the sounds you want
to hear (e.g., voices) and not the sounds you do not want to
hear (e.g., traffic noise).
Assessing vision and hearing loss is an important task that
is fulfilled by professional optometrists and audiologists
with great competence. At the heart of each of these pro-
fessions is applying the ideas of psychophysics to diag-
nosing visual and auditory problems. In this Application
section, we take an in-depth look at this aspect of applied
psychophysics, that is, focusing on the psychophysics tests
optometrists and audiologists typically perform.
According to the National Institute on Deafness and Other
Communication Disorders, there are 35 million people in the
United States alone with some form of hearing impairment.
That’s roughly 10% of the nation’s population. In adults
65 years and older, the percentage exceeds 33% (National
Institutes of Health, n.d.). Hearing loss can be caused by
any number of factors, including genetic disposition, but
also age, disease, and exposure to noise. Hearing loss in
children and younger adults is usually due to genetic condi-
tions. But among older adults, hearing loss is just as likely
to be caused by environmental conditions. Hearing loss is
particularly common among those who work in professions
in which exposure to loud noise (or music) is chronic. This
includes airport employees, police officers, DJs and bartend-
ers at nightclubs, and, yes, rock musicians. Indeed, many
older rock musicians have serious hearing loss, including
Ozzy Osbourne, Phil Collins, and Pete Townshend.
Hearing loss can be divided into two broad categories,
sensorineural hearing loss and conductive hearing loss.
Sensorineural hearing loss refers to permanent hearing
loss caused by damage to the cochlea or auditory nerve.
This means that the hearing loss is due to problems in the
transduction of the physical sound waves into a neural
signal. Sensorineural hearing loss can result either from
genetic causes or from damage to hair cells or auditory
nerve fibers. Conductive hearing loss refers to the inabil-
ity of sound to be transmitted to the cochlea. This means
that the problem is that inadequate levels of sound reach
the cochlea to be transduced into a neural signal. Some
conductive hearing loss may be as simple as clogged path-
ways, but conductive hearing loss may also be permanent.
In many cases, medical treatment can restore hearing loss
caused by conductive causes, which may include earwax
buildup or a punctured eardrum (tympanic membrane).
Sensorineural hearing loss is seldom treatable, although in
extreme cases, cochlear implants can restore some hearing
lost through sensorineural damage.
The first step in assessing hearing loss is visiting a
professional audiologist. An audiologist is a trained
professional who specializes in diagnosing hearing
impairments. Audiologists usually train to the doctoral
level and obtain a degree known as a doctorate in audi-
ology (AuD). This qualifies them to diagnose and treat
hearing impairment (Figure 2.20). An audiologist can fit
a patient with the appropriate hearing aids or refer the
patient to a medical doctor if the audiologist thinks the
situation requires medical intervention.
Sensorineural hearing loss: permanent hearing loss caused
by damage to the cochlea or auditory nerve or the primary
auditory cortex
Conductive hearing loss: the inability of sound to be transmitted
to the cochlea
Audiologist: a trained professional who specializes in diagnosing
hearing impairments
47 Chapter 2: Research Methodology
The audiologist uses a device called an audiometer to assess
hearing loss. An audiometer can present tones of different
frequencies, from low in pitch to high in pitch, at different
volumes from soft to loud. A patient will listen on head-
phones in a soundproof room to a series of tones presented
by the audiometer. Tones are presented to one ear at a time, so
as to determine if there is hearing loss in each ear. Typically, an
audiologist will use the method of constant stimuli combined
with a touch of the forced-choice method and vary the loud-
ness of the tone among trials. The patient will typically indi-
cate if he or she heard the tone in the left or the right ear. If the
patient cannot hear the tone, this will be obvious from chance
performance for that frequency at that sound level. Usually,
the audiologist includes catch trials in which tones are not
presented. This allows the audiologist to determine the crite-
rion at which the patient is indicating hearing a sound.
After the test is complete, the audiologist will plot the
threshold for each frequency as a function of decibels.
That is, the audiologist makes a graph indicating how
loud each frequency needs to be in order for the patient
to hear it. The audiogram is the graph that illustrates the
threshold for the frequencies as measured by the audiom-
eter (Figure 2.21). The y-axis represents intensity, mea-
sured in decibels, and the x-axis represents frequency,
©
iStockphoto.com
/Fotosm
urf03
FIGURE 2.20 Audiologists
Audiologists are trained to treat hearing loss. They assess
hearing loss and help fit people with hearing aids. If medical
issues arise, they will forward patients to medical doctors who
specialize in auditory issues.
FIGURE 2.21 Audiology Report
This audiology report concerns a middle-aged woman with moderate sensorineural hearing loss. In the left graph, the y-axis indicates
how loud in decibel units a tone must be presented in order for the patient to hear it. The x-axis indicates frequency, from low
frequency (low notes) to high frequency (high notes). This patient shows maximum hearing loss for medium frequencies, unfortunately
in the range of human voices.
48 Sensation and Perception
measured in Hertz. The threshold is then compared with
a standardized curve, which represents normal or aver-
age hearing. This graph can then be used to determine
if there is hearing loss at any frequency. If there is, the
audiologist can help the patient with choosing hearing
aids or other remedies.
Particularly important for human hearing is the ability
to hear human speech sounds. Many hearing-impaired
people can detect sounds but have difficulty hearing
words, especially if there is background noise. A deficit
in hearing the voices of family members is often what
brings a patient to an audiologist in the first place.
Thus, audiologists will assess patients’ ability to hear
speech sounds against background noise. Specialized
tests have been developed to allow audiologists to check
for speech recognition in hearing-impaired individuals
in many different languages (Zokoll, Wagener, Brand,
Buschermöhle, & Kollmeier, 2012). In setting up hearing
aids for patients, audiologists can program the hearing
aids to filter out sounds that are not likely to be voices
and amplify sounds that are likely to be human voices.
When programmed correctly, hearing aids can selectively
filter out noise and increase the volume of human voices.
Turning now to vision, most of us may be more expe-
rienced with optometry, as minor visual problems are
more frequently corrected with eyeglasses than minor
auditory problems are corrected with hearing aids.
Optometrists have a similar job to audiologists but with
respect to vision. Optometrists provide most people’s
primary eye care. Optometrists have doctoral degrees in
optometry and are licensed to diagnose and give pre-
scriptions for many eye-related problems. But the most
common task they do is an eye examination, in which
they run a patient through a battery of tests, some to
look for diseases of the eye and others to look at basic
psychophysical properties of the vision of each patient.
Like audiologists, if an optometrist detects a medical
problem, that patient will be directed to an ophthalmol-
ogist, that is, a medical doctor who specializes in care
and diseases of the eye.
Included in the eye exam is a test of visual acuity. The test of
visual acuity measures a person’s ability to resolve an object
in focus at a particular distance. An individual person’s acu-
ity is then compared with a “standard” or normal reference.
The most common form of the test of visual acuity is the
ubiquitous Snellen chart (Figure 2.22). Using a Snellen chart,
an optometrist will ask a patient to read off the chart each
line until the letters become difficult to resolve. Typically,
this is done one eye at a time, as one eye may be normal
but the other may need to be corrected. Results from the
Snellen chart yield the typical measure of visual acuity that
most people are familiar with. A person of normal vision
is said to have 20/20 vision, as he or she can see what a
normal person can distinguish at 20 feet. If a person sees at
20 feet what a normal person sees at 60 feet, then that per-
son has 20/60 vision. If so, the optometrist would prescribe
corrective lenses, either glasses or contact lenses. In other
countries, these tests are done in meters, so 6/6 would be the
standard for 6 meters (6 meters = 19.7 feet).
Someone who has trouble seeing distant objects is
said to have myopia. Myopia is a condition in which
Audiometer: a device that can present tones of different
frequencies, from low in pitch to high in pitch, at different
volumes from soft to loud
Audiogram: a graph that illustrates the thresholds for the
frequencies as measured by the audiometer
Optometrist: a trained professional who specializes in
diagnosing visual impairments and diseases
©
iS
to
ck
ph
ot
o.
co
m
/a
lfa
br
av
oa
lfa
ro
m
eo
FIGURE 2.22 The Snellen Chart
A patient is asked to read the lowest line that he or she can.
This measures visual acuity and is the first test for myopia
(nearsightedness). Normal vision is considered 20/20. Anyone
who cannot see what a normal person can see at 20 feet may be
myopic.
49 Chapter 2: Research Methodology
incoming light does not focus directly on the ret-
ina but in front of it. An optometrist can easily treat
myopia by prescribing glasses or contact lenses. In
older adults, presbyopia becomes more frequent.
Presb yopia is a condition in which incoming light
focuses behind the retina, leading to difficulty focusing
on close-up objects. People with presbyopia need
glasses to read small print. Even adults who have
had 20/20 vision their entire lives are likely to develop
presbyopia as they age into their 40s and 50s. To see
what it would be like to have these conditions, go to
ISLE 2.13.
Optometrists serve as initial screeners and diagnos-
ticians of a number of diseases that affect the eye,
including glaucoma, macular degeneration, diabetic ret-
inopathy, and conjunctivitis. However, these diagnoses
do not require psychophysical testing, and therefore we
do not consider them
here. The American
Optometric Association
has valuable educa-
tional resources on its
website. If you are interested, go to http://www.aoa.org/
patients-and-public/eye-and-vision-problems?sso=y.
ISLE 2.13
Seeing With Myopia and Presbyopia
CHAPTER SUMMARY
2.1
Explain the nature of psychophysical scales and
how they measure the relations between real-
world stimuli and our perceptions of them.
In this chapter, we covered the basics of psychophysics.
The method of limits, the method of constant stimuli, and the
method of adjustment are used to determine psychophysical
properties of the observer, including the observer’s thresh-
olds, or ability to detect differences between stimuli along a
particular dimension. Absolute thresholds are the smallest
amount of a stimulus necessary for an observer to detect its
presence, whereas a difference threshold (also known as a
JND) is the smallest difference between two stimuli that can
be detected. Closely and inversely related to the concept of
threshold is the idea of sensitivity. Sensitivity is the ability to
perceive a stimulus. Magnitude estimation is a psychophysi-
cal method in which participants judge and assign numerical
estimates to the perceived strength of a stimulus. Magnitude
estimation fits Stevens’s power law, a mathematical formula
that describes the relation between the intensity of physical
stimuli and the magnitude of the perceptual response
2.2
Demonstrate an understanding of signal detec-
tion theory.
Signal detection theory is the theory that in every sensory
detection or discrimination, there is both sensory sensitivity
to the stimulus and a criterion used to make a cognitive deci-
sion. In signal detection theory, there is a trade-off between
successful detection of the target (e.g., a hit) and a detec-
tion response when there is no stimulus (e.g., a false alarm).
An observer wants to maximize his or her hits and correct
rejections (saying “no stimulus” when none is present) and
minimize his or her false alarms and misses (saying “no stim-
ulus” when a stimulus is actually present). Critical in signal
detection theory is the idea of sensitivity but also criterion,
an internal threshold, determined by the observer, above
which the observer makes one response and below which
the observer makes another response. Mathematically using
signal detection theory allows researchers to determine the
ROC curve, which is usually a plot of hits as a function of
false alarms.
2.3
Evaluate neuroscience methods and what they
tell us about sensation and perception.
Neuroimaging techniques are technologies that permit
visual examination of living human brains. These techniques
allow scientists to correlate perception with brain activity.
Two goals of neuroimaging are to reveal where perception
happens in the brain and how perception unfolds through
the brain over time. A number of different neuroimaging
techniques are reviewed in this chapter. EEG measures
electrical output of the brain. Although EEG provides good
temporal resolution of the brain, it lacks the spatial resolu-
tion of other methods. MEG measures the brain’s magnetic
fields. MEG provides good temporal resolution and better
spatial resolution than does EEG. In fMRI, magnetic fields
create a three-dimensional image that can capture both
the structure and the function of the brain. This technique
allows for good imaging of the brain in both time and space.
Finally, TMS is a procedure in which a magnetic coil is used
to stimulate electrically a specific region of the brain. This
allows one to probe the brain to see which areas produce
which kinds of perceptions.
Sensation and Perception50
REVIEW QUESTIONS
1. What does the Scoville scale measure? Why is it
considered to be a psychophysical scale?
2. What is the method of limits? How is it used to deter-
mine absolute thresholds?
3. What is the method of adjustment? How is it used to
determine the point of subjective equality?
4. What is the two-point touch threshold? How does it
illustrate the concept of a JND? How do two-point
touch thresholds differ across the human body?
5. What is the difference between response expansion
and response compression? How do both relate to
Stevens’s power law?
6. What is signal detection theory? How is it used to
predict performance on perception tests?
7. Define the terms criterion and sensitivity. How do
they interact in signal detection theory?
8. What are the neuroimaging techniques? How does
each one allow the brain to be examined in terms of
both space and time?
9. What is visual masking? How is it affected by consis-
tent and inconsistent odors?
10. How is an audiogram used to assess hearing loss?
How might an audiogram help an audiologist pro-
gram a hearing aid?
PONDER FURTHER
1. Why are the methods of psychophysics still relevant
and important when we have neuroimaging tech-
niques at our disposal? What information might we
still gather from psychophysics that we would not be
able to know by observing neuroimaging results?
2. Signal detection theory applies some basic mathe-
matics to understanding perceptual thresholds. But
we have also seen how it might apply in other situa-
tions, from military applications to deciding whether
your car needs to go to the shop. What other domains
of psychology or life in general might signal detection
analyses be good for? If you cannot think of any, try to
apply signal detection analysis to surfing!
KEY TERMS
Absolute threshold, 30
Ascending series, 31
Audiogram, 47
Audiologist, 46
Audiometer, 47
Capsaicin, 27
Catch trial, 36
Conductive hearing loss, 46
Correct rejection, 37
Criterion, 37
Crossover point, 31
d′ (d-prime), 41
Descending series, 31
Difference threshold (JND), 30
Electroencephalography (EEG), 43
False alarm, 37
Forced-choice method, 36
Hit, 37
Magnetoencephalography (MEG), 43
Magnitude estimation, 34
Masking, 44
Method of adjustment, 33
Method of constant stimuli, 32
Method of limits, 29
Miss, 37
Optometrist, 48
Point of subjective equality (PSE), 33
Psychophysical scale, 28
Receiver-operating
characteristic (ROC) curve, 41
Response compression, 34
Response expansion, 34
Scoville scale, 27
Sensitivity, 34
Sensitivity (signal
detection theory), 41
Sensorineural hearing loss, 46
Signal detection theory, 36
Stevens’s power law, 35
Transmagnetic
stimulation (TMS), 43
Two-point touch threshold, 31
Chapter 2: Research Methodology 51
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
2.1 Explain the nature of psychophysical scales and how they
measure the relations between real-world stimuli and our
perceptions of them.
Differences in Our Sensory Worlds: Invalid Comparisons
With Labeled Scales
The Two-Point Threshold: Not a Measure of Tactile Spatial
Resolution
2.2 Demonstrate an understanding of signal detection theory. “Utilizing” Signal Detection Theory
Tracking and Controlling Pain by Sight
What Is Signal Detection Theory?
2.3 Evaluate neuroscience methods and what they tell us about
sensation and perception.
Human Brain Activity Measured by fMRI
A Few Tips for Critically Evaluating fMRI Studies
Using EEG to Map Brain Dynamics
3Visual System: The Eye
LEARNING OBJECTIVES
3.1
Appraise the nature of light as electromagnetic energy to
explain the relation of wavelength to perception.
3.2 Sketch the anatomy of the eye to show how it makes vision possible.
3.3
Interpret how the retinae transduce light energy into
a neural signal that is sent to the brain.
3.4
Illustrate how the visual system adapts to the dark and then adapts
again to the light to help us adjust to changing light levels.
3.5
Diagram the receptive fields of retinal ganglion cells,
and show how they need contrast to operate.
3.6
Judge the different refractive errors and eye diseases
on how they affect the ability of the eye to see.
INTRODUCTION
We live in a visual world. As human beings, we typically first seek out information
around us with our amazing eyes and the visual system behind them. Indeed, our ability
to see affects so much of our lives. Before you read on, pause for a minute and think of
all the reasons for which we need to see. Write them down before reading on. We use
vision to read, to look at photographs on Instagram, and to ponder the stars at night by
observing them. We need to see to drive our cars, to cook our meals, to mow our lawns,
and to sew our clothes. Despite all the ways seeing is vital to us, most of us often take
seeing for granted. But all it takes is one scare with an eye injury, such as a detached
retina, or the onset of a disease, such as glaucoma, to make us realize how critical our
vision is to our everyday well-being. One of the authors (JHK) was playing pickup bas-
ketball. At his height, he is sometimes below the notice of defenders. In one game the
defender reached out and his fingernail scratched the cornea of the author’s eye. It was
a minor and temporary injury, thankfully, but for days the author was very sensitive to
light and had to wear sunglasses inside and often look down to avoid the lights. Driving
and many other visually demanding tasks were out of the question. Reading was nearly
impossible. It was a pretty tough way to begin the school year.
ISLE EXERCISES
3.1 The Basics of Waves
3.2 Accommodation
3.3 Presbyopia
3.4 Letters and the Fovea
3.5 Map Your Blind Spot
3.6 Photopic vs. Scotopic
Vision
3.7 Purkinje Shift
3.8 Convergence
3.9 Dark Adaptation
Function
3.10 Automatic Light
Adjustment in Cockpits
3.11 Center-Surround
Receptive Fields
3.12 Mach Bands
3.13 Correcting Myopia
and Hyperopia
3.14 Astigmatism
3.15 Living With Macular
Degeneration and
Retinitis Pigmentosa
3.16 Compound Eyes
3.17 Vision Prostheses
Mike Agliolo/Science Source
54 Sensation and Perception
Vision can also be a source of much joy to us (Figure 3.1). Imagine looking across
a field at a bright red rose in full bloom against the green foliage of its leaves. The
texture, color, and contrast all create an experience of beauty. Consider further being
at the Louvre museum in Paris, patiently waiting for your chance to see the Mona
Lisa. You’ve paid thousands of dollars and traveled thousands of miles to wait
uncomfortably in a packed crowd, just to get a glimpse of this famous Leonardo
da Vinci painting, a distinctly visual experience. Think about watching a movie and
how much excitement and relaxation you may get from watching, that is, seeing,
the adventure unfold before you. And perhaps imagine looking at the face of your
significant other; the sight of this person’s face should also bring you joy.
To summarize, our visual system provides us with necessary information all the
time, so we can find our way, not bump into walls, and obtain information from the
landscape. It also transcends these practical aspects by providing us with a sense of
beauty and wonder. Whether mundane or majestic, most of all visual experiences
FIGURE 3.1 Visual Images Can Be Beautiful
We often find great beauty and emotional comfort in merely looking at visual images. Do these
images make you smile?
©
S
hu
tt
er
st
oc
k/
Sc
an
ra
il1
©
S
hu
tt
er
st
oc
k/
ca
na
da
st
oc
k
©
S
hu
tt
er
st
oc
k.
co
m
/S
eb
as
tia
n
D
ud
a
(a) (b)
(c) (d)
©
S
hu
tt
er
st
oc
k.
co
m
/M
en
no
S
ch
ae
fe
r
(f)
©
iS
to
ck
ph
ot
o.
co
m
/L
eo
Pa
tr
iz
i
(e)
Sh
ut
te
rs
to
ck
.c
om
/O
lg
a
Sa
vi
na
55 Chapter 3: Visual System: The Eye
start with a light source, which is where this chapter starts. Before we can talk about
any part of the visual system, we need to introduce light as a scientific concept.
Review the sequence of steps of sensory systems in ISLE 1.1. We are starting at the
beginning of this sequence when we talk about light.
LIGHT
3.1
Appraise the nature of light as electromagnetic energy to
explain the relation of wavelength to perception.
Vision is the sensory system that allows us to perceive light. Thus, before we begin
describing the visual system, it is important to know just a little bit about the nature
of light. We live in a world bathed in light, sunshine by day, artificial light by night,
and the constant omnipresence of glowing screens, big and small, but what exactly
is light? Visible light is an example of electromagnetic energy (Feynman, 1985,
1995). As most of us know, light, like other forms of electromagnetic radiation,
moves very fast—approximately 186,000 miles per second (300 million meters per
second) in a vacuum. Visible light is one part of the electromagnetic spectrum, which
also includes radio waves, infrared radiation, ultraviolet radiation, and gamma rays.
These varied types of electromagnetic radiation differ only in their wavelengths,
which we discuss shortly. According to modern physics, light, curiously, is made up
of particles called photons that also behave in a wavelike manner (see Feynman,
1985, for a more thorough explanation of our current understanding of light in
lay terms). The wavelike behavior of light is important to vision, as we see differ-
ent wavelengths (or frequencies, wavelengths’ inverse) as distinct colors. So, in this
chapter, we are concerned with light behaving more as a wave phenomenon than as
discrete photons.
When thinking of light as a wavelike phenomenon, we can look at other waves
to help us understand light. Waves are waves. So, consider waves at the beach
before they break on the shore. The waves are up-and-down undulations of the
water’s surface. As a result, waves are usually drawn as going up and down (ISLE
3.1). If you watch the waves coming in, you can tell that not all waves are the
same. Some are taller than others, and some peaks are closer together, and other
peaks are farther apart. Surfers look for “sets” of waves that come in with higher
peaks, though these higher peaked waves also often come close together, so that a
surfer may be able to ride only one per set. These observations allow us a way to
describe what makes waves different from each other. We can quantify these dif-
ferences by both how high they are (amplitude) and how close they are to adjacent
waves (wavelength). Thus, the distance between the peaks of a wave is called the
wavelength, and the height of the wave is called its intensity. We call the amplitude
of a wave intensity because the higher the wave is, the stronger it is. Think of the
difference between ripples (low amplitude), the waves you might bodysurf on a
day on the beach (medium amplitude), and a tsunami, the ultimate high-amplitude
wave. The number of waves per unit of time is called the frequency, which is equal
to 1 divided by the wavelength. In perceptual terms, wavelength roughly correlates
with color, and intensity correlates with brightness. To make matters confusing for
students everywhere, the tradition is to refer to light waves by their wavelengths
but sound waves by their frequencies. Because this is the tradition throughout the
field, we respect it here.
Electromagnetic energy:
a form of energy that includes
light that is simultaneously both
a wave and a particle
Wavelength: the distance
between two adjacent peaks
in a repeating wave; different
forms of electromagnetic
energy are classified by their
wavelengths
Intensity: when referring to
waves, the height of a wave
Frequency: the number
of waves per unit of time;
frequency is the inverse of
wavelength
ISLE 3.1
The Basics of Waves
56 Sensation and Perception
Visible light represents a tiny slice
of the electromagnetic spectrum. The
electromagnetic spectrum is the com-
plete range of wavelengths of light
and other electromagnetic energy. We
measure the wavelength of light in
nanometers (nm). A nanometer is one
billionth of a meter. Visible light rep-
resents wavelengths between 400 and
700 nm, but electromagnetic radiation
extends in both directions beyond those
boundaries, from wavelengths being far
shorter to wavelengths of several miles
(Figure 3.2). Wavelength is also related
to energy. The shorter the wavelength
is, the higher the energy is. The longer
the wavelength is, the lower the energy
is. Thus, wavelengths shorter than visi-
ble light come with higher energy, such
as gamma rays, X-rays, and ultravio-
let rays. With longer wavelengths than
those of visible light comes lower energy
radiation, such as infrared radiation, microwaves, and radio waves.
Consider an old-fashioned candle (Figure 3.3). The burning wick creates electro-
magnetic radiation at many wavelengths. Some of the electromagnetic radiation is in
the visible wavelength range. We see this radiation as the pretty yellow glow of the
flame, with the (higher energy) blue by the wick itself and the less energetic yellow light
toward the top. We also feel some of the energy in the form of heat, which is electro-
magnetic energy being emitted in the infrared range.
The shortest wavelengths we see are about 400 nm, and we perceive these as
violet. Blue has a wavelength of about 470 nm, and green has a wavelength of about
500 nm. Red has a wavelength approaching 700 nm, the longest wavelengths that we
can perceive under normal circumstances. Other animals have different sensitivities
to wavelength of light. Bees, for example, can see shorter wavelengths than we can
(ultraviolet) (Horridge, 2012). Flowers are colorful to us, but bees and hummingbirds
may use ultraviolet coloring of flowers to determine when they can obtain nectar
from those flowers. Some birds use ultraviolet coloration to attract mates. For exam-
ple, male blue tits have ultraviolet crowns on their heads, which they display during
mating courtships. A human observing the birds would not see any differences, but
female blue tits prefer shinier ultraviolet colorings (Figure 3.4). Interestingly, these
ultraviolet colors are not visible to predators who tend to see better in longer wave-
lengths, allowing the male to show off without drawing too much attention from
predators (Håstad, Victorsson, & Ödeen, 2005). Even some mammals such as bats
and rodents see shorter wavelengths than we do (Beran, 2012).
Recall that in physics terms, light can be thought of as either a wave phenomenon
or a particle phenomenon. When physicists are thinking of light as a wave, they refer to
wavelength, but when they are thinking of light as a particle phenomenon, they refer to
photons. Photons are single particles of light. Photons are useful for thinking about the
amount of light. A very bright light has many more photons than a dim light, regard-
less of its wavelength. This means that bright sunshine sends many more photons your
way than does a single candle burning at night. As psychophysicists, we use the ter-
minology of wavelength when discussing color but the terminology of photons when
400 nm
400 500
Visible
light
Gamma rays
10–11 10–9 10–7 10–5 10–3 10–1 101 103 105 107 109 1011 1013 1015 1017
Radio waves
x
rays
UV
rays
Infrared
radiation
Wavelength (nm)
Micro-
waves
600 700
500 nm 600 nm 700 nm
FIGURE 3.2 The Electromagnetic Spectrum
Electromagnetic radiation varies in wavelength from very low-energy,
long-wavelength waves (shown to the right of the visible spectrum) to very high-
energy, short-wavelength waves (shown to the left of the visible spectrum). Visible
light is just a tiny segment of this continuum. Within the visible spectrum, we see
shorter wavelengths as bluish and longer wavelengths as reddish.
Electromagnetic spectrum:
the complete range of
wavelengths of light and other
electromagnetic energy
Photon: a single particle
of light
57 Chapter 3: Visual System: The Eye
discussing intensity and brightness. We also use the concept of light as particles when
talking about the process of transduction, the process whereby the eye captures light.
Most light reaches our eyes indirectly, after bouncing off objects in our world.
We see the rose in the garden because its surface reflects the light of the sun (or your
flashlight, if you are prowling around the garden after dark). Surfaces, such as the
rose petals, tend to absorb some wavelengths and reflect others. We see the rose as
red because it absorbs most wavelengths but reflects the long wavelengths that we
perceive as red. Similarly, the grass is green because the plant is absorbing most
wavelengths, but reflecting green light back into the world.
TEST YOUR KNOWLEDGE
1. Evaluate the nature of electromagnetic radiation, focusing on the range that is considered
light.
2. Create a diagram to show how the selective absorption and reflection of different
wavelengths allows us to see different colors.
THE EYE AND ITS ROLE
IN THE VISUAL SYSTEM
3.2 Sketch the anatomy of the eye to show how it makes vision possible.
It will not come as a surprise to most readers that the eye is the primary organ of visual
perception, what was called the accessory structure in ISLE 1.1. However, how the eye
converts light into signals that allow us to see colors, objects, motion, and a third dimen-
sion is a fascinating topic, which this and the next several chapters cover. The eye is a
finely tuned instrument, with many integrated parts working together to capture light
in a way to allow our visual perception. To understand visual perception, it is necessary
to understand the anatomy and the physiology of the eye. Thus, our first task will be
to consider the structure of the human eye, its physiology, and how it relates to seeing.
The human eye is a fairly typical mammalian eye. See the Exploration section for
a discussion of a few other types of animal eyes. Like most primate eyes, our eyes are
located at the front of our heads and are slightly spaced. This gives us good depth per-
ception. Relative to other mammals, human beings have excellent visual acuity (i.e.,
the ability to see fine details) but are relatively poor at seeing in dim light compared
with familiar animals such as cats and dogs. Cats are especially good at seeing in dim
light. Because of the structure of the receptors in the retina, humans are good at color
vision. Dogs can see in color but are similar to humans with red–green color defi-
ciency. Other animals seem to have better color vision than us, though. Indeed, gold-
fish see many more colors than we do (Neumeyer, 1985). It is interesting to think that
compared with your pet goldfish, swimming in its bowl, you are seemingly colorblind.
The basic story of how humans see is as follows. Light emanates from a light
source, such as the sun or an overhead light in an indoor location. Light falls on
objects in the environment, and, in turn, some wavelengths are reflected by those
objects. It is this reflected light from objects that we actually see. The reflected light
enters the eye through the pupil and is focused on the retina by the cornea and lens.
The retina contains specialized cells called rods and cones, which transduce, or con-
vert, the light energy into an electrochemical signal, which is then sent to the brain for
processing through the optic nerve. Of course, humans, like most animals, have two
FIGURE 3.3
Light in the Visible Spectrum
A burning candle emits light in
the visible spectrum. We can
use this light to illuminate a room
when the electricity is off and we
cannot use our electric lights.
©
iStockphoto.com
/aga7ta
FIGURE 3.4 Blue Tits
Blue tits are pretty birds, with
beautiful colorations. However,
there are colors present in the
ultraviolet range that we cannot
see, but other blue tits can. Blue
tit females prefer males with
shiny ultraviolet crowns.
©
iStockphoto.com
/G
lobalP
58 Sensation and Perception
Visible
60°
80°
Invisible
Invisible
Invisible
Visible
to both eyes
(stereoscopic
depth
perception
possible)
Visible to
right
eye only
Visible to
left
eye only
110° 190°
Invisible
Invisible
Invisible
FIGURE 3.5 Field of View
Our eyes give us a large zone of binocular vision, that is, an area we can see with both eyes. Beyond that is a region in which
we see with only one of our eyes. However, we cannot see the world behind us. If you think of the world as a circle around
you, you can see approximately 190 degrees in front of you, but you cannot see the 170 degrees behind you.
Field of view: the part of the
world you can see without eye
movements
eyes, so coordinating the slightly different view of each eye is critical to vision, espe-
cially depth perception. So, let’s look at each of the events in greater detail.
Field of View
Human eyes are located approximately 6 cm (2.4 inches) apart from each other. Of course,
there is variation depending on genetics and how big one’s head is. In humans, as in other
primates, the eyes have evolved to be adjacent to each other to allow for accurate depth
perception. Frontally placed eyes allow us to see in stereo, as each eye has a slightly differ-
ent view of the world. By computationally comparing the two images, our visual systems
can estimate distance from the offset of the two images. Such depth perception is useful
for animals that must hunt for food or that live in trees and must judge distances from
branch to branch. The drawback of this arrangement is that such animals can see only in
front of themselves (Figure 3.5). Large herbivores, such as deer and antelope, are often
subject to predation. For these animals, detecting incoming predators is paramount. For
this reason, these species have evolved eyes placed on the sides of the head rather than
in front. Animals with eyes positioned on the sides of their head such as antelope have a
greater field of view but weaker depth perception (Figure 3.6). This allows them to detect
predators coming from almost any position relative to them, except usually a small area
directly behind their heads. Your field of view is the part of the world you can see without
eye movements. For humans, that is approximately 190 degrees horizontally (side to side)
and 140 degrees vertically (up and down).
Anatomy of the Eye
The complexity of the human eye has often led to debates as to how it got that way. Before
Darwin, the eye was often held up as a marvel of intelligent design. Indeed, the naturalist
William Paley labeled the design of the eye a “miracle.” For Paley, he could not see how
such a complex piece of biological machinery could have just happened. He reasoned that
because it was so complex, it must have been designed. Perhaps because of this challenge,
many evolutionary biologists have studied the evolution of complex eyes in great detail.
Biologists have carefully mapped out how nature has selected for complex eyes and have
FIGURE 3.6
Pronghorn Antelope
The pronghorn antelope can be
found in the American West,
such as this one in Montana. The
pronghorn antelope has eyes on
the sides of its head. This limits its
depth perception but allows it to
see behind its head as well as in
front. This allows the pronghorn
antelope to detect incoming
predators, such as mountain lions.
©
iS
to
ck
ph
ot
o.
co
m
/p
ho
to
gr
ap
hy
by
JH
W
ill
ia
m
s
59 Chapter 3: Visual System: The Eye
investigated various intermediaries. Indeed, complex eyes have
evolved independently. For example, the octopus is a mollusk
more related to clams and barnacles than it is to us. However,
the octopus has a complex eye that evolved along a very differ-
ent pathway than our human eye. Our concern here is not how
eyes evolved in the distant past but how humans use their eyes
now. The result of human evolution is a remarkably complex
apparatus designed for transforming light energy into percep-
tual information.
In this section, we describe the anatomy and physiology
of the parts of the eye, with an emphasis on their func-
tion in vision (review Figure 3.8 first). Make sure you learn
both the vocabulary and the concepts. That is, memorize
the technical terms, but also make sure you understand
the function of each part of the eye and how information
moves from the eye to the brain. We start now with the
cornea and iris, the outermost parts of the eye.
The Cornea
The cornea is the clear front surface of the eye that allows
light in. It is also a major focusing element of the eye. The
cornea is transparent and is the outermost surface of the eye
(see Figure 3.8). It begins the process of refracting or bending
the light to come into focus on the retina of the eye, which
Cornea: the clear front surface
of the eye that allows light in;
also a major focusing element
of the eye
Optic
axis
Pupil Cornea
Iris
Lens
Sclera
Choroid
Retina
Fovea
Sheath
Optic nerve
Optic disc
(blind spot)
Vitreous
chamber
Zonule
fibers
Ciliary muscle
Posterior chamber
Anterior chamber
FIGURE 3.8 Anatomy of the Human Eye
Light enters the eye through the pupil, an opening in the outer layer of the eye, surrounded by the iris,
the colored area that gives eyes their characteristic color (brown, blue, green, etc.). Ciliary muscles
control the zonule fibers that pull on the lens, allowing light to focus on the retina at the back of the eye.
The fovea is a little pit at the center of the retina that picks up light from the point in space the eye is
looking at. Information leaves the eye via the optic nerve through a part of the eye called the optic disc.
FIGURE 3.7 Retina Layers, Colored Scanning
Electron Micrograph (SEM)
The retina of the human eye is found on the inside of the eyeball
and is formed from a number of layers. The light-detecting part
is formed of rod and cone photoreceptor cells. The lower third
of this image contains the blood vessels and nerves that form
the upper layer. The light entering our eyes has to penetrate
this layer to reach the tightly packed photosensitive “outer
segments” of the photoreceptors (top third of image) that lie
just below a layer of retinal pigment epithelium cells (top).
Magnification: ×480 when printed at 10 centimeters across.
Louise H
ughes/Science Source
ISLE 3.2
Accommodation
ISLE 3.3
Presbyopia
60 Sensation and Perception
is the back surface inside the eye. Indeed, the cornea does
most of the focusing of images toward the retina. However,
the cornea is rigid and can only focus clearly at one dis-
tance. Therefore, changes in refraction to allow us to see
clearly at different distances must come from the adjust-
able lens. The cornea is the transparent part of the sclera, a
tough membrane, which provides a protective covering for
the eye. The sclera is the “white” of the eye as well. Between
the cornea and the iris is the fluid-filled anterior chamber.
Just behind the cornea is a part of the eye called the iris.
The iris is really two muscles with an opening in the mid-
dle. Light enters through this opening. The opening itself
is called the pupil. In dim light, the iris opens to allow the
pupil to expand (or dilate) and it allows more light into
the eye. In bright light, the iris contracts and the pupil
narrows, allowing less light into the eye. This is a process
that is not directly under conscious control and is known
as the pupillary reflex. Shine a bright light into someone’s
eyes, and his or her pupil will immediately contract. When
you enter a dim room after being outside in the sunshine,
your pupils will quickly dilate. The two eyes coordinate
their pupillary reflexes, so that each dilates and contracts
simultaneously. In this way, the pupil can range from a
diameter of about 2 mm to about 8 mm, depending on
lighting conditions (Figure 3.9). Interestingly, it is the iris that gives individual eyes (or
pairs of eyes) their characteristic colors, whereas the pupil appears dark or black (Figure
3.10). The amount of melanin in the iris is a major factor in whether one has blue eyes
or brown eyes, though other factors contribute as well. Heterochromia is a condition
in which a person has two irises of different colors. It is rare in people (but not in
Siberian huskies) and is often a sign of ocular disease. The posterior chamber is the
space between the iris and the lens. It is filled with fluid, known as aqueous humor.
The Lens
The lens (also called the crystalline lens) is the adjustable focusing element of the eye. It
is located just behind the iris. This process of adjusting the focus for different distances by
changing the shape of the lens is called accommodation. Accommodation is the process of
FIGURE 3.9 The Pupillary Reflex
In dim light, the iris relaxes control, and the pupil expands (or dilates) to allow more light into
the eye (a). However, when a bright light is shined into the eye, the iris contracts and the pupil
narrows, allowing less light into the eye (b).
(a) (b)
FIGURE 3.10 Irises
The iris is the part of the eye that gives the eye its characteristic
color. Those eyes containing the most melanin will appear brown.
Those with less melanin may appear blue or sometimes green.
©
iS
to
ck
ph
ot
o.
co
m
/P
eo
pl
eI
m
ag
es
Sclera: the outside surface of
the eye; a protective membrane
covering the eye that gives the
eye its characteristic white
appearance
Anterior chamber: the fluid-
filled space between the cornea
and the iris
Iris: the colored part of the
eye; a muscle that controls the
amount of light entering through
the pupil
Pupil: an opening in the middle
of the iris
Pupillary reflex: an automatic
process by which the iris
contracts or relaxes in response
to the amount of light entering
the eye; the reflex controls the
size of the pupil
Heterochromia: a condition in
which a person has irises of two
different colors
Posterior chamber: the space
between the iris and the lens;
it is filled with fluid known as
aqueous humor
61 Chapter 3: Visual System: The Eye
adjusting the lens of the eye so that you can see both near and far objects
clearly. This process is very rapid, although changing accommodation
from a near object to a far object is faster than from a far object to
a near object (Kirchhof, 1950). Accommodation is controlled by mus-
cles connected to the lens, called ciliary muscles. The ciliary muscles
work in concert with the zonule fibers, which connect the lens to the
choroid membrane. As with the control of the iris, the ciliary muscles
work automatically, without conscious control. Indeed, we seldom need
to think about whether what we are looking at is in focus. The ciliary
muscles can contract and increase the curvature of the lens so that the
lens thickens. The increased curvature of the lens allows the eye to focus
on a close object. When the person then looks at a faraway object, the
muscles relax, and the focus of the lens changes to an object farther away
(Figure 3.11). For a demonstration of how this works, go to ISLE 3.2.
The process of accommodation allows us to focus on near objects
and far objects and switch between them effortlessly. Look up from
your textbook now and look out the window. As you do, your lens
relaxes and allows you to focus on a distant object. Look back at the
text and your lens contracts, allowing you to focus on the words on
the page or screen. But accommodation has limits. Close one eye and
with the other look at your index finger at arm’s length and then slowly
bring it toward your eye. At some distance, probably close to your
nose, you will no longer be able to focus on your finger, and it will start
to look a bit blurry. If you can bring your finger right up to your nose
and still focus on it, switch to a smaller object. When you can no longer
focus on the object, you have reached your near point. The near point
is the closest distance at which an eye can focus.
As people age, the near point shifts farther away from the eyes.
For younger adults, say, around 20 years of age, the near point is
usually about 10 cm from the eyes. However, it averages about 100
cm for people around 60 (Rutstein & Daum, 1998). This condi-
tion in older adults is called presbyopia. Because of the decreased
elasticity of the lens, accommodation does not occur to the extent
it does in younger eyes. This relative failure of accommodation
moves the near point farther from the eye. Presbyopia usually
starts to become noticeable in adults in their 40s and accelerates
after that (Figure 3.12). When presbyopia first becomes noticeable,
people may simply hold their reading material farther from their
eyes. But as it progresses, reading glasses or bifocals, which help
bring near images into focus, become necessary. For a demonstra-
tion of how this works, go to ISLE 3.3.
Development: The
Emerging and Aging Eye
The eye is an incredibly complicated structure. A natural question is
about how it develops prior to birth. This is not a text on embryol-
ogy, but we can give a brief overview of the incredible speed of the
development of the major structures of the eye. The eye begins to
develop very early after fertilization—by the 17th day in fact. That
is less than 3 weeks after conception. Shortly thereafter, the retina
and lens begin to develop. By the 32nd day you can identify the lens,
Retina
A
A
B
Lens
Cornea
Object far – eye relaxed
Focus on retina
Focus on retina
Focus behind retina
Object near – eye relaxed
(a)
(b)
Object near – accommodation(c)
Moving object
closer pushes
focus point back
Accommodation
brings focus
point forward
FIGURE 3.11 Curvature of the Lens
(a) The increased curvature of the lens allows the
eye to focus on a close object. (b) When the person
then looks at a faraway object, the muscles relax
and the focus of the lens changes to an object
farther away.
60
50
40
30
Near point of newborn
about 5 cm
Near point about 400
cm (4 m) by age 70
Near point about
10 cm by age 20
N
e
a
r
p
o
in
t
(c
m
)
Age (years)
20
10
0
0 10 20 30 40 50 60 70
Near point
about arm’s
length (40 cm)
by mid-50s
Near point about
reading distance
(20 cm) by mid-40s
FIGURE 3.12 Presbyopia and the Near Point
In this graph, the x-axis represents age, and the y-axis
represents the near point in centimeters from the eye. As
you can see in the graph, the near point is closest when
we are young and then accelerates after we reach the
age of approximately 50. There are very few among us
who do not need reading glasses by the time they are in
their 50s. This presbyopia (“old vision”) is the result of the
fact that the lens becomes less flexible as we age.
62 Sensation and Perception
and by day 35 you can start to see the iris. Although the retina, the most complex structure
of the eye, begins to develop early in utero, it continues to develop for months after birth
(Gilbert, 2000).
Turning now to aging, in the discussion of presbyopia, we described one way in
which the eye changes as we age. This is one of many changes, but let us examine one
other way that the lens changes as we age. Our lens loses its transparency to some degree
as we age, and not as much light gets through. However, it does not lose the ability to
transmit all wavelengths equally; rather, the lens loses the ability to transmit blue wave-
lengths the most (Salvi, Akhtar, & Currie, 2006). So, as we age, we are less able to see
blue colors. Figure 3.13 shows a simulation of how a scene may look to a person with
an older lens that extremely limits blue wavelengths. Figure 3.13a shows the scene as
normal, and Figure 3.13b shows the scene through the older lens. Figure
3.13b looks like a yellow filter has been placed over the scene.
TEST YOUR KNOWLEDGE
1. Sketch the eye and indicate how the cornea and lens work together to
produce a focused image on the retina. Then indicate how the lens changes
to allow us to see near and far objects clearly.
THE RETINA
3.3
Interpret how the retinae transduce light energy
into a neural signal that is sent to the brain.
In English, the word retina is singular, referring to one eye. The words reti
nae and retinas are both acceptable as the plural form of the word retina. To
be more formal, we will use retinae when talking about both retinae. Before
we discuss the retina, perhaps the most complex part of a complex eye, let
us review what we have covered so far. The iris and the lens direct light and
focus that light. The pupil allows more or less light in, depending on ambient
conditions. The goal of these processes is to focus an image on the retina,
which is the eye’s photosensitive, that is, light-capturing, surface. This image
is known as the retinal image. Receptor cells on the retina transform the
light image into a neural signal to be sent to the brain. The intricacy and
precision of the arrangement of the retina is very complex but at the same
time fascinating (Figure 3.14). Although very thin, the retina is composed of
several interconnected layers. Let’s see how this process takes place.
FIGURE 3.14 An Optometrist’s View
of the Retina of One of the Authors
This is an image of the fundus, or the back
surface of the right retina. The bright yellow
spot is the optic disc, where the optic nerve
leaves the eye to head into the brain. This
also corresponds to the blind spot of the eye.
The dark patch just to the right of the yellow
disc is the macula or fovea, the part of the eye
designed for visual acuity. The eye depicted
belongs to Dr. Bennett Schwartz.
Lens: the adjustable focusing
element of the eye, located right
behind the iris; also called the
crystalline lens
Accommodation: the process
of adjusting the lens of the eye
so that both near and far objects
can be seen clearly
Ciliary muscles: the small
muscles that change the
curvature of the lens, allowing
accommodation
Zonule fibers: fibers that
connect the lens to the choroid
membrane
Near point: the closest
distance at which an eye can
focus
Presbyopia: a condition in
which incoming light focuses
behind the retina, leading to
difficulty focusing on close-up
objects; common in older
adults, in whom the lens
becomes less elastic
FIGURE 3.13 The Aging Lens and Loss of Seeing Blue
(a) You see a scene as normal, in effect, through a young lens. (b) You see the scene, somewhat
exaggerated, as through an older lens that does not let blue wavelengths through as well as other
wavelengths. The scene looks like a yellow filter has been place over the image.
(a) (b)
63 Chapter 3: Visual System: The Eye
Anatomy of the Retina
The retina is the third and innermost of the three membranes in the eye. Retinal anatomy is
quite complicated, but it can be understood when one thinks of the functions of the retina.
First, the retina is the location in the eye where transduction takes place. Photoreceptors
convert light into a neural signal. Thus, part of retinal anatomy is designed to help the
photoreceptors capture light. Second, the retina starts the process of transmitting visual
information to the brain. Thus, part of the retinal anatomy is designed to allow the retina
to send accurate signals to the brain. Figure 3.15 illustrates this complex anatomy, and
Table 3.1 lists the functions of different neural cells in the retina. Looking at the retina,
you can see that it is organized into layers. Let us look at the cells in these layers and see
how they connect to each other. Interestingly, some cells help carry the signals toward the
brain, whereas others seem to connect within their layers. The cells at the back of the eye
are the photoreceptors. These cells then synapse (i.e., connect) with two types of cells. The
horizontal cells connect from one photoreceptor to another while the bipolar cells convey
the signal from the photoreceptors to the next inner layer. The bipolar cells synapse with
amacrine cells and ganglion cells. Amacrine cells connect across different bipolar cells and
ganglion cells. The ganglion cells send their axons to the optic disc where they exit the
eye. These axons then become the optic nerve carrying the signals from the retina to the
brain. These bipolar cells and amacrine cells are interesting in that they connect within
their layers. Later on, we will discuss the important role these cells play in vision.
Ganglion cell layer
Inner synaptic layer
Inner nuclear layer
Outer synaptic layer
Outer nuclear layer
Inner and outer segments
of photoreceptors
Pigment epithelium
V
itr
eo
us
c
ha
m
be
r
Choroid
Pigment
epithelium
Axons of
optic nerve
Retinal
ganglion cell
Amacrine
cell
Bipolar
cell
Horizontal
cell
Cone Rod
C
ho
ro
id
Fovea
Fovea Retina
Retina
Ganglion cell layer
Retinal ganglion cells
Inner nuclear layer
Bipolar, horizontal, and
amacrine cells
Outer nuclear
layer
Photoreceptors
(rods and cones)
Inner and outer
segments of
photoreceptors
Inner synaptic layer Outer synaptic layer
(a)
(b)
FIGURE 3.15
Anatomy of the Human
Retina
In Figure 3.15a, we see the
location of the retina relative
to other anatomical structures
in the eye. As you can see, the
foveal region looks like a pit,
as the top layers of the retina
are swept aside so that there
is no scatter of light reaching
the receptor cells (i.e., the
cones). In Figure 3.15b, we
see a schematic of what the
retina would look like if it were
stretched out to reveal the
layers. Oddly, the rods and
cones form the back layer of
the retina, even though they
are the light-sensitive portion
of the retina. The horizontal,
amacrine, and bipolar cells
serve as a middle layer and
connect the photoreceptors
to the retinal ganglion cells,
which exit the retina and bring
visual information to the brain.
Retina: the paper-thin layer
of cells at the back of the eye
where transduction takes place
Retinal image: the light
projected onto the retina
64 Sensation and Perception
The Receptors: Rods and Cones
There are two types of receptors in vision (or photoreceptors), the rods and the cones.
These are the cells that transform light energy into an electrochemical signal. Rods predom-
inate at the periphery (away from the center) of the retina, whereas cones cluster in and near
the fovea of the retina. The fovea is a small pit at the center of the retina (indeed, the word
fovea means “small pit” in Latin). The fovea and the area around it are called the macula.
Beyond that is the periphery of the retina. There are about 120 million rods and only about
7 million cones in each eye. There is only one type of rod, whereas there are three classes of
cones (Nathans, Piantanida, Eddy, Shows, & Hogness, 1986; Neitz & Jacobs, 1986, 1990).
We return to these cone types a bit later in the chapter, as each is important in detecting
different frequencies of light and perceiving color. Because there is only one type of rod,
these receptors see only in shades of gray (from black to white). The rods and cones are not
spread evenly across the eye. If you examine Figure 3.16, you will see that the cones are
most centrally located in the fovea. There are no rods in the fovea. The rods are mostly at
the periphery, starting about 20 degrees off the fovea away from your nose and toward your
temples. In one region, however, the two receptor types mix. This is in the outer areas of the
fovea, or where the fovea blends into the periphery, sometimes called the parafoveal region.
Here, both kinds of cells can be found (Curcio, Sloan, Kalina, & Hendrickson, 1990).
The human fovea is densely packed with cones. It looks like a little pit on the ret-
ina because the cells that are above the retinal surface, such as retinal ganglion cells,
horizontal cells, and amacrine cells, are pushed to the side so that the cones are at the
surface making the retina even thinner. Because of the layers that are swept away, there
is less scattering of light in the fovea, allowing visual acuity to be higher in the fovea. It
is the foveae of the retinae that give humans our excellent color vision and our excel-
lent visual acuity. By visual acuity, we mean clarity of vision. Thus, the visual image
of the words you are reading right now is falling on the foveae of your retinae. Words
you have just read or have not yet read are tailing off into the periphery of the retinae.
When you move your eyes to look at something new, say, a family member walking
into the room, it is your foveae that are directed toward the new stimulus. Therefore, it
is said that the foveae represent the direction of your gaze. For a demonstration of how
much space on the retina is occupied by the high-acuity fovea, go to ISLE 3.4.
The fovea is unique anatomically. First, it is the location on the retina with the
highest density of cones. Second, other retinal cells are brushed away from the sur-
face of the retina. This allows light to reach the surface of the fovea with minimal
scatter of that light. Both of these factors evolved to enhance our visual acuity.
ISLE 3.5
Map Your Blind Spot
ISLE 3.4
Letters and the Fovea
Neuron Type Function
Receptors Transduce light into a neural signal
Rods Night vision, light detection, grayscale vision
Cones High visual acuity, color vision, daytime vision
Horizontal cells Receive information from photoreceptors and other horizontal cells;
cross talk across photoreceptors
Bipolar cells Receive information from photoreceptors; send signals to retinal
ganglion cells
Amacrine cells Receive information from bipolar cells and other amacrine cells; cross
talk function
Retinal ganglia Receive information from bipolar cells; send signal to brain via the
optic nerve
Rods: photoreceptors at the
periphery of the retina; they
are very light sensitive and
specialized for night vision
Cones: photoreceptors in the
fovea of the retina; they are
responsible for color vision and
our high visual acuity
Fovea: an area on the retina
that is dense in cones but lacks
rods; when we look directly at
an object, its image falls on the
fovea
Macula: the center of the
retina; the macula includes the
fovea but is larger than it
TABLE 3.1 Neurons in the Retina
65 Chapter 3: Visual System: The Eye
Interestingly, other animals have different arrangements of rods and cones in their
eyes. Many birds, for example, have a fovea in the middle of the retina for good central
vision but have a second, cone-rich fovea along the edge of the retina. Birds with this
visual arrangement include such diverse species as birds of prey, hummingbirds, and
swallows (Ruggeri et al., 2010). This second fovea gives these birds
accurate vision to their sides as well as in front of them, useful to
birds that must perform complex aerial movements. Other animals,
including many mammals such as dogs, have no foveae at all (Walls,
1963). The lack of a fovea is characteristic of animals that tend to be
nocturnal or rely primarily on senses other than vision. These animals
are more concerned about detecting moving objects than pinpointing
an exact location. Thus, rod vision is more critical than foveal vision.
In Figures 3.14 and 3.15, you can see a part of the retina called the
optic disc. The optic disc is the part of the retina where the optic nerve
leaves the eye and heads to the brain. In the optic disc, there are no
receptor cells. Axons of the retinal ganglion cells gather at the optic disc
and form the optic nerve, which carries the neural signal into the brain.
Because there are no receptors at the site of the optic disc, this location is
also called the blind spot. Because the blind spot in the left eye does not
correspond to the same region in space as the blind spot in the right eye,
humans really do not have a blind spot in their visual field. Even when
viewing the world with only one eye, we are not aware of our blind spot.
Higher areas of visual processing “fill in” the blind spot (Ramachandran,
1992). To observe your blind spot, see Figure 3.17. For an interactive
look at the blind spot, go to ISLE 3.5.
Retinal Physiology
Retinal anatomy concerns the structures of the retina. This refers to where cells are
located and how they connect with one another. Retinal physiology refers to the func-
tions of these structures—how they accomplish the processes that allow us to see. Because
we have reviewed the structures of the eye, we can now turn to how the eye converts
Optic disc: the part of the
retina where the optic nerve
leaves the eye and heads to the
brain; along the optic disc, there
are no receptor cells
200
150
100
50
10
Temporal
P
h
o
to
re
ce
p
to
r
d
e
n
si
ty
(t
h
o
u
sa
n
d
s/
m
m
2
)
NasalDistance from foveal center (mm)
0 10 20
20 0 20
Visual angle (degrees)
10 µm
O
p
ti
c
d
is
c
Rods
Cones
16.0 8.0 5.0 1.35 0.0 1.35 5.0 8.0 16.0
FIGURE 3.16 Receptor
Density in the Retina
The graph shows the density of
cones and rods in the retina. The
density of cones is highest in the
fovea, whereas cones become
very sparse as one moves away
from the fovea. Rods become
more common at the periphery.
Source: Curcio, C. A., Sloan, K. R., Kalina, R. E., & Hendrickson, A. E. (1990). Human photoreceptor topography.
Journal of Comparative Neurology, 292, 497–523.
FIGURE 3.17 Finding Your Blind Spot
Close your right eye and hold the book or your
laptop at arm’s length. Slowly move the book toward
you while looking at the orange circle with your left
eye. At some point, the plus sign will disappear. The
plus sign disappears when its image lands on the
optic disc, where there are no receptor cells.
66 Sensation and Perception
light into a neural signal at a physiological level. Retinal physiology is difficult, so read
carefully, review, and test yourself. Once you understand the physiology of transduction
in vision, the transduction processes for other senses will be more straightforward.
Transduction of Light
The rods and cones of the retina are equipped with the ability to convert light into a
neural signal. They accomplish this task by using chemicals known as photopigments.
Photopigments are molecules that absorb light and by doing so trigger events that alter
the voltage in the cell. When a photopigment absorbs a photon of light, it changes shape.
This change in shape initiates a series of biochemical processes, which result in a change in
electric potential, which allows a signal to exit the photoreceptor. In this way, a neural signal
leaves the photoreceptor and is, ultimately, transmitted to the optic nerve to be sent to the
brain. Once the photopigment has changed shape, it can no longer capture light. So other
biochemical processes reset the photopigment to its original shape so that it can detect more
light. Photopigments are contained in discs within the rods and cones. Each photoreceptor
may contain about 100 to 200 of these discs, and in each disc, there may be billions of pho-
topigment molecules (Fain, 2003). The many biochemical steps necessary to convert pho-
topigments from one form to another have been heavily investigated (see Rodieck, 1998).
Photopigments are composed of two molecules, which are bound together, a pro-
tein called an opsin in rods (and chromodopsin in cones) and a form of vitamin A
called retinal. The photopigment in the rods is called rhodopsin. The photopigments
in the cones are similar to rhodopsin, but there are three classes of these cone pho-
topigments (Bowmaker, 1998). The nature of the photopigment is central to deter-
mining how a receptor behaves with regard to light. These different photopigments
in each type of receptor tend to absorb different wavelengths of light, and it is the
differences in the opsins that are key to these differences. (See Figure 3.18 for a
Photopigment: a molecule
that absorbs light and by doing
so releases an electric potential
by altering the voltage in the
cell
Opsin: the protein portion of
a photopigment that captures
the photon of light and begins
the process of transduction; the
variation in opsin determines
the type of visual receptor
Retinal: a derivative of
vitamin A that is part of a
photopigment
FIGURE 3.18 Opsins
The figure shows a depiction of the four most common opsins found in human eyes. Panels (a) and (b) show the rod opsin. Panel (c) at the bottom
shows the three opsins found in the different classes of cones. The different color dots show how each opsin is different from the opsin to its left.
Source: Nathans et al., 1986.
(a)
(b)
(c)
67 Chapter 3: Visual System: The Eye
depiction of the rod and the
three cone options and how
they differ from each other.)
The role of retinal in the rho-
dopsin explains one piece
of folk knowledge you may
have heard about. You may
have been told that eating
carrots will help your night
vision. Carrots are very rich
in vitamin A, which is the
source of retinal. If you have
a healthy diet, you will proba-
bly not improve your vision by
eating more carrots, but diets
that are deficient in vitamin
A can result in night blind-
ness, that is, an inability to
see under dim light conditions
(Wald, 1968).
In the photopigment that
is ready to respond to light,
retinal is in a bent form, called
11-cis, that fits into the opsin.
When a photon of light is
absorbed by the photopigment, the rhodopsin straightens out and the photopigment
breaks apart (Wang, Schoenlein, Peteanu, Mathies, & Shank, 1994). This straight-
ening of the bond takes place during an incredibly fleeting time period (Schoenlein,
Peteanu, Mathies, & Shank, 1991). See the two shapes of retinal in Figure 3.19. The
effect of this absorption of the photon by the photopigment causes the receptor to
have a more negative voltage inside relative to outside the receptor (Tomita, 1970).
This is called hyperpolarization, referring to the polarization of electric charge
increase. This hyperpolarization causes the receptor to release less of the neurotrans-
mitter, which are molecules that neural cells release to communicate with subsequent
neural cells. In this way, the receptor can communicate with the rest of the retina.
Thus, oddly, light is inhibitory to receptors. So, the question naturally arises, how
does light act to stimulate the visual system so that we can see? It turns out that the
neurotransmitter of the rods, probably glutamate, is inhibitory to the other cells of
the retina; that is, it stops the responses of these bipolar and horizontal cells (Schiells
& Falk, 1987). Thus, light inhibits the release of an inhibitory neurotransmitter and,
ultimately, excites the visual system, like multiplying two negative numbers and
getting a positive number. There is no good explanation for why the visual system
evolved this seemingly illogical system.
Given that one photon of light can change a photopigment molecule in one
receptor and induce a neural signal, a natural question to ask is how many pho-
topigment molecules must be activated to create a perception of light, to reach
absolute threshold? In particular, because we know that rods are sensitive to small
amounts of light, we will look to the photoreceptors at the periphery to answer
this question. In fact, if you optimize the conditions for light detection, a single rod
may start a signal in response to as little as one photon of light, and a person may
actually see a light with as few as seven photopigment molecules activated (Hecht,
Schlaer, & Pirenne, 1942).
Hyperpolarization: a change
in the voltage of a neuron
whereby the inside of the cell
becomes more negative than it
is in its resting state
Neurotransmitter: a chemical
substance neural cells release
to communicate with other
neural cells
FIGURE 3.19 Transduction at the Molecular Level
The photopigment molecule has one of two shapes, each called an isomer of the other. In
the photopigment that is ready to respond to light, retinal is in a bent form, called 11-cis, that
fits into the opsin. When a photon of light is absorbed by the photopigment, the rhodopsin
straightens out and the photopigment breaks apart. This straightening of the bond takes place
during a very short time period. The effect of this absorption of the photon by the photopigment
causes the receptor to have a more negative voltage inside relative to outside the receptor.
H
3
C
H
3
C
HC
C
C
C
C
C
C
C
11-CIS RETINAL
ALL-TRANS RETINAL
C
C
C
H
3
C
H
2
C
H
2
C
H
2
C
H
2
C
CH
3
CH
3
CH
3
CH
3
CH
3
CH
3
CH
3
C
H
2
C
H
2
CH
CHC
H
C
H
C
H
C
H
C
H
C
H
H
C
H
C
H
C
H
C
H
C
O
O
Photoisomerization
Photon of light
Photopigment
regeneration
68 Sensation and Perception
Classes of Receptors
The human eye uses four different photopigments, one for the rods and three in differ-
ent cone classes in the retina (Figure 3.20). Each of these photopigments is maximally
sensitive to a particular frequency of light (Table 3.2). It is the interaction of these three
photopigments and subsequent perceptual processing that provides for our complex
color vision. This classification system is actually a simplification, as each class of cone
photopigment has many subtypes, especially in the cones that respond to red and green.
In rare cases, some people (most often women) have a fourth cone class with a fourth
photopigment. There is some evidence that these people see a greater range of colors
than do normal people (Jameson, Highnote, & Wasserman, 2001).
TEST YOUR KNOWLEDGE
1. Summarize the mechanism of transduction in the rods and cones.
2. Determine the reason we have more rods than cones in our eyes and predict what impact
having the cones in one area on our retina will have on how we use our visual system and
eyes.
THE DUPLEX THEORY OF VISION
3.4
Illustrate how the visual system adapts to the dark and then adapts
again to the light to help us adjust to changing light levels.
The duplex theory of vision is the idea that there are functionally two distinct ways in
which our eyes work. The first system is called the photopic system, and the second is
the scotopic system. The photopic system is associated with the cones, and the other,
the scotopic system, is associated with the
rods. The duplex theory is the idea that our
visual system can operate in fundamentally
different ways, depending on the conditions
in the environment. Daytime is the domain
of photopic vision, but nighttime is when
our scotopic vision comes to the forefront.
These hypothesized differences in visual
function derive from the following observa-
tions. First, rods are more sensitive to light
overall than are cones. Second, rods are
most sensitive to different wavelengths than
cones are. That is, they have a different spec-
tral sensitivity. Third, rods and cones have
different spatial and temporal summation
properties, which we discuss shortly. Finally,
cones support color vision, but rods do not.
In general, the photopic system is associated
with daytime vision, and the scotopic sys-
tem is our night vision system, but there is a
range of intermediate ambient light intensity
within which both systems work. This inter-
mediate zone is said to be mesopic vision.
Duplex theory of vision:
the doctrine that there are
functionally two distinct ways
in which our eyes work, the
photopic, associated with
the cones, and the scotopic,
associated with the rods
Photopic vision: the vision
associated with the cones; it is
used in the daytime, has good
acuity in the fovea, and has
color vision
Scotopic vision: the operation
of the visual system associated
with the rods; it has relatively
poor acuity and no color ability
but is very sensitive to light
FIGURE 3.20 Wavelength Sensitivity of Cones and Rods
The photopigments in each cone and in the rods vary with respect to their ability
to absorb light at different wavelengths. Rods show a peak sensitivity at just shy
of 500 nm, which would be seen as dark green by the color system. With respect
to the cones, the S-cones’ peak sensitivity is at 420 nm, the M-cones’ at 530 nm,
and the L-cones’ at 560 nm. Note that each photoreceptor responds to a broad
band of wavelengths but at less strength than to the peak. We determine color by
a complex comparison of the responses from each of the cone photoreceptors.
100
50
R
e
la
ti
v
e
s
e
n
si
ti
v
it
y
(
%
)
0
400 450 500 550
530
Wavelength (nm)
560420380
S
-c
o
n
e
s
Ro
ds
M
-cones
L-cones
600 650 700
69 Chapter 3: Visual System: The Eye
See ISLE 3.6 to see differences between photopic vision and scotopic vision. Table 3.3
also illustrates the differences between these two parts of the duplex system.
Spectral Sensitivity and the Purkinje Shift
Spectral sensitivity refers to the relative sensitivity of a receptor type to all of the
wavelengths. Rods are relatively more sensitive to the shorter wavelengths, whereas
cones are relatively more sensitive to the longer wavelengths. Indeed, cones, taken as a
whole, are most sensitive to about 555 nm, and rods are most sen-
sitive to just under 500 nm. This difference in spectral sensitivity is
named the Purkinje shift, after the Czech anatomist Jan Evangelista
Purkyně. He would take long walks during dawn and noticed that
his favorite bright red flowers appeared very dark before the sun
climbed high into the sky (Wade & Brožek, 2001). This shift occurs
as we transition from day vision to night vision and back again. We
have simulated these differences in the relative sensitivity of rods
and cones to long- and short-wavelength light in ISLE 3.7.
An interesting practical implication of the Purkinje effect is
that, as nighttime conditions appear, longer wavelengths of light
will appear darker, whereas shorter wavelengths will appear rela-
tively brighter. This means that red objects become more difficult
to see at night than blue or green objects with similar reflectance
values. It is for this reason that, some years ago, fire departments
started shifting away from traditionally red vehicles. Because
red is harder to see at night, fast-moving red fire trucks will be
more difficult for other drivers to see than fast-moving blue fire
trucks. Nonetheless, tradition is often hard to break, and many
fire departments still opt for the traditional fire-engine red, even
though it puts both firefighters and other drivers at more risk. However, another
driving convention does have perceptual validity. Red light is less likely to affect our
ability to adjust our eyes to see in the dark (dark adaptation) than other colors. This
validates the decision to make taillights on cars red. Drivers will see red taillights
at night, but the red light will not affect their dark adaptation as much as taillights
of other colors would. You may have noticed how distracting a white (or broken)
Purkinje shift: the observation
that short wavelengths tend to
be relatively brighter than long
wavelengths in scotopic vision
versus photopic vision
ISLE 3.6
Photopic vs. Scotopic Vision
ISLE 3.7
Purkinje Shift
Characteristic Photopic Scotopic
Color vision Yes (three cone
classes)
No (only one type of rod)
Peak spectral sensitivity ~550 nm ~505 nm
Acuity (spatial summation) Good Poor
Temporal resolution (temporal
summation)
Good Relatively poor
Regions of greatest sensitivity Fovea ~20 degrees at the
periphery
Relative sensitivity 1,000,000 1
Receptor
Type
Peak Sensitivity
(Nanometers)
Rods 496
S-cones 420
M-cones 530
L-cones 560
TABLE 3.2 Receptor Types
NOTE: Each receptor type shows a peak sensitivity to light at a
particular wavelength. The receptor type is shown on the left,
and the peak sensitivity (in nanometers) is shown on the right.
These peak sensitivities are approximate and may vary among
people with normal vision.
TABLE 3.3 Photopic Versus Scotopic Vision
70 Sensation and Perception
taillight can be at night, as it interferes with your ability to see well in the dark. This
is also why the little screens of cell phones can be so distracting in an otherwise dark
movie theater.
Spatial Summation and Acuity
The next difference between photopic and scotopic vision is the relative acuity of the
two systems. Acuity refers to the ability to see or resolve fine details. The reason for
the acuity difference is partially that rods and cones have different spatial summation
characteristics. Spatial summation refers to the ability to pool light across different
regions of space. At night, you want to detect as much light as possible, even if spatial
summation causes things to be a bit blurry. During the day, there is ample light, so
acuity becomes the prominent issue. As you know by now, rods are more sensitive to
dim light than cones are. Part of this light sensitivity occurs because many rods connect
to one retinal ganglion cell where their responses are added together. This allows the
scotopic system to pool responses across different rods in order to maximize sensitivity
to light. However, by pooling across rods, the scotopic system loses some ability to
resolve light to particular locations in the visual world. This pooling of information is
called convergence, and it is much greater for rods than for cones. The lowest level
of convergences is for cones in the fovea, thus maximizing the ability to pinpoint the
source of the light in space, even if it does not allow sensitivity to dim lights. In fact,
in the fovea our acuity is determined by the density of cones, whereas in the periphery,
even in photopic vision, our acuity is determined by the density of a particular type of
ganglion cell, the midget cell, that we will discuss later (Rossi & Roorda, 2010). See
ISLE 3.8 to explore how changes in convergence alter how we see details. Try the image
provided or upload one of your own.
To illustrate convergence with an example, consider admiring the fine coat of a
Bengal cat (Figure 3.21). You want to be able to make out the intricate patterns on
the coat and see them in fine detail. To do this, you cannot confuse one location along
the cat’s fur with another. Thus, neutrally, you want as little spatial summation as
possible. This is what the cones provide. The cones, particularly in the fovea, pick
up light in one very small area and project that through one ganglion cell, so as not
to cause spatial confusion. Thus, cones allow us to see with greater visual acuity,
whereas rods are more sensitive to low levels of light.
Dark and Light Adaptation
Imagine waking up in the middle of the night. It is dark, and there are other people still
asleep in your house, so you do not want to turn the lights on and alarm them. But you
are hungry, and you want a snack. You know that there are still some of your favorite
brownies in the kitchen. You feel your way along the wall into the kitchen and enjoy
the chocolate brownies in the middle of the night. With your late-night craving satisfied,
you are ready to return to sleep. But before you return to bed, you may notice that after
you have been up for a little while, you can see in the dark. What before was obscured
you can now discern. This is the process of dark adaptation. It takes nearly 30 minutes
for the process to transition from seeing in bright day to seeing your best in the dark,
but the shift from photopic to scotopic vision allows people to see much better in the
dark. See ISLE 3.9a and 3.9b to see how fast we can dark adapt and a simulation of our
changing sensitivities on dark adaptation.
What is going on during dark adaptation? First, a definition: Dark adaptation
is the process in the visual system whereby its sensitivity to low light levels is
increased. During the first 8 minutes of trying to see in the dark, it is still the
cones that are doing most of your seeing. Then, your sensitivity to low levels of
light increases, as your scotopic system rods come online and start taking over.
ISLE 3.8
Convergence
Convergence: the number of
photoreceptors that connect
to each ganglion cell; more
convergence occurs for rods
than for cones
Dark adaptation: the process
in the visual system whereby its
sensitivity to low light levels is
increased
ISLE 3.9
Dark Adaptation Function
71 Chapter 3: Visual System: The Eye
Part of the explanation for dark adaptation includes the properties of the pho-
topigments themselves. Dark-adapted eyes have a higher concentration of rho-
dopsin, the active pigment in the rods. In the darkness, the levels of rhodopsin
increase. Thus, one factor in dark adaptation is the concentration of photopig-
ment (Rushton, 1965). Other factors include dilation of the pupil, which happens
rapidly in lower light levels, and other factors in how the retina processes light
(Figure 3.22 and ISLE 3.9).
Light adaptation occurs when light returns, such as when electric lights are turned
on in an otherwise dark room. It is acceptable to think of light adaptation as being
like dark adaptation but in reverse. However, there is one major difference: Light
adaptation will be completed in about 5 minutes, or even less, as the visual system
switches back to relying on cones rather than rods. Dark adaptation is therefore
much slower. It seems that this difference is due partly to the fact that light adap-
tation is driven actively by the light entering the eye, whereas dark adaptation is a
more passive response to the lack of light. Of course, under natural conditions, in
which the only source of light is the sun, dark adaptation is sufficiently fast to adjust
to changing light conditions as the sun sets, and light adaptation might be mostly
gradual as well. The change from afternoon sun, through dusk, to evening is about
the time it takes dark adaptation to complete its total swing.
There are some interesting implications of the shift from light adaptation to dark
adaptation and back again, especially in our constructed world, in which a person
may go back and forth from lit rooms to dark ones every
few minutes. Think about a police officer, patrolling at
night. He should be dark adapted to survey the nighttime
scene, but may need to shift to photopic vision to read the
computer in the patrol car. If a task requires a person (such
as our police officer) to go quickly from a lighted area to a
dark area in a short period of time, then the period required
for full dark adaptation may present problems. If the offi-
cer, after checking his computer, must enter a dark alley
in pursuit of a suspect, his vision may not be optimized.
This dark adaptation period delays how fast the person can
begin functioning in the dark. However, this limitation can
be overcome by having the person work in an environment
with only red lights. The red light will not be absorbed by
the rods as well as other wavelengths, allowing the dark
adaptation process to begin in the rods while the cones
respond to the red light. Then, when the light is removed,
the person is dark adapted to a large degree and can oper-
ate immediately in the dark, an advantage for a police offi-
cer in the field. This works because the cones are relatively
more sensitive to long-wavelength light than the rods. The
greater sensitivity of cones than rods to the long wavelengths is so significant that
cones are actually more sensitive to these wavelengths than rods are in an absolute
sense, not just a relative sense (Cornsweet, 1970).
A common example of this technique is the use of red flashlights when observing
with a telescope at night. An observer can look at a star chart or other information
using the red flashlight. This will give her the ability to use her photopic vision to read
the details of the star chart. Then, when the light is turned off, she still has her scotopic
rod vision to see the subtle detail in the night sky, such as a faint galaxy or nebula. In
modern smartphones, apps are available to help you determine which star is which
when you stargaze. Smartphone apps, such as Google Sky Map, can be put into night
mode, in which the display is in red.
FIGURE 3.21 The Fine
Coat of a Bengal Cat
Our photopic system allows us
to see the fine detail of patterns
and colors in the coats of these
beautiful cats.
©
iStockphoto.com
/photodeti
Dark adaptation
curve for rods only
6
5
4
3
2
1
0
0 5 10 15
Minutes in dark
B
ri
g
h
tn
e
ss
o
f
li
g
h
t
th
a
t
is
j
u
st
b
a
re
ly
v
is
ib
le
20 25 30
Dark adaptation
curve for cones only
Maximum cone
sensitivity
Maximum visual
sensitivity
Overall dark adaptation
curve (for rods and
cones combined)
Rod-cone
break
FIGURE 3.22 The Process of Dark Adaptation
As a dark period extends in time, sensitivity to light increases.
In the graph, the blue line shows the overall increase in
sensitivity to light. The orange line shows the change in
sensitivity for cones in the fovea.
Light adaptation: the process
whereby the visual system’s
sensitivity is reduced so that
it can operate in higher light
levels
72 Sensation and Perception
Another application of the knowledge of dark adaptation takes place in the
modern aircraft cockpit. There are a lot of visual situations that can alter a person’s
ability to read a cockpit display. Think of a pilot flying with the sun directly in his
face. The pilot may light-adapt to the sun and then not have sufficient sensitivity
to read the electronic display when needed. The opposite problem occurs at night,
when it is desirable to not have the displays so bright that the pilot will light-adapt
to the display and not be able to see the runway clearly. To avoid these problems,
researchers determined the light levels needed to see the sky in front of the airplane
and also to see the displays inside the cockpit in situations with high light intensity
and low light intensity. From these data, Krantz, Silverstein, and Yeh (1992) devel-
oped automatic adjustments so that pilots do not have to spend time adjusting the
luminance of their displays when the lighting conditions change. When it is dark
outside, the displays inside the cockpit will switch to a red light that allows the
pilots to dark-adapt for seeing outside the plane but also allows them to read their
instruments inside the plane (Figure 3.23). Some smartphones have incorporated
some of this research. See ISLE 3.10 for how automatic lighting adjustment works
in airplanes.
Development: Infant Acuity
Parents and grandparents stare intently at their newborn child or grandchild, but what
does the child see if they are looking back (Figure 3.24)? Studies of the developing eye
indicate that although the rods are nearly adultlike in their development by birth, the
cones are not. Cones are not packed as closely together in the fovea of children as they
are in the fovea of adults (Banks & Bennett, 1988). As discussed earlier, the density
of cones in the fovea is critical to the high level of acuity we enjoy as adults (Rossi &
Roorda, 2010). If infants have a lower density of cones at birth, then they should have
a lower acuity, but how do we determine what their acuity is?
In Chapter 2, we discussed psychophysics, which depends on asking the partic-
ipant a question such as “Did you see the stimulus?” A researcher could try that
with an infant, but it is unlikely to be very successful. Researchers must consider
the fact that infants do not talk, but they get fussy easily and are not noted for
their patience with researchers’ interests. As such, researchers have been very cre-
ative in developing methods that allow us to examine the visual abilities of infants.
Some methods rely on the observation that infants show preferences for some
stimuli over others by various behaviors, such as widening of the eyes or, when a
little older, looking in one direction or another. Other methods employ variations
of recording brain activity such as electroencephalography
(EEG) and event-related potentials (ERPs). In all of these
methods, two stimuli are presented, one an acuity stim-
ulus (such as alternating white and black bars) and the
other a plain gray field. If the infant responds differently
to the two stimuli, preferring the bars to the gray field, or
having a different brain activity, then it is determined that
the infant can see those bars. Thus, we can determine an
infant’s acuity by finding the smallest bars that the infant
responds to.
Several studies have examined infant acuity with a variety of
these methods (e.g., Atkinson, Braddick, & Moar, 1977; Mayer &
Dobson, 1982; Salomão, Ejzenbaum, Berezovsky, Sacai, &
Pereira, 2008; Sokol, 1978), and although the absolute values
of acuity often disagree, they all find the same general pattern as FIGURE 3.23 Dark Adaptation in an Aircraft Cockpit
®
R
og
er
R
es
sm
ey
er
/C
or
bi
s/
VC
G
/C
or
bi
s
D
oc
um
en
ta
ry
/G
et
ty
Im
ag
es
ISLE 3.10
Automatic Light
Adjustment in Cockpits
73 Chapter 3: Visual System: The Eye
shown in Figure 3.25. An infant’s acuity is quite poor when he is
born but it develops rapidly, particularly in the first year of life.
However, the child does not have adult acuity (indicated by the
Snellen acuity of 20/20 on the figure) at that time. Acuity con-
tinues to improve over the next few years but at a much slower
rate (Figure 3.25). There is a reason that when children are first
learning to read, the letters are larger than in books for adults.
TEST YOUR KNOWLEDGE
1. Diagram the different elements of the visual system that allow
us to adjust to a wide range of lighting conditions.
2. Devise an outline that describes the difference between
daylight vision and nighttime vision.
RETINAL GANGLION CELLS
AND RECEPTIVE FIELDS
3.5
Diagram the receptive fields of retinal ganglion cells,
and show how they need contrast to operate.
Each photoreceptor is connected to several different retinal
ganglion cells, which convey the signal into the optic nerve and
toward the brain. There are only about 1.1 million ganglion
cells, many fewer than the total number of rods and cones.
Therefore, most ganglion cells receive inputs from many dif-
ferent photoreceptors (called convergence; see Figure 3.26).
A ganglion cell receives input from receptors that are next to
each other on the retina, which form a grouping of adjacent
receptors. This grouping is called a receptive field. A receptive
field is the area in the visual world that a particular vision neu-
ron responds to. But in this case, it also refers to the array of
photoreceptors from which each retinal ganglion cell receives
input. In the retina, the first visual receptive fields studied were
the receptive fields of the ganglion cells. Kuffler (1953) was the
first researcher to study these remarkable cells. A particular
ganglion cell that receives input from the fovea might have a
receptive field that corresponds to exactly the point you are
looking at. A ganglion cell that receives input from the far
periphery might have a receptive field that corresponds to a
point in space just at the edge of your visual field, away from your point of central fix-
ation. Receptive fields are illustrated in Figure 3.26. Examine this figure carefully; there
is a lot of information in it.
In the fovea, just a few cones map onto one retinal ganglion cell. Therefore, the
receptive fields of these ganglion cells are quite small and correspond to small regions
in visual space, consistent with the idea that the fovea is designed for high visual acu-
ity. In the periphery, however, many cones or rods, in some cases hundreds of them,
will map onto a single ganglion cell. As you move away from the fovea, ganglion
receptive fields get progressively larger (Watanabe & Rodieck, 1989). These greater
receptive fields allow greater convergence and greater sensitivity to dim light. This
FIGURE 3.24 Parents With Newborn Baby
Parents and grandparents enjoy staring at newborns, but
what does the newborn see?
20/20
20/32
20/50
20/80
20/125
20/200
20/320
0 6 12 18 24 30 36
S
n
e
ll
e
n
a
cu
it
y
Age (months)
Mean
FIGURE 3.25
Development of Visual Acuity in Young Children
Children show a rapid development in acuity over the first
year of life and then a slower development of acuity to adult
levels in the next few years.
Source: From Salomão, S. R., Ejzenbaum, F., Berezovsky, A., Sacai, P. Y., &
Pereira, J. M. (2008). Age norms for monocular grating acuity measured
by sweep-VEP in the first three years of age. Arquivos Brasileiros de
Oftalmologia, 71(4), 475–479.
Receptive field: a region of
adjacent receptors that will
alter the firing rate of a cell
that is higher up in the sensory
system; the term can also apply
to the region of space in the
world to which a particular
neuron responds
Jennifer Volker Krantz
74 Sensation and Perception
summation across adjacent rods is called convergence (reviewed earlier in the section
on spatial summation and different from the meaning of convergence as applied to
the lens). Thus, retinal ganglion cells are processing for acuity in the fovea and light
detection in the periphery.
Retinal ganglion cells also start the process of edge detection. Critical to vision,
edge detection involves determining the location at which one object ends and the
next object begins. This is important in discriminating objects, detecting camouflage,
and many other important visual functions. We focus on edge detection in terms of
perception later. But for now, it is important to know that the visual system searches
for these edges and enhances them, so that we can clearly see them. The earliest stage
of edge detection occurs in the retinal ganglion cells and is known as center-surround
receptive fields (Figure 3.27 and ISLE 3.11).
Kuffler (1953) noticed during single-cell recording of retinal ganglion cells that he
could stimulate the center of a receptive field, resulting in a different response from
the cell than when he stimulated the surrounding area of the receptive field of that
cell. In some cases, stimulating the center of the field resulted in an increase in the
number of neural responses, called excitation. In other cells, stimulating this same
part of the receptive field resulted in a decrease in the number of neural responses,
called inhibition. Note that both a positive (excitation) and a negative (inhibition)
High
Moderate
Firing rates
Low
Baseline
High
convergence
High convergence, low acuity
Same signal sent
into optic nerve
Different patterns of signals
sent into optic nerve
No convergence, high acuity
Moderate
convergence
No
convergence
Cones
Incoming light
Neural
signals
Retinal
ganglion
cell
Action
potentials
(a) Degrees of convergence
Low firing
rate
Moderate
firing rate
High
firing rate
(b) Spatial summation
(c) Acuity
FIGURE 3.26 Convergence of Photoreceptors Onto Ganglion Cells
In the fovea, there is little convergence or no convergence, as one receptor cell matches onto one ganglion cell. However, as one
moves into the periphery, there is more convergence, as multiple photoreceptors match onto the same ganglion cell. The more
convergence, the greater the light sensitivity, whereas the less convergence, the greater the acuity.
Edge detection: the process
of distinguishing where one
object ends and the next
begins, making edges as clear
as possible
Center-surround receptive
field: a receptive field in which
the center of the receptive field
responds opposite to how the
surround of the receptive field
responds; if the center responds
with an increase of activity to
light in its area, the surround
responds with a decrease in
activity to light in its area
75 Chapter 3: Visual System: The Eye
response are still responses, just of different kinds. If you stimulate an area outside a
particular cell’s receptive field, you will get no response, neither excitation nor inhi-
bition. This difference in excitation and inhibition allows the cell to start coding for
edges. We will explain why shortly.
There are two kinds of center-surround receptive fields. They are known as
on-center receptive fields and off-center receptive fields. In on-center receptive
fields, the cell’s center produces excitation, whereas the surround produces inhibi-
tion. In off-center receptive fields, the center produces inhibition, whereas the sur-
round produces excitation. In either case, if you present light that covers the entire
receptive field of the cell, the response will be small, as the excitation and inhibition
will cancel each other out. However, if you present a pattern with edges (contrasting
light and dark), the cell may respond strongly. That is, these cells respond to lumi-
nance contrast, or differences in light intensity across the field. To make sense of this,
think of the following: A uniform field in the visual world is usually not interesting
or important (think of a blank wall or a uniformly blue sky). Contrast, however, is
(a) ON-center ganglion cell
(b) OFF-center ganglion cell
Spot in
center
Spot in
surround
Light on
Light on
Response
Spot in
center
Response
Response
+
+
+ + −
−
−
−
+
+
+ + −
−
−
−
+
+
+ + −
−
−
−
Spot in
surround
Response
+
+
+ + −
−
−
−
FIGURE 3.27
Center-Surround Receptive Fields
(a) An on-center ganglion cell. The image shows
a receptive field for an on-center ganglion cell.
When a light is shined in the center, the ganglion
cell becomes more active than its base-rate
state. However, when a light is shined at the
periphery of the receptive field, the ganglion cell
is inhibited below base rate. (b) An off-center
ganglion cell. The image shows a receptive field
for an off-center ganglion cell. When a light is
shined in the center, the ganglion cell becomes
less active or inhibited relative to its base-rate
state. However, when a light is shined at the
periphery of the receptive field, the ganglion cell
becomes more active than base rate.
ISLE 3.11
Center-Surround Receptive Fields
On-center receptive fields:
retinal ganglion cells that
increase their firing rate
(excitation) when light is
presented in the middle of the
receptive field and decrease
their firing rate (inhibition) when
light is presented in the outside
or surround of the receptive field
Off-center receptive fields:
retinal ganglion cells that
decrease their firing rate
(inhibition) when light is presented
in the middle of the receptive
field and increase their firing
rate (excitation) when light is
presented in the outside or
surround of the receptive field
76 Sensation and Perception
important—whether it be the change of lightness where the wall meets the door or
the roiling patterns of clouds of an impending thunderstorm. Or think about our
police officer on patrol at night. She wants to be able to make out the dim form of a
prowler as distinguished from the background night. Thus, the visual system should
be looking for these contrasts, as they indicate interesting features of the visual world.
Indeed, it appears that edge detection, such as what is seen in center-surround orga-
nization, starts early in visual processing, already occurring in the retinae themselves.
For an illustration of this, go to ISLE 3.11 to simulate how Kuffler (1953) conducted
his experiments and see how these receptive fields need contrast to respond.
The physiological mechanism that creates center-surround receptive fields is quite
complex. To understand how it works, one must consider the roles of horizontal cells
and bipolar cells, as well as the rods, cones, and retinal ganglion cells. Consider the
receptive field of retinal ganglion cells in the foveal region of the retina. A person
directs his or her gaze to an object, such as a cup of coffee on a table. The image of the
coffee cup is now projecting directly onto the fovea. Cones in the fovea will initiate an
excitatory signal in response to the light reflecting off the coffee cup. This signal will
move to both the bipolar cells and the horizontal cells. In response to the signal from
the cones, horizontal cells send inhibitory signals back to adjacent cones. Horizontal
cells also send excitatory signals across to other horizontal cells, thus increasing the
inhibitory feedback on the cones. That is, these cells act to minimize the responses to
uniform fields (an empty table) and maximize the response to changing fields (a coffee
cup on that table). However, this inhibition decreases across space, so that cones far-
ther from the source of the image are less inhibited. The combination of the positive
signals coming from bipolar cells and the inhibition coming from the horizontal cells
determines the strength of a signal to a retinal ganglion cell, which then has its own
center-surround characteristics. The result of these complex processes is known as lat-
eral inhibition (Hartline & Ratliff, 1958).
The goal of lateral inhibition is to facilitate edge detection. Edge detection is the
result of lateral inhibition which is the outcome of center-surround receptive fields.
That is, it is lateral inhibition working in receptive fields that make edges as clear as
possible. Edge detection is important—think about trying to see a camouflaged pred-
ator, perhaps a lioness, in the tall dry grass. The lioness’s fur and the grass are roughly
the same color, important for the lioness as she slowly stalks her prey (you, in this case).
However, the fur and the grass are not identical, and you want your visual system to
pick up where the grass ends and where the lion begins (so you can jump back into
your Land Rover and speed away and have stories to tell for a long time). This involves
edge detection and gestalt figure–ground discrimination (see Chapter 5). Some animals
have developed patterns on their fur or skin to confuse edge detection. For example,
the stripes on tigers break up the outlines of their body and make them harder to spot
when partially hidden. But if we think of it in terms of figuring out where one object
ends and the next begins, we have the basic function of edge detection (Figure 3.28). It
is for this reason that edge detection evolved. As we will see throughout our discussion
of the visual system, edge detection is built in at every level.
Lateral inhibition explains a famous visual illusion known as Mach bands, named
after their discoverer, Ernst Mach (1838–1916). Mach bands are illustrated in
Figure 3.29. Examining the pattern in the figure, you see bands of dark gray on the
left and progressively lighter bands of gray to the right. If you look at each band, it
looks as if it is slightly lighter on the left side than on the right side. This is an illu-
sion. The reflectance of each band is uniform. That is, the perceived intensity appears
to take a big step at the border of each band and then gradually declines until you get
to the next edge. This is edge enhancement. Lateral inhibition accentuates the edges
of the stimulus, so that you see the borders of reflectance more clearly. However, it is
also an illusion, as each band has the same reflectance across its space. In the Mach
Lateral inhibition: the
reduction of a response of
the eye to light stimulating
one receptor by stimulation of
nearby receptors, caused by
inhibitory signals in horizontal
cells
77 Chapter 3: Visual System: The Eye
bands, the enhanced edges are illusory. But the system has functional value—in
the real world, perceiving shape is critical, and lateral inhibition helps us do so. See
ISLE 3.12 for an interactive version of Mach bands.
TEST YOUR KNOWLEDGE
1. Create a diagram for yourself to show the spatial summation of rods and cones to create
a center-surround receptive field.
2. Critique the operation of center-surround receptive fields. How do they enhance vision
and create illusions?
REFRACTIVE ERRORS AND
DISEASES OF THE EYE
3.6
Judge the different refractive errors and eye diseases
on how they affect the ability of the eye to see.
As you can tell from reading this chapter, the human eye is an extremely complicated
organ, and vision is a very complex process. The result, seeing, is remarkable when
you consider all the eye and brain must do in such a short time to allow us to see
FIGURE 3.28
Edge Enhancement
These Thomson’s gazelles are alert
for the possibility of approaching
predators. (a) A normal photograph.
(b) Same photo with edges
enhanced. This kind of enhancement
allows better detection of objects
against a uniform background.
©
S
hu
tt
er
st
oc
k.
co
m
/
Th
eL
ea
rn
in
gP
ho
to
gr
ap
he
r
Isle 3.12
Mach Bands
(a) (b)
Stimulus
(b)
Receptors
Ganglion cells
What you
experience
1 2
2
3
3
4
4
5
5
6
6
7
7
8 9 10 11 12 13 14 15
8 9 10 11 12 13 14 151
FIGURE 3.29 Mach Bands
(a) Each bar in this picture is uniform in lightness. However, we see a different level of lightness in each bar from left to right. For each bar, the
left edge looks blacker than the right edge, which looks lighter or whiter. (b) This illusion is the result of processes of edge detection, such as
lateral inhibition. When cells with receptive fields that straddle the bars detect the lightness contrast, they act to enhance the edges.
(a)
78 Sensation and Perception
as we do. Nonetheless, problems can arise that interfere with clear visual perception.
Undoubtedly, you know people who wear eyeglasses or contact lenses, and you may
wear them yourself. The origin of these minor problems is interesting and is discussed
in this section. You may also know someone with more serious visual problems, such as
cataracts or macular degeneration. We discuss these two disorders as well.
Myopia (Nearsightedness)
Myopia is a common form of mild visual impairment, often called nearsightedness
because people with myopia can focus well on near objects, but faraway objects appear
blurry. There is usually a parallel problem with both eyes,
but a person can potentially be myopic in one eye but not
the other. Moreover, if the person has myopia, it is typ-
ical that each eye has a different level of myopia. With
myopia, the eye tends to be too long from front to back
for the lens. The process of accommodation cannot make
the lens thin enough to focus the light from more dis-
tant objects onto the retina. Because these distant objects
are focused in front of the retina instead of onto it, the
objects appear blurry. Another way to state this is that
the lens is too strong for the length of the eye. To correct
the problem, the lens must be weakened. To weaken the
lens, a diverging or negative artificial lens is used, that is,
typical eyeglasses. A diverging or concave lens is wider
at the edges than at the middle; this is the opposite of
the eye’s own lens and the lenses that have been used in
the figures. As a result, light spreads out even more after
it has passed through the lens than it would otherwise.
Eyeglasses or contact lenses refract or bend light just
enough so that the image can be focused onto a person’s
retinae, allowing a focused image. However, once the
glasses or contacts are removed, light comes into focus
in front of the lens, and objects at a distance will again
appear blurry, though objects up close will be in focus.
Thus, myopia is readily compensated for with glasses (or
contacts), but people must wear their eyeglasses in order
to compensate for this condition. The optics of the lens
in myopia are illustrated in Figure 3.30. For a dynamic
demonstration, see ISLE 3.13. Myopia is quite common. There are an estimated
70 million people in the United States alone with myopia.
Hyperopia (Farsightedness) and
Presbyopia (Old-Sightedness)
Both hyperopia and presbyopia are common forms of mild visual impairment, often
called farsightedness because people with these impairments can focus well on faraway
objects, but near objects may appear blurry. With hyperopia, the eye tends to be too
short for the lens (Figure 3.31). The lens is not strong enough for this eye. The process
of accommodation does not make the lens thick enough to focus the light from closer
objects onto the retinae. Because these close objects are focused behind the retinae
instead of on them, the objects will appear blurry. Distant objects, however, are seen just
fine. As with myopia, eyeglasses can be fitted that will allow near objects to be imaged
Myopia: a condition causing
an inability to focus clearly
on far objects, also called
nearsightedness; occurs
because accommodation
cannot make the lens thin
enough
Focus on retina
Light from
distant object
Normal vision
Normal optic axis
Focus in front
of retina
Thin lens
Thin lens
Light from
distant object
Myopia (Nearsightedness)
Long optic axis
FIGURE 3.30 Myopia
If the eye is too long internally, the lens cannot become thin
enough to focus an image on the retina. Instead, the image
focuses in front of the retina, making the image on the retina
blurry. Myopia is correctable with eyeglasses.
79 Chapter 3: Visual System: The Eye
ISLE 3.13
Correcting Myopia and Hyperopia
Hyperopia: a condition
causing an inability to focus
on near objects, also called
farsightedness; occurs because
accommodation cannot make
the lens thick enough
Astigmatism: a condition
that develops from an irregular
shape of the cornea or the lens,
which makes it impossible for
the lens to accommodate a fully
focused image
FIGURE 3.31 Hyperopia, or Farsightedness
If the eye is too short internally, the lens cannot become thick
enough to focus an image on the retina. Instead, the image
focuses behind the retina, making the image on the retina blurry.
Hyperopia is correctable with eyeglasses. Similar to hyperopia
is presbyopia, in which a hardened lens tends to focus images
behind the retina. Presbyopia is very common as people age into
their 40s and 50s.
Focus on retina
Normal vision
Normal optic axis
Focus behind
retina
Thick lens
Thick lens
Light from
nearby object
Light from
nearby object
Hyperopia (Farsightedness)
Short optic axis
on the retinae. These glasses use converging or convex lens that are thicker in the mid-
dle like the lenses of our eyes.
Presbyopia, as discussed earlier, is a condition associated with older eyes (or older
people). As we age, the lens hardens and the ciliary muscles lose power. This makes
it harder for older eyes to accommodate to nearby objects. Presbyopia increases the
distance of the near point, which is the closest object we can bring into focus. As with
hyperopia, the lens now focuses objects behind the retina, requiring eyeglasses to be fit-
ted to allow magnification, which will focus objects onto the retinae. But the difference
is that in hyperopia, one corrective lens will allow the person to see near and far but, in
presbyopia, the person needs different corrections for near and far. Thus, your parents
might have reading glasses scattered around the house to use when reading but not when
looking in the distance, or they might wear bifocals where they look through the top for
seeing in the distance and the bottom to see up close. Presbyopia is a seemingly universal
condition. It is seldom noticed before the age of roughly 40. But by the age of 50, there
are few people who do not need reading glasses to correct presbyopia. Indeed, after 50
years of age, the rate at which presbyopia advances might be quite steep, requiring fur-
ther magnification in order for individuals to see small objects close to their eyes.
Astigmatism
Astigmatism develops from an irregular shape of the cornea or an irregular shape of the lens,
which makes it impossible for the lens to accommodate a fully focused image. Usually the lens
will accommodate to a relatively small area of the visual world. In the case of the cornea, the
surface of the cornea may be asymmetrical, and in the case of the lens, the shape of the lens
may not be sufficiently spherical. In astigmatism, the cornea bends the light more strongly in
one direction, say in the vertical direction, than it does in the direction that is at a right angle to
the first direction, say the horizontal direction. Thus, no matter how the lens changes shape, an
object in a particular location and orientation will not be in focus (Figure 3.32). Astigmatism
makes seeing some orientations blurry, whereas others are still relatively clear. Look at ISLE
3.14 for an example of what it looks like to have astigmatism. To correct this problem, a
80 Sensation and Perception
complex, conelike lens is used to offset the differences, though
it is often difficult to correct an astigmatism with eyeglasses
alone. Sometimes contact lenses are used to directly correct the
problem. More recently, LASIK (laser-assisted in situ ker-
atomileusis) surgery is used to reshape the cornea to bend the
light in the correct fashion.
Cataracts
Cataracts result from the clouding of the lens. Cataracts
affect older adults more than they do younger adults, but they
can occur in anyone at any age. With cataracts, over time,
the clear appearance of the lens becomes cloudy because of
water buildup, eventually leading to blindness unless there is
surgical intervention. Cataracts may result from complica-
tions of diabetes, exposure to ultraviolet radiation, or sim-
ply natural aging. Cataracts can now be fixed surgically. The
biological lens is removed and replaced by an artificial lens.
After surgery, patients will need glasses to focus at particular
distances, but they can see normally with glasses.
The conditions we have discussed so far arise from
problems with the lens or cornea. However, there are also
some conditions that affect the retina itself. These problems tend to be far more tragic
than most problems with the lens, which are now treatable with eyeglasses or, in the case
of cataracts, with a relatively straightforward surgical procedure.
Macular Degeneration
Macular degeneration is a disease that destroys the fovea and the area around it. The
medical term macula refers to the center of the retina. The macula includes the fovea but
is larger than it. The destruction of the macular region causes a blind spot in central vision.
A patient will direct his or her point of gaze to a point in space and then promptly lose
sight of it. Macular degeneration can occur in younger adults but is more common in older
adults. Macular degeneration occurs in two forms, known as wet and dry. Wet macular
degeneration has a very fast onset but is partially treatable. Dry macular degeneration may
take years to develop, but no treatment is available at present. Wet macular degeneration
occurs because of abnormal growth of blood vessels, leading to the leaking of blood below
the retina. This leakage leads to scarring of the macula. Wet macular degeneration can
be treated with a variety of medicines that shrink the damaged blood vessels, leading to
some improvement of vision. However, injections must be given frequently to maintain
this improved visual function (Arroyo, 2006). Wet macular degeneration is the less com-
mon form of macular degeneration (Bressler, 2004). Dry macular degeneration, the more
common form, results from degeneration of the cells that produce photopigments (pigment
epithelium) for the cones (and rods) in the macular region of the retina. This results in
impaired function of those photoreceptors (Stone, 2007). No treatment is yet available for
the dry form of macular degeneration. Figure 3.33 in the middle photograph illustrates
what the visual world looks like to patients with macular degeneration. Figure 3.34a is an
ophthalmoscopic fundus photograph of a patient with macular degeneration. You can also
go to ISLE 3.15 for an interview with a person living with this vision disorder.
Retinitis Pigmentosa
Retinitis pigmentosa is an inherited progressive degenerative disease of the retina
that may lead to blindness. Over a long period of time, retinitis pigmentosa leads to
Cornea—sphere shape
Cornea—oval shape
One focal
point
Multiple
focal points
Astigmatism
XX
Normal
vision
X
(a)
(b)
FIGURE 3.32 Astigmatism
(a) A normal cornea. (b) A cornea with an irregular shape,
allowing astigmatism to develop.
©
C
an
S
to
ck
P
ho
to
In
c.
/a
lil
a
Cataracts: a condition that
results from a darkening of the
lens
Macular degeneration: a
disease that destroys the fovea
and the area around it
Retinitis pigmentosa:
an inherited progressive
degenerative disease of the
retina that may lead to blindness
81 Chapter 3: Visual System: The Eye
ISLE 3.14
Astigmatism
ISLE 3.15
Living With Macular
Degeneration and
Retinitis Pigmentosa
FIGURE 3.33 Seeing With Macular Degeneration and Retinitis Pigmentosa
Macular degeneration affects central vision, blurring our perception of whatever it is we are trying to look at. Retinitis pigmentosa
affects peripheral vision, creating a “tunnel” vision effect in which we see what we are looking at with normal acuity but cannot see
what surrounds our focus.
©
C
or
de
lia
M
ol
lo
y/
Sc
ie
nc
e
So
ur
ce
degeneration and destruction of the photoreceptors, particularly rods at the periph-
ery. Indeed, some patients will exhibit symptoms such as night blindness as children,
whereas in other patients, the condition might not develop until adulthood (Hartong,
Berson, & Dryja, 2006). In many cases, the rods are affected first, particularly those
midway through the periphery. This results in tunnel vision (Figure 3.33 on the right),
in which a person can see only in a small area in the middle of the visual field. Retinitis
pigmentosa may progress and cause complete blindness as the destruction of photore-
ceptors spreads to the cones (Figure 3.34b). At present, there is no treatment for this
condition. However, some recent research suggests that gene therapy might be useful
in the near future (Wert, Davis, Sancho-Pelluz, Nishina, & Tsang, 2013). You can see a
person describe his experience with retinitis pigmentosa in ISLE 3.15.
TEST YOUR KNOWLEDGE
1. Examine how differences in the structure of the eye contribute to the differences between
myopia and hyperopia.
2. Choose a refractive error you do not have and predict what vision is like to a person with that
refractive error (it would not hurt to ask someone with this refractive error and see if you are right).
FIGURE 3.34 Macular Degeneration and Retinitis Pigmentosa and the Retina
(a) The retina of a person with advanced dry macular degeneration. (b) The retina of a person with retinitis pigmentosa.
©
B
io
ph
ot
o
A
ss
oc
ia
te
s
/
Sc
ie
nc
e
So
ur
ce
©
S
ci
en
ce
S
ou
rc
e
(a) (b)
82 Sensation and Perception
EXPLORATION: Animal Eyes
Earlier we briefly covered the topic of how our eyes have
resulted from evolutionary processes. From this perspec-
tive, our eyes are the way they are because they helped our
ancestors survive. We have an eye that works for us and
the things that we as humans do. Different animals live in
different ecological niches and, thus, have different eyes.
They use their vision differently to survive in their niches.
There is not space here to cover all the different types of
animal eyes, but we briefly examine a few examples to
show some of the variety in eyes and their visual func-
tions. Some eyes are more complex and some are simpler,
but that is not the same as better or worse. If the eye helps
the animal survive and reproduce, it does its job. So, if the
animal is surviving then that eye works, even if it is not
equally complex to ours. Certainly, we would not enjoy
having any of these other eyes, but then we are humans,
not cats or fiddler crabs.
Cats
Let us start with a familiar animal that, in many ways, has
eyes similar to ours, cats. They are fellow mammals and
have the same basic structure to their eyes and retinae. The
similarity of their eyes to ours has made them useful sub-
jects for learning about our visual systems. Kuffler (1953)
studied cats to discover center-surround receptive fields.
Cats can see well in both daylight and dark. In particular,
they function in the dark much better than humans do.
This need to function in the dark has led to some very
interesting adaptations in their eyes. First, notice the pupil
of cats (Figure 3.35). Instead of a round pupil like ours,
they have a slit pupil, like snakes. This type of pupil allows
them to adjust the size of the pupil to a much greater
degree than we can. Figure 3.35a shows a small pupil for
daytime and Figure 3.35b shows a large pupil for seeing in
the dark. You can barely make out the iris in Figure 3.35b.
This greater ability to change pupil size helps cats function
well in both daylight and nighttime, but it comes at a cost.
This pupil shape does not help make as clear an image as
our circular pupil, so cats have poorer acuity than we do
(Blake, Cool, & Crawford, 1974).
Another way that cats are adapted to see in the dark is
that they do not have a fovea. They have an area cen
tralis, which is related to their direction of gaze but
does not support high acuity as our fovea does. Another
interesting difference in cat eyes relative to ours has to
do with the layer of cells right behind the receptors.
Our pupils look black because behind our receptors we
have the pigment epithelium (review Figure 3.7). This
layer captures most of the light that is not caught by
a receptor, preventing light scatter, which would make
our retinal image blurrier. Cats, needing to function well
at night, need to get all of the light they can. Instead of
the pigment epithelium, they have a tapetum, which is
a reflective layer bouncing light not caught by receptors
back into the retina (Figure 3.36). It is a tapetum in the
eyes of a deer, another animal that needs to see at night,
that leads to the glow when a “deer is caught in the
headlights.”
FIGURE 3.35 Cat’s Slit-Shaped Pupil
(a) The pupil closed for seeing in bright lights. (b) The pupil opened to assist seeing in the dark.
(a) (b)
83 Chapter 3: Visual System: The Eye
Nautiluses
Cats’ eyes are recognizable to us because of the simi-
larity of their structure and their use, but some eyes are
strange indeed. Let us consider the nautilus. The nautilus
is a marine mollusk (Figure 3.37a) that seems not to have
significantly evolved during the past 500 million years.
To give some context, the very first dinosaurs emerged
230 million years ago and became extinct 66 million
years in the past. Nautliuses live in deep water with lim-
ited light and they are mostly scavengers, so their food
does not try to escape them. There is not a lot of light in
deep water, and the visual detection task of getting food
is not very complicated.
The nautilus has a very unusual eye that could even be
called a primitive eye, a pinhole eye. It does not have a
lens or cornea at all, and its pupil is quite small. Thus,
the nautilus eye is open to the sea (Figure 3.37b). This
is a simple eye, but a pinhole can focus images (Nilsson,
1989). Figure 3.38 shows several images of a partial
eclipse of the sun seen through the holes of a colander.
The small holes, similar to a pinhole pupil, can focus
an image somewhat similarly to a lens. Each hole in
the colander created its own image of a crescent sun.
However, for pupils to focus clearly, they must be small
and, as such, let in only a little light. So, this way of
seeing is only good when you have plenty of light. The
eyes of nautiluses stayed simple while the octopuses
and squids, to whom they are closely related, evolved
eyes that are similar to those of mammals in their
complexity.
Arthropods (insects and crustaceans) have compound
eyes. We will use the fiddler crab as an example but
emphasize the common features of their compound
eyes (Alkaladi & Zeil, 2014). In the compound eye,
FIGURE 3.36 The Reflective Tapetum Layer
The green seen in the cat’s eye in this flash photograph shows
light reflecting back from the tapetum.
FIGURE 3.37 The Nautilus and Its Eye Without a Lens
(a) A photograph of a nautilus. (b) A cross section of the eye.
Notice the lack of a lens and how the eye is open to the water.
©
S
hu
tt
er
st
oc
k.
co
m
/w
ild
es
ta
ni
m
al
(a)
(b)
84 Sensation and Perception
there is no single entrance to the eye but many small
structures called ommatidia (ISLE 3.16). The surface of
the eye is then a complex faceted structure with each
facet being the entrance to a different ommatidium.
Each ommatidium has its own small lens and a small
collection of pigment cells that capture the light and do
transduction. In addition, they have additional pigment
cells that, like our pigment epithelium, limit light scat-
ter, but in this case keep light from passing to adjacent
ommatidia (Figure 3.39). These different ommatidia
have their own neural connections, but they also inter-
act similar to light falling on one cone inhibiting light
responses to adjacent
cones through horizon-
tal cells. As such, these
eyes have lateral inhi-
bition. In fact, one of the very early studies of lateral
inhibition is in the compound eye of the limulus or
horseshoe crab (Hartline & Ratliff, 1958). Compound
eyes are particularly good at detecting motion. Given
the size of the ommatidium relative to our receptors,
motion of objects creates a flicker effect as adjacent
ommatidia turn on and off. As we will see in Chapter
8, motion detection is a very important task for our
visual systems.
ISLE 3.16 Compound Eyes
FIGURE 3.39 Compound Eye of the Fiddler Crab
(a) A photograph of a fiddler crab. Note the eyes at the end of the stalks. (b) A diagram of a representative compound eye showing a
few of the ommatidia.
©
S
hu
tt
er
st
oc
k.
co
m
/N
ic
ho
la
s
To
h
FIGURE 3.38 Light Passing Through the Small
Pinholes of a Colander
Light passing through the small pinholes of a colander. Each hole is a
pinhole and each pinhole focuses a separate image of the solar eclipse.
The picture was taken August 21, 2017, during the Great American
Eclipse. This is the partial eclipse on the way to totality.
TEST YOUR KNOWLEDGE
1. Examine how differences in the structure of the eyes of different animals alter their
experience of the visual world.
2. Formulate how the structure of an animal’s eyes, including ours, might have evolved to
match the animal’s needs to survive.
Tapetum: a reflective layer behind the receptors of
nocturnal animals that bounces light not caught by
receptors back into the retina
Compound eye: an eye that does not have a single entrance
but is made up of many separate components called ommatidia
(a) (b)
85 Chapter 3: Visual System: The Eye
APPLICATION: Vision Prostheses
Vision prostheses are mechanical devices intended to
restore visual function to blind individuals. They are
sometimes referred to as bionic eyes. Unlike the Bionic
Woman of television fame, vision prostheses are real and
are being developed to restore vision to those who have
become blind for a number of reasons. In particular,
they may be of use in people with macular degeneration
and retinitis pigmentosa, diseases that affect transduc-
tion in the eye. Blindness due to brain damage will not
be improved by vision prostheses. Moreover, although
vision prostheses are potentially useful to people who
have lost vision, at present, they are not helpful to con-
genitally blind individuals.
In the Western world, macular degeneration and retinitis
pigmentosa are the most common forms of blindness. In
both conditions, the photoreceptors are damaged, but
the underlying retinal ganglion cells and the optic nerve
remain intact. Therefore, the goal of vision prostheses
is to replace the missing photoreceptors with essentially
an artificial layer of photoreceptors, sometimes called an
“artificial retina.” There are a number of developments
in artificial retinae, but only one company has market-
ing approval for its device from the U.S. Food and Drug
Administration, granted in 2013, having previously
received approval in Europe in 2011. It is called the
Argus II, developed by California-based Second Sight
Medical Products (McKeegan, 2013). At present, it is
approved only for patients with profound retinitis pig-
mentosa. See Figure 3.40 for an illustration.
Unlike the Bionic Woman, the Argus II is still a bit bulky.
A small video camera is mounted on a pair of eyeglasses
the patient wears. Images from the video camera are
relayed wirelessly to a chip placed directly (via surgery)
on the patient’s retina or retinae. The chip’s electrodes
then stimulate the retinal ganglion neurons in a pat-
tern that roughly approximates the image the camera
is detecting. In its current form, the Argus II creates a
visual field approximately 20 degrees wide, thus allow-
ing some central vision, though with only limited periph-
eral vision. In the current version of the Argus II, there
are only 200 electrodes in the chip. It is estimated that
it would take 1,000 of these to allow the patient to see
clearly enough to recognize individual faces (Humayun
et al., 2012). Thus, at present, this system also has
limited visual acuity. It is likely that at present, reading is
also still not an option. But as the technology improves,
more electrodes may be loaded onto the chip, allowing
enhanced acuity.
Interestingly, patients don’t immediately “see” again.
They have to be trained to interpret the signals they
are receiving. However, with just a few hours’ worth
of training, patients can avoid obstacles, locate objects,
recognize colors, and even recognize very large letters.
Obviously, it is far from perfect. Although patients can
localize objects, tests of visual acuity show that they
improve to, at best, only approximately 20/1,000.
Moreover, the camera is not stable relative to the eyes,
and patients have to keep up with these small move-
ments of the camera relative to their eyes. It appears
they use their auditory system to assist in these needed
adjustments (Barry & Dagnelie, 2016). Nonetheless,
many patients are pleased to have some vision restored.
You can see a video of a person with the Argus II in
ISLE 3.17.
The Argus II is not the only device being built that uses
remote cameras to directly stimulate the optic nerve.
A number of other companies are developing similar
devices. One device, the artificial silicon retina, implants
the visual sensors directly into the damaged retina
(Chow et al., 2004). It then electrically stimulates the
retinal ganglion cells (DeMarco et al., 2007). This device
has the advantage of not requiring cameras and external
electronics. However, at present, clinical trials are still
ongoing, and the device is not yet approved for general
use. Another interesting approach to restoring eyesight
in those with retinal disease involves regrowing photo-
receptor cells using stem cell therapy. This research is
still in its beginning stages but is showing some prog-
ress. Other researchers are using fetal retinal tissue to
regrow photoreceptors in patients with retinitis pigmen-
tosa. One study found improvements in patients’ vision
up to 5 years later. One patient improved from 20/800
to 20/200 acuity after tissue implants (Radtke et al.,
2008). Like other techniques, this one is still in the clin-
ical trials stage.
There is also one device, BrainPort, that tries to use tactile
senses on the tongue to help those who are blind. As with
86 Sensation and Perception
the Argus II, patients wear glasses with a camera. However,
there is no implant. The camera goes to a controller that
converts the visual signals from the camera to tactile signals
that travel to a pad worn on the tongue. The pad vibrates
a pattern to match the visual information, and people can
learn to interpret this information to allow them to “see” in
much the same way as the blind can read using their fingers
in Braille (Grant et al., 2016).
Although wearing a pad in
the mouth all the time has its
limitations, this type of visual
prosthesis will work for those who have damage in the
visual cortex. Go to ISLE 3.17 for more about BrainPort,
including a video of people using this device.
TEST YOUR KNOWLEDGE
1. Apply your knowledge of center-surround receptive
fields to the challenges of building successful visual
prostheses.
2. Evaluate if visual prostheses would have to perform light
and dark adaptation.
Electronics Case
Antenna
Processor
Electrode Array
Camera
Antenna
FIGURE 3.40 Vision Prostheses
In the Argus II, images are created by a video camera mounted
on eyeglasses worn by the patient. The images are then sent to
a computer processor on the eyeglasses themselves. The signal
is then sent wirelessly to a chip embedded on the retina, which
then stimulates the retinal ganglion cells.
CHAPTER SUMMARY
3.1
Appraise the nature of light as electromagnetic
energy to explain the relation of wavelength to
perception.
Visible light is a small slice of the electromagnetic spectrum.
The electromagnetic spectrum is the complete range of
wavelengths of light and other electromagnetic energy. Light
from a light source such as the sun or a reading lamp reflects
off objects in the environment and enters our eyes. The pat-
tern of light enters our eye, and then our visual processes
start decoding it. Light is made up of particles called photons
that also behave in a wavelike manner. We see differences
in wavelengths as different colors.
3.2
Sketch the anatomy of the eye to show how it
makes vision possible.
The cornea and the pupil control the amount of light that
enters the eye. The size of the pupil adjusts to control the
amount of light entering the eye, and then the lens focuses
that light on the retina to make a retinal image. The retina
contains photoreceptors, which convert the light energy into
a neural signal.
3.3
Interpret how the retinae transduce light energy
into a neural signal that is sent to the brain.
The rods and cones of the retina are able to convert light
into a neural signal through chemicals known as photopig-
ments. Photopigments are molecules that absorb light and by
doing so release an electric potential by altering the voltage
in the cell. When a photopigment absorbs a photon of light,
it changes shape. This change of shape initiates a series of
biochemical processes, which result in a change of electric
potential, which allows for a signal to exit the photoreceptor.
In this way, a neural signal leaves the photoreceptor and is
transmitted to the optic nerve to be sent to the brain. Opsin is
the protein portion of a photopigment that captures the photon
of light and begins the process of transduction. It is the vari-
ation in this opsin that determines the type of visual receptor.
3.4
Illustrate how the visual system adapts to the
dark and then adapts again to the light to help us
adjust to changing light levels.
The retina has two types of photoreceptors, rods and cones.
The rods are specialized for night vision (scotopic) and light
ISLE 3.17
Vision Prostheses
Chapter 3: Visual System: The Eye 87
detection, whereas the cones are specialized for visual acuity
(photopic) and color vision. The duplex theory of vision states
that there are functionally two distinct ways that our eyes
work, one, the photopic, associated with the cones, and the
other, the scotopic, associated with our rods. Dark adaptation
takes about 15 minutes. Technologies have been developed to
allow people to see visual displays, such as computers with
red light that do not interfere with dark adaptation. The rods
and cones project to the retinal ganglion cells.
3.5
Diagram the receptive fields of retinal ganglion
cells, and show how they need contrast to
operate.
The rods and cones project to cells called the retinal ganglion
cells, whose axons exit the eye through the optic nerve. Retinal
ganglion cells have receptive fields. Receptive fields are regions
of adjacent receptors that will alter the firing rate of cells that
are higher up in the sensory system. The term can also apply to
the region of space in the world to which a particular neuron
responds. These receptive fields have a characteristic shape
known as center-surround. Center-surround receptive fields
occur when the center of the receptive field responds opposite
to how the surround of the receptive field responds. If the center
responds with an increase of activity to light in its area, the sur-
round will respond with a decrease in activity to light in its area
(on-center). If the center responds with a decrease of activity
to light in its area, the surround will respond with an increase
in activity to light in its area (off-center). This creates the phe-
nomenon of lateral inhibition. Lateral inhibition is the reduction
of a response of the eye to light stimulating one receptor by
stimulation of nearby receptors. It is caused by inhibitory sig-
nals in horizontal cells and creates the Mach band illusion. It is
responsible for enhanced edge detection by our visual system.
3.6
Judge the different refractive errors and eye dis-
eases on how they affect the ability of the eye to
see.
We also described a number of diseases and problems with
the eye. Myopia, presbyopia, and hyperopia are common
problems in the refracting power of the lens. Astigmatism is
a problem in the shape of the lens or cornea. They are all cor-
rectible with eyeglasses. Cataracts occur when the lens gets
cloudy and allows less or no light to pass through. Macular
degeneration and retinitis pigmentosa are diseases of the ret-
ina that can lead to serious visual impairment. Macular degen-
eration leaves a blind spot right at the location we are trying
to look at. Retinitis pigmentosa can cause tunnel vision in its
early and middle phases and lead to total blindness later on.
REVIEW QUESTIONS
1. What is light? Why is it considered both a wave and
a particle?
2. What are the roles of the cornea, the iris, the pupil,
and the lens in human vision?
3. What is accommodation? Explain how it produces a
focused image on the retina.
4. What are the different classes and subclasses of
photoreceptors? How do they convert light into a
neural signal?
5. What is the difference between photopic vision and
scotopic vision? What is each used for, and what
physiological mechanism underlies each?
6. What is the Purkinje shift? What does it tell us about
photopic vision and scotopic vision? How does it
relate to dark adaptation?
7. What are retinal ganglion cells? What do they do in
visual processing?
8. What are center-surround receptive fields? What
is the difference between on-center and off-cen-
ter center-surround receptive fields? How do these
explain lateral inhibition?
9. Distinguish between myopia, presbyopia, and hyper-
opia. What are the differences between macular
degeneration and retinitis pigmentosa?
10. What are some of the ways that eyes vary across
different animals?
11. What are vision prostheses? How do they restore
vision to people with retinal disease?
Sensation and Perception88
PONDER FURTHER
1. It is often written that the eye is like a camera, but that
analogy is not quite correct. You have read a lot about
the eye in this chapter. Create a diagram that compares
the eye to a camera, and consider what functions are
similar and where the analogy breaks down. Consider
both light-gathering elements of the eye and what is
done after light is captured, that is, after transduction
in the eye and after light falls on the film in the camera.
2. Review ISLE 13.11 (both parts) and ISLE 13.12. The ear-
lier discussion suggests that these receptive fields play
a role of edge enhancement. Survey graphic designs
around you, on the web, in print ads, or anywhere else,
and consider how these ads seem to take advantage of
this edge enhancement feature of our eye.
KEY TERMS
Accommodation, 60
Anterior chamber, 60
Astigmatism, 79
Cataracts, 80
Center-surround receptive field, 74
Ciliary muscles, 61
Compound eye, 83
Cones, 64
Convergence, 70
Cornea, 59
Dark adaptation, 70
Duplex theory of vision, 68
Edge detection, 74
Electromagnetic energy, 55
Electromagnetic spectrum, 56
Field of view, 58
Fovea, 64
Frequency, 55
Heterochromia, 60
Hyperopia, 78
Hyperpolarization, 67
Intensity, 55
Iris, 60
Lateral inhibition, 76
Lens, 60
Light adaptation, 71
Macula, 64
Macular degeneration, 80
Myopia, 78
Near point, 61
Neurotransmitter, 67
Off-center receptive fields, 75
On-center receptive fields, 75
Opsin, 66
Optic disc, 65
Photon, 56
Photopic vision, 68
Photopigment, 66
Posterior chamber, 60
Presbyopia, 61
Pupil, 60
Pupillary reflex, 60
Purkinje shift, 69
Receptive field, 73
Retina, 62
Retinal, 66
Retinal image, 62
Retinitis pigmentosa, 80
Rods, 64
Sclera, 60
Scotopic vision, 68
Tapetum, 82
Wavelength, 55
Zonule fibers, 61
Chapter 3: Visual System: The Eye 89
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
3.1 Appraise the nature of light as electromagnetic energy to
explain the relation of wavelength to perception.
Light
3.2 Sketch the anatomy of the eye to show how it makes vision
possible.
The Eye Pupil’s Response to Static and Dynamic Illusions of
Luminosity and Darkness
3.3 Interpret how the retinae transduce light energy into a neural
signal that is sent to the brain.
2-Minute Neuroscience: The Retina
Bionic Eye Opens New World of Sight for Blind
3.4 Illustrate how the visual system adapts to the dark and then
adapts again to the light to help us adjust to changing light levels.
The Eye Pupil Adjusts to Imaginary Light
3.5 Diagram the receptive fields of retinal ganglion cells, and show
how they need contrast to operate.
On and Off Center Retinal Cells
3.6 Judge the different refractive errors and eye diseases on how
they affect the ability of the eye to see.
The Manital Cortex in the Blind: Lessons About Plasticity
and Vision
Darkness Provides a Fix for Kittens With Bad Vision
4Visual System: The Brain
Richard Kail/Science Source
LEARNING OBJECTIVES
4.1
Identify the anatomy of the optic chiasm and how that
affects the lateralization of vision in the brain.
4.2
Diagram the anatomy of the lateral geniculate nucleus and the
superior colliculus, and describe their roles in visual processing.
4.3 Explain the nature of the retinotopic organization of V1 and the organization of V2.
4.4 Compare the difference between the dorsal pathway and the ventral pathway.
4.5 Interpret the concepts of blindsight and conjugate gaze palsy.
INTRODUCTION
In 1981, two Harvard professors won the Nobel Prize in Physiology or Medicine for
their work on the anatomy and physiology of the visual cortex (Figure 4.1). The two
men, Torsten Wiesel (born 1924) and David Hubel (1926–2013), collaborated for more
than 20 years on research that has revolutionized our understanding of the mammalian
visual cortex, including the human visual cortex. Dr. Wiesel, originally from Sweden,
and Dr. Hubel, born in Canada to American parents, started their collaboration as
postdoctoral fellows with Stephen Kuffler (whose work was discussed in Chapter 3).
A postdoctoral fellow, or postdoc, is someone who has earned his or her PhD but is
learning new techniques in a senior researcher’s laboratory. Later, they both moved to
Harvard and continued working together as they rose through the ranks at Harvard.
Their contribution to the field of sensation and perception cannot be overstated. We
refer to work they did 50 years ago, and it is just as relevant today as it was when it was
first done. Both men continued to be active professionally well into their 80s. Indeed,
in 2005, they published a book together outlining their collaborative research over
the decades, including much work done after their Nobel Prize was awarded (Hubel
& Wiesel, 2005). Wiesel also has been active in promoting global human rights and in
promoting collaboration between Israeli and Palestinian scientists.
Among their amazing discoveries is that areas of the visual brain, including
areas in the thalamus and areas in the occipital cortex, are specifically sensitive to
certain kinds of stimuli and that this sensitivity can be mapped into predictable
patterns (Hubel & Wiesel, 1965). That is, they discovered neurons in the brain
that have specific visual fields; the cells respond to some patterns of stimuli but not
ISLE EXERCISES
4.1 From Eye to LGN
4.2 Simple Cells
4.3 Complex Cells
4.4 Hypercolumns
4.5 Navigation in
Blindsight
92 Sensation and Perception
others. They also found that these stimulus-specific cells are
organized into complex but predictable columns. In related
research, they also pioneered how environmental input
affects the development of the mammalian nervous system,
that is, how these systems grow and change as mammalian
babies get older.
In this chapter, we consider the visual brain, namely, the
networks in the lateral geniculate nucleus (LGN) of the thal-
amus and the networks in the occipital cortex that allow
us to see in the way we do. It is these areas of the brain
that allow us to perceive beautiful sunsets, drive very fast
cars at racetracks, and quietly read at night by the glow of
our tablet computers. However, at the outset, we issue our
readers a warning: Do not read this chapter once and think
you understand the material. The organization of the visual
system is complex, and our derived naming system for it can
tax our mnemonic abilities—you will encounter parasol ret-
inal ganglion cells, parvocellular layers, hypercolumns, and
one area of the brain referred to by five different names.
Therefore, our advice is to review repeatedly, do all of the online demonstrations,
and self-test as you go through the material in this chapter. You will be glad you
did—the organization of the human visual system is a wonder of the natural world,
one to which science has paid particularly close attention.
In Chapter 3, we discussed how light is transduced by the retinae of the eyes
and converted into a neural signal. The retinae begin the processing of the visual
signal, already looking for edges and coding for color. This process intensifies when
the optic nerves leave the eyes and head for their first synapses in the brain. In this
chapter, we follow the neural signal as it leaves the eye and travels first to the LGN
of the thalamus and from there to the visual cortex in the occipital lobe. We also
consider other pathways of visual information after it leaves the eye. Much of the
information we consider in this chapter comes from research on nonhuman eyes
and brains, as most of the electrophysiological research was done on rats, cats, and
monkeys. However, much of what we know about mammalian visual systems gener-
alizes to our own. At the end of this chapter, we also consider a neuropsychological
condition called blindsight, which results from damage to the visual regions of the
brain without damage to the eyes. We will also consider conjugate gaze palsy, which
arises from damage in the brain stem. Both of these peculiar conditions underline the
critical nature of the brain in our ability to see.
THE OPTIC NERVE AND CHIASM
4.1
Identify the anatomy of the optic chiasm and how that
affects the lateralization of vision in the brain.
Approximately 1 million retinal ganglion cells form the optic nerve of each eye. The optic
nerve of the left eye and the optic nerve of the right eye meet just a couple of centimeters
behind the eyes, in an area called the optic chiasm. Here at the optic chiasm, your visual
system does one of its most interesting tricks, which is also one of the most difficult
©
Ir
a
W
ym
an
/S
yg
m
a/
Co
rb
is
FIGURE 4.1 David Hubel and Torsten Wiesel
David Hubel and Torsten Wiesel in 1982, shortly after
winning the Nobel Prize in 1981 for their work on the visual
system.
ISLE 4.1
From Eye to LGN
Optic chiasm: the location in
the optic tract where the optic
nerve from each eye splits in
half, with nasal retinae crossing
over and temporal retinae
staying on the same side of the
optic tract
Optic tract: the optic nerve
starting at the optic chiasm and
continuing into the brain
Contralateral representation
of visual space: the
arrangement whereby the left
visual world goes to the right
side of the brain, and the right
visual world goes to the left side
of the brain
Ipsilateral organization:
same-side organization; in the
visual system, the temporal
retina projects to the same side
of the brain
93 Chapter 4: Visual System: The Brain
aspects of visual anatomy for people new to the area to
keep straight (Figure 4.2). So again, we warn you to pay
close attention and review this information multiple times.
The optic nerve from each eye splits in half at the
optic chiasm. The axons from the ganglion cells from
the right half of the right retina and the ganglion cells
from the right half of the left retina combine, forming
the right optic tract, which then proceeds to the right
hemisphere of the brain. Axons from the ganglion cells
in the left half of the right retina and the left half of the
left retina combine, forming the left optic tract, which
then proceeds to the left hemisphere of the brain. For an
illustration of how the optic nerve divides in the optic
chiasm, see ISLE 4.1.
Why is this organization important for the visual
system? Consider the right optic tract. It combines ret-
inal signals from the temporal side (near the temple
or toward the forehead) of your right retina with ret-
inal signals of the nasal side (toward the nose) of your
left retina. If you examine Figure 4.2, you will see that
these two retinal areas receive input from the left visual
world. Similarly, the left optic tract receives information
from the right visual world. Thus, initially, the brain is
respecting the outside visual world in terms of its rep-
resentation in the brain. The left world goes to the right
hemisphere, and the right world goes to the left hemi-
sphere. This organization is known as contralateral rep-
resentation of visual space.
We wish to reiterate this point, as it serves to dispel
some myths about the eyes and the brain. Here’s the
main point of this paragraph: (a) Information from each
eye goes to both hemispheres, and (b) each hemisphere
of the brain receives input from the contralateral visual
field. So the left eye sends information to both the left
and right hemisphere. However, the left visual field of
the world is initially sent to the right hemisphere. For
example, if you consider the left eye only, the left tem-
poral retina receives information from the right visual
world, which stays on the same side of the brain and
goes to the left hemisphere (ipsilateral organization, or
same-side organization). The left nasal retina receives
information from the left visual world, which crosses
over and goes to the right hemisphere (contralateral
organization). Thus, each eye sends a signal to each
hemisphere. And it is the visual world that projects to
the contralateral side of the brain. We know: It sounds
confusing. Study Figure 4.2 closely, as in this case, the picture better conveys this
organization.
Once the optic tract has left the chiasm, 90% of the axons make their way to
the LGN of the thalamus. Here, the organization continues to respect the left-field/
Contralateral organization:
opposite-side organization; in
the visual system, the nasal
retina projects to the opposite
side of the brain
FIGURE 4.2
The Optic Chiasm and Visual Space in the Brain
(a) The optic nerves leave the eyes and travel toward the brain. At the
optic chiasm, each optic nerve splits apart. Information from the left
visual world first travels toward the right side of the brain, whereas
information from the right visual world first travels toward the left side of
the brain. Information from each eye, however, goes to both sides of the
brain. For example, the left temporal retina receives information from the
right visual world, which stays on the same side of the brain and goes to
the left hemisphere (ipsilateral or same-side organization). The left nasal
retina receives information from the left visual world, which crosses
over and goes to the right hemisphere (contralateral organization).
(b) Use your anaglyph glasses to see the optic chiasm as it appears in
the sheep brain. It is nearly identical to how it appears in the human brain.
Optic nerve
Optic chiasm
Lateral
geniculate
nucleus
Visual cortex
A
A
A A
B
B
B B
(a)
(b)
94 Sensation and Perception
right-field distinction. This pathway then leads to the visual cortex. However, 10% of
the axons from the optic tract go to other locations in the brain. Many of these axons
that do not go to the thalamus go instead to a locus in the brain known as the superior
colliculus, a midbrain structure that sits below the LGN. The superior colliculus is an
important structure in eye movements. A small number of these axons also head to
the frontal eye field region—an area in the frontal lobe also instrumental in eye move-
ments. Some fibers also go to the pineal gland, which regulates our circadian rhythms.
It is for this reason that exposure to bright lights can help “reset” our internal clocks.
We will first consider the main pathway from the retinae to the brain.
TEST YOUR KNOWLEDGE
1. What is meant by the term contralateral representation of visual space? Why would the
visual system represent visual space? What function does it serve?
2. Describe how information moves through the optic chiasm. How does this lead to left and
right field organization in the brain?
THE LATERAL GENICULATE NUCLEUS
4.2
Diagram the anatomy of the lateral geniculate nucleus and the
superior colliculus, and describe their roles in visual processing.
The lateral geniculate nucleus is a bilateral structure (one is present in each hemi-
sphere) in the thalamus that relays information from the optic nerve to the visual cor-
tex. The thalamus is a large structure that serves as a relay station for a number of
sensory systems, including both vision and audition (we discuss the medial geniculate
nucleus, critical in hearing, in Chapter 11). The LGN is the critical locus in the thalamus
for vision. We now know that the LGN has complex functions and is not simply a relay
station but is already doing visual processing. However, it is often thought of as a relay
center because it holds an intermediate position between the retinae of the eyes and the
visual cortices.
Anatomically, the LGN is divided into six layers (Figure 4.3). Layers 1 and 2 are
called the magnocellular layers because the cells in these layers are large. Layers 3
through 6 are called the parvocellular layers because the cells are somewhat smaller.
The very thin layers between each of the two magnocellular levels and the four par-
vocellular layers are called koniocellular layers, and they consist of very small cells.
Thus, there are six koniocellular layers, one under each of the two magnocellular
layers and each of the four parvocellular layers.
LGN anatomy gets complicated very quickly. Please read carefully, review what
you just read, and then write it down, so you can be confident that you have under-
stood and retained this material. You should also study the figures to reinforce your
understanding of the organization of the LGN.
First, keep in mind that we have two LGNs, one in each hemisphere. The left
LGN receives input primarily from the right visual world, and the right LGN receives
input primarily from the left visual world. Also remember that each eye projects
inputs to both the left and right LGNs when half of the retinal axons cross over in
the optic chiasm. Once in the brain, it is the representation of the visual world that is
more important than which eye this information came from (except when consider-
ing depth perception). This is important to repeat, because it is often misrepresented
outside of scientific publications.
Lateral geniculate nucleus:
a bilateral structure (one is
present in each hemisphere)
in the thalamus that relays
information from the optic
nerve to the visual cortex
Magnocellular layers:
layers of the lateral geniculate
nucleus with large cells that
receive input from M ganglion
cells (parasol retinal ganglion
cells)
Parvocellular layers: layers
of the lateral geniculate
nucleus with small cells that
receive input from P ganglion
cells (midget retinal ganglion
cells)
Koniocellular layers: layers
of the lateral geniculate
nucleus with very small cells
that receive input from K
ganglion cells (bistratified
retinal ganglion cells)
95 Chapter 4: Visual System: The Brain
FIGURE 4.3 The Lateral Geniculate Nucleus (LGN)
The LGN is a six-layered structure. Layers 1 and 2 are called the magnocellular layers because the cells in these layers are large.
Layers 3 through 6 are called parvocellular layers because the cells are somewhat smaller.
Cortex
1
2
3
4
5
6
Left LGN
Thalamus
Right LGN
Optic tract
Optic nerve Layers 1 and 2 are the magnocellular layers.
Layers 3–6 are the parvocellular layers.
So here are some important facts about the LGN. First, each LGN layer receives
input from only one eye. Magnocellular layer 1 and parvocellular layers 4 and 6
receive input from the contralateral eye (i.e., the eye on the opposite side of the
head). This is also true for the koniocellular layers underneath each of these layers.
Magnocellular layer 2 and parvocellular layers 3 and 5 receive input from the ipsi-
lateral eye. This is also true for the koniocellular layers underneath each of these lay-
ers (Hendry & Reid, 2000). This means that the LGN preserves information about
where information in the visual world is coming from and which eye is detecting
that information. Obviously, it is critical to know where objects are in the world, but
knowing which eye an image comes from is important in constructing a three-dimen-
sional image.
It is also critical that particular retinal ganglion cells are projecting to par-
ticular layers in the LGN. The magnocellular layers of the LGN receive input
from the parasol retinal ganglion cells (M cells). The parvocellular layers of
the LGN receive input from the midget retinal ganglion cells (P cells). And
the koniocellular layers of the LGN receive input from the bistratified retinal
ganglion cells (K cells).
The last general feature of the LGN that is important to understand is that the
neurons in each layer of the LGN show retinotopic organization. This means that
retinal ganglion cells from adjacent regions of the retina connect to cells in adja-
cent areas of the LGN. This also means that the LGN has an organization oriented
Parasol retinal ganglion cells
(M cells): retinal ganglion cells
that project to the magnocellular
layer of the lateral geniculate
nucleus; they represent 10% of
ganglion cells and possess high
sensitivity to light
Midget retinal ganglion cells
(P cells): retinal ganglion cells that
project to the parvocellular layer of
the lateral geniculate nucleus; they
represent 80% of ganglion cells,
possess low sensitivity to light, and
are sensitive to wavelength
Bistratified retinal ganglion
cells (K cells): retinal
ganglion cells that project to
the koniocellular layer of the
lateral geniculate nucleus; they
represent 10% of ganglion cells,
possess low sensitivity to light,
and are sensitive to wavelength
96 Sensation and Perception
to the visual world, as adjacent areas in
the visual world are picked up by adja-
cent areas of the retina, which are in turn
projected to adjacent areas of the LGN.
To see all this information graphically,
examine Figure 4.4.
To understand the functional signifi-
cance of this complex anatomy, it is nec-
essary to backtrack a bit and examine
different kinds of retinal ganglion cells.
Remember that the retinal ganglion cells
emerge from specific locations along the
retina. Those close to the fovea receive
input from few or just one receptor cell,
and those at the periphery may be collect-
ing input from many more receptor cells.
However, not all retinal ganglion cells are
the same. Indeed, we see the beginning of
three unique pathways that start in the
retinae and continue to the visual cortex.
We consider each of these pathways now.
The parvocellular pathway (or simply
P pathway) is characterized by the retinal
ganglion cells known as midget retinal
ganglion cells (so named because of their
small size). Midget retinal ganglion cells
usually receive input from a single cone
in the fovea of the retina, thus carrying
detailed information necessary for visual
acuity. When stimulated, these cells show
a sustained response; that is, they continue
to fire throughout the time period when a
stimulus is present. These retinal ganglion
cells are sensitive to wavelength (the basis
for color perception). The koniocellular
pathway (or simply K pathway) starts
with bistratified retinal ganglion cells and
projects to the koniocellular layers of the
LGN. These retinal ganglion cells also
receive input from cones. However, there
is more convergence among these cells,
so that they show lower acuity than the
P-pathway cells. But they do show some
role in color vision.
The magnocellular pathway (or sim-
ply M pathway) starts with the parasol
retinal ganglion cells and projects to
the magnocellular layers of the LGN.
These retinal ganglion cells receive
input from many photoreceptors, including both rods and cones. As such, they
have large receptive fields and are sensitive to light but not to color. They have lower
acuity relative to the K-pathway or P-pathway cells. For this reason, the M system is
usually associated with visual functions such as light detection and motion detection.
FIGURE 4.4 Organization Within the LGN
Objects in the left visual world initially go to the right hemisphere, whereas objects
in the right visual world initially go the left hemisphere. This is represented here
in both the eye and the optic chiasm with color coding. Different types of ganglion
cells project to different layers of the LGN. The parvocellular layers receive input
from the midget retinal ganglion cells, whereas the magnocellular levels receive
input from the parasol retinal ganglion cells. The koniocellular layers receive input
from the bistratified retinal ganglion cells.
Note: RGCs = retinal ganglion cells
Fixation point
Left eye Right eye
Objects in left half
of visual field
Objects in right half
of visual field
Temporal retina
Temporal
retina
Optic chiasm
Left LGN
1
2
3
4
5
6
1
2
3
4
5
6
Right LGN
Parvocellular
layer
Magnocellular
layer
Koniocellular
layer
Signals from right
half of visual field
Signals from left
half of visual field
Signals from
midget RGCs
Signals from
parasol RGCs
Signals from
bistratified RGCs
Nasal retina
Parvocellular pathway
(P pathway): a pathway
characterized by the retinal
ganglion cells known as midget
retinal ganglion cells
97 Chapter 4: Visual System: The Brain
Processing in the LGN
The LGN maintains a retinotopic map of the left or
right visual world in each of its layers (Figure 4.5).
Interestingly, each of these layers emphasizes differ-
ent aspects of visual processing. We know this from
single-cell studies that found adjacent cells in the LGN
that respond to visual stimuli that excite adjacent cells
in the retina. However, the receptive fields of LGN
cells are more like retinal ganglion cells than receptors.
LGN neurons have receptive fields that are similar
in characteristics to the retinal ganglion cells, with cen-
ter-surround organization (Xu, Bonds, & Casagrande,
2002). That is, some LGN cells respond maximally
to stimuli that are present in the center of the cell’s
receptive field but absent outside the center (or
reversed). Thus, like the retinal ganglion cells, LGN
neurons show specific responding to edges, spots,
and gratings. As we discussed earlier, edge detection
is critical to perception, because it allows the visual
system to determine where one object ends and the
next object begins.
Originally, the LGN was thought of as a relay
point—a synapse between the retina and the visual
cortex, where the complex processing occurred. But,
as with much of the human brain, the LGN turns
out to be much more complex than that. There are
many feedback loops from the cortex back to the
LGN and many connections from the LGN to other
areas of the brain (Babadi, Casti, Xiao, Kaplan, &
Paninski, 2010). The LGN receives input from the
cortex, from the brain stem, from other loci in the
thalamus, and from within the LGN itself. Indeed,
there are more connections from the cortex back
to the LGN than there are from the LGN to the
cortex. Many of these pathways are only now being
investigated. Thus, much remains to be discovered
about the complex function of the LGN.
As indicated earlier, studies suggest that the dif-
ferent layers of the LGN have different functions.
The magnocellular layers are sensitive to motion, light detection, and sudden changes
in the visual image. The parvocellular level specializes in foveal functions—color,
acuity, texture, and depth. The koniocellular layers also seem to specialize in color.
One obvious question is about how we know this. Most of what we know about
these functions comes from single-cell recording experiments using nonhuman mam-
malian models. We turn to those now.
Many of the single-cell recording experiments on the LGN use rhesus macaques
as the research participants. Their visual brains are similar to our own. Because the
visual system does not require the animal to be conscious while it is looking at stim-
uli, the monkey does not experience pain or discomfort, as it is fully anesthetized
during the procedure. Using single-cell recording on particular neurons, different
stimuli can be presented to the monkey. For example, a cell in the magnocellular
layer may be sensitive to movement in a particular area of the visual world. A cell in
FIGURE 4.5 Organization in the LGN
Stimuli in the world are mapped in a consistent fashion onto each layer
of the LGN. Input from the left visual field goes to the right LGN, and
input from the right visual field goes to the left LGN. Layers 1 and 2 are
the magnocellular layers receiving input, whereas layers 3 to 6 are
parvocellular. The koniocellular layers, not pictured, are in between.
Left LGN
F E D
6
F E D
5
F E D
4
F E D
3
F E D
2
F E D
1
Right LGN
C B A
6
C B A
5
C B A
4
C B A
3
C B A
2
C B A
1
Left eye Right eye
F
F
E
ED DC
CB
B
A
A
A B C D E F
Left visual field Right visual field
Koniocellular pathway (K
pathway): a pathway that
starts with bistratified retinal
ganglion cells and projects to
the koniocellular layers of the
lateral geniculate nucleus
Magnocellular pathway
(M pathway): a pathway that
starts with the parasol retinal
ganglion cells and projects to
the magnocellular layers of the
lateral geniculate nucleus
98 Sensation and Perception
the parvocellular layer may be maximally sensitive to light of a particular wavelength
in a particular region in central vision. In this way, we can map which cells respond
to which kinds of stimuli (Nassi & Callaway, 2009).
We end our discussion of the LGN with one interesting fact. As mentioned earlier,
the LGN is part of the thalamus. During sleep, the thalamus is inhibited by complex
neural circuitry in the brain. Thus, unless very bright lights are shined directly into the
eye, a person’s eyes can be open during sleep, but they will not see, because information
does not leave the LGN. Information is registered on the retina and is sent to the LGN,
where it stops. Inhibition prevents the information from being sent on to visual areas
of the cortex, thus preventing conscious vision during sleep.
TEST YOUR KNOWLEDGE
1. Describe the neuroanatomy of the lateral geniculate nucleus. How do the different
ganglion cells project to the different layers of the LGN?
2. What are the differences between parasol retinal ganglion cells (M cells), midget retinal
ganglion cells (P cells), and bistratified retinal ganglion cells (K cells)? What kind of
information does each one carry?
THE SUPERIOR COLLICULUS
We have two superior colliculi, one on each side of the brain. The superior colliculus
is at the top of the brain stem, anatomically just beneath the thalamus (Figure 4.6).
Like the LGN, the left superior colliculus receives input from the right visual world,
and the right superior colliculus receives input from the left visual world. Its main
function in mammals (including humans) is the control
of rapid eye movements. The superior colliculus is part
of a largely nonconscious system that helps us direct our
eyes toward new or approaching objects.
Approximately 90% of retinal ganglion cells synapse
in the LGN, but about 10% go to the superior colliculus.
It is likely that these retinal ganglion cells are bistratified
retinal ganglion cells (the K pathway) (Foldvari & Chen,
2016). Like the LGN, the superior colliculus receives
feedback from the visual cortex, and the superior col-
liculus also projects to the koniocellular levels of the
LGN (May, 2006). The superior colliculus also projects
to areas of the visual cortex beyond the primary visual
cortex. As with the LGN, one can find a retinotopic map
of the visual world in cells inside the superior colliculus.
Nonetheless, the main pathway is directly from the ret-
inal ganglion cells to the superior colliculus, allowing
the superior colliculus to produce quick eye movements.
The superior colliculus is often implicated in the phe-
nomenon of blindsight, a phenomenon we examine in
depth at the end of the chapter.
To understand the role of the superior colliculus, we
must first discuss the nature of human eye movements.
In general, human eyes can make two kinds of voluntary
eye movements, smooth-pursuit eye movements and
FIGURE 4.6 The Superior Colliculus
This illustration shows the location of the superior colliculi relative
to other brain structures relevant for vision. The superior colliculus
is involved in controlling eye movements.
Eye
Optic nerve
Optic chiasm
Optic tract
Superior
colliculus
Lateral
geniculate
nucleus
Cerebral cortex
99 Chapter 4: Visual System: The Brain
saccades. We will start with smooth-pursuit movements. Think about watching a bird
fly across the sky: Your eyes slowly and smoothly move as the bird moves across your
field of vision. These smooth-pursuit eye movements can be made only when we are
watching a moving object. If you don’t believe it, try it. Try to slowly move your eyes
across a stationary landscape. Have someone watch you. You will find that you cannot
slowly move your eyes. Rather, your eyes jump from one point to another.
The superior colliculus is vital in making smooth-pursuit eye movements. Consider
that when we are looking directly at an object without moving our eyes (fixation),
activity can be registered in the region of the superior colliculus that responds to the
fovea. When the object begins to move, cells adjacent to the foveal area in the superior
colliculus become active. This helps guide our smooth-pursuit movement, which we
can do only in response to a moving object. There are also close connections between
the superior colliculus and the innervation of the muscles that control our eyes.
The rapid movement of the eye from one stationary object to another is called a
saccade. We make saccades when we move our eyes from one stationary object, such
as a sleeping cat, to another, such as a clock on the wall. We also make saccades as we
read, moving our fixation from one word to the next. If an object abruptly appears at
our periphery, activity in the area of the superior colliculus responsible for that area in
visual space becomes active, leading to a saccade, that is, a sudden movement directly
from our fixation to the new point in space. Think of a light going on in an adjacent
room. The light surprises you, and you make a sudden eye movement toward the
source of the light. Saccades are also the responsibility of the superior colliculus.
Another interesting feature of the superior colliculus is that it receives input from
other sensory systems, most noticeably the auditory system and the somatosensory
system. This allows our eyes to be directed quickly to the location of a sound or a
touch. Thus, when someone taps our shoulder, we quickly move our eyes in that
direction. This is adaptive—we want to be able to orient our visual system to any
surprising stimulus, regardless of how it is detected. We feel a strange tug on our
arm, and we want to be able to look at what is happening. We hear a loud sound
off to our side, and we want to be able to see what caused the noise. Interestingly,
these responses in the superior colliculus are additive. If we visually detect something
at the periphery and hear a loud sound off to the same side, our superior collicular
response will be larger than for either stimulus alone. In this way, the superior collic-
ulus is thought to be an area of multisensory integration (Stein & Meredith, 1993).
TEST YOUR KNOWLEDGE
1. What are the differences between saccades and smooth-pursuit eye movements?
2. How does the superior colliculus control eye movements?
THE PRIMARY VISUAL CORTEX
4.3 Explain the nature of the retinotopic organization of V1 and the organization of V2.
We now return to the main visual pathway. After leaving the LGN, the next synapse
in the visual pathway is in the primary visual cortex, in the occipital lobe of the brain.
The primary visual cortex, unfortunately, is referred to by a number of names. In dif-
ferent contexts, you may hear different nomenclature, but all refer to the same area of
the brain. So get ready for a list of terms that all refer to the same area of the brain:
Superior colliculus: a
structure located at the top of
the brain stem, just beneath
the thalamus, whose main
function in mammals (including
humans) is the control of eye
movements
Smooth-pursuit eye
movements: voluntary
tracking eye movements
Saccades: the most common
and rapid of eye movements;
sudden eye movements that are
used to look from one object
to another
100 Sensation and Perception
primary visual cortex, V1, striate cortex, area 17, and BA 17. Here’s the significance
of each term. The terms primary visual cortex and V1 refer to its position along the
flow of information in the visual system—the first area in the cortex to receive visual
information. Striate cortex refers to the way the brain cells in this area look under
certain staining conditions. They appear striated, whereas other adjacent areas of the
occipital cortex are “extrastriate.” Area 17 and BA 17 refer to the area’s position on
Brodmann charts. We use the terms primary visual cortex and V1 in this text, but
it is important to be aware of the other terms, as they are used just as frequently in
other discussions of the human visual system. When V1 is the specific topic being
discussed, we will use the term V1 for brevity. When the primary visual cortex is sec-
ondary to the main discussion, we will switch to the term primary visual cortex to
avoid excessive jargon.
The cerebral cortex is the outer surface of the brain. Indeed, the word cortex
comes from a Latin term for a tree’s bark. The cerebral cortex is only 2 mm thick,
but it is essential for all higher perception and cognition in humans and other mam-
mals. The cerebral cortex is divided into four lobes (Figure 4.7). The frontal lobe,
located behind the forehead, is the seat of higher cognition—thinking, planning, and
speaking, as well as a variety of motor functions. The temporal lobe is responsible
for memory, language comprehension, and auditory perception. The parietal lobe is
involved in attention and somatosensory perception. The occipital lobe, at the back
of the brain, is the visual cortex. This large area is responsible for vision and nothing
else. At the very back of the visual cortex is the area known as V1.
Primary visual cortex (V1):
the area of the cerebral cortex
that receives input from the
lateral geniculate nucleus,
located in the occipital lobe
and responsible for early visual
processing
Retinotopic map: a point-
by-point relation between the
retina and V1
Cortical magnification: the
allocation of more space in
the cortex to some sensory
receptors than to others; the
fovea has a larger cortical area
than the periphery
FIGURE 4.7 The
Four Lobes of the Brain
There are four lobes of the
brain: frontal, temporal,
parietal, and occipital. The
occipital lobe is the visual
area of the brain. This
figure shows the location
of V1 within the occipital
lobe. V1 is the first area in
the cortex that receives
input from the retinae.
Parietal lobe
Occipital lobe
V1
V4
MT
V2
V3
Frontal
lobe
Lateral
fissure
Temporal lobe
Central sulcus
101 Chapter 4: Visual System: The Brain
You can easily locate your own V1. Run your hand
along the back of your head, just above the neck. At the
very back of your head is a slight bump, known as the
inion, on the occipital bone. Press your finger against that
bone. Underneath the inion is V1. Because your inion is
right at the center or your head, your finger will be above
both the left and right V1s. You can also see its position
in Figure 4.8.
Mapping the Eye on the Brain
One of the important characteristics of the visual cortex is
that it is highly organized. This means that its anatomical
structure can be correlated directly with its function. That
is, if we know where a neuron is, we know what it does for
the visual system. This knowledge has come about from
more than 50 years of intensive study, starting with the
work of Hubel and Wiesel (see Hubel & Wiesel, 2005). We
now take a look at this exquisite organization.
The primary visual cortex is a bilateral structure—
there is one in the left hemisphere that receives input
from the right visual world, and there is one in the
right hemisphere that receives input from the left visual
world. The left and right V1s meet in the middle of the
brain (Figure 4.9). The area where they meet in the cen-
ter is the area responsible for representing the fovea, or
the area in space we are looking at.
The left V1 receives input from the left LGN, and the
right V1 receives input from the right LGN. As we saw
above, this means that each V1 will receive input from
the opposite half of the visual world. The left V1 receives
input from the left half of each retina, which corresponds
to the right half of the world. More than that, adjacent
locations on the retina project to adjacent points on V1.
Think of the retina as a terrain and the V1 as a map of
that terrain. There is a point-by-point relation between
the retina and the V1, as seen on a topographic map. As a
result, V1 is said to have a retinotopic map of the retina
(see Figure 4.9).
Just as maps of the world are not exactly the same as
the original terrain, neither is V1 a precisely exact map
of the retina. Some regions of the retina get to take up a
much greater proportion of V1 than others. This feature
is called cortical magnification. Cortical magnification
means that there is more space in the cortex devoted to
some sensory receptors than to others. In this case, the
fovea has a larger cortical area than the periphery. In par-
ticular, the fovea takes up a huge proportion of V1 and
the rest of the visual cortex. Indeed, the fovea is less than
1% of the retina in terms of size, but its representation
takes up over 50% of V1 (Mason & Kandel, 1991). That
©
S
hu
tt
er
st
oc
k.
co
m
/A
M
A
FIGURE 4.8
The Inion Marks the
Occipital Lobe
On this bald person’s skull,
you can see a prominent inion.
Right underneath that bone at
the back of the skull is V1 in
the occipital cortex.
FIGURE 4.9
Organization of the Visual World in V1
As in earlier areas in visual processing, the right V1 represents
the left visual world, and the left V1 represents the right visual
world. Note that the representation of the point of fixation, or
the foveae of the retinae, is toward the middle of V1, with the left
and right V1s adjacent to each other.
1
Left eye Right eye
Optic chiasm
Optic tract
Optic nerve
Foveal image
Superior
colliculus
Optic
radiations
Visual cortex
2 3 4 5 6 7 8 9
12345
1
1
2
2
3
3
4
4
5
5
5
5
6
6
7
7
7
6
8
8
8
23456789
9
9
102 Sensation and Perception
is a lot of the brain’s real estate in the cortex dedicated to a small portion of the
retina. Of course, it is the fovea that is specialized for color vision and visual acuity,
and these features are often the important features we need to determine what an
object is. So it is not surprising that representation of the fovea of the retina takes up
so much space in the cortex.
V1 is a six-layered structure, like all of the cerebral cortex. Each layer is num-
bered 1 through 6. However, in V1, most anatomists divide layer 4 into at least
three separate sublevels, and one of these sublevels is typically also divided into still
smaller sublevels. Layer 4 is the critical layer that receives input from the LGN. As we
discussed earlier, there are three distinct pathways coming from the retina through
the LGN to V1. Two of these arrive at V1 in layer 4, the magnocellular synapses
in sublayer 4Cα and the parvocellular layer synapses in sublayer 4Cβ (Yabuta &
Callaway, 1988) (Figure 4.10).
Receptive Fields of V1 Cells
When Hubel and Wiesel set out to do research on the anatomy and physiology of
V1, they expected to find receptive fields in V1 similar to those that were found in
retinal ganglion cells and in the LGN—that is, the basic center-surround organiza-
tion. What they found was much more complicated. They found a host of different
types of cells that had differing sensitivities to objects in their receptive fields. For
example, they found that V1 cells in cats were most sensitive to bars of different
orientations in different locations in the visual world. Thus, a particular neuron in
V1 might respond maximally to a vertical bar at 3 degrees off the fovea on the left.
An adjacent neuron in V1 might respond maximally to a bar 2 degrees off vertical
bar at 3 degrees off the fovea to the left. And this pattern would continue from one
cell to the next. They had not expected the organization to be so logical, but cells
seem to line up in columns sensitive to the orientation of objects in particular areas
in the visual field.
They also discovered two distinct kinds of cells in V1, which they called simple
and complex cells. We turn to them next.
FIGURE 4.10 V1 Layers
This illustration shows the multiple layers of V1. Layer 4 has been subdivided into three sublayers (A, B, C). Layer 4C is
then further subdivided.
O
ut
er
s
ur
fa
ce
o
f c
or
te
x
in
a
re
a
V
1
1 2 3
4
A B C 5
α β
6
White
matter
Area V1
Simple cells: V1 neurons that
respond to stimuli with particular
orientations to objects within
their receptive field; the preferred
orientation of a simple cell is
the stimulus orientation that
produces the strongest response
Orienting tuning curve: a
graph that demonstrates the
typical response of a simple cell
to stimuli or different orientations
103 Chapter 4: Visual System: The Brain
ISLE 4.2
Simple Cells
FIGURE 4.11
A Bar Detector
This cell’s receptive field allows
it to respond to a bar of light
at a particular orientation. It is
best stimulated by a light bar
surrounded by a dark field.
+
+
+
+
−
−
−
−
−
−
−
−
Simple Cells
Simple cells are V1 neurons that respond to stimuli with particular orientations to
objects within their receptive field. Simple cells are found in layer 4B of V1 and receive
input primarily from layer 4C of V1. Like cells in the LGN, they have clear excit-
atory and inhibitory regions. But unlike LGN cells, they have orientation selectivity
rather than center-surround visual fields. Hubel and Wiesel (1959) found that elongated
stimuli that looked like bars seemed to be particularly effective stimuli for these cells.
Indeed, they found that some cells wanted dark bars on a light background, and others
responded to white bars on a dark background. The bars may also occur at varying
angles of orientation, and these vary in a predictable pattern (Figure 4.11). This selec-
tive firing rate to the orientation shows the selectivity of the cell to orientation. You can
find an interactive illustration of simple cells on ISLE 4.2.
The preferred orientation of a simple cell is the stimulus orientation that produces
the strongest response from the simple cell. Experiments using single-cell recordings
demonstrate orienting tuning curves for any particular simple cell in V1. These ori-
enting tuning curves are graphs that demonstrate the typical response of a simple cell
to stimuli of different orientations. Such a curve can be seen in Figure 4.12. As you
can see in the curves in Figure 4.12, simple cells respond best to a stimulus with a
particular orientation; as the orientation gets larger or smaller, the response of the
cell decreases. If the orientation is greatly off, the cell will not respond at all. Other
cells have different peak sensitivities. Thus, V1 indicates the orientation of lines in
the visual world by having select cells respond to different angles of orientation.
Complex Cells and V1 Responses to Visual Features
Complex cells are also neurons in V1 that respond optimally to stimuli with particular
orientations. But, unlike simple cells, they respond to a variety of stimuli across different
locations. For example, a complex cell will respond to a dark bar on a light background
and a light bar on a dark background. In contrast, a simple cell responds to one but not
the other. Moreover, complex cells do not have peak location sensitivity, as simple cells
do. That is, they will respond equally well to an optimal orientation regardless of where
Complex cells: neurons in V1
that respond optimally to stimuli
with particular orientations;
unlike simple cells, they respond
to a variety of stimuli across
different locations, particularly to
moving stimuli
FIGURE 4.12 Tuning
Curves of Simple Cells in V1
You can see here the response
patterns of two simple cells. One
is tuned best to a perpendicular
90-degree bar, whereas the other
one is tuned to a 60-degree bar.
You can see that the cells will
respond to other orientations, but
they peak for one orientation.
60
50
40
Orientation
tuning curve of
Simple Cell B
R
e
sp
o
n
se
a
b
o
v
e
b
a
se
li
n
e
(s
p
ik
e
s/
se
c)
Orientation
tuning curve of
Simple Cell A
Responses to bar
oriented at 90°
30
20
10
0
0° 30° 60° 90° 120° 150° 180°
104 Sensation and Perception
it is within their receptive field. Some complex cells also receive
input from both eyes and may be involved in depth perception
(Read, 2005). Complex cells also respond best to moving stim-
uli. For moving stimuli, some complex cells are responsive to
movement in one direction, whereas other complex cells are
responsible for movement in the other direction. Complex cells
are found in layers 2, 3, 5, and 6 of V1, but not layer 4. You
can find an interactive illustration of complex cells in ISLE 4.3.
We have focused on the observation that simple and com-
plex cells are particularly sensitive to edges and bars with
specific orientations. But it is also important to keep in mind
that neurons in V1 are tuned to many different features,
including color, motion, depth, direction, length, and size.
This is particularly true of the complex cells. There are also
neurons in V1 called end-stopped neurons. End-stopped
neurons respond to stimuli that end within the cell’s receptive
field. If the pattern continues beyond the receptive field, these
cells do not respond as greatly. Because of this pattern, end-
stopped cells are considered to be involved in the detection of
corners and the boundaries of shapes.
The Organization of V1
When Hubel and Wiesel were recording from single cells, they
recorded from several cells in a single penetration of the elec-
trode into the brain. They recorded from one cell, and then they moved the electrode
slowly further into the brain until they found another cell (Figure 4.13). Then Hubel
and Wiesel would record from that cell and determine its receptive field, and repeat the
procedure again. If their electrode entered the brain perfectly perpendicular to the brain’s
surface, they found an interesting pattern. All of the cells in the perpendicular column
responded to a bar in the same location on the retina, thus demonstrating the same recep-
tive field (see Hubel & Wiesel, 1979). This is consistent with the idea of a retinotopic map.
Hubel and Wiesel also discovered that some cells prefer to respond to inputs from
one eye, and other cells prefer to respond to the other eye. This is called the ocular domi-
nance of the cell. These were also organized in columns, with some cells responding more
to stimuli from the right eye and some to stimuli from the left eye (Figure 4.14).
Moreover, Hubel and Wiesel also found that simple cells all selected for bars at par-
ticular locations. If they inserted their electrode at a different angle, they could find cells
that all responded to the same location, but for different orientations. At a different
angle, the electrode might find cells that responded to the same orientation along an
adjacent column. Thus, this vertical arrangement of cells that all responded to cells in
the same orientation in the same retinal location Hubel and Wiesel called a column.
Next, they noticed that adjacent columns responded to lines that were tilted only slightly
differently from one another. In fact, the columns formed an organized pattern accord-
ing to their orientation. It was later discovered that orientational selectivity goes in one
direction in V1, whereas the input from the two eyes goes in the other direction in V1.
Thus, Hubel and Wiesel found both ocular dominance columns and orientation col-
umns. The ocular dominance columns are made up of neurons that respond only to
one eye, and these columns are perpendicular to orientation columns, which selectively
respond to small variations in orientation. Ocular dominance columns alternate systemati-
cally between left-eye and right-eye dominance. Orientation columns change systematically
across orientations (Hubel & Wiesel, 1962). When ocular dominance columns and orienta-
tion columns are combined, they form something Hubel and Wiesel called a hypercolumn.
ISLE 4.3
Complex Cells
End-stopped neurons:
neurons that respond to stimuli
that end within the cell’s
receptive field
Ocular dominance column:
a column within V1 that is made
up of neurons that receive input
from only the left eye or only the
right eye
Orientation column: a column
within V1 that is made up of
neurons with similar responses
to the orientation of a shape
presented to those neurons
FIGURE 4.13 Orientation in V1
When an electrode is inserted into a column of cells in V1, all
respond to a specific orientation of bars.
Microelectrode
1
2
3
4A
2 mm
4B
4C
5
6
Outer surface
of cortex
Layer of cortex
105 Chapter 4: Visual System: The Brain
A hypercolumn is a 1-mm block of V1 contain-
ing both the ocular dominance and orientation
columns for a particular region in visual space.
This view of V1 persisted into the 1980s,
when researchers discovered that there was more
to the story. Hold on to your hat here, because
we are about to throw a whole bunch of new
terms at you. Livingstone and Hubel (1984)
discovered blobs and interblobs interspersed
within V1 (also see Wong-Riley, 1979). Blobs
are areas within V1 sensitive to color, whereas
interblobs are areas sensitive to the orientation
of an object. Recall that in the LGN, there are
two types of cells, the magnocellular and the
parvocellular. These two layers divide into three
types of cells in the cortex: the blobs, the inter-
blobs, and the cells in layer 4B. The interblob
cells respond as the simple cells described ear-
lier. The blobs show color responses, and the
layer 4B cells respond well to moving stimuli
and stimuli of very low contrast.
Now we need to integrate the blobs, interblobs, and layer 4B into the organization
of the striate cortex that has been discussed. This organization is seen in the hypercol-
umn. The orientational selectivity goes in one direction, and the ocular dominance goes
at right angles. In each set of orientation columns for each eye, there are two blobs.
Layer 4B runs throughout all of the cortex and cuts across all of the columns. This
hypercolumn is one functional unit, processing all of the information from one region
of the cortex. Adjacent hypercolumns process information from adjacent regions of
the cortex, and it is these hypercolumns that make up the topographical map discussed
earlier. The portions of the hypercolumns that are active at any point in time will indi-
cate the features of what is stimulating that region of the retina. Figure 4.15 gives you
Hypercolumn: a 1-mm block
of V1 containing both the ocular
dominance and orientation
columns for a particular region
in visual space
Blobs: groups of neurons within
V1 that are sensitive to color
Interblobs: groups of neurons
that are sensitive to orientation
in vision
FIGURE 4.14 Ocular
Dominance Columns in V1
Alternating columns in V1
receive signals from either the
left eye or the right eye through
the LGN.
1
2
3
4
5
6
C
or
tic
al
la
ye
rs
Left-eye
ocular dominance slab
Right-eye
ocular dominance slab
Blobs
Color code for orientation columns
FIGURE 4.15 Hypercolumns in V1
The hypercolumns organize the orientation columns, the location columns,
and the ocular dominance columns into a predictable pattern. The image
here is a schematic showing everything at right angles. In real mammalian
brains, the pattern may be curved or folded in on itself. In this figure, you can
also see the “blobs,” which are designed to detect color.
Blobs
Right-eye
ocular
dominance
Left-eye
ocular
dominance
Column
of cells
Row of cells with different orientational preferences
1 mm
106 Sensation and Perception
a sense of what all this would look like in the brain if everything were all straightened
out. For an interactive illustration of hypercolumns in V1, examine ISLE 4.4.
We understand that we are advancing a very complicated picture of the brain.
Many researchers have spent their careers investigating this so that we can under-
stand the visual system. But in other ways, it is remarkable that nature could have
designed such an incredible mechanism for decoding visual information and that it
does so in such a systematic fashion. We think that the organization of V1 is one of
the great accomplishments of nature and the work to understand it one of the great
feats of science.
TEST YOUR KNOWLEDGE
1. What is a hypercolumn? What are the subcomponents of it? How were these columns
discovered by neuroscientists?
2. Describe the relation of retinotopic organization to representation in the external world.
V2 AND BEYOND
You might wonder how the visual system goes from detecting edges and bars at partic-
ular angles to perceiving waving palm trees, skittering dragonflies, and smiling people.
This question has also motivated researchers for some time. Although this question
cannot be adequately answered yet, some progress has been made. To begin to answer
this question, V1 is not the end of visual processing. Indeed, it is more the beginning.
Information leaves V1 and proceeds to a
number of other areas within the occipital
lobe. Many of these areas eventually project
to sites in the temporal lobe or to sites in
the parietal lobe. The number of such dis-
tinct regions identified in the occipital lobe
grows as more research continues, but we
will touch on a few of the important areas
and also describe the two critical pathways
that emanate from V1.
V2
After information leaves V1, it travels to
other areas in the occipital cortex. These
areas are collectively called the extrastri-
ate cortex or secondary visual cortex.
The visual signals that leave V1 go in many
different directions. One of the major
pathways is from V1 to the adjacent V2
region (Figure 4.16). There are three dis-
tinct regions within V2, which match up directly with the three different types of cells
in V1. The blobs connect to the thin stripes. Layer 4B connects to the thick stripes,
and the interblobs connect to the interstripes (Zeki, 1993). It is possible to deduce
something of how these regions of V2 respond on the basis of their inputs from V1.
Thin stripes will have color responses, thick stripes will be sensitive to motion, and
interstripes will be sensitive to shape and position. V2 cells also combine input from
both eyes (Pasternak, Bisley, & Calkins, 2003).
ISLE 4.4
Hypercolumns
FIGURE 4.16 Visual Areas of the Rhesus Macaque Brain
This illustration shows a rhesus macaque brain. These monkeys have occipital
lobes very similar to those of humans. You can see the relative locations of V2
and V1, as well as other areas of the occipital cortex.
V1
V2
V3
V3A
V4
V5
V5A
Extrastriate cortex
(secondary visual cortex): the
collective term for visual areas
in the occipital lobe other than V1
107 Chapter 4: Visual System: The Brain
Other regions, such as V3, V4 (color processing), and V5 (also known as MT, a
motion detection area), receive input from only some of the cell types in V1 and V2.
V1 and V2 send information in parallel to these regions. We return to these higher
areas of visual processing later, after we discuss the dor-
sal and ventral pathways. V2, however, still seems to be
involved in representing what is out there rather than
making sense of it.
TEST YOUR KNOWLEDGE
1. What is meant by the term extrastriate cortex? How
does it differ from the striate cortex?
2. What are the purported functions of areas V3, V4,
and V5 (MT)? What might happen if these areas are
damaged?
FUNCTIONAL PATHWAYS
IN THE VISUAL CORTEX
4.4 Compare the difference between the dorsal
pathway and the ventral pathway.
We know the final goal of the visual system because most
of us, except for those with extreme visual impairment,
know the end result: fluent perception of the visual world
around us. Because we mostly take the act of seeing for
granted, we seldom consider how complex visual percep-
tion is. We have seen the complexity of the eye and the intricacy of visual processing
in V1. We next consider two essentially parallel pathways that have been discovered
within the visual system. We have begun to discuss these pathways, as we have already
introduced the terms P pathway (and K pathway) and M pathway as they relate to the
retinal ganglion cells. However, in V1, these pathways show very distinct organization,
and even more so, as these pathways leave V1 toward other regions of the cortex. The
P pathway has been described as the “what” or ventral pathway and the M pathway
as the “where” or dorsal pathway (DeYoe & Van Essen, 1988; Mishkin, Ungerleider,
& Macko, 1983). You can see the anatomy of this system in Figure 4.17. Let us take a
closer look at each of these systems.
The most straightforward way of learning these pathways is to examine Figure
4.18. This figure shows the flow of information from the retinal ganglion cells through
the LGN and occipital lobe and into other areas of the brain, including the temporal
and parietal lobes. What is striking about these pathways is that (a) very early in the
visual system, information is being sorted and channeled into different directions, and
(b) these pathways are both anatomically distinct and functionally separate. The ven-
tral pathway starts with bistratified and midget retinal ganglion cells. These retinal
ganglion cells connect with the koniocellular and parvocellular layers of the LGN,
respectively, which in turn project to V1 layers 2 and 3 and sublayer 4Cβ, respectively.
From V1, the signal is sent to other visual areas in the occipital cortex, which we
discuss shortly, and then to an area in the temporal lobe known as the inferotempo-
ral cortex. This area is known from a great deal of research to be involved in object
V2: the second area in the
visual cortex that receives input;
often considered the area that
starts with visual associations
rather than processing the input
(sometimes called the prestriate
cortex)
Ventral pathway: starts with
midget and bistratified retinal
ganglion cells and continues
through the visual cortex into
the inferotemporal cortex in the
temporal lobe; often called the
“what” pathway, as it codes for
object identification as well as
color vision
Dorsal pathway: starts with
parasol retinal ganglion cells
and continues through the
visual cortex into the parietal
lobe; often called the “where”
pathway, as it codes for the
locations of objects and their
movement
FIGURE 4.17
The Ventral and Dorsal Pathways in the Brain
This illustration shows the important visual areas of the occipital lobe and
the flow of information in both ventral and dorsal pathways. The ventral
pathway flows through V2 and eventually into the temporal lobe and is
concerned with object identification, as well as color perception. The
dorsal pathway flows through V2 to area MT and then to the parietal lobe.
It is concerned with where objects are in visual space as well as motion.
Posterior
parietal cortex
Ventral stream
Dorsal stream
V1
V4
MT
V2
V3
Inferotemporal cortex
108 Sensation and Perception
FIGURE 4.18 The Flow of Information in the Brain
This figure illustrates the flow of information schematically from retinal ganglion cells to higher areas in the cortex of the human
brain. Note that the ventral and dorsal pathways are defined very early, starting in the retinal ganglion cells. Thus, from early in visual
processing, the “what” and the “where” pathways are distinct.
Retina
Parasol
Midget
Bistratified
Retinal
Ganglion
Cells
(RGCs)
Lateral
geniculate
nucleus
(LGN)
Layers of V1 V2
Cortex
Magnocellular
layers
Parvocellular
layers
Koniocellular
layers
12/34A4B4Cα4Cβ56
Blobs
Blobs
Blobs
Thick bands
(motion)
Pale bands
(form)
Thin bands
(color)
Parietal
Cortex
(perceiving
space and
motion)
V4
(form,
color)
Inferotemporal
Cortex
(object
recognition)
V3
V3
V5/MT
(motion)
V4/V5
Interblob
region
Dorsal (“where”/“how”) pathway
Ventral (“what”) pat
hway
recognition. Hence, the ventral system is often called the “what” system. The dorsal
system starts with the parasol retinal ganglion cells, which project to the magnocellular
cells in the LGN. From there, the pathway leads to sublayer 4Cα in V1. The pathway
then projects to V2 and from there to such areas as MT, ending up in the parietal
cortex. This pathway codes for place and movement, hence its nickname, the “where”
system. Ultimately, what remains unclear is where in the brain the systems rejoin so
that we see a unified perception of the world.
We consider an experiment that was done to establish the reality of the dorsal and
ventral pathways. Keep in mind that all the knowledge we have been presenting is the
result of careful experimentation, like the study we are about to describe. In this study,
Mishkin et al. (1983) trained rhesus monkeys (Macaca mulatta) to do two different
tasks. One task was called a landmark task, which required the monkeys to remember
the location of an event, and the other task was called an object task, which required the
monkeys to learn a particular object. In the study, monkeys saw two containers, one of
which contained food. In the landmark task, the monkey was required to select the con-
tainer that was closer to a specific landmark in the room. In the object task, the monkey
was required to select the container that was covered by a particular object. Rhesus mon-
keys learn these tasks quickly and then seldom make errors. Note that for each task, the
monkey is expected to do something that emphasizes a different system. In the landmark
task, the monkey is focusing on where an object is (the dorsal stream), whereas in the
object task, the monkey must remember what the object is (the ventral stream).
Mishkin et al. (1983) then created damaged areas in parts of the monkeys’ brains
(Figure 4.19), a process known as lesioning. In some monkeys, they lesioned the infero-
temporal cortex, an important area in the ventral or “what” pathway. In other monkeys,
they lesioned the parietal lobe, part of the dorsal or “where” pathway. After recovering
from surgery, the monkeys were again presented with the landmark task and the object
task. The monkeys with damage to the inferotemporal cortex showed normal perfor-
mance on the landmark task but were impaired on the object task, consistent with the
contention that the inferotemporal cortex is involved in establishing the “what” of an
object. In contrast, the monkeys with parietal lobe lesions showed normal performance
109 Chapter 4: Visual System: The Brain
Lesion in
inferotemporal
cortex
Lesion in
parietal cortex
Bin with food
Landmark
Landmark task
(a “where” task)
Find food in bin closer to landmark.
Object task
(a “what” task)
Find food in bin under square object.
Square object
FIGURE 4.19 A Lesion
Study Illustrating the Reality
of the Dorsal and Ventral
Pathways
Monkeys learned one of two
tasks, a landmark task and
an object task. Lesions to the
parietal lobe interfered with the
landmark task, and lesions to the
inferotemporal lobe interfered
with the object task. This study
provides support for the view
that the dorsal and ventral
streams are separate.
on the object task but were impaired on the landmark task, consistent with the conten-
tion that the parietal lobe is involved in establishing where an object is. Thus, damaging
the inferotemporal cortex interferes with visual object recognition, but damaging the
parietal lobe interferes with seeing the spatial relation of objects.
Although it is unethical to do such an experiment with human beings (and many would
argue the experiment with rhesus monkeys was unethical as well), accidents have resulted
in damage that approximates what Mishkin et al. (1983) did to the monkeys. In one case,
a patient known as D.F. suffered carbon monoxide poisoning, which damaged her ven-
tral pathway (Goodale, Milner, Jakobsen, & Carey, 1991). As a consequence of the brain
damage, D.F. showed severe deficits in her ability to perceive and therefore name objects
(a condition known as object agnosia). Despite her inability to perceive objects, which is
a function of her ventral system, she was able to grasp and manipulate them, presumably
because of her intact dorsal system. For example, when asked to estimate the length of an
object, her accuracy was severely impaired relative to a normal person. However, when
asked to lift the object, her hands adjusted appropriately to the size of the object.
The Ventral Pathway
The ventral pathway starts with midget and bistratified retinal ganglion cells and con-
tinues through the visual cortex into the inferotemporal cortex in the temporal lobe.
The ventral pathway is often called the “what” pathway, as it codes for object iden-
tification as well as color vision. After being processed in layers 2, 3, and 4Cβ of V1,
information is sent to V2 and from there to areas such as V3 and V4 in the extrastriate
cortex. V4 then sends information to the inferotemporal cortex. V4 has some interest-
ing properties. V4 neurons are sensitive to binocular disparity, helpful in recognizing
three-dimensional objects in space. Thus, V4 is seen as primarily involved in shape rec-
ognition (Pasupathy & Connor, 2002). However, V4 also seems critical in color vision:
Patients with damage to V4 have disorders of color vision (Zeki, 1993). We return to
V4 and disorders of color vision in Chapter 6.
From V4, information flows out the occipital lobe and into the temporal lobe
to an area of the cortex known as the inferotemporal cortex. The inferotemporal
cortex is the region in the temporal lobe that receives input from the ventral visual
pathway. One of its major functions is object identification. Early studies of the
inferotemporal cortex showed that its neurons are sensitive to highly specific kinds
of shapes (Bruce, Desimone, & Gross, 1981). Although some neurons in the infero-
temporal cortex are sensitive to basic visual features such as size, shape, color, and
orientation, the studies that attracted interest found neurons with specific responses
Object agnosia: an acquired
deficit in identifying and
recognizing objects even though
vision remains intact
Inferotemporal cortex: the
region in the temporal lobe that
receives input from the ventral
visual pathway; one of its
functions is object identification
110 Sensation and Perception
to such complex features as hands, paws, and faces. Indeed, research demonstrated a
region within the inferotemporal cortex called the fusiform face area (FFA). The FFA
seems to be a region specifically dedicated to recognizing familiar faces (Kanwisher
& Yovel, 2006). Single-cell recording studies with monkeys show that neurons
in the FFA are maximally responsive to the faces of other same-species monkeys.
Neuropsychological studies with brain-damaged patients show that patients with
damage to the FFA have deficits in identifying familiar faces (Schwartz, 2017; Susilo
& Duchaine, 2013). We return to the topic of face recognition in Chapter 5. Other
areas of the inferotemporal cortex appear to be sensitive to other kinds of object
recognition. Indeed, one study showed that a particular area of the inferotemporal
cortex is sensitive to the perception of individual persons. Cells in this area become
active when particular individuals are presented—either pictures of them or the
spelling of their names (Quiroga, Reddy, Kreiman, Koch, & Fried, 2005). Thus, the
ventral or “what” pathway is the neural pathway that allows us to perceive and
recognize the objects in our environment, regardless of whether they are the faces of
our family members or the books, pillows, clocks, smartphones, and eyeglasses that
populate our visual world.
The Dorsal Pathway
The dorsal pathway starts with parasol retinal ganglion cells and continues through
the visual cortex into the parietal lobe. The dorsal pathway is often called the “where”
pathway, as it codes for the locations of objects and their movement. After informa-
tion leaves V2 in the dorsal pathway, it is sent to an area in the occipital lobe known
as MT (for middle temporal, its location in the occipital lobe). MT is also known as
V5. MT is also connected to noncortical visual movement areas, such as the superior
colliculus (Born & Bradley, 2005). Single-cell studies with monkeys show that neu-
rons within MT are sensitive to the direction and speed of motion (Albright, 1984).
These data have been confirmed in human studies using functional magnetic resonance
imaging (fMRI) (Born & Bradley, 2005). Transcranial magnetic stimulation studies,
which render an area of the brain temporarily disrupted, have also been used to probe
human MT function. These studies show that interfering with MT functioning results
in a disruption of motion perception (Schenk, Ellison, Rice, & Milner, 2005). Finally,
patients with damage to MT have difficulties perceiving motion. We return to these
issues in Chapter 8.
After the signal leaves MT, it is sent across the occipitoparietal junction into the
parietal lobe. Specific regions in the parietal lobe that are part of the dorsal pathway
include the anterior intraparietal, the lateral intraparietal, and the medial intrapari-
etal areas. These areas are involved in the visual guidance of action. Research in both
humans and monkeys suggests that these areas are involved in the visual guidance
of reaching for and grasping objects (Culham, Cavina-Pratesi, & Singhal, 2006). We
return to these topics in Chapter 8.
TEST YOUR KNOWLEDGE
1. What are the functions of the dorsal and ventral pathways?
2. Why might color information be important for the ventral pathway but not the dorsal
pathway?
MT (V5): an area of the
occipital lobe in the dorsal
pathway, specific to motion
detection and perception
111 Chapter 4: Visual System: The Brain
WHERE DOES VISION COME TOGETHER?
So, we know that object perception comes through the ventral pathway and that move-
ment and object location come through the dorsal pathway. But what we perceptually
experience are moving objects—a unified world. Thus, as a result of our discussions of
brain regions and visual pathways, you might be wondering where all of vision comes
together, that is, what region of the brain is responsible for giving us a unified and
common perception of the world. After all, when we look at the world, we see talking
people, running cats, and airplanes moving across the sky, rather than the objects and
their movement separately, as might be inferred from our discussion of pathways. One
can simplify the question: Where in the brain do these pathways come together to give
us this common perception? At present, such a region has not been found, and many
researchers think it does not exist. In fact, nowhere in the brain has a single loca-
tion been found where all visual information converges (Dennett, 1991; Zeki, 1993).
Remember, V1 and V2 are the last areas to have all of the visual information, and that
is only for the central visual pathway (Zeki, 1993). It now appears that conscious vision
happens with simultaneous or approximately simultaneous activation across all visual
areas. Perhaps important to this neurologically are the feedback loops that exist in the
brain. At every level, there is return feedback to earlier levels in the pathways from
higher levels in the pathways. Forward and backward connections are thought to play
a role in synchronizing a response in the brain, so that our perceptual experiences are
of whole objects and not fragmented parts. Thus, our experience of vision is distributed
at least across the areas of the visual cortex. So one answer to why we experience the
world as a unified whole is that the constant feedback loops from higher to lower levels
integrate our perceptions.
TEST YOUR KNOWLEDGE
1. In your view, will the search for an area of the brain that unifies visual processes into a
common perception be successful? Why or why not?
DEVELOPMENT OF THE VISUAL SYSTEM
We have seen that the brain organization involved in vision is complex, highly struc-
tured, and supremely well adapted. However, regardless of whether we have been
discussing the visual systems of cats, monkeys, or people, we have so far been consid-
ering mature individuals. An important question pertains to how our visual systems
mature and develop. In this section, we take up the issue of development. Often
critical in discussions of development is whether a particular ability requires practice
and experience or whether it will develop innately, regardless of experience. In other
words, is the organization of our visual system hardwired? That is, is it set specifically
by our DNA, does it follow a set course of development, and is this unchangeable?
Or are environmental inputs necessary for the visual system to develop normally?
If so, how flexible is our visual system, depending on that environmental change?
As we will see shortly, there is much flexibility in the development of the visual sys-
tem. Certain patterns appear to be fixed, but much can be altered by the organism’s
early environment.
112 Sensation and Perception
Is it nature (our genetics) or nurture (our experiences) that is more important
in how our sensory systems operate? Texts usually present the two extreme posi-
tions and contrast them. At one extreme, there is the genetic position, that all that
is needed for our sensory systems, or whatever biological or psychological factor is
being discussed, is coded in our genes. Sensory operation is thus essentially “pre-
ordained.” On the other side is the tabula rasa position, that we are blank slates at
birth, and experience writes on these slates to determine who we are going to be. The
fact is, however, that genes and the environment interact in incredibly complex ways
to allow development to occur, and nearly all scientists agree that this interaction is
inevitable and complex. Indeed, it may not be possible in many cases to specify what
is innate and what is learned when it comes to something as complex as the mam-
malian visual system. Certainly the interaction position fits all the data and studies
we discuss here.
One landmark research study on the development of the visual brain comes
from work by Held and Hein (Held, 1965, 1980; Held & Hein, 1963). These
studies, which some of you may find distasteful, concerned the development of
the visual system in young cats. The researchers carefully showed how important
environmental input is to the development of the visual brain. Held and Hein
raised kittens in complete darkness for a few weeks. After the initial period of
darkness, the kittens were divided into two groups. Both groups were still kept
in darkness most of the day but now spent an hour a day on a “kitten carousel”
(Figure 4.20). The kittens in one group were free to
move themselves. As they moved, the visual environ-
ment moved around them. Thus, they could correlate
their movement with the movement around them.
The second group of kittens were kept in little bas-
kets and were moved by the movements of the other
kittens. Thus, their movement was passive—tied not
to their own motor systems but to those of the other
kittens.
Later, the kittens were tested on a variety of visual
tasks. In all cases, the active kittens performed better
than the passive kittens, despite their identical visual
experience. For instance, in a test of visually guided
paw placement, the active kittens were better able to
extend a paw to touch a point on a flat surface than
were the passive kittens. In another test, the active kit-
tens were more likely to avoid a “visual cliff,” that is,
an illusion that a sharp drop-off is present where they
are walking. In yet another test, the active kittens were
better at the visual pursuit of a moving object, which
is important for carnivorous cats, which must chase
fast-moving prey. Indeed, the active kittens showed no
differences from cats raised normally with full visual
experience. It was only the control-deprived passive
kittens that did poorly on the visual tests. These results
suggest that there is flexibility in the development of
the visual system, that early visual–motor experience can later influence perceptual
abilities (Held & Hein, 1963).
At the same time that Held and Hein were doing pioneering work with the kitten
carousel, Hubel and Wiesel were also examining developmental issues in the visual
FIGURE 4.20 The Kitten Carousel Experiment
The illustration shows two kittens, both reared in an all-dark
environment, seeing vertical stripes in the experimental setup.
The kitten on the left is active in its exploration, whereas the kitten
on the right is yoked to the first. Because of its lack of active
experience, the yoked kitten shows slowed visual development
(Held & Hein, 1963).
113 Chapter 4: Visual System: The Brain
brain (Wiesel & Hubel, 1965). Like Held and Hein, they also focused on deprivation
studies, that is, studies in which young organisms (usually cats) were deprived of
visual experience of one form or another. In Hubel and Wiesel’s research, the goal
was to examine the receptive fields of individual neurons rather than the cats’ behav-
ior in general. They found that, consistent with the “nature” view of the brain, some
organization already existed at birth in the cats’ visual system. Even with no visual
experience, there was some organizational structure in the cats’ visual cortices (Daw,
2009; Hubel & Wiesel, 2005).
Wiesel and Hubel (1963) also showed that there is degeneration in the cortex if an
organism is denied visual experience. For example, in one study, kittens were deprived
of visual experience in one eye (monocular deprivation). The other eye allowed the
kittens to interact normally with their environment. Later, Wiesel and Hubel looked
at the receptive fields of neurons in the kittens’ V1s. They found clear evidence that
monocular deprivation resulted in a reduction in the number of cells that responded to
the deprived eye and fewer cells that responded to both eyes. However, such changes
occurred only if the kittens were deprived of visual experience during the first 3 months
of life. Visual deprivation after 3 months had no effect on neural organization. Thus,
Wiesel and Hubel’s studies suggest that both innate organization and environmental
inputs are important to the developing visual system (Daw, 2009).
Conducting such a deprivation experiment with human infants would be highly
unethical. So experiments cannot be applied to young human visual systems. But
correlational research can be done, examining changes in the visual cortex as infants
begin to mature. In one such study, Huttenlocher and de Courten (1987) found that
during early infancy (2–4 months), there is rapid growth of synapses within V1 of
the cortex. This is followed by a loss of synapses later in childhood (8–11 years). This
suggests that early visual experience is necessary for establishing the parameters of
vision, but unnecessary connections will later be pared down. Thus, it is likely that
human visual development follows a similar trajectory in terms of some innate pat-
terns elaborated on by experience.
TEST YOUR KNOWLEDGE
1. Is our visual system hardwired, or do learning and change take place as the mammalian
eye and visual system mature?
2. Describe the “kitten carousel” experiment. What does it tell us about visual development?
4.5 Interpret the concepts of blindsight and conjugate gaze palsy.
EXPLORATION: Blindsight
Patient T.N., born in Burundi, Africa, but living in
Switzerland, is a doctor who worked for the World Health
Organization. In 2003, while in his mid-50s, T.N. had two
serious and successive strokes over a period of 5 weeks,
each stroke causing lesions on one side of his visual cor-
tex. The first stroke affected his left visual cortex, and the
second stroke, 5 weeks later, destroyed his right visual
cortex (de Gelder, 2010). Subsequent anatomical testing
showed that T.N.’s entire primary visual cortex (V1) was
compromised (de Gelder et al., 2008). As a consequence
of these strokes, T.N. is now completely blind. He reports
no visual experience, though his overall intelligence and
verbal abilities remain completely intact. Not relying solely
on these subjective reports, de Gelder and her team ran
a series of routine tests of vision. The tests turned up
nothing—T.N. showed no evidence of seeing in these
114 Sensation and Perception
standard tests. Moreover, structural MRI revealed exten-
sive structural damage to V1, and functional MRI revealed
no activity in this region of the brain when T.N. was shown
visual stimuli (de Gelder et al., 2008). However, because
the strokes affected his visual cortex, his eyes themselves
were undamaged.
What makes T.N.’s case fascinating is that despite his
complete perceptual blindness, he still makes visual
responses. Indeed, in 2008, de Gelder et al. staged a
stunning demonstration of this. T.N. was told that a
cluttered corridor was empty and that he would not
need his cane to walk down the corridor. Reluctantly,
T.N. agreed. As he walked down the corridor, he was fol-
lowed by another person (a prominent researcher in this
area) to ensure that he would not stumble. When you
watch the video, you can see that despite his total blind-
ness, T.N. avoided the obstacles placed in front of him.
He sidesteps a box and avoids a tripod. After completing
the trip down the hallway, T.N. does not know what he
has avoided or whether there was anything in his way at
all. In other words, he made visually guided movements
in the absence of conscious sight. This is a phenome-
non known as blindsight. Blindsight is the presence of
visual abilities even though a person experiences blind-
ness because of damage to V1. The patient is subjectively
blind but makes accurate visual responses.
To see T.N. walking down the corridor, you can watch
a video at the Scientific American website (http://www
.youtube.com/watch?v=ACkxe_5Ubq8, see also ISLE 4.5).
The researcher who followed him down the hallway
reported that T.N. did not make vocalizations for which he
might listen for slight echoes,
the way a bat or dolphin
uses echolocation. However,
they had no sound-monitor-
ing equipment, so this could
not be completely ruled out. Amazingly, in your textbook
authors’ opinion, the researchers failed to do a simple con-
trol—to have T.N. negotiate an obstacle course with a blind-
fold on. If blindsight were the explanation for his avoiding
the obstacles, then cutting off input to the retinae would
render him unable to negotiate the course. Indeed, they did
only one trial with T.N., and they did not perform appropri-
ate control investigations. Nonetheless, this demonstration
is now a well-cited example of the abilities of blindsight
patients (de Gelder, 2010). Luckily, other research has been
done with T.N. and on other patients with similar condi-
tions that have used the necessary experimental controls.
T.N.’s case is unique in that his entire V1 was compromised
(Figure 4.21). In other cases of blindsight, the patient has
damage in some areas of V1 but not all. The result is a sco-
toma, an area of partial or completely destroyed cells, result-
ing in a blind spot in a particular region of the visual field.
In these patients, vision may be normal in most regions of
the visual field, allowing them to see normally under most
circumstances. However, when these patients keep their eyes
still, there is a blind spot (the scotoma) where they cannot
see or cannot see normally. In a number of patients tested,
blindsight may exist within the scotoma region (Weiskrantz,
1996). Such patients have been yielding an understanding
and exploration of blindsight for many years, but T.N.’s case
is unique in that the scotoma consists of his entire visual field.
The first studies of blindsight go back to the 1970s. At the
time, Lawrence Weiskrantz, an English neurophysiologist,
was examining the visual responses of monkeys with lesioned
V1s. He found that monkeys were still able to make visually
guided responses even without this region. He then focused
his research on the superior colliculus, the part of the brain
described earlier that guides eye movements. Weiskrantz rea-
soned that intact colliculi allowed the monkeys to respond
to visual stimuli in the absence of V1 (see Weiskrantz, 1996).
Indeed, despite their missing V1 regions, these monkeys
appeared to be behaving normally and responding appro-
priately to visual stimuli. However, he knew from neuropsy-
chological research that humans with damaged V1 regions
had visual problems known as scotomas, that is, areas in the
visual field in which they could not see. The blind field in the
visual world corresponds to the damaged area in V1, which
is responsible for that region in space.
Then Weiskrantz discovered patient D.B., and the two
began a long collaborative investigation of D.B.’s blindsight
(Weiskrantz, Warrington, Sanders, & Marshall, 1974).
D.B. was a 34-year-old British man, working as a computer
programmer. He was married with young children. He was
also an amateur musician and an amateur rugby player.
He started developing headaches, and his doctor sent him
to a neurologist. The neurologist discovered a large tumor
located in the primary visual cortex of his right hemisphere.
To ensure his long-term health, much of D.B.’s right V1 was
removed surgically along with the tumor, leaving him with
a large left-field scotoma. Nonetheless, his vision was still
ISLE 4.5
Navigation in Blindsight
Blindsight: the presence of visual abilities even though a
person experiences blindness because of damage to V1
Scotoma: an area of partially or completely destroyed cells,
resulting in a blind spot in a particular region of the visual field
115 Chapter 4: Visual System: The Brain
fine in his right visual field, and D.B. was able to return
to his normal life. However, he agreed to continue having
his scotoma investigated by Weiskrantz and his colleagues
(Weiskrantz, 1986). Note that D.B., unlike T.N., still has
much of his V1 intact, meaning that he can still see much
of the world. His left V1, responsible for his right visual
field, was just fine. He could see normally in this region.
His scotoma (blind spot), however, extended through much
of his left visual field.
When shown objects in his intact right visual field, D.B.
was able to identify and describe them as any sighted per-
son would. However, when objects were presented in the
scotoma in his left visual field, D.B. reported not being able
to see them, nor could he identify them. To D.B., he sim-
ply could not see in this field, and like T.N., D.B. was sub-
jectively blind in the scotoma region. To test for blindsight,
Weiskrantz used a forced-choice procedure in which D.B.
had to guess what he saw. In this procedure, D.B. might feel
as if he had not seen anything, but he had to make a response
anyway. In one study, Weiskrantz presented either a square
shape or a diamond shape, and D.B. had to guess which
was presented. Even though the image was presented to his
scotoma and the only difference between the two images
was orientation, D.B. guessed at the correct shape at a rate
significantly higher than chance. In another study, D.B. could
discriminate between X and O at above-chance rates. In yet
another study, D.B. had to determine whether an image in
his scotoma was stationary or moving. Again, D.B. reported
no conscious seeing of the movement, but his guesses were
significantly greater than chance (Weiskrantz, 1986). Since
then, this phenomenon has been observed in many patients
and continues with D.B. today as well (Tamietto et al., 2010).
Having established that patients with blindsight (a) are
truly without visual experience in their scotoma fields,
and (b) are able to make visual responses, the term
blindsight may seem slightly less paradoxical. Starting
with Weiskrantz et al. (1974), the predominant view is
that blindsight is mediated by mechanisms in the supe-
rior colliculus that continue to get input from the retina
even when the pathways to the visual cortex have been
damaged. Here is the basis of Weiskrantz’s view.
Patients such as T.N. and D.B. have extensive damage to
the visual cortex, which creates the experience of blind-
ness. However, their retinae continue to project axons,
FIGURE 4.21 Damage to Blindsight Patient’s Brain
An MRI study of patient T.N.’s brain, showing the bilateral destruction of the V1 region of his brain. This damage means that his V1 does
not process visual information. As such, T.N. is blind. However, other areas of the brain, such as the superior colliculus, allow him to
make visual responses. From de Gelder et al. (2008).
116 Sensation and Perception
which reach the superior colliculus and other noncorti-
cal areas of the brain. In people without brain damage,
the superior colliculus is an area of the brain involved
in the rapid movement of the eyes and the head toward
the source of an incoming visual stimulus. These mech-
anisms appear to be intact in patients with blindsight,
as they may move their heads toward incoming stimuli
even though they cannot see the stimuli. Consider T.N.—
he cannot see the obstacles placed in front of him, but
as he moves toward them, he slowly but surely avoids
them. His actions are consistent with the explanation that
blindsight is caused by spared noncortical routes from the
retinae to the brain.
Given that there are several routes from the retinae to
noncortical areas of the brain, one might expect to find
other kinds of blindsight in addition to object avoidance
and forced-choice discrimination. Indeed, research with
T.N. demonstrates a form of emotional blindsight (Pegna,
Khateb, Lazeyras, & Seghier, 2005). When presented with
images of fearful faces, T.N. made cringing expressions
himself and showed activity in his amygdala (an area of the
brain associated with emotion), even though he could not
report what the stimuli were that he was seeing. Remember
that T.N. shows no activity in his V1 during these studies.
Thus, it is likely that the responses are mediated by the
superior colliculus route. Interestingly, some research now
demonstrates that the superior colliculus projects to higher
order areas in the visual cortex (Ptito & Leh, 2007). This
may account for T.N.’s emotional responses.
Over the years, blindsight has drawn significant interest
from philosophers. For them, the intriguing phenomenon
is that someone is blind but is making responses to visual
stimuli. This seeming paradox is resolved when we think
of conscious seeing as being a function of V1 in the cortex.
When V1 is damaged, we lose conscious vision. However,
intact retinae continue to project to noncortical areas,
which allow us to respond to visual stimuli, despite the lack
of visual seeing.
APPLICATION: Conjugate Gaze Palsy
Ophthalmology, though nearly impossible to spell, is a
major area of medicine. Healthy vision is an important
aspect of human life for most people. However, vision
can be impaired by things as humdrum and simple as a
misshapen lens to complex disorders of vision, such as
agnosia (in which people see and can describe accurately
what they see, but they do not extract meaning). A work-
ing ophthalmologist must, in addition to working with
patients who have diseases of the eye, work with patients
who have incurred damage to any number of regions of
the brain, damage that manifests as visual problems. In
this section, we describe the conjugate gaze palsies, a
series of disorders of vision, brought about by damage to
the oldest part of the brain, namely, the brain stem.
Human beings, like all mammals, have two eyes. In many
ways, we take this for granted. In Chapter 7, we will dis-
cuss how having two eyes allows humans the ability to
create a binocular image, which enhances our ability to
see at depth. Humans and many other mammals use bin-
ocular vision, which requires that both eyes be trained on
the same object at the same time. If one eye is looking far
to the left and the other to the right, the corresponding
images are not focused on the same object and not only is
depth perception lost, but double images may occur. Try
“crossing” your eyes, and you may be able to produce
such a double image. Thus, having two eyes requires our
visual systems to have mechanisms in place that are able
to keep our eyes coordinated. In most of us, these mecha-
nisms are functional, and we seldom worry about whether
our eyes are focused on the same thing. The supranuclear
ocular motor system, located in the brain stem, is a system
concerned with linking eye movements in each eye to each
other. The supranuclear ocular motor system connects to
a great many regions in the brain that are used in visual
processing, including the frontal eye fields. However, in
conjugate gaze palsy, brain damage to the brain stem
affects the ability of our eyes to train on the same object
(Goldberg & Trattler, 2015). Conjugate palsies are some-
times seen as complications in Parkinson’s disease, after
cardiac surgery (Eggenberger, 2014), and when the pineal
gland is compromised (Goldberg & Trattler, 2015).
Parinaud’s syndrome occurs from lesions in the superior
colliculus. Rather than irregular movements and difficul-
ties coordinating the two eyes, patients with Parinaud’s
Conjugate gaze palsies: neurological disorders that affect
the ability of the eyes to coordinate their movements; this
inability to move together may affect eye movements in both
vertical and horizontal directions
117 Chapter 4: Visual System: The Brain
syndrome have a paralysis of gaze. They must move their
heads, rather than their eyes, to track motion.
Conjugate gaze palsies are, therefore, neurological disorders
that affect the ability of the eyes to coordinate their movements.
This inability to move together may affect eye movements in
both vertical and horizontal directions (Goldberg & Trattler,
2015). The cause of these palsies lies not in the peripheral
musculature of the eyes but in locations in the brain, partic-
ularly in the brain stem region that regulates eye movements
(Xie, Yu, Wang, Liu, & Meng, 2016). Let us look at one form
of conjugate gaze palsy in more detail. Internuclear ophthal-
moplegia results from selective damage to the medial longi-
tudinal fasciculus (MLF). The MLF is a bilateral structure in
the brain stem, consisting of mostly axons (i.e., white-matter
structure). In this condition, if a patient is asked to look to the
left, the left eye will make the appropriate movement, but the
right eye will not move. Similarly, if a patient is asked to look
to the right, the right will make the appropriate movement,
but the left eye will not move. When this occurs, the patient
will have “double vision” and blurry vision because the eyes
are not focused on the same object.
When areas like the MLF and other related areas are
damaged, the result is often double vision (seeing two of
individual objects in the environment), blurry vision, and
the making of unwanted eye movements (Eggenberger,
2014). These symptoms can be quite troubling, as they
impair many basic functions, such as visual guided move-
ments, including walking and driving as well as reading.
For example, Eggenberger described a patient who was
given a strong antibiotic as treatment for an unrelated
eye problem. The antibiotic induced changes in the brain
stem, which left him with gaze palsy symptoms. The
patient, though otherwise healthy, found he could no lon-
ger drive and that reading was impaired.
There is no reliable treatment that works every time.
However, there are a variety of ways of helping peo-
ple with gaze palsies. In general, doctors will work
to remove the cause of the initial impairment by restor-
ing blood supply to the affected areas. Still, treatments
vary, as in some cases, the symptoms of gaze palsies
will dissipate with time, presumably as other adjacent
areas in the brain stem take up the regulation of coor-
dinating eye movements. However, for some patients,
the symptoms persist. In these cases, there are various
remedies, depending on the patient. In some cases, special
prisms can be constructed for eyeglasses to bring the eyes
back into common focus (Eggenberger, 2014). In other
cases, it may be possible to have the patient work on ver-
gence exercises, to strengthen the control over eye move-
ments (Eggenberger, 2014). In cases in which the damage
leads to tremor in addition to uncoordinated movements
of the eyes, drugs similar to those used in epilepsy may
be tried. These drugs may include antitremor drugs such
as gabapentin and antiseizure drugs such as clonazepam
(Aladdin, Scozzofava, Muayqil, & Saqqur, 2008). Because
these drugs reduce tremor, they may allow patients to
regain control over their eye movements. Because of the
underlying cause, it is difficult to predict the prognosis in
most cases of conjugate gaze palsy. Patients may recover
rapidly in some cases, but, in other cases, recovery does not
occur (Aladdin et al., 2008).
CHAPTER SUMMARY
4.1
Identify the anatomy of the optic chiasm and how
that affects the lateralization of vision in the brain.
When information from the optic nerve enters the optic chi-
asm, information crosses over, so that the axons from the
ganglion cells from the right half of the right retina and the
ganglion cells from the right half of the left retina combine,
forming the right optic tract, which then proceeds to the
right hemisphere of the brain (and similarly for the other half
of the system).
4.2
Diagram the anatomy of the lateral geniculate
nucleus and the superior colliculus, and describe
their roles in visual processing.
The optic nerve projects to the lateral geniculate nucleus
(LGN). The LGN is a six-layered structure in the thalamus
that serves as a relay point for the transmission of visual
information, although processing of information also occurs
in the LGN. Each of the three types of retinal ganglion cells
(parasol, midget, and bistratified) projects to a particular
Internuclear ophthalmoplegia: a conjugate palsy resulting
from damage to the brain stem region known as the medial
longitudinal fasciculus
Sensation and Perception118
layer of the LGN. The parasol retinal ganglion cells pro-
ject to the magnocellular layer of the LGN (forming the M
pathway), the midget retinal ganglion cells project to the
parvocellular layer of the LGN (forming the P pathway), and
the bistratified retinal ganglion cells project to the konio-
cellular layer of the LGN (forming the K pathway). The supe-
rior colliculus can be found at the top of the brain stem,
just beneath the thalamus. Its main function is the control
of rapid eye movements.
4.3
Explain the nature of the retinotopic organization
of V1 and the organization of V2.
After leaving the LGN, the next synapse in the visual path-
way is in the primary visual cortex in the occipital lobe of the
brain. The primary visual cortex is also known as V1 (and area
17). The cerebral cortex is the outer surface of the brain. It
consists of four lobes: the frontal, the temporal, the parietal,
and the occipital. The occipital lobe is the visual brain. V1 is
in the occipital lobe right toward the back of the head. It is
a six-layered structure with different layers receiving input
from different regions of the LGN. V1 is organized in retino-
topic coordinates, which also refer to the spatial organiza-
tion of the external world. One of the features in V1 is cortical
magnification. Cortical magnification means that there is
more space in the cortex devoted to some sensory receptors
than to others. In this case, the fovea has a larger cortical
area than the periphery.
The Nobel prize–winning scientists Hubel and Wiesel dis-
covered both simple cells and complex cells in V1, which are
sensitive to different properties of the visual stimulus. Simple
cells are V1 neurons that respond to stimuli with particular
orientations to objects within their receptive field. The pre-
ferred orientation of a simple cell is the stimulus orientation
that produces the strongest response from the simple cell.
Complex cells are also neurons in V1 that respond optimally
to a stimulus with a particular orientation. But, unlike sim-
ple cells, they respond to a variety of stimuli across differ-
ent locations. In particular, they also respond best to moving
stimuli. End-stopped neurons respond to stimuli that end
within the cell’s receptive field. V1 is organized into columns,
which are sensitive to orientation and ocular dominance. A
hypercolumn is a 1-mm block of V1 containing both the ocular
dominance and orientation columns for a particular region in
visual space. Hypercolumns also include information about
where in space those columns are. Blobs are groups of neu-
rons within V1 that are sensitive to color, whereas interblobs
are the groups of neurons that are sensitive to orientation.
The M pathway, K pathway, and P pathway all enter the cor-
tex through V1. There are three distinct regions within V2,
which match directly up with the three different types of
cells in V1. Thin stripes have color responses, thick stripes
are sensitive to motion, and interstripes are sensitive to
shape and position.
4.4
Compare the difference between the dorsal
pathway and the ventral pathway.
Starting with V1, we can see two distinct pathways, the dor-
sal and ventral pathways. The dorsal pathway is responsible
for information about movement and continues through MT
in the occipital lobe and then into the parietal lobe. The ven-
tral pathway is responsible for object and color recognition.
It goes through areas such as V2 and V4 before heading into
the inferotemporal cortex in the temporal lobe. Nowhere
in the brain has it been found where all of the visual infor-
mation converges to a single location. It now appears that
vision happens with the simultaneous or approximately
simultaneous activation across all of the visual areas.
Forward and backward connections are thought to play a
role in synchronizing a response in the brain, so that our
perceptual experiences are of whole objects and not frag-
mented parts.
4.5
Interpret the concepts of blindsight and conju-
gate gaze palsy.
In the Exploration section, we discussed blindsight, the neu-
ropsychological condition in which damage to V1 causes
a blind spot or scotoma. However, because of noncortical
areas such as the superior colliculus, the patient can still
make visual responses in the absence of conscious seeing.
Blindsight has drawn significant interest from philosophers.
For them, the intriguing phenomenon is that someone is blind
but is making responses to visual stimuli. This seeming para-
dox is resolved when we think of conscious seeing as being
a function of V1 in the cortex.
In the Application section, we discussed conjugate gaze pal-
sies, a series of disorders of vision, brought about by damage
to the oldest part of the brain, namely, the brain stem. In conju-
gate gaze palsy, brain damage to the brain stem occurs that
affects the ability of our eyes to train on the same object.
Conjugate palsies are sometimes seen as complications
in Parkinson’s disease, after cardiac surgery, and when
the pineal gland is compromised. Parinaud’s syndrome
occurs from lesions in the superior colliculus. Rather than
irregular movements and difficulties coordinating the two
eyes, patients with Parinaud’s syndrome have a paralysis of
gaze. They must move their heads, rather than their eyes, to
track motion.
Chapter 4: Visual System: The Brain 119
REVIEW QUESTIONS
1. What is the optic chiasm? Describe how retinal gan-
glion cells cross over in the optic chiasm. How does
this crossing over affect the representation of the
visual world in the LGN?
2. What are the three types of layers in the LGN?
What kind of retinal ganglion cell innervates
each? What is the functional significance of each
layer?
3. What is the function of the superior colliculus?
Where in the brain is it found?
4. What is meant by the term cortical magnification?
How does it explain the retinotopic organization of
V1 of the visual cortex?
5. Describe the receptive fields of simple and complex
cells in V1. What is the function of each type of cell?
6. What are ocular dominance columns? How were
they discovered by Hubel and Wiesel? What role do
they play in the hypercolumns of V1?
7. What are V2 and V3? Where are they found in the
brain, and what is their functional role in vision?
8. What is the dorsal pathway? What is the ventral path-
way? What is the functional significance of each
pathway?
9. What is blindsight? Describe its expression in neuro-
psychological patients. What is the likely anatomical
cause of blindsight?
10. What is conjugate gaze palsy? What is the neurolog-
ical damage in this condition?
PONDER FURTHER
1. Consider the dorsal and ventral pathways and their
perceptual specialties. What might a hypotheti-
cal brain region look like that combined information
from the two systems? What kinds of cells would you
expect to find? What kinds of connections to other
areas of the brain might you see?
2. Scientists have studied receptive fields in very technical
ways, by passing bars of light in front of the eyes of perceiv-
ers. How might these receptive fields respond when pre-
sented with the varied stimuli that occur in the real world?
Would they still respond to the same features, or might
receptive fields actually be tuned to more complex stimuli?
KEY TERMS
Bistratified retinal ganglion cells
(K cells), 95
Blindsight, 114
Blobs, 105
Complex cells, 103
Conjugate gaze palsies, 116
Contralateral organization, 93
Contralateral representation of
visual space, 93
Cortical magnification, 101
Dorsal pathway, 107
End-stopped neurons, 104
Extrastriate cortex (secondary
visual cortex), 106
Hypercolumn, 105
Inferotemporal cortex, 109
Interblobs, 105
Internuclear ophthalmoplegia, 117
Ipsilateral organization, 93
Koniocellular layers, 94
Koniocellular pathway (K pathway), 96
Lateral geniculate nucleus, 94
Magnocellular layers, 94
Magnocellular pathway
(M pathway), 96
Midget retinal ganglion cells
(P cells), 95
MT (V5), 110
Object agnosia, 109
Ocular dominance column, 104
Optic chiasm, 92
Optic tract, 93
Orientation column, 104
Orienting tuning curve, 103
Parasol retinal ganglion cells
(M cells), 95
Parvocellular layers, 94
Parvocellular pathway (P pathway), 96
Primary visual cortex (V1), 100
Retinotopic map, 101
Saccades, 99
Sensation and Perception120
Scotoma, 114
Simple cells, 103
Smooth-pursuit eye movements, 98
Superior colliculus, 98
Ventral pathway, 107
V2, 106
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
4.1 Identify the anatomy of the optic chiasm and how that affects
the lateralization of vision in the brain.
Visual Pathways
4.2 Diagram the anatomy of the lateral geniculate nucleus and
the superior colliculus, and describe their roles in visual
processing.
Visual Consciousness Revisited: Magnocellular
and Parvocellular Contributions to Conscious and
Nonconscious Vision
4.3 Explain the nature of the retinotopic organization of V1 and the
organization of V2.
Ocular Dominance Columns: Enigmas and Challenges
Confuse Your Illusion: Feedback to Early Visual Cortex
Contributes to Perceptual Completion
Hubel and Wiesel
4.4 Compare the difference between the dorsal pathway and the
ventral pathway.
Functional Streams and Cortical Integration in the Human
Brain
The Thatcher Illusion Reveals Orientation Dependence in
Brain Regions Involved in Processing Facial Expressions
4.5 Interpret the concepts of blindsight and conjugate gaze palsy. Some Veterans Return With “Hidden” Vision Problems
Blind Man Sees With Subconscious Eye
Pawan Sinha: On How Brains Learn to See
Richard Kail/Science Source
5Object Perception
SSPL/Hulton Archive/Getty Images
LEARNING OBJECTIVES
5.1
Interpret the computational difficulties the visual system must overcome in
recognizing objects as themselves under a multitude of situations and angles.
5.2
Assess the difference between top-down processing and
bottom-up processing and how they affect object perception.
5.3 Describe the gestalt laws of perceptual grouping.
5.4 Explain why the ventral pathway is critical for object perception.
5.5
Discuss how we can distinguish human faces from doll
and mannequin faces, and interpret how object perception
research can inform the airport screening process.
INTRODUCTION
Dr. P. was a professor of music at a college in New York City (Sacks, 1985). His wife
and his colleagues were concerned that he was having problems seeing, though these
problems were not the ordinary problems, such as presbyopia that eyeglasses can cor-
rect. Dr. P. failed to recognize both longtime colleagues and new students. Only when
his acquaintances spoke did he know who they were. In the street, he might stop to
talk to a fire hydrant and be surprised when it did not reply. Finally, his wife had him
visit Oliver Sacks, the noted neurologist and writer, and Sacks wrote of this case in his
famous book The Man Who Mistook His Wife for a Hat (Sacks, 1985). Sacks deter-
mined that Dr. P. had lost none of his intelligence or any of his musical ability. However,
he had a form of agnosia we now know as object agnosia. Agnosias are acquired sen-
sory deficits that occur without any loss of sensation. Dr. P. could not identify simple
objects, despite the fact that he could see them. For example, Dr. Sacks handed Dr. P. a
rose, and Dr. P. responded by telling him that it was “about six inches in length, a con-
voluted red form with a linear green attachment” (p. 13). When given a glove to inspect,
Dr. P. responded by describing it as “a continuous surface, infolded on itself. It appears
to have five outpouchings . . . It could be a change purse” (p. 14). In each case, Dr. P.
demonstrated that he saw the object and could describe it accurately, but he had lost
the ability to identify it, despite what would be to us the obvious nature of each object.
Whereas others might not be able to describe these objects in such eloquent terms,
most people would instantly see a rose and a glove. Although Sacks’s interests lie in the
ISLE EXERCISES
5.1 Segregation and
Grouping
5.2 Ambiguous Figure–
Ground Perception
5.3 Figure–Ground
Symmetry
5.4 Gestalt Laws
5.5 Necker Cube
5.6 Illusory Contours
5.7 Geons
5.8 Facial Responses
in the Brain
(Inferotemporal Region)
124 Sensation and Perception
philosophical interpretations of such a condition, we now know that such descriptions
mark a case of object agnosia, which is likely the result of damage to the inferotemporal
cortex (see Figure 4.19).
What object agnosia shows is that we have specialized areas in the brain that
are necessary for identifying specific objects. Dr. P. sees the shape of the flower, but
he cannot identify it as such. His color perception is accurate, his shape perception
is accurate, but he cannot put them together to see the rose, something any normal
sighted person does effortlessly (Figure 5.1). This suggests that perceptual processes
we take for granted are actually quite complicated. Although it may be difficult to
imagine what it is like to be agnosic, we hope to show you how complex the pro-
cesses are that allow us to effortlessly visualize objects. Examine the two photo-
graphs in Figure 5.2. Both depict the same TV remote, each from a different angle.
The representation of the remote is very different on the retina in each photograph.
In Figure 5.2a, we are looking directly down on the remote. It is flat against the sur-
face, and we can see only one side. In Figure 5.2b, the remote is on its side, and we
are viewing straight on rather than from above. Yet most of us will have no difficulty
seeing the same object. This is an example of shape constancy, the concept that an
object remains the same despite changes to its retinal image. How the visual system
recognizes objects despite such changes is one of the topics we explore in this chapter.
INTRODUCTION TO OBJECT PERCEPTION
5.1
Interpret the computational difficulties the visual system must overcome in
recognizing objects as themselves under a multitude of situations and angles.
Despite Dr. P.’s intelligence and musical ability, he probably would not be able to func-
tion in everyday life if he did not have his wife to guide him through it. Think of trying
to prepare a meal for oneself when one mistakes one’s newspaper for the frying pan,
and one’s telephone for the spatula. It would be a real disaster and quite dangerous.
Indeed, under such circumstances, it might be wiser for Dr. P. to blindfold himself and
rely exclusively on his other senses, rather than trust his distorted vision. Dr. Sacks
never followed up on his patient, so we never learned what happened to him after their
initial meeting. Nonetheless, Dr. P.’s dilemma illustrates an important concept for the
rest of us. Being able to recognize quickly the
objects in our environment is critical.
Consider the environment you are in now.
Surrounding you are many objects. Most
likely you have a book or laptop (or tablet
device) in front of you. If you have come this
far in the course, this textbook has already
become a familiar if hefty companion. If you
are reading it on your tablet computer, that
object was already familiar to you before you
started the course. Perhaps you are drinking
coffee from your favorite mug. Your eye-
glasses and phone rest on the table near you.
You are sitting in the comfortable chair that
your aunt purchased for you last year. You
are surrounded by the familiar objects that
you recognize instantly. However, our ability
FIGURE 5.1 Roses
Convoluted red forms or roses?
What do you see?
©
iS
to
ck
ph
ot
o.
co
m
/D
N
Y5
9
FIGURE 5.2 Two Perspectives of the Same Object
The same object looks very different from different angles and creates very
different images on the retina. But those of us with normal visual perception
have no difficulty deciding that these photographs depict the same object.
(a) (b)
125 Chapter 5: Object Perception
to recognize objects goes far beyond that with which we are immediately familiar. A
friend comes in with a new mug, and we recognize the mug instantly as a mug, and we
do not have to ask what such an object is. Another friend enters with the latest cellular
phone, and we recognize it as a cell phone even if we have never seen that particular
model before. In fact, we recognize individual unfamiliar examples of familiar catego-
ries all the time—a new species of tree, a paper clip shaped like a musical note. Only
occasionally do we come across a genuinely unfamiliar object—one about which we
have no knowledge of what it is made of, what its function is, or where it came from
(Figure 5.3). We see here how much knowledge influences our perception. When we see
a genuinely unfamiliar object like this, even its size may not be clear.
However, even recognizing a familiar object is an enormously difficult compu-
tational problem (however effortless it feels to us). Consider Figure 5.4. In order to
recognize the television remote in this picture (and yes, it is the same as in Figure 5.2),
our visual systems must do a great deal of computation. Consider first that the top
half of the remote is being illuminated by the light from a nearby window and, as a
consequence, is reflecting significantly more light than the bottom half, which is in
the shadow of the wall. Nonetheless, we see the remote as a continuous object. The
pen in the glass bowl is obscuring part of the remote. Finally, the glass bowl is dis-
torting the image of the far upper corner of the remote. But what we see is a standard
TV remote, not some odd space-age object. The point here is that our visual system
has to make a lot of complex inferences for us to see even an ordinary object in a
familiar scene.
Our ability to detect objects must overcome three aspects of the environment:
image clutter, object variety, and variable views. To overcome image clutter, we
must discern the object despite the overlapping presence of nearby objects, such
as coasters, other remotes, and glass bowls. Although detection of objects is nor-
mally easy, increased clutter can make it difficult, as in the Where’s Waldo? series
of children’s books. With respect to object variety, we must recognize a particu-
lar object as a member of a particular class or
category despite small or large differences from
our general prototype of that category. That is,
the remote in Figure 5.4 is likely one that you
have never seen before. However, because of its
similarity to other remotes, chances are you had
no difficulty assigning it to the correct category.
Finally, in variable views, we must recognize an
object despite its being placed in very different
orientations relative to ourselves and casting
different images onto our retinae. That is, we
must be able to identify the same object from
different vantage points (as in Figure 5.2). This
is particularly important when it comes to face
recognition. You want to be able to recognize
your friend regardless of the angle at which you
are looking at him or her. The point here is that
object recognition actually is a computationally
difficult task for our visual systems.
Another way of examining the idea that
object recognition is a hard problem is to look
at the development of self-driving cars (see Cain
Miller & Wald, 2013; Findling, 2017). Although
self-driving cars have come a long way, no state
FIGURE 5.3
A Genuinely Unfamiliar Object
Can you tell what this object is?
Can you judge its approximate
size? What function might this
object have? What is it made
of? When you do not have
knowledge about the object,
these questions may be very
tricky to answer.
©
Shutterstock.com
/Charles Curtis
FIGURE 5.4 A Complex Scene
Despite the presence of odd lighting, obstructions, and a clutter of
other objects, we can still recognize the remote behind the glass bowl.
Our visual systems are tuned to identify objects across a wide range of
transformations.
126 Sensation and Perception
allows them unless there is also a human driver
sitting at the wheel. Why do we still not trust
self-driving cars? One reason is the difficulty of
object recognition. The computer that responds
to the video input must be able to quickly and
accurately recognize many thousands of objects
from any number of angles. More important than
distinguishing between two views of a remote,
the self-driving car must distinguish between dis-
carded dolls, which may not require swerving, and
children on the street, which must be avoided at all
costs. At present, according to Findling (2017), the
technology is finally there, though issues of legal
responsibility for accidents remain wide open.
Self-driving cars, of course, have certain advan-
tages over human drivers: They do not get tired,
they do not get angry or feel road rage, they do not
text while driving, they do not drink alcohol, and
they can be programmed not to tailgate. Thus, as
object recognition software improves, it is likely
that self-driving cars will ultimately become much
safer than human driving (Figure 5.5).
TEST YOUR KNOWLEDGE
1. What is object agnosia? How is object agnosia different than blindsight?
2. What computational difficulties does the visual system face in recognizing objects? How
are these difficulties related to the difficulty in building self-driving cars?
TOP-DOWN PROCESSING AND
BOTTOM-UP PROCESSING
5.2
Assess the difference between top-down processing and bottom-
up processing and how they affect object perception.
In sensation and perception research, we seek explanations both at the neurological level
and at the psychological level. We need to understand what is going on in the sensory
organs and with the brain in order to make sense of sensory processes, but we also need
to understand psychological processes in order to determine how we go from sensation
of a pattern of light to the recognition of objects, such as individual people, roses, and
self-driving cars. To this point, we have mostly been discussing the physiology and anat-
omy of sensation, but in this chapter, we begin discussing the more psychological issues
of perception. One way to view this distinction is in the cognitive psychology logic of
top-down and bottom-up processing. Bottom-up processing means that physical stim-
uli influence how we perceive them. This is relatively straightforward: Our eyes detect
reflected long-wavelength light when we examine the object depicted in Figure 5.1, and,
therefore, we see it as red. Top-down processing means that our existing knowledge of
objects influences how we perceive them. Thus, we perceive a “rose” because we already
know that roses are bright red and have this particular pattern of shape and shadow. If we
did not know about roses, we might give a description similar to the one given by Dr. P.
©
B
ro
ok
s
Kr
af
t/
Co
rb
is
N
ew
s/
G
et
ty
FIGURE 5.5 A Self-Driving Car
This is a photo of Google’s prototype of a self-driving car. The computer
that navigates the car must make real-time computations on a dizzying
amount of data to negotiate the road and avoid obstacles. These
computations are done routinely in the human brain but are difficult to
program into a computer.
Bottom-up processing: a
process whereby physical
stimuli influence how we
perceive them
Top-down processing: a
process whereby our existing
knowledge of objects influences
how we perceive them
127 Chapter 5: Object Perception
Look back again at the object depicted in Figure 5.3. Because we do not know
what the object in Figure 5.3 is, we have a hard time perceiving many of its important
aspects, such as its size. Could you fit this object in your hand, or could you fit yourself
inside the object? It is hard to tell. As you read through this chapter, think about when
the issue at hand is bottom-up processing and when it is top-down processing.
Recognition and Representation
Although the focus of this chapter is object perception, the issues discussed here dovetail
with issues of memory, in this case our knowledge base of visual objects. As we just dis-
cussed, our existing knowledge of the world is important in identifying individual objects
in it. Because existing knowledge is important to perceiving objects, it is necessary to have
a memory system capable of storing this knowledge. Thus, memory and perception are
integral to understanding object perception. As
a result, we need to define two memory terms
here. Recognition refers to the ability to match
a currently viewed item with an item in memory.
In more technical terms, it refers to the percep-
tual matching of something currently present to
our visual system with a stored representation
in memory. We can think of recognition as being
equivalent to a police lineup (Figure 5.6). A wit-
ness is shown several possible suspects and must
pick out the one who was seen at the crime. In
perceptual terms, recognition implies that we
know something about what we are seeing—that
is, we are able to match the object we see with a
stored memory. Obviously, recognizing objects is
an important part of our visual perception. In the
case of Dr. P., he sees objects but does not recog-
nize them as members of learned categories, such
as gloves or flowers. In normal vision, we must
recognize two classes of objects. We must recog-
nize specific objects as members of larger classes.
For example, we must recognize the object on the
shelf as a screwdriver. But we also must recognize objects as specific instances of that cat-
egory. For example, that screwdriver on the shelf is my favorite screwdriver. Being able to
recognize specific instances of a particular category is vital in face recognition, in which you
must recognize a person as, for example, your uncle, rather than as a member of a category,
such as men (Schwartz, 2017).
Representation refers to the processes that translate stimulus information into a per-
ceptual experience of that stimulus. Thus, an object appears in the visual field. Neural
processes detect it and send an image to V1. The process of representing that object
starts immediately, in parallel across the dorsal and ventral system. The representation
then is the neural code for what the object actually is. This use of the term is not to be
confused with other meanings of the term representation in related fields. In neurosci-
ence, representation refers to how neurons code for information, such as the shapes
and colors of objects. It can also denote how networks of neurons across the brain
store the information we will need to retrieve at some point. In cognitive psychology, a
representation is the form in which information itself is stored. If you consider a class of
objects, such as familiar faces, we need to be able to represent information about them.
We need to be able to represent the general form of human faces and the specific forms
of particular human faces (e.g., your mother, your brother, your landlord).
©
iStockphoto.com
/RichLegg
FIGURE 5.6 Recognition and Representation
Recognition: the ability to
match a presented item with an
item in memory
Representation: the storage
and/or reconstruction of
information in memory when
that information is not in use
128 Sensation and Perception
TEST YOUR KNOWLEDGE
1. What is the difference between top-down processing and bottom-up processing?
2. What processes are necessary in order to be able to remember an object that you
saw earlier?
Perceptual Organization
Perceptual organization is the process by which multi-
ple objects in the environment are grouped, allowing us
to identify those objects in complex scenes. Look around
you. You are likely to see a complex scene. Books, com-
puter equipment, pens, and pencils, as well as other
personal possessions, probably surround you if you are
reading this book at home. Other people, bookshelves,
paintings, and other objects are likely to surround you
if you are reading this at the library. Perceptual organi-
zation is necessary, as almost any scene will be complex,
with overlapping objects, occluding objects, and some-
times ambiguous objects. Perceptual organization per-
mits us to group what we see into coherent perceptions.
That is, it is necessary to group some objects together
(e.g., books) and separate other objects even if they have
similar shapes (books from bricks, e.g.).
Two important processes in perceptual organiza-
tion are grouping and segregation. Grouping is the pro-
cess by which elements in a figure are brought together
into a common unit or object. In Figure 5.4, we see the
remote as one object or grouped together, even though
the glass bowl occludes part of the remote. Segregation
is the process of distinguishing two objects as being
distinct or discrete. Thus, in Figure 5.4, we need to seg-
regate where behind the glass bowl the end of the first remote is located and where
the beginning of the second remote starts. In the formal table scene depicted in Figure
5.7, a perceiver will group the plates together, the chairs together, and the squares on
the tablecloth together. However, segregation will be used to distinguish those plates
that will contain people’s individual meals and the serving dishes that will be spared.
You can see an illustration of these principles on ISLE 5.1.
GESTALT PSYCHOLOGY AND
PERCEPTUAL ORGANIZATION
5.3 Describe the gestalt laws of perceptual grouping.
In the early 20th century, while behaviorists were ascendant in the United States, a school
of psychology known as gestalt psychology pursued a different path in research, largely
in Western Europe, particularly Germany. The gestalt psychologists were led by such
psychological greats as Max Wertheimer, Kurt Koffka, and Wolfgang Köhler. In a general
sense, the gestalt theorists claimed that the brain is holistic, with self-organizing tenden-
cies. The higher levels of organization take precedence over the lower levels. This differs
Perceptual organization: the
process by which multiple objects
in the environment are grouped,
allowing us to identify multiple
objects in complex scenes
Grouping: the process by
which elements in a figure are
brought together into a common
unit or object
Segregation: the process of
distinguishing two objects as
being distinct or discrete
Figure–ground organization:
the experience viewers have as to
which part of an image is in front
and which part of an image is in the
background of a particular scene
ISLE 5.1
Segregation and Grouping
FIGURE 5.7 Fancy Dinner
How many distinct candles are there on the table? You probably
have no difficulty determining the number of candles, despite the
visual obstruction of some of the candles. Moreover, it is trivial
for you to determine where one object ends, such as the chairs in
the front, and where the table begins. Although easy in practice,
this is a complex process computationally and relies on stored
representations of objects.
©
iS
to
ck
ph
ot
o.
co
m
/a
lo
ha
_1
7
129 Chapter 5: Object Perception
to some extent from current research trends, which are often
reductionist, in the sense that we try to build our models from
the lowest levels upward. In terms of vision, gestalt psychol-
ogy argues that what we see is greater than its individual parts.
That is, the processes of perception are designed to see the scene
rather than bits of light here and there. In this way, gestalt psy-
chologists thought that stimuli were sufficiently rich in structure
to allow the perceptual system to extract meaning directly from
the stimuli, rather than building it up from image to thought.
As such, it was important for them to establish the rules that
governed the building of bigger perceptual units.
The gestalt psychologists were structuralists who thought
that conscious perception rested on the building blocks of
sensation. However, unlike Helmholtz, gestalt psychologists
thought that stimuli were rich enough for meaning to be inter-
preted directly rather than through unconscious inference.
Thus, we sense incoming stimuli, but perception is an active
process that interprets perceptions out of these sensory build-
ing blocks. Gestalt psychology also maintained that the whole
is often different from the sum of its parts. That is, the percep-
tion that emerges from a physical scene may not be directly
predicted by the sensory components that it is composed of;
rather, it emerges when we integrate the components into a
whole. Think of the standard way in which comic books
used to be created. The images were composed of many col-
ored dots. Each dot was just a little speck of red, but when put
together, one saw Spiderman. Examine Figure 5.8. The eye in
Figure 5.8 is composed of many dots. To gestalt psychologists,
the dots make up the sensory components of the stimuli, but
seeing the eye emerges from perception. Moreover, the stimulus
makes no sense unless we see it as an eye. It is just dots other-
wise. Thus, this immediate perception of higher level interpreta-
tions is necessary in any visual system.
For these reasons, gestalt psychologists were interested in
understanding the rules by which perception picked out the
whole from its parts. In particular, they investigated three prin-
ciples concerning how our perceptual systems do this. These
principles are figure–ground relations; the laws of Prägnanz, or
good fit; and the laws of grouping. Although these ideas were
developed approximately 100 years ago, they still apply to the
science of vision in important ways. We start with figure–ground
organization.
Figure–Ground Organization
Figure–ground organization refers to the experience viewers have
as to which part of an image is in the foreground and which part
is in the background of a particular scene. In essence, we divide
the world into two elements: the figure that is the object of regard
and the rest, which is ground or background (here they mean the
same thing). In many cases, we can choose what will be the figure.
For example, if you are giving a public lecture, you can look at
©
iStockphoto.com
/jc_design e
FIGURE 5.8 Eye or Dots?
All that is really present physically in this image is a
series of dots on a background. However, the arrangement
of the dots creates the image of an eye. Gestalt
psychologists argue that the process behind seeing the
eye instead of the dots is fundamental to perception. Our
visual systems extract this higher meaning from the array
of stimuli in the world.
FIGURE 5.9 Figure–Ground
If you are looking at the cat, other aspects of the stimulus
become ground or background. However, if you switch
your focus from the cat to the oranges, the cat becomes
background.
130 Sensation and Perception
one person’s face in the audience. As you look at that
face, that face is the figure, and everyone else at that
moment is ground. When you look at a new face, the
last person’s face is now ground. Consider Figure 5.9.
When you look at this photograph, when you direct
your gaze toward the oranges, the cat is ground and
the oranges are figures. However, when you look at the
cat, figure–ground reverses. In other situations, figure
and ground may be determined by other components
of the stimulus. If you look around, you will see objects
close to you and objects farther away. Objects close
to you tend to be lower in your visual field and less
obstructed by other objects than those farther away. Is
such information useful to your visual system? Indeed
it is, as normally, figure–ground determinations are rel-
atively easy, as is apparent in Figure 5.10. In this figure,
we tend to see the puffins as the foreground and the sea
as the background.
However, there are exceptions in which the bot-
tom of an image may not represent what is close, and
the top of an image may not represent what is far away. Consider the photograph in
Figure 5.11. Here we are looking down and across at a pond in the Everglades. Here,
the figure circles the background. There are branches hanging down from the top of
the image that are close to the observer in addition to the vegetation at the bottom,
which is also in the foreground. The background of the photograph is the stuff in the
middle, which is farthest from the observer. Because of this, this photograph takes
a moment or two to figure out, because it does not conform to ordinary rules of
figure–ground. Note the turtle swimming just beneath the surface of the pond at the
center of the photograph.
©
R
oi
ne
M
ag
nu
ss
on
/P
ho
to
di
sc
/G
et
ty
Im
ag
es
FIGURE 5.10 Figure–Ground
In this figure, we tend to see the resting puffins as the figure, because
they are closer to us, and the distant sea as background.
FIGURE 5.11 Figure–Ground
In this photograph of an Everglades alligator hole, the construction of the
scene leads one to see the middle as foreground and the top, bottom, and
sides as background.
FIGURE 5.12 More on Figure–Ground
Do you see two faces looking at each other in front of an
orange background? Or do you see an orange vase in front of
a white background? You may see one or the other and switch
between the two, but you cannot see both at the same time.
131 Chapter 5: Object Perception
There are other situations in which figure–ground can be highly ambiguous, and
it may not be possible to determine which part of the image is the front and which is
the back. This is true of many classic visual illusions. One such classic example is the
face–vase figure, first introduced into the literature by psychologist Edgar Rubin in
1915 (Figure 5.12). In this figure, the border between the orange and white regions
is seen as being part of one or the other, not both. Thus, either the orange vase at the
middle stands out as the foreground and the white faces are in the background, or
the white faces stand out as the foreground and the orange space is the background.
Interestingly, in these ambiguous figures, people see either one interpretation or the
other, and although they can flip back and forth, they cannot see both at the same
time. You can see a demonstration of this illusion on ISLE 5.2.
One of the useful aspects of such illusions is that we can make systematic changes
in the way the images are presented and see how those changes affect the perception
of the figure. Consider Figure 5.13. In this figure, we see that the field representing
the faces and the vase are offset. When the vase is lowered and moved to a corner, it
stands out as the figure, and it is nearly impossible to see the faces. When the faces
are lowered and moved to the corner, they stand out as the figure, and the vase is no
longer visible in the background. This illustrates the point that figures tend to be in
the front and the background on top.
A Few Rules That Govern What We See as
Figure and What We See as Ground
We have already seen that the top of an image is more
likely to be seen as the background and that what is in
the front of an image is likely to be seen as the figure.
But there are other rules as well that apply to the figure–
ground relation. We outline them here (also see ISLE 5.3).
We can identify another environmental feature that
influences our perception of figure–ground. As we have
seen already, perceived depth is one feature. The figure
that appears in the foreground is often below the fig-
ure that appears in the background. Another feature is
symmetry. A figure with symmetrical borders is more
likely to be judged as being in the foreground than in
the background (Figure 5.14).
ISLE 5.2
Ambiguous Figure–Ground
Perception
FIGURE 5.13 The
Face–Vase Figure–Ground
Illusion
(a) With the shifting down of the
position of the orange area, we
are more likely to see the vase.
(b) With the shifting down of the
position of the white area, we
are more likely to see the faces.
(a)
ISLE 5.3
Figure–Ground Symmetry
FIGURE 5.14
Symmetry Affects Figure–Ground Organization
Images that are symmetrical are more likely to be seen as figure
and therefore in the foreground, whereas less symmetrical images
are more likely to be perceived as background.
(b)
132 Sensation and Perception
Another feature that affects figure–ground percep-
tion is that a figure is more likely to be perceived as
being in the foreground if it is perceived to be on the
convex side of a border. That is, the figure that appears
to be in the foreground is the one with outward bulg-
ing (convex) borders, not the one with inward-facing
(concave) borders. This point is illustrated nicely in
an ambiguous figure taken from research by Stevens
and Brookes (1988). In Figure 5.15, you can see either
swirly ropes descending or a thorny branch descend-
ing. Most perceivers, though, see the swirly ropes, as
these are the convex figures.
That convex images are perceived as figure and
concave images as ground was also illustrated in an
experiment by Peterson and Salvagio (2008). These
researchers presented figures like those depicted in
Figure 5.16. In Figure 5.16, one can see convex blue bands and concave white bands.
According to the ideas concerning convexity and figure–ground relations, we should
see the blue bands as the figure and the white bands as the background. Peterson and
Salvagio placed a small red square at some point on the figure and had participants
make judgments of front or back. When the square landed on a convex band, partic-
ipants indicated that it was in the front, but when the square was on a concave band,
they indicated that it was in the background.
In summary, there are a number of rules that govern figure–ground relations. These
rules allow us to make sense of complex scenes because we use our existing knowledge
of the world to help us interpret what is visually in front of us. For example, we know
from experience that heavy objects do not usually float 3 feet above the ground. Thus,
even though we cannot see the bottom of a chest of drawers, we infer that there must
be a bottom, and that the couch we see in its entirety is in front of the chest of drawers.
Thus, the couch becomes the figure and the chest is ground behind it. We next turn to
more of these rules developed by the gestalt psychologists.
Gestalt Laws of Perceptual Grouping
The process by which visual systems combine figures within an image into wholes is called
perceptual grouping. Perceptual grouping involves using existing knowledge to place simi-
lar items together or to group images in different parts of the visual field into a perception
of the same object. Consider Figure 5.4 once more. When you view this image, you imme-
diately group figures into coherent wholes. Thus, even though the blue on the two coasters
is the same, you see these as two differ-
ent objects because they are not contin-
uous; one blue pattern is associated with
the “pig” coaster, whereas the other blue
pattern is associated with the “rooster”
coaster. This is also why we see a complete
glass bowl even though it is possible that
the bowl is broken, as the reflection of sun-
light makes it difficult to see the complete
bowl.
The gestalt psychologists, especially
Max Wertheimer, developed a number
of “laws” that predict how perceptual
FIGURE 5.15
Convexity Affects Figure–Ground Organization
Images with convex borders are more likely to be seen as figure,
whereas those with concave borders are more likely to be seen as
ground. Adapted from Stevens and Brookes (1988).
FIGURE 5.16 Figure–Ground Judgments
The participants’ task was to decide if the red square was on the figure or in the
background. When the square landed on a convex band, participants indicated
that it was in the foreground, but when the square was on a concave band, they
indicated that it was in the background. Based on stimuli from Peterson and
Salvagio’s (2008) experiment.
133 Chapter 5: Object Perception
grouping occurs under a variety of circumstances (Wertheimer,
1923/1938). Technically, in sciences, “laws” are predictions
that are always true, no matter the conditions. In reality, these
laws are better classified as principles, which are true most of
the time. However, the term laws has stuck with these prin-
ciples because they were established so long ago. So we will
continue to refer to them as laws, even though technically they
are not scientific laws.
The law of good continuation means that figures that have
edges that are smooth are more likely to be seen as continuous
than those with edges that have abrupt or sharp angles. This
law is best seen rather than described. Examining Figure 5.17a,
most people see a horizontal orange bar behind a blue vertical
bar. This is because the two orange rectangles would meet if
each was extended. So we see them as continuous behind the
blue vertical bar. However, in Figure 5.17b, the two orange
rectangles would not be continuous behind the blue vertical bar. Therefore, we see
them as two separate entities.
The law of proximity is the gestalt grouping law that states that elements that are
close together tend to be perceived as a unified group. This straightforward law states
that items close to one another tend to be grouped together, whereas items farther
apart are less likely to be grouped together. In Figure 5.18, we tend to see five groups
of 3 letters rather than one group of 15 letters.
The law of similarity is the gestalt grouping law that states that elements that are
similar to one another tend to be perceived as a unified group. Similarity can refer to
any number of features, including color, orientation, size, or, indeed, motion. This is
illustrated in Figure 5.19.
The law of symmetry is the gestalt grouping law that states that elements that are
symmetrical to one another tend to be perceived as a unified group. Similar to the law
of similarity, this rule suggests that objects that are symmetrical to one another will
FIGURE 5.17 Good
Continuation
(a) We see one bar on top
of another bar. The good
continuation of the bar in the
back suggests its presence.
(b) We see two separate bars
behind the front bar because
the break in the figure does not
suggest continuity.
(a)
(b)
FIGURE 5.18 Proximity
When we see these letters, we
see five groups of three letters
because of the proximity of the
three letters together. That is,
elements that are close together
tend to be grouped together.
FIGURE 5.19 The Law of Similarity
We tend to group together objects that look similar. Thus, we see objects grouped together by
color (c) and objects grouped together by size (d).
(a) No grouping
(b) Proximity
(c) Similarity of color
(e) Similarity of orientation
(d) Similarity of size
(f) Common fate
Law of good continuation:
the gestalt grouping law stating
that edges that are smooth
are more likely to be seen as
continuous than edges that
have abrupt or sharp angles
Law of proximity: the
gestalt grouping law stating
that elements that are close
together tend to be perceived
as a unified group
Law of similarity: the gestalt
grouping law stating that
elements that are similar to one
another tend to be perceived as
a unified group
Law of symmetry: the
gestalt grouping law that
states that elements that are
symmetrical to each other tend
to be perceived as a unified
group
LKS AJC QWE PKX JPB
134 Sensation and Perception
FIGURE 5.20 The Law of Symmetry
In this figure, the figures that are
symmetrical are grouped together.
Symmetry
be more likely to be grouped together than objects not symmetrical to one another.
This is illustrated in Figure 5.20.
The law of common fate is the gestalt grouping law that states that
elements that are moving together tend to be perceived as a unified
group. Think of watching a flock of geese moving across a fall sky.
The geese are all flying in the same direction at approximately the
same speed. Therefore, we see them as a gestalt group or, in this case,
a flock. We might see a second flock flying in a different direction in
a different pattern. You can see an illustration of each of the gestalt
principles on ISLE 5.4.
Perceptual Interpolation
In real-world scenes, as we have already mentioned, particular objects are often par-
tially occluded. That is, a particular object may be blocked by another object, rendering
the physical image of the first object disjointed. Yet our perceptual systems see objects
as continuous wholes despite that blocking. In Figure 5.21a, for example, the leaves
of the tree do not impede our perception of a single koala, even though parts of the
koala are not visible. In Figure 5.21b, the iron gate breaks up our view of the grass
field beyond, but we see a continuous field of grass rather than a series of smaller ones
divided by some unseen fence that coincides exactly with the grates of the gate. Look
around you. Many of the objects around you are occluded by other objects, yet you see
each object as a whole rather than a set of disjointed parts. Thus, filling in edges and
completing surfaces are important jobs of our object recognition system.
One important process used in perceptual interpolation is edge completion.
Edge completion is the perception of a physically absent but inferred edge, allow-
ing us to complete the perception of a partially hidden object. A stunning exam-
ple of edge completion comes from illusory contours, as illustrated by the famous
ISLE 5.4
Gestalt Laws
Law of common fate: the
gestalt grouping law that states
that elements that are moving
together tend to be perceived
as a unified group
Edge completion: the
perception of a physically
absent but inferred edge,
allowing us to complete the
perception of a partially hidden
object
©
iS
to
ck
ph
ot
o.
co
m
/P
ix
el
-P
ro
du
ct
io
ns
FIGURE 5.21 Perceptual Interpolation
We infer the continuation of objects even when they are partially occluded by other objects. In Figure 5.21a, for example, the leaves
of the tree do not impede our perception of a single koala, even though parts of the koala are not visible. It could be that the koala is
terribly disfigured and the leaves are arranged so that we cannot notice it. But it is more likely that this is a normal super-cute koala. In
Figure 5.21b, the iron gate breaks up our view of the grass field beyond, but we see a continuous field of grass rather than a series of
smaller ones divided by some unseen fence that coincides exactly with the grates of the gate.
©
iS
to
ck
ph
ot
o.
co
m
/V
ik
to
rC
ap (a) (b)
135 Chapter 5: Object Perception
FIGURE 5.22
Kanizsa Triangle
These illusory contours illustrate
the principle of edge completion.
The arrangement of the circles
with the bites taken out of them
suggest that a white triangle
overlaps three blue circles.
Because we unconsciously
infer this, we see the triangle as
slightly brighter in color than the
white background, even though
it is not.
FIGURE 5.23
An Illusory Necker Cube
Perceptual interpretation here
creates the appearance of a
white-barred cube resting on
top of a number of blue circles.
The bars that appear to define
the cube seem brighter than
the surrounding background.
This is due to the nonconscious
inference of the cube. Moreover,
the cube created is ambiguous
and can be seen in one of two
orientations.
ISLE 5.5 and 5.6
Necker Cube
Illusory Contours
Kanizsa triangle (see Kanizsa, 1979;
Petry & Meyer, 1987). Kanizsa devel-
oped these illusions explicitly working
in the tradition of gestalt psychology,
and you can apply many of the princi-
ples of gestalt psychology to interpret
or predict the presence of illusory con-
tours. Illusory contours (or subjective
contours) are perceptual edges that
exist because of edge completion but
are not actually physically present.
In Figure 5.22, we see a bright white
triangle imposed on a background of
blue circles. However, looking closer,
there is no real difference in bright-
ness between the white of the triangle
and the white of the background. In
fact, if you can force yourself to see
three blue Pac-Man figures rather than
three occluded triangles, the illusion
of the bright triangle may disappear.
Important to note here is that most
people really do see a brightness dif-
ference. Only when you block out
the figure and compare the brightness
of the center of the triangle with the
brightness of the background do you
perceive them as being identical. And to really “mess with your mind,” examine the
illusory Necker cube in Figure 5.23 and ISLE 5.5. You can try ISLE 5.6 to control
the parameters yourself and see how they affect the perception of illusory contours.
Illusory contours have interested perception researchers for a long time (see
Petry & Meyer, 1987). This includes neuroscientists as well as gestalt psycholo-
gists. Neuroscience data suggest that illusory contours are processed at a very early
level in vision, consistent with the illusory brightness differences. The physiological
explanation for illusory contours arises from studies on V2 neurons in the brains of
monkeys (von der Heydt, Peterhans, & Baumgartner, 1984). In these studies, von
der Heydt et al. (1984) showed that edge detection cells responded to illusory edges
as strongly as they did to real ones when the stimuli were aligned to create percep-
tual illusions of edges. However, the cells did not fire when stimuli without implied
edges were presented. Other research shows that cells in V1 are activated by illusory
contours in the same way that they are activated by actual contours (Maertens &
Pollmann, 2005). Thus, illusory contours appear to be a relatively low-level feature
of object identification. This reinforces the notion that the gestalt principles are
based on low-level features of perception, consistent with the gestalt view that we
pick up these features in the stimulus rather than as a function of nonconscious
processing.
TEST YOUR KNOWLEDGE
1. What is figure–ground symmetry? Why is it important in visual perception?
2. What are the laws of perceptual grouping? What do they account for?
Illusory contours: perceptual
edges that exist because of
edge completion but are not
actually physically present
136 Sensation and Perception
RECOGNITION BY COMPONENTS
Whereas the gestalt psychologists emphasized organization, that is, how we use implicit
knowledge to help us perceive objects in the environment, other researchers have
emphasized the bottom-up approach, that is, how we use the information in the world
to construct a perception of what we see. One of the most influential bottom-up the-
ories advanced to account for object recognition was developed by Irving Biederman
in the 1980s (see Biederman, 1987). In this view, the complexity of object recognition
is solved when the visual system breaks down objects in the environment into what
Biederman called geometric ions, or geons. Geons represent the basic units of objects
and consist of simple shapes, such as cylinders and pyramids. Recognition by com-
ponents theory states that object recognition occurs by representing each object as a
combination of basic units (geons) that make up that object. We recognize an object
by the relation of its geons. Biederman tentatively proposed that there were roughly 40
independent geons and that just about any object could be represented by some com-
bination of these geons. Figure 5.24 shows a few sample geons, and Figure 5.25 shows
simple objects made up of geons. You can also do an interactive version of building
shapes from geons on ISLE 5.7.
One of the advantages of this model is that if any object is a combination of a
few basic geons, then the object is specified by those components, and its position
relative to the observer should not matter. Thus, this model accounts for the view-
point invariance of objects, that is, that objects are seen as the same regardless of the
vantage point relative to a viewer (see Figure 5.4 again). However, recently recog-
nition by components theory has fallen into disfavor, largely because of its limits in
accounting for some phenomena, such as letter recognition and face recognition, two
big categories of object recognition in humans.
TEST YOUR KNOWLEDGE
1. What are geons, and why are they considered the building blocks of object perception?
FIGURE 5.24 Geons
These basic shapes, or geons, were thought by Biederman
(1987) to be the basic building blocks of object perception.
ISLE 5.7
Geons
Geons: the basic units of
objects, consisting of simple
shapes such as cylinders and
pyramids
Recognition by
components: a theory stating
that object recognition occurs
by representing each object
as a combination of basic
units (geons) that make up that
object; we recognize an object
by the relation of its geons
Viewpoint invariance: the
perception that an object does
not change when an observer
sees the object from a new
vantage point
FIGURE 5.25 Objects From Geons
When we put various geons together, we can create various
recognizable objects.
(a) (b) (c) (d) (e)
137 Chapter 5: Object Perception
THE NEUROANATOMY AND
PHYSIOLOGY OF OBJECT PERCEPTION
5.4 Explain why the ventral pathway is critical for object perception.
We start this section with a brief review of some of the material covered in the last
chapter. Remember that two pathways emerge from area V1 of the occipital cortex.
One of these pathways is known as the “where” pathway or the dorsal pathway. This
pathway works its way through the extrastriate cortex and then continues on to the
parietal lobe. The dorsal pathway is concerned mainly with locating objects in space
and perceiving motion. We focus on this pathway in Chapter 8. The second pathway
that emerges from V1 is known as the “what” pathway or ventral pathway. This path-
way works its way through the extrastriate cortex and then continues on to the tem-
poral lobe. One of its main functions is object recognition. We focus on this pathway
in this section.
Representation of Shapes in Area V4
After information leaves V1 and travels toward the extra-
striate cortex along the ventral pathway, one of the impor-
tant loci is area V4 in the occipital cortex (Figure 5.26). V4
has been linked to color vision but also to shape perception.
V4 neurons seem to have a clear preference for edges, but a
more complex analysis of edges than seen in V1 or V2. For
example, V4 neurons can respond to edges that are either
straight or curved, whereas V1 neurons show a strong pref-
erence for straight edges (Pasupathy & Connor, 2002). Also,
like V1 neurons, V4 neurons respond to contours (Pasupathy
& Connor, 2002). However, V4 neurons respond to either
convex or concave contours. Thus, this area is involved in
delineating shapes, necessary for object recognition.
Object Recognition in the
Inferotemporal Area
Information in the ventral pathway leaves the occipital lobe
and heads into the inferotemporal area of the temporal lobe
(see Figure 5.26). Neurons in the inferotemporal area have
much larger receptive fields than those in V1 and V4 and seem to be devoted to detect-
ing particular kinds of objects anywhere in the visual field rather than specific features
in specific places. Indeed, some areas in the inferotemporal area seem to be very specific
to particular kinds of shapes or forms (Brincat & Connor, 2004). That is, rather than
detecting edges or contours, the inferotemporal area seems to specialize in detecting
specific objects from chairs to bears to faces.
Neuroscience researchers have known for a long time of the relation between the
inferotemporal cortex and object recognition. Back in the 1930s, Klüver and Bucy
(1939) lesioned the temporal lobes of monkeys in their lab. After creating these lesions,
V4: an area of the brain
involved in both color vision and
shape perception
Inferotemporal area: the area
of the temporal lobe involved in
object perception; it receives
input from V4 and other areas in
the occipital lobe
FIGURE 5.26 Object Recognition in the Brain
Area V4 and the inferotemporal area are two critical areas in
the neural substrate of object recognition.
V4
Inferotemporal cortex
138 Sensation and Perception
Klüver and Bucy observed what they called “psychic blindness” but
what we now call object agnosia. The monkeys were able to demon-
strate that they could see, but they could not discriminate among dif-
ferent objects. For example, the monkeys could press a button when
a light flashed, thus indicating that they could see, but they could not
discriminate among shapes. Later research pinpointed these symp-
toms to disruption of the inferotemporal area (Barlow, 1995).
Other lesion studies in monkeys found cells that appeared to
be specific for face recognition. For example, Rolls and Tovee
(1995) presented monkeys with pictures of faces and other
images. Recording from single cells within the inferotemporal
area, Rolls and Tovee identified a class of cells that responded
strongly to faces, both monkey and human, but barely responded
to nonface stimuli. As we will see in the next section, this finding
is consistent with what we see in the human inferotemporal area
as well (ISLE 5.8).
The Fusiform Face Area
and Face Recognition
One important area within the inferotemporal cortex is known as the
fusiform face area (FFA). The FFA appears to be a specific region in
the brain designed for a specific kind of object recognition, that is, the
recognition of familiar faces (Kanwisher & Dilks, 2013; Kanwisher,
McDermott, & Chun, 1997). The FFA is located on the ventral surface
of the temporal lobe. This area can be seen in Figure 5.27. Although
there is some debate as to how specific the FFA is to face recognition,
most research now suggests that the area is involved in the recognition
of familiar faces after an object has already been perceived as a face
(Liu, Harris, & Kanwisher, 2010). That is, we use the FFA to distin-
guish Aunt Sally’s face from Aunt Mary’s face rather than to identify a strange array of
colors and textures as a face in the first place. Another area of the brain known as the
occipital face area (OFA) appears to be responsible for making the initial identification
of a face as being a face, regardless of its familiarity. That is, the OFA is an area associated
with recognizing faces as distinct from other objects. The OFA is located in the extrastri-
ate cortex and is strongly connected to the FFA (Liu et al., 2010).
Grill-Spector, Knouf, and Kanwisher (2004) examined the role of the FFA in face
recognition using functional magnetic resonance imaging (fMRI) technology. In one
condition of their experiment, they used photographs of the face of the actor Harrison
Ford as their face stimulus. In control conditions, participants saw another face, or
they simply saw a texture gradient with no face. They saw these stimuli for only 50
ms, followed immediately by a masking stimulus, which made it difficult to identify the
stimulus they had just seen. The participants’ task was to identify the briefly presented
photo as Harrison Ford, another face, or nothing at all. The participants did the task
while the fMRI machine was monitoring activity in the FFA.
Grill-Spector et al. (2004) found strong activity in the FFA when participants
identified Harrison Ford in the stimulus. Interestingly, they got strong, though not as
strong, activity in the FFA when the participants thought they saw Ford in the stim-
ulus, but it had actually been a control stimulus. When participants saw the other
face or the texture pattern and identified it as such, there was much less activity
ISLE 5.8
Facial Responses in the Brain
(Inferotemporal Region)
FIGURE 5.27 The Fusiform Face Area (FFA)
and the Occipital Face Area (OFA)
The FFA is an area within the inferotemporal cortex
that is associated with the recognition of familiar
faces in humans. The OFA is located within the
occipital lobe and is associated with recognizing any
face as a face.
Inferotemporal
cortex
Fusiform face
area (FFA)
Occiptal face
area (OFA)
Fusiform face area: an area in
the inferotemporal area of the
temporal lobe that specializes in
recognizing familiar faces
Occipital face area: an area
of the brain in the occipital lobe,
associated with recognizing
faces as distinct from other
objects
139 Chapter 5: Object Perception
in the FFA. Importantly, the response in the
FFA was greatest when the participants recog-
nized Harrison Ford and not the nonfamous
face (Figure 5.28). The FFA shows a selective
response to seeing faces already known rather
than all faces. In summary, this study shows
a strong relation between the recognition of
familiar faces and activity in the FFA.
Prosopagnosia
Damage to the FFA results in a condition known
as prosopagnosia. The term prosopagnosia comes
from two Greek words, one meaning “face” and
one meaning “knowledge.” Prosopagnosia is a
selective deficit in recognizing faces. Prosopagnosia
is a neurological condition in which face recogni-
tion is impaired, but other forms of visual object
recognition are relatively intact. Thus, a patient
with prosopagnosia will have difficulty recog-
nizing particular people but will not have diffi-
culty identifying roses or gloves. It usually occurs
in patients who have had strokes, but there are
some cases of people born with prosopagnosia
(Duchaine & Nakayama, 2006). Patients with
prosopagnosia recognize faces as faces but fail to
recognize specific faces, even of close family mem-
bers. For example, when a prosopagnosic patient
is presented with a photograph of the face of a
family member or a celebrity, the patient will be
able to identify the object as a face but will not be
able to identify the specific person. However, pro-
sopagnosic patients can recognize familiar people
by other cues, such as their voices, their particular
ways of walking, and even distinctive features such
as a big nose or a large facial scar.
One question researchers have debated
is whether prosopagnosia occurs on its own or
whether it is always associated with a more general object agnosia. Most of this research
suggests that, in some cases, a person can have impairment of face recognition but
intact recognition of other objects. For example, Moscovitch and Moscovitch (2000)
compared prosopagnosic patients and object-agnosic patients. Patients with object
agnosia were normal at face recognition but showed deficits in object recognition.
In contrast, the prosopagnosic patients showed deficits in facial recognition but not
object recognition. That is, the prosopagnosic patients, relative to control patients,
were just as able to recognize common objects, such as spoons, pianos, slippers, and
candles. However, these patients could not recognize the faces of people who were
otherwise familiar to them. The object-agnosic patients were able to recognize famil-
iar faces, but they had difficulty recognizing the common objects. This pattern has
now been found in many studies (Busigny & Rossion, 2011).
©
iStockphoto.com
/bloodstone
FIGURE 5.28 The Grill-Spector et al. (2004) Experiment
Participants briefly saw Harrison Ford’s face followed by a mask, or a control
stimulus followed by a mask (a). In (b), we can see the activity in the FFA when
the participant recognized the photo as Harrison Ford and when the participant
did not. Note that the highest response in the FFA is for correct recognition.
Stimulus
Brain activity
measured
Mask
Observer’s
response
Indicate either
(a) “Harrison Ford”
(b) “Another object”
(c) “Nothing”
See either
(a) Harrison Ford
(b) Another person’s face
(c) A random texture
Correct identi�cation
Saw face but
incorrect identi�cation
151050
−0.2
0
0.2
fM
R
I
si
g
n
a
l
Time (sec.)
0.4
Did not see face
(a)
(b)
©
iS
to
ck
ph
ot
o.
co
m
/E
dS
to
ck
140 Sensation and Perception
There is also a very rare condition known as develop-
mental prosopagnosia, which occurs in individuals who
have normal vision and normal social functioning but
show a selective deficit in face recognition (Duchaine &
Nakayama, 2006). Recent fMRI research shows less activity
in the FFA in patients with developmental prosopagnosia,
compared with normal controls, when identifying famil-
iar faces than when viewing other objects (Furl, Garrido,
Dolan, Driver, & Duchaine, 2011). Thus, the evidence with
developmental prosopagnosics also supports the view that
the FFA is an area unique to face recognition.
Other Inferotemporal Cortex
Areas With Specific Object
Recognition Functions
The parahippocampal place area (PPA) is an area within the
inferotemporal cortex that has the specific function of scene
recognition. This area is selectively tuned for the recognition of
spatial landscapes, both indoor and outdoor scenes (Epstein,
2005; Epstein & Kanwisher, 1998). This area is responsive to
photographs of spatial landscapes but shows no additional
activity when images of people are present in those landscapes.
As with the FFA, there is a form of agnosia that accompanies
damage to the PPA. Topographic agnosia involves a deficit in
recognizing spatial landscapes and is related to damage to the
PPA (Mendez & Cherrier, 2003).
Another area in the inferotemporal cortex with a specific function is the extra-
striate body area. The extrastriate body area is activated when its cells view bodies or
body parts but not faces (Downing, Jiang, Shuman, & Kanwisher, 2001). This inter-
esting area is responsible for visual recognition of body areas other than the face. It
may be that other areas of the inferotemporal cortex are also sensitive to particular
stimuli as well. These areas can be seen in Figure 5.29.
Grandmother Cells and Specific
Coding in the Inferotemporal Cortex
An early issue in the history of neuroscience was how specific brain regions are to function
and to particular stimuli. This debate often centered on whether the brain worked as a
whole or was composed of the many separate areas we know it to be composed of now. But
part of the debate concerned where memories were stored in the brain. Thus, for example,
early neuroscientists wanted to know where in the brain was the memory of your cat. When
your cat enters the room, you recognize the cat not just as any cat but as your cat. Clearly,
areas in the inferotemporal cortex are helping you recognize this animal as a cat and as your
good friend Whiskers. The question addressed in this section is whether there is an area of
the brain that is specific to Whiskers but not to your other cat, Fluffball, or any other cat.
In the past, this question was phrased not in terms of cats but rather in terms of another
equally cute category, grandmothers (Figure 5.30). Is there an area in the brain or, more spe-
cifically, in the inferotemporal cortex, that codes for your grandmother but no other person?
Inferotemporal
cortex
Parahippocampal
place
Extrastriate body
Extrastriate
body
Parahippocampal place
area (PPA): an area within
the inferotemporal cortex that
appears to have the specific
function of scene recognition
Topographic agnosia: a
deficit in recognizing spatial
landscapes, related to damage to
the parahippocampal place area
Extrastriate body area: an
area within the inferotemporal
cortex that is activated when its
cells view bodies or body parts
but not faces
FIGURE 5.29 The Parahippocampal Place Area
(PPA) and the Extrastriate Body Area
The PPA is an area within the inferotemporal cortex involved
in scene recognition. The extrastriate body area is associated
with recognizing parts of the body other than the face.
141 Chapter 5: Object Perception
In memory research, this quest has been labeled the
search for the engram. The engram is the specific location
of a specific memory, such as the visual identity of your cat
or your grandmother (Schacter, 2001). Note that the FFA
is responsive to familiar faces but does not necessarily dis-
criminate between the face of your grandmother and that
of your aunt. For many years, the general wisdom was that
such “grandmother” cells would not be found. Identifying
an individual requires the coordination of networks of cells
and communications among them. However, one remark-
able demonstration suggests that grandmother cells may
in fact exist. This study examined famous landmarks and
celebrities rather than grandmothers, but the investigators
found remarkable characteristics of specific object recogni-
tion in inferotemporal neurons (Quiroga et al., 2005).
Quiroga et al. (2005) were able to conduct a very unusual
study because of particular circumstances of their partici-
pants. Their participants were all people about to undergo
elective brain surgery to treat epilepsy. During this procedure, neurosurgeons need
to be very careful about the function of brain regions on which they are about to
operate. As such, as a matter of course, single-cell recordings are taken in some areas
of the brain in these patients. These recordings allow the doctors to determine which
tissue is critical to normal functioning and thus where they need to be extra careful
during surgery. Normally, single-cell recording in live people is not permitted, but in
this case, electrodes were to be implanted in the brains of the patients anyway, and
thus the patients themselves were under no additional risk from Quiroga and col-
leagues’ experimental procedure. Although the results of this study are remarkable,
there has been some controversy over whether these results can be replicated in other
studies.
Quiroga et al. (2005) asked their patients to look at a series of pictures presented
on a computer screen while individual neurons were being monitored. The cells that
were monitored were in the medial temporal lobe, adjacent to but not identical to
the inferotemporal cortex. They found cells that appeared to be specific to individual
people. For example, one cell was selectively responsive to photographs of the bas-
ketball player Kobe Bryant but did not respond to photographs of the actor Mark
Hamill (i.e., Luke Skywalker). Another cell was responsive to photographs of Mark
Hamill but not to Kobe Bryant. The cell responded to Kobe Bryant’s photo with dif-
ferent hairstyles, to a photo of Mr. Bryant and a teammate, and to his printed name.
Different cells in this area appeared to make stronger responses to Mark Hamill as
Luke Skywalker, to other photos of him, and to his name in print. Similarly, Quiroga
et al. found a cell in the medial temporal lobe that was responsive to images of the
leaning tower of Pisa but not to the Golden Gate Bridge, and another cell that was
responsive to the Golden Gate Bridge but not the leaning tower of Pisa. Thus, these
cells are astonishingly like the grandmother cells, responding to a particular person
or landmark from different angles and in different contexts but not to other people
or other famous landmarks (Figure 5.31).
There are some problems, however, with Quiroga and colleagues’ (2005) study,
some of which the researchers themselves have discussed (Quiroga, Reddy, Kreiman,
Koch, & Fried, 2008). First, they did not have much time to test each patient. Thus, they
were not able to test related stimuli. For example, would the “Kobe Bryant” cell also
respond to his fellow Laker star Shaquille O’Neal? Would the “Golden Gate Bridge”
©
iStockphoto.com
/m
ichellegibson
FIGURE 5.30 Grandma and Her Cat
Where in the brain is the representation of the memory of your
grandmother and her favorite cat?
142 Sensation and Perception
cell also respond to a photograph of the San Francisco–Oakland Bay Bridge? These
were questions the investigators were not able to answer, given the time constraints
before the patients’ surgeries. It is also possible, given that the medial temporal lobe
is more involved in memory than visual perception, that the cells were involved in the
retrieval of photograph-related information rather than recognizing specific objects or
people, although such a result would still be surprising. Finally, this study has proved
difficult to replicate, though there has now been at least one conceptual replication
(Gelbard-Sagiv, Mukamel, Harel, Malach, & Fried, 2008). Nonetheless, these studies
show that areas in the temporal lobe may be highly specialized in recognizing partic-
ular objects in the visual world. Thus, Quiroga et al.’s findings are consistent with the
goals of the ventral system—identifying objects in the environment.
TEST YOUR KNOWLEDGE
1. What is prosopagnosia? Is it a form of object agnosia or something different?
2. What is the inferotemporal area? What does it do, and what happens when it is damaged?
5.5 Discuss how we can distinguish human faces from doll
and mannequin faces, and interpret how object perception
research can inform the airport screening process.
FIGURE 5.31 Results of the Quiroga et al. (2005) Study
These data are from single cells within the human temporal cortex. One cell responded to the image of Kobe Bryant but
not to images of other people. Similarly, one cell responded to the image of the Golden Gate Bridge but not to images of
other landmarks.
©
iS
to
ck
ph
ot
o.
co
m
/p
ho
to
qu
es
t7
©
iS
to
ck
ph
ot
o.
co
m
/m
ar
eb
ts
©
iS
to
ck
ph
ot
o.
co
m
/p
ho
to
qu
es
t7
©
iS
to
ck
ph
ot
o.
co
m
/s
te
ve
na
lla
n
©
iS
to
ck
ph
ot
o.
co
m
/E
dS
to
ck
©
iS
to
ck
ph
ot
o.
co
m
/E
dS
to
ck
©
iS
to
ck
ph
ot
o.
co
m
/E
dS
to
ck
©
iS
to
ck
ph
ot
o.
co
m
/E
dS
to
ck
143 Chapter 5: Object Perception
EXPLORATION: Vision and Animacy:
How Do We Tell a Who From a What?
Creepy dolls are almost a cliché in horror movies. Every
couple of years, we see another movie about Chucky, the
crazed doll who terrorizes all who come into contact with
him in the Child’s Play and Chucky movies. Creepy dolls
are a staple of other horror movies, including The Woman
in Black (2012) and one movie aptly named The Creepy
Doll (2011). But dolls are supposed to be playthings for
very young children. How could we give to young chil-
dren objects that produce terror in adults? Store manne-
quins are also often the stuff of horror fantasies, from The
Twilight Zone to Dr. Who. But mannequins are supposed
to inspire us to buy particular clothes. So why do we see
dolls both as cute and harmless toys for our children and
as representations of our deepest fears? And why do seem-
ingly harmless mannequins also bring our fears to the
forefront? Well, we think there is an interesting answer.
Recent research by Thalia Wheatley and her colleagues
at Dartmouth College shed some light on this issue (e.g.,
Looser & Wheatley, 2010).
In Looser and Wheatley’s view, what draws us to dolls
and repels us at the same time is that they have faces
(Figure 5.32). Humans are drawn to see and seek out
faces. Presumably, this was important in human evolu-
tion. Adults need to be able to recognize familiar kin
and distinguish them from potentially dangerous strang-
ers. Young infants must be able to recognize their moth-
ers and distinguish them from other women. Thus, it is
likely that strong evolutionary pressures led to the spe-
cial module for face recognition that exists in the FFA of
the inferotemporal lobe, which allows us to quickly rec-
ognize and identify familiar faces. However, a module
that is designed to seek out faces wherever they are may
seek out faces where none actually exist. It is perhaps
for this reason that we see faces in clouds, mountains,
constellations, and various inanimate objects (Figure
5.33). For many years, for example, the symbol of the
state of New Hampshire was a rock formation on a
mountain that bore a passing resemblance to a human
face. Dolls and mannequins are an interesting case, as
they are deliberately designed to strongly resemble peo-
ple, but they are clearly not people. Dolls have faces, but
they are inanimate objects. Thus, we are drawn to them,
but at the same time, we must recognize that they are not
real human faces. The question that Wheatley’s group
was interested in was what differences might exist in the
perception of real and simulated faces. For a fascinating
take (albeit in a commercial) on our detection of human
faces in odd stimuli, watch this YouTube video: http://
www.youtube.com/watch?v=TQk7Zh-dXCk.
Looser and Wheatley (2010) pointed out that all human
minds have faces, but not all faces have human minds. Dolls
FIGURE 5.32 Dolls Have Faces
A doll has human features but is decidedly not human.
©
iStockphoto.com
/m
itza
FIGURE 5.33 A Smiley Face?
We are tuned to see faces and often see them in objects that do
not really have eyes, noses, and mouths. We often see faces in
clouds, on the sides of mountains, and in tortillas. This is likely
due to an evolutionary disposition to detect human faces.
©
w
anderw
orldim
ages/A
lam
y
144 Sensation and Perception
and mannequins are not the only mindless faces—we have
masks, sculptures, and even photographs and painted por-
traits. So why are dolls and mannequins potentially creepy
but photographs are not? Dolls and mannequins are not
exact duplications of faces (as in photographs) or clearly
iconic representations (as are masks and sculptures). The
better the doll is made, the more closely it resembles a
real human baby or other human figure. Whereas most of
the research we have discussed so far examines how we
detect faces, Wheatley’s research goes a bit further and
asks how we detect faces that have minds attached. When
we see a face, it instantly activates face-sensitive areas of
the brain, such as the FFA. However, animate face recog-
nition requires an additional step: to associate the face
with a moving, living, animate being. Thus, we must make
an additional step to go from face to mind.
This is supported by Wheatley’s research. Wheatley,
Weinberg, Looser, Moran, and Hajcak (2011) used
electroencephalographic (EEG) technology to look at
responses to photographs of real faces and photographs
of dolls and mannequins. The EEG responses were aver-
aged to look at characteristic wave patterns, known as
event-related potentials, in response to these face stimuli.
Wheatley et al. found that they could identify an event-
related potential wave that occurred after recognizing
faces, real or inanimate, but not other stimuli, presum-
ably emanating from the FFA. When dolls and manne-
quins were presented to participants, the face response
on the EEG decreased about 200 ms after presentation.
However, for real faces, the EEG response continued.
Wheatley’s team could therefore tell what kind of face,
animate or inanimate, a person had
examined by looking at the EEG
response. Thus, human visual sys-
tems can quickly distinguish between
human faces and inanimate replicas.
In the Looser and Wheatley (2010)
experiment, they combined the
images of real faces and inani-
mate faces, as can be seen in Figure
5.34. They found images of statues
and dolls that matched the faces
of actual people and, using a com-
puter program, morphed the images
together. Looser and Wheatley then
varied the level at which each image
contained more human or more
doll in the face, with some being all
doll and some being all human, as
well as various in-between levels.
Participants then made a number of
different judgments concerning the
faces, including alive or not alive,
realistic or unrealistic, has a mind
or does not have a mind, and able
to feel pain or not able to feel pain.
Regardless of the particular judg-
ment, Looser and Wheatley found a
tipping point at about 65% human.
That is, if the combined image was
at 65% human face or higher (i.e.,
35% doll), it was judged to be alive,
to be realistic, to have a mind, and to
FIGURE 5.34 Transformation From Real Baby to Doll
Consider the middle two faces. Are they of a doll or a person?
FIGURE 5.35 Results of Looser and Wheatley’s (2010) Study of Animacy
These data show participants’ perceptions of whether the figures were animate or not.
The colored lines indicate the ratings for attributes of animacy, such as animacy itself,
having a mind, the ability to plan, and the ability to feel pain. From Looser & Wheatley
(2010), Figure 2, p. 1856.
De�nitely
has
Attribute
De�nitely
lacks
S
u
b
je
ct
s’
p
e
rc
e
p
ti
o
n
s
o
f
a
tt
ri
b
u
te
Actual physical difference
PSE
1.0.9.8.7.6.5.4.3.2.1.0
.0
.1
.2
.3
.4
.5
.6
.7
.8
Animacy
Plan
Pain
.9
1.0
*
Mind
145 Chapter 5: Object Perception
APPLICATION: The Science of Airport Screening
Most of you are probably familiar with the chaotic
scenes at crowded modern airports. As we walk to our
gates at the airport, we dodge people with large roll-
ing suitcases, strollers, and wheelchairs, and we also
now dodge the people who are so trustworthy of others
that they feel comfortable texting and walking in large
crowds. Equally ubiquitous are the inevitable lines that
form as we go from unsecured areas to secured areas
in the airport. At airport security, all travelers and their
bags must go through machines designed to help agents
detect objects that travelers are not allowed to bring
on airplanes. These objects may vary from seemingly
innocuous objects such as jars of jam to much more
dangerous objects such as knives, box cutters, and guns.
Although these machines are very adept at looking into
your belongings, there still must be a pair of human eyes
watching the ongoing stream of bags. These security offi-
cials are looking for something very uncommon, as most
of us know better than to pack forbidden objects for
air travel. Thus, the dangerous object, such as a knife,
is among a tremendously greater number of innocuous
objects. Part of the job of such a security official (TSA
agents, in the United States) is the ability to recognize the
dangerous objects among all of the harmless ones in real
time under rushed and degraded conditions.
The general study of object perception and applied stud-
ies on detecting dangerous objects in X-ray displays have
tremendous importance for our system of deterring crime
in the air. These studies should have an influence on how
feel pain. At less than 65%, the animacy ratings tailed
off quickly (Figure 5.35). Looser and Wheatley found it
significant that this tipping point was higher than 50%.
They think it is important that we have a high criterion
for recognizing animacy in a human face.
Looser and Wheatley (2010) compared their results with
earlier social-psychological data on object perception
that showed that, in many situations, we find facelike
inanimate objects to be likable (e.g., a rock with eyes
drawn on it), but we are often suspicious of or revolted
by clearly inanimate objects that look too human (e.g.,
mannequins, dolls). It may be for this reason that many
children’s cartoons use anthropomorphic animals or
caricature images of children to portray their characters
rather than more lifelike representations.
In another experiment, Looser and Wheatley (2010)
examined individual features of faces, including the eye,
the mouth, the nose, and the skin, and then compared
the judgments of animacy from just these facial features
with those from whole faces. Overall, they found lower
animacy judgments for parts of a face than for a whole
face, but they also found that animate-looking eyes were
the biggest predictor of animacy. Seeing an eye by itself
allowed participants to judge animacy in a way in which
mouths and noses did not. In evaluating inanimate faces,
it may be that the other features of the face activate the
brain’s face detectors, but the lack of animate eyes may
give a doll or mannequin its “creepy” look (Figure 5.36).
To summarize this research, human visual systems are
extremely sensitive to stimuli that look like human faces.
This means that we may often get “false alarms,” that
is, stimuli that look like human faces but are actually
not. We can quickly reject faces in stones and clouds as
not being really human, but dolls and mannequins give
us pause. In most cases, we reject dolls as being human,
but perhaps every so often, they tweak our “mind”
detectors. This causes us to wonder, if only for a second,
if they are watching us and observing our actions. This
leads to a creepy feeling that the old unused doll gath-
ering dust in the closet is really plotting its revenge on
us. Thus, the creepy feeling we get from dolls is really
the activation of face areas in the brain, the activation
of “mind” areas in the brain, but the knowledge that
the doll does not have a mind. This causes us to worry
about what might lurk behind that face, and danger and
creepiness result.
FIGURE 5.36 The Perception of Creepiness
Is this creepy or what?
©
iStockphoto.com
/sqback
146 Sensation and Perception
FIGURE 5.37 Airport Security Checkpoint
Ed
uc
at
io
n
Im
ag
es
/U
ni
ve
rs
al
Im
ag
es
G
ro
up
/G
et
ty
Im
ag
es
screeners look for dangerous objects, how those screeners
are trained to look for dangerous objects, and how the
technology can be modified in the future to make it easier
for TSA agents to do their job effectively. Let’s consider a
few of these studies and their recommendations.
Airport screeners are looking for any number of contra-
band objects, from concealed firearms to oversized tooth-
paste. While on duty, each screener is looking for all of
these objects simultaneously. Research suggests, however,
that screeners would be better at detecting forbidden
objects if they were only scanning for one type of object.
That is, one screener should be looking just for guns, while
another looks just for knives. The research shows that as
the number of objects for which a screener is looking goes
up, the harder it is to detect any of these objects individu-
ally (Godwin et al., 2010). That is, if a screener is looking
for just one type of object (e.g., firearms), he is more likely
to detect a hidden firearm than if he is also looking for
knives and oversized liquids. This problem with searching
for multiple types of objects is known as the dual-target
cost. The dual-target cost means that as the number of
objects searched for increases, the likelihood of detecting
one of those objects decreases (Godwin et al., 2010; Smith,
Redford, Washburn, & Taglialatela, 2005). This dual-target
cost shows up in the accuracy of detecting objects as well
as the time it takes to recognize a to-be-rejected item.
It occurs in the lab for random objects, and it occurs in
simulated screening environments for banned weapons
(Godwin et al., 2010).
Eye-movement tracking shows that the dual-target costs
result from ineffective guidance during the visual search
process (Menneer, Stroud, Donnelly, & Rayner, 2008). In
this research, when participants are looking only for a sin-
gle type of target, they look at any object in the array that
resembles the target, thus allowing them to pick up on slight
deviations in the basic pattern (e.g., a handgun with a short
barrel but a large magazine). However, when participants
are looking for two types of objects, they tend to perse-
verate on objects that resemble neither target. This makes
it not only more difficult to pick out objects that deviate
from the basic pattern but also more time-consuming to
find objects that are typical of the category. As such, time is
wasted examining objects not part of the screening process
(Menneer et al., 2008). This wasted time may be inconse-
quential in a laboratory task, but when you have a huge line
forming at Security in an airport, it may encourage screeners
to rush through without adequately checking all items. This
finding has been shown not only in many laboratory studies
with more limited realism to airport screening but also in a
situation that directly mimics what screeners do at security
at airports (Godwin et al., 2010).
Can agents be trained to more accurately detect banned
objects? The research here is mixed. Some research
points to improvements with training, but other
research does not (see Nodine, Krupinski, & Kundel,
2002). It turns out it depends on what aspects of the
task the training is directed toward. McCarley, Kramer,
Ca
m
az
in
e
Sc
ot
t/
Sc
ie
nc
e
So
ur
ce
/G
et
ty
Im
ag
es(a) (b)
Dual target-cost: as the number of objects searched for
increases, the likelihood of detecting one of those objects
decreases
147 Chapter 5: Object Perception
Wickens, Vidoni, and Boot (2004) trained participants
in a simulated airport screening task. Participants had
to examine X-rays and look for knives in the suitcases.
McCarley et al. found that people got better and were
able to do the task faster as they practiced more and
more. However, their analysis of their participants’ eye
movements suggested that what the participants were
learning was how to get better at detecting specific
objects, rather than their ability to quickly move their
eyes and scan across the bag. In addition, the improve-
ment was limited to the specific objects on which the
participants were trained. When they were then asked
to look for different kinds of knives, the improvement
based on practice was lost (McCarley et al., 2004).
Other research shows that even after training, the
dual-target costs remain (Godwin, Houpt, Walenchok,
Hout, & Goldinger, 2015).
This research suggests that a better model of screen-
ing might be to train each TSA agent for a specific type
of banned object. Thus, while one agent is looking for
knives, another is looking for handguns, and another is
looking for liquid explosives. Given that each agent is
looking for only one class of object, they will benefit
from training and practice and will be better at detecting
that danger, leaving all of us safer when we travel.
CHAPTER SUMMARY
5.1
Interpret the computational difficulties the visual sys-
tem must overcome in recognizing objects as them-
selves under a multitude of situations and angles.
Object perception concerns our ability to visually identify the
world around us, from socks to bird feeders to our Aunt Sally.
Object agnosia is an acquired deficit in identifying and rec-
ognizing objects even though vision remains intact.
5.2
Assess the difference between top-down pro-
cessing and bottom-up processing and how they
affect object perception.
Object perception requires both bottom-up processing,
from stimulus to perception, and top-down processing, from
knowledge to perception, in order to function efficiently.
Object perception requires a memory representation system
that allows us to recognize familiar objects when we see
them.
5.3 Describe the gestalt laws of perceptual grouping.
Perceptual organization is the process by which multi-
ple objects in the environment are grouped, allowing us to
identify those objects in complex scenes. Two important
processes in perceptual organization are grouping and
segregation. Gestalt psychology argues that what we see
is greater than the sum of its individual parts and, as such,
emphasizes the rules that govern how objects in scenes are
determined from background noise. One set of these rules
concerns figure–ground organization, which refers to the
inference viewers must make as to which part of an image is
in front and which part of an image is in the background of a
particular scene. Gestalt psychologists also emphasized the
laws of perceptual grouping, which allow us to infer which
parts of an image go with which other parts. One such illus-
tration of these principles comes from illusory contours, in
which we see figures present that are not part of the physi-
cal stimulus.
5.4
Explain why the ventral pathway is critical for
object perception.
Object perception occurs along the ventral pathway in
the brain, which leads from V1 in the occipital lobe to the
inferotemporal area of the temporal lobe. V4 is an area in the
extrastriate cortex involved in shape perception. The infero-
temporal area is the area of the temporal lobe involved in
object perception. It receives input from V4 and other areas
in the occipital lobe. Part of the inferotemporal lobe is known
as the fusiform face area (FFA). The FFA is an area in the
inferotemporal cortex of the temporal lobe that specializes in
recognizing familiar faces. There is also a region known as
the occipital face area (OFA), which is an area of the brain in
the occipital lobe that is associated with recognizing faces
as distinct from other objects. Damage to the FFA results in a
condition known as prosopagnosia. The term prosopagnosia
comes from two ancient Greek words, one meaning “face”
and one meaning “knowledge.” Prosopagnosia is a selec-
tive deficit in recognizing faces. The parahippocampal place
area (PPA) is an area within the inferotemporal cortex that
appears to have the specific function of scene recognition.
Topographic agnosia involves a deficit in recognizing spa-
tial landscapes, related to damage to the PPA. Quiroga et al.
Sensation and Perception148
(2005) conducted a study that found cells in the temporal lobe
that responded to specific people, regardless of whether a
photograph or a name was presented. Some people regard
this study as evidence for neural areas that code for very
specific information about individual objects or people.
5.5
Discuss how we can distinguish human faces
from doll and mannequin faces, and interpret how
object perception research can inform the airport
screening process.
When we see a face, it instantly activates face-sensitive areas
of the brain, such as the FFA. However, animate face recog-
nition requires an additional step: to associate the face with
a moving, living, animate being. Research by Wheatley and
her colleagues shows that faces are recognized rapidly, but
an extra step exists to distinguish real human faces from fac-
similes, such as dolls. Human agents must inspect bags as
they go through airport screening. This is a task very much
dependent on people’s ability to recognize specific objects,
in this case, dangerous ones, such as guns and knives.
Research shows a dual-target cost, which means screen-
ers are slower and less accurate when they are looking for
multiple objects. Moreover, improvements in training occur
when screeners are scanning for only one class of objects.
Looking for multiple objects slows people down. Thus, the
research suggests that specific agents train for the detec-
tion of only one class of dangerous object.
REVIEW QUESTIONS
1. What is object agnosia? What areas of the brain
likely cause it, and what are its symptoms?
2. Define object perception. What are some of the
obstacles programmers must overcome to design a
computer system with object perception?
3. What is the difference between top-down and bot-
tom-up processing?
4. What is meant by perceptual organization? What is
the difference between grouping and segregation?
5. Who were the gestalt psychologists? How did they
contribute to our understanding of figure–ground
perception?
6. What is edge completion? How does it account for
illusory contours?
7. Describe the neural pathway that leads from V1
to the temporal lobe that is responsible for object
perception.
8. What is the difference between the FFA and the
OFA in perceiving faces? Which area is damaged in
prosopagnosia?
9. Several experiments have demonstrated the role of
the FFA in face perception. Describe one of these
experiments and how it confirms this area’s function.
10. Why is judging animacy in a face important? Why do
dolls and mannequins elicit “creepy” responses, but
pictures of real faces do not? What difference do we
see in EEG scans when people view photographs of
real faces and those of dolls?
PONDER FURTHER
1. Do you think recognizing words and letters follows
similar principles to the ones outlined here for object
perception? How might you test, in a behavioral exper-
iment, whether recognizing letters follows the same
gestalt principles as recognizing routine objects?
2. Faces are clearly important stimuli to human beings.
What other kinds of visual stimuli are as important
as faces? Might there be specific areas of the brain
for these classes of objects? How might you test for
these areas?
KEY TERMS
Bottom-up processing, 126
Dual-target cost, 146
Edge completion, 134
Extrastriate body area, 140
Figure–ground organization, 129
Fusiform face area, 138
Chapter 5: Object Perception 149
Geons, 136
Grouping, 128
Illusory contours, 135
Inferotemporal area, 137
Law of common fate, 134
Law of good continuation, 133
Law of proximity, 133
Law of similarity, 133
Law of symmetry, 133
Occipital face area, 138
Parahippocampal place area (PPA), 140
Perceptual organization, 128
Recognition, 127
Recognition by components, 136
Representation, 127
Segregation, 128
Top-down processing, 126
Topographic agnosia, 140
V4, 137
Viewpoint invariance, 136
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
5.1 Interpret the computational difficulties the visual system
must overcome in recognizing objects as themselves under a
multitude of situations and angles.
From Fragments to Geometric Shape: Changes in Visual
Object Recognition Between 18 and 24 Months
Visual Agnosia
Object Agnosia
5.2 Assess the difference between top-down processing and
bottom-up processing and how they affect object perception.
Top-Down Visual Processing
5.3 Describe the gestalt laws of perceptual grouping. A Perceptually Completed Whole Is Less Than the Sum of
Its Parts
5.4 Explain why the ventral pathway is critical for object
perception.
Object Recognition: Insights From Advances in fMRI Methods
Prosopagnosia
Face Blindness, Part 1
5.5 Discuss how we can distinguish human faces from doll and
mannequin faces, and interpret how object perception research
can inform the airport screening process.
Thalia Wheatley: How the Brain Perceives Other Minds
6Color Perception
David Parker/Science Source
LEARNING OBJECTIVES
6.1 Examine the relation of the wavelength of light to perceived color.
6.2
Diagram the perceptual principles of hue, saturation, and
brightness and the role they play in our perception of color.
6.3
Formulate the idea of a metamer in additive and subtractive color
mixing in terms of what we learn from color-matching experiments.
6.4 Examine the role of having three cone classes for our perception of color.
6.5
Describe the trichromatic theory of color vision and its
relationship to the three classes of cones.
6.6
Illustrate the opponent-process theory of color vision focusing on what this
theory can explain about color vision that trichromatic theory cannot.
6.7 Explain what we know about color vision in infancy
and how it changes as we age.
6.8
Diagram the different types of color deficiency and explain why this
term is, almost always, a better term than color blindness.
6.9 Assess the term constancy and how it applies to color vision.
INTRODUCTION
If you live in South Florida, seeing rainbows is a frequent occurrence. In the summer,
rainbows are quite common after a late afternoon thunderstorm. Driving along Route
1 in the Florida Keys in the summer, one can often see layer upon layer of rainbows
as one heads east in the late afternoon (Figure 6.1). Many people find rainbows to be
beautiful, partly because they appear to be pure color—just color, not attached to a par-
ticular object, seemingly magically suspended in the air. The physical explanation for
rainbows, millions of water droplets acting as prisms, just makes the phenomenon more
mysterious. We know it has to be true, but for many, the physical explanation just does
not connect with their perceptual experience. When most of us look at rainbows, we see
seven distinct bands: red, orange, yellow, green, blue, indigo (a dark blue), and violet
ISLE EXERCISES
6.1 Different Types of
White Lights
6.2 Dimensions of Color
6.3 Newton’s Prism
Experiment
6.4 Color Mixing
6.5 Color-Matching
Experiment: Metameric
Matches
6.6 Trichromatic Theory
and Cone Responses
6.7 Univariance and
Color Matching in
Monochromat or During
Scotopic Vision
6.8 Color Aftereffect
6.9 Simultaneous Color
Contrast
6.10 Hue Cancellation
6.11 Single- and Double-
Opponent Cells
6.12 Color-Deficiency Tests
6.13 Rod Monochromat
Vision
6.14 Dichromacy
6.15 Illumination and
Color Constancy
6.16 Lightness Constancy
6.17 Gelb Effect
6.18 Color Camouflage
and Dichromacy
152 Sensation and Perception
(a reddish blue resembling purple). However, a
rainbow is actually a continuous band of wave-
lengths—the seven bands are a function of our
eyes and brains. As we will see in this chapter,
colors are usually properties of objects, but in a
rainbow, we do not see the raindrops that create
the rainbows.
So, do all people and animals see color the
same way? Many of you may have heard that
your cat is color-blind. This is not quite true.
Cats do have some ability to see in color but
much less than we do (Buzás et al., 2013). Cats
are actually “color deficient,” meaning that
they have a two-cone color system, compared
with our three-cone system. Cats also have
fewer cones in total than humans, but they
can see colors. Cats’ eyes are better adapted
than ours for nocturnal vision, and their eyes
are more specialized for detecting low levels of
light at night. (Review the Exploration section
of Chapter 3.) Nonetheless, because cats are
active during the day, they also have some color vision. Dogs are also color deficient
relative to us, but they do see in color as well. It turns out that their retinae resemble
those of color-deficient people, in having a two-cone system. You probably know a
person who is red–green color-blind (better called, “color deficient”). Whereas you
see a green light or a red light at a traffic signal, he sees both the green and the red
lights as the same color. Luckily, he knows that the red light is always above the green
light, so red–green color deficiency is not a risk for driving. Are there animals with
better color vision than ours? You may have heard that goldfish have a four-cone
system, compared with our three-cone system. On the basis of research on goldfish,
it is known that they can see color differences that look the same to us (Neumeyer &
Arnold, 1989). So, some animals see fewer colors and some see more. What about
other people?
Interestingly, it turns out that some people may also have functional four-cone
systems that allow them to see more colors than the more common people with three
cones do. Gabriele Jordan, a researcher at the University of Newcastle in the United
Kingdom, recently identified a woman with a functional four-cone system, who seem-
ingly can see different colors when most of us would just see one color (Greenwood,
2012; Jordan, Deeb, Bosten, & Mollon, 2010). However, Jordan and her colleagues
think functional four-cone vision is extremely rare in people. In their study, they looked
at the genetics that cause some women to have four-cone systems and then tested
behaviorally whether women with four-cone systems could actually discriminate more
colors. Because many of the genes for color vision are on the X chromosome, men are
more likely to be color deficient and less likely to have the extra cone system. Jordan
et al. examined many people (all women) who have a genetic mutation that gives them
what looks like an extra cone system in their retinae. The question was whether this
would be expressed in terms of seeing more different colors than trichromats do. Only
one of these women actually was able to discriminate colors that looked identical to
the other participants or to controls with three cones. Jordan et al. estimated that this
woman may see millions more hues than other people do. Current research by Jordan’s
©
R
EU
TE
RS
/M
ar
c
Se
ro
ta
FIGURE 6.1 Rainbow
A rainbow is a continuous band of wavelengths that we see as seven colors blending
into one another. In addition to being a beautiful sight, a rainbow can tell us a bit
about color perception.
153 Chapter 6: Color Perception
group aims to understand what this woman sees, how it differs from typical color
vision, and whether it really gives her abilities the rest of us do not possess. If color
vision varies across animals and even people, how does color vision happen and what
allows for these variations?
WAVELENGTHS OF LIGHT AND COLOR
6.1 Examine the relation of the wavelength of light to perceived color.
In Chapter 3, we introduced the idea of the wavelength of light and its relation to
the perception of color. Humans can see wavelengths of light that vary between 400
and 700 nm, often known as the visual spectrum (or visible spectrum). Within the
visual spectrum, we see different wavelengths as different colors. It is important to
keep in mind that the physical stimulus is the wavelength of the light entering our
eye. Color is a perceptual attribute, or our response to this physical feature of light.
The term wavelength refers to the distance between two peaks of light energy. It
is the inverse of frequency. As frequency increases, wavelength decreases. In color
vision, the wavelength of light is usually referred to, and as we will see, with sound
waves, we tend to use frequency instead of wavelength (just to keep students on
their toes).
Sunlight is a mix of many different wavelengths, which blend together to form
white light. Because the wavelengths are bunched together within our acuity limits,
we cannot discriminate the different wavelengths in white light. But because sunlight
is composed of so many wavelengths, raindrops can diffract (i.e., spread out) the light
into the multiple wavelengths that make up the rainbow. The raindrops act as a prism
and separate the many wavelengths that are mixed together. Once they are separated,
we can see the individual bands of wavelengths as colors. Natural sunlight, however,
varies in the distribution of wavelengths during the course of a day. At noon, there is
more blue light than in the morning, and evening is well known for its lingering red
light. Many artificial sources of light tend to be mixes of multiple wavelengths that can
also be classified as white light. Normal incandescent light bulbs tend to emit more
long-wavelength light than short-wavelength light. This gives incandescent light bulbs
their characteristic yellow color. Fluorescent light bulbs tend to have the opposite pat-
tern, giving them their slightly blue hue (Figure 6.2 and ISLE 6.1). All of these are vari-
ants of white light, that is, heterochromatic light consisting of many wavelengths. In
contrast, monochromatic light, which can be produced by special light bulbs, is light
of only one wavelength or a very narrow band of wavelengths. When monochromatic
light reflects off of a white surface, we see that surface as the color associated with that
wavelength.
Another important feature in the perception of color is the spectral reflectance of objects
in the world. Spectral reflectance is the ratio of light reflected by an object at each wave-
length. This means that every object has particular characteristics that permit it to absorb
some wavelengths of light and reflect other wavelengths of light. Thus, white clothes reflect
wavelengths equally, whereas blue jeans absorb most wavelengths but reflect light at about
450 nm, which we perceive as blue. Thus, the color of any object is determined by what
wavelengths it reflects the most. Leaves are green because their surfaces absorb most light
but reflect those wavelengths we see as green. Carrots are orange because they absorb
most wavelengths but reflect light at about 650 nm, which we perceive as orange. Figure 6.3
Visual spectrum (visible
spectrum): the band of
wavelengths from 400 to 700
nm that people with the most
common classes of cones
vision can detect
Heterochromatic light:
white light, consisting of many
wavelengths
Monochromatic light: light
consisting of one wavelength
Spectral reflectance: the
ratio of light reflected by an
object at each wavelength
ISLE 6.1
Different Types of White Lights
154 Sensation and Perception
FIGURE 6.2 The
Distribution of Wavelengths
in Natural and Artificial Light
(a) The top part of the figure shows
the visible spectrum of light on
a continuum of electromagnetic
radiation. The figure makes it clear
that visible light is just a small range
on this continuum. The bottom part
of the graph shows the distribution
of wavelengths across natural
sunlight, incandescent light bulbs,
and fluorescent bulbs. Note the
interesting peaks in the fluorescent
bulbs, which are very strong in the
blue and green range, whereas
incandescent light bulbs show a
gradual increase, peaking in the
longer red wavelengths. (b) In
this figure, two different types of
artificial illumination are visible, both
considered white. Over the museum
and lounge, the light source has
more long wavelengths, and over the
hallway, the light source has more
short wavelengths. Because the two
light sources are next to each other,
you can see the differences in the
whites more easily.
Visible Spectrum
Gamma rays
10–11 10–9 10–7 10–5 10–3 10–1 101 103 105 107 109 1011 1013 1015 1017
Radio waves
Spectrum of
electromagnetic
radiation
x-
rays
UV
rays
Infrared
radiation
Wavelength (nm)
Micro-
waves
Monochromatic light
Wavelength (nm)
400
0
1
2
3
4
5
6
500 600 700
R
e
la
ti
v
e
i
n
te
n
si
ty
Sunlight
Fluorescent bulb
Incandescent bulb
shows objects in their characteristic color and different colors to
illustrate how reflectance is used to determine an object’s color
and how we rely on that characteristic color.
Surfaces that reflect all light equally can be said to be ach-
romatic (which means “without color”) because we do not see
them as containing color. Achromatic surfaces are judged to be
white to gray to black (Figure 6.4). With such surfaces, what
matters is the proportion of ambient light they reflect. Surfaces
that reflect most of the light that hits them will be seen as white
surfaces (e.g., 90% or higher reflectance). Surfaces that reflect
some but not all light will be seen as gray (e.g., 50% reflectance),
and those that absorb most light will be seen as black (10% or
lower reflectance). An important property of our visual system
is that we respond to the percentage reflected rather than the
FIGURE 6.3 Familiar Colors
Objects with their familiar characteristic colors, and the same
objects but with odd colors. Objects get their characteristic colors
because they reflect light at particular wavelengths. Ripe bananas
absorb most light but reflect light at about 550 nm, giving them their
yellow color.
(a)
(b)
155 Chapter 6: Color Perception
total amount reflected. This allows us to see surfaces as the same
level of grayness despite changes in the total amount of light. Thus,
we still see a gray cat’s fur as gray in bright sunlight or by a dim
lamp in the evening, even though the fur is reflecting much more
total light in broad daylight. With this background, we can now
turn to perceptual features of color.
TEST YOUR KNOWLEDGE
1. How do the colors of the rainbow map onto wavelength as
measured in nanometers?
2. Describe the difference between monochromatic and
heterochromatic lights.
HUE, SATURATION, LIGHTNESS,
AND BRIGHTNESS
6.2
Diagram the perceptual principles of hue, saturation, and brightness
and the role they play in our perception of color.
The perception of color is often described by referring to three dimensions of the
color experience: hue, saturation, and brightness. It is recommended that you fol-
low along while reading this section with having ISLE 6.2 open to help you expe-
rience these dimensions. We start with hue. Hue refers to the color quality of the
light and corresponds to the color names that we use, such as orange, purple, green,
indigo, yellow, cyan, aquamarine, and so on. In fact, hue is the quality of color. A
quality is a value that changes, but it does not make the value larger or smaller.
For example, when intensity (the amount of light present) changes, it gets larger or
smaller. But when hue or color changes, it does not make sense to say, for example,
that red has more or less hue than green. This is because color is a quality, not an
amount. We see red and green as distinct units, even though some greens may seem
darker or lighter, but this corresponds to the dimension of brightness (discussed
later in this section). But certainly, red is very different from green. Many hues
have direct correspondence to particular wavelengths, such as red (650 nm) and
green (550 nm). Colors that are associated with particular wavelengths are called
monochromatic colors, which include the basic colors or spectral colors, such as
red, green, orange, yellow, and blue. There are also colors known as nonspectral,
which are made of combinations of more than one monochromatic color. These are
colors such as purple, brown, silver, and gold. Brown, for example, is a yellow or
orange spectral color with very low saturation, that is, mixed with black. Purple is
usually a mix of red and blue, though it can be combined in other ways as well.
Saturation refers to the purity of light. The more saturated the stimulus is, the stronger
the color experience will be, and the less saturated the stimulus is, the more it appears
white or gray or black, that is, achromatic. The classic example of saturation differences
concerns the continuum from red to pink. Pink is a combination of red light and white
light. The more that white light is added, the less “red” the pink is. A pastel pink may
contain just a bit of red light along with a lot of white light. Eventually, the red may be so
overwhelmed by the white that we barely notice the pink at all. A solid blue becomes less
saturated as we add more white, eventually becoming the “baby blue” we might paint a
baby’s room’s walls (Figure 6.5).
FIGURE 6.4 Achromatic Lightness
When objects reflect all light wavelengths equally, they are
said to be achromatic. The three squares depicted here do
not show any differences in the reflectivity of wavelengths.
However, the white square reflects most light that shines on it,
the gray square reflects about half of the light that shines on it,
and the black square absorbs most of the light that shines on it.
ISLE 6.2
Dimensions of Color
Hue: the color quality of
light, corresponding to the
color names we use, such as
orange, green, indigo, and
cyan; hue is the quality of
color
Quality: a value that changes
but does not make the value
larger or smaller
Saturation: the purity of light
FIGURE 6.5 Saturation
On the left side are hues with strong
saturation. We see these colors as very
strong. On the right, we see hues with less
saturation. The red becomes pink, and the
blue becomes baby blue. The figures at the
right have more white light mixed with the
red or blue light in the shape.
156 Sensation and Perception
Hue and saturation can be represented as a color circle
(Figure 6.6). Along the perimeter of the circle, we find hues,
such as red, orange, yellow, green, blue, indigo, and violet.
As we head toward the center of the circle, we get less and
less saturated colors. Thus, a deep red and a deep blue exist
on the perimeter, but pink and baby blue exist toward the
center. You can explore an interactive illustration of these
principles on ISLE 6.2.
Brightness is related to the amount of light present and
is our experience of the intensity of this light. The brighter
an object is, the easier it is to see and the more notice-
able the colors are. Brightness is the psychological dimen-
sion that goes vertically through the color circle, now a
color solid (Figure 6.7). Brightness does have a relation to
color—it is easier to see color at higher brightness values.
Brightness is distinguished here from lightness. Lightness
refers to the perceived intensity that relates to the amount
of light that gets reflected by a surface. This is a different
property than the amount of light present. Brightness usu-
ally applies to colors, whereas lightness usually refers to
the white-gray-black continuum.
TEST YOUR KNOWLEDGE
1. How is hue related to wavelength?
2. Describe the difference between brightness and intensity.
ADDITIVE AND
SUBTRACTIVE COLOR MIXING
6.3
Formulate the idea of a metamer in additive and subtractive color
mixing in terms of what we learn from color-matching experiments.
Color has an odd characteristic that is suggested by the color circle. Colors can be
mixed. That may not seem odd, but that is because you have been doing it for so
long—probably first during preschool art sessions. Usually, children in kindergarten
have a pretty good intuitive sense about how to mix paints. But it is a relatively unique
feature of color within the domain of visual perception, and the science is quite com-
plex. To understand this statement, consider the following questions: Can you try
to mix forms or motions? Can you mix size and depth? Most of our sensations and
perceptions do not mix in the ways that colors do. Isaac Newton’s classic experiments
with prisms illustrate the profundity of the idea that colors mix (Figure 6.8). You can
explore an interactive illustration of this principle on ISLE 6.3.
There are two main types of color mixing: subtractive color mixing and additive color
mixing. Additive color mixing is the creation of a new color by a process that adds one
set of wavelengths to another set of wavelengths (remember spatial summation). Additive
color mixing is what happens when lights of different wavelengths are mixed. When we add
all of the different wavelengths of sunlight, we see white light rather than many individual
colors. This is called additive because all of the wavelengths still reach our eyes. It is the
combination of different wavelengths that creates the diversity of colors. Subtractive color
FIGURE 6.6 The Color Circle
The color circle is a two-dimensional representation of how hue and
saturation interact. Hue is represented around the perimeter, whereas
saturation is represented as distance from the center (along the radius
of the circle). The most saturated hues are along the perimeter, and
saturation decreases as one moves toward the center.
Green
(550 nm)
Yellow
(600 nm)
Hue
Red
(650 nm)
Cyan
(500 nm)
Saturation
No
ns
pe
ctr
al
pu
rpl
es
Blue
(450 nm)
FIGURE 6.7
The Color Solid
The color solid is a three-dimensional
representation of the relations
between brightness, saturation, and
hue. As in the color circle, hue is
represented around the perimeter,
whereas saturation is represented
as distance from the center (along
the radius of the circle). The new
dimension, brightness, is represented
by the vertical dimension.
Hue
Saturation
Brightness
ISLE 6.3
Newton’s Prism Experiment
157 Chapter 6: Color Perception
mixing is the creation of a new color by the removal
of wavelengths from a light with a broad spectrum of
wavelengths. Subtractive color mixing occurs when we
mix paints, dyes, or pigments. When we mix paints,
both paints still absorb all of the wavelengths they did
previously, so what we are left with is only the wave-
lengths that both paints reflect. This is called subtrac-
tive mixing because when the paints mix, wavelengths
are deleted from what we see because each paint will
absorb some wavelengths that the other paint reflects,
thus leaving us with a smaller number of wavelengths
remaining afterward. The easy way to remember the dif-
ference between additive and subtractive color mixing
is that additive color mixing is what happens when we
mix lights of different colors, whereas subtractive color
mixing occurs when we mix paints or other colored
materials.
In the theater, lighting technicians use colored lights
to create additive color mixing to illuminate the stage.
When we look overhead at the lights, we may see a vari-
ety of colored lights projecting onto the stage, although
the mix of these lights may create a different color than
any present in the bank of lights overhead. Professional
painters (and preschool children) can create a larger
of palette of colors by mixing different paints, thereby
using subtractive color mixing. But if you do not know
what you are doing when mixing paints, the result very
often looks muddy and unappealing. We now look more
closely at the science of each form of color mixing.
Additive Color Mixing
(Mixing Lights)
Additive color mixing occurs when lights of different
wavelengths are mixed. This is what occurs in televisions. All of the colors one sees on a
television screen are the result of the mix of three different light sources built into the tele-
vision and controlled at different intensities. The same is true for our computer screens.
What causes us to see colors such as chartreuse on our computer screens is a carefully bal-
anced mix of three lights. When we shine equally bright green and red lights on the screen,
the lights add and we see yellow. However, if the red light is brighter than the green light,
you will most likely perceive an orange hue. This is how televisions can create so many
colors using just three dots. The principle of additive color mixing is illustrated in Figure
6.9. You can see a demonstration of additive color mixing on ISLE 6.4.
In Figure 6.9, you can see the color circle. It can be used to predict perceived colors
in additive mixtures. The center of the circle represents the point at which any additive
mixture contains equal amounts of the different wavelengths present. This center point is
perceived as a gray. If you draw a line between two colors on the circle, say yellow and
blue, the perceived color will fall on that line, depending on the relative intensities of the
two lights. When you mix three lights, the color form is a function of a triangle between
the three primary lights. Exactly what hue is perceived within that triangle is a function
of the relative intensity of the three primary lights.
In the late 19th century, artists such as Georges Seurat, Paul Signac, and Vincent van
Gogh invented a technique of painting that came to be known as pointillism (Figure 6.10).
Brightness: the perceived
intensity of the light present
Lightness: the psychological
experience of the amount of light
that gets reflected by a surface
Additive color mixing: the
creation of a new color by a
process that adds one set of
wavelengths to another set of
wavelengths
Subtractive color mixing:
color mixing in which a new
color is made by the removal
of wavelengths from a light
with a broad spectrum of
wavelengths
FIGURE 6.9 Additive Color Mixing
Predicting what color will be created when mixing monochromatic lights
involves using the color circle. If you are mixing two lights, you just draw a
straight line from one color along the perimeter to the one you are mixing
it with. The color you create will lie somewhere along that line, depending
on the brightness of each light. To predict what color will be created when
mixing three monochromatic lights, you can connect the three colors along
the perimeter to create a triangle as seen in the figure. The color created
will fall somewhere inside that triangle. Where it falls will depend on the
respective degrees of brightness of the three monochromatic lights.
Green Yellow
25% green + 25% blue
Cyan
50% cyan + 50% red
Blue Magenta
Red
80% red + 20% green
45% red + 45% green + 10% blue
No
nsp
ect
ral
pur
ple
s
ISLE 6.4
Color Mixing
FIGURE 6.8 Newton’s Prism Experiment
By Sascha G
rusche (O
w
n w
ork) [CC BY-SA
4.0 (http://creativecom
m
ons.org/licenses/by-
sa/4.0)], via W
ikim
edia Com
m
ons
158 Sensation and Perception
In pointillism, an artist uses small distinct dots of simple pri-
mary colors as the basis of a painting. From a distance, the
dots of colors blend together through a process similar to
additive color mixing to form a rich array of colors. What
makes pointillism relevant here is that it uses additive color
mixing in painting rather than subtractive color mixing, the
approach typically used in painting. The difference is that
colors are created not by mixing paints but by keeping each
dot a specific color, so that the dots blend together in a per-
son’s vision when viewed from a distance.
Subtractive Color Mixing
(Mixing Paints)
Subtractive color mixing is more common in the natural
world, as there are many more situations in which pigments
on the surfaces of objects interact than situations in which
lights interact, as outside of artificial lighting, all lighting
in nature comes from the sun and is therefore white light,
not monochromatic light. Subtractive color mixing occurs
when we mix substances with different absorption spectra.
That is, when we mix substances, the mixture will absorb
the wavelengths both substances absorb, leaving only those
wavelengths to reflect that both do not absorb. For exam-
ple, consider repainting a room in your house. Perhaps as a
young child, you wanted pink walls. Your parents may have
painted your room with a very low saturation pink. Pink, as
a low-saturation red, absorbs most wavelengths but reflects
red light more than it does other wavelengths. As paints are
likely to have a bit of spread in the wavelengths they reflect,
there is also some yellow light that may be reflected (Figure
6.11). Now you want your room to be a light shade of green.
So, when the first coat of paint is applied, you use a light
green paint on top of the existing pink. To your dismay, when
you look at the swath of color on your wall, you have a
drab yellow wall instead of a light green one. How does this
occur? Indeed, the green paint may include a little reflection
of light in the yellow zone as well. So, when the two paints
are mixed, green pigment now absorbs the red wavelengths
that were previously being reflected, and the old pink paint
absorbs the green wavelengths from the new paint. What is
left is the yellow in between. You can see a demonstration of
subtractive color mixing on ISLE 6.4b.
Color-Matching Experiments
Color mixing and matching can be quite a complex phenom-
enon. Nonetheless, understanding how we match colors is
critical to the development of theories of human color vision,
which is the focus of much of this chapter. Therefore, before
we introduce the physiology of color vision, we briefly discuss
color-matching experiments. Our contention here is that with a
M
et
ro
po
lit
an
M
us
eu
m
o
f a
rt
, o
nl
in
e
co
lle
ct
io
n
FIGURE 6.10
A Sunday Afternoon on the Island of La Grande Jatte
This famous painting by Georges Seurat (1859–1891) illustrates the
principles of pointillism. In pointillism, an artist uses small dots of color
to form bigger images. With respect to color, the dots may be of very few
primary colors, but when seen from a distance, the colors form an additive
mixture, and we see a richer array of colors.
FIGURE 6.11 Subtractive Color Mixing
When light green paint is applied to the pink wall, the green paint
continues to absorb most wavelengths other than green and, to some
extent, close-by colors such as yellow. The pink paint continues to
absorb most wavelengths other than red and, to some extent, close-by
colors such as yellow. So when the first coat of green paint is put on the
wall, the net result may be a yellow color.
159 Chapter 6: Color Perception
mix of three primary (monochromatic) col-
ors, we can re-create most any other color.
This is how televisions and computer moni-
tors can reproduce any color: by mixing red,
green, and blue lights. However, there are
other possible primary colors that can be
mixed to re-create other colors. For exam-
ple, color printers, using subtractive color
mixing, employ cyan, magenta, and yellow
to create a large array of colors. Review
ISLE 6.4, particularly noting the different
primaries used in the additive and subtrac-
tive color mixing versions of the illustration.
Many psychophysical experiments
have looked at the perceptual reality of
color matching. These experiments are
known as metameric color-matching
experiments (Silverstein & Merrifield,
1985). A metamer is a psychophysical
color match between two patches of light
that have different sets of wavelengths.
This means that a metamer consists of two
patches of light that look identical to us in
color but are made up of different phys-
ical combinations of wavelengths. For
example, a monochromatic light at 520
nm looks green. But we can create a color
that looks identical by balancing the right
amounts of light at 420, 480, and 620 nm.
In an experiment in metameric match-
ing, an observer is shown two patches
of light. One is called the test patch, and
the other is called the comparison patch.
The test patch is a single wavelength of
an unchanging illumination or brightness
(e.g., a monochromatic light at 520 nm at
a set brightness). The comparison patch is
composed of three primary colors, such
as the red, green, and blue used in a tele-
vision. The observer has control over the
intensities of the three lights in the com-
parison patch. The observer’s task is to
adjust the level of each of the three pri-
mary colors in order to make the color of
the comparison patch equal to that of the
test patch. When the observer does this to
his or her satisfaction, a metameric match
is achieved for that individual. In general, a match that satisfies one individual will also
satisfy other individuals of the most common level of color-vision abilities. That is, most
observers will see this match as identical unless they have some form of color deficiency or
the four-cone system described earlier. This type of matching is illustrated in Figure 6.12.
You can try metameric matching for yourself on ISLE 6.5.
Metamer: a psychophysical
color match between two
patches of light that have
different sets of wavelengths
Test patch
(monochromatic
light)
Test patch Comparison patch
Dials to adjust
color intensities
of three primary lights
Monochromatic
light (test color)
Comparison patch
(mixture of three
monochromatic lights)
Blue
Green
Red
FIGURE 6.12 Metameric Matching
The participant in a metameric matching study is shown a test patch of monochromatic light.
The participant has control over three primary lights in the comparison patch. He must adjust
the intensity of each of the primary lights until the mix of the three lights looks subjectively
identical to the monochromatic test patch.
160 Sensation and Perception
In Figure 6.12, you can see the test patch with a wavelength of 550 nm (light green).
The observer has control over three primary lights, with wavelengths of 440 (dark
blue), 490 (dark green), and 650 (red) nm. These three primary lights are projected onto
the comparison patch and combined through additive color mixing (they are lights, not
pigments or paints). The observer has control over the intensities of the three primary
lights making up the comparison patch and can change them until a metameric match is
made. Even though none of the comparison patch primary lights is the same as the test
patch light, we see the two patches as identical. This is the essence of metameric match-
ing and, to some extent, the basis of much of the color vision we experience, given the
amount of time modern people spend looking at computer screens, cell phone screens,
and television screens.
TEST YOUR KNOWLEDGE
1. Define a metamer, and describe how color-matching experiments contribute to
this concept.
2. Contrast additive and subtractive color mixing.
THE RETINA AND COLOR
6.4 Examine the role of having three cone classes for our perception of color.
In Chapter 3, we introduced the cone systems in the retinae of the eyes (see Table 3.2).
Cones are photoreceptors in the foveae of the retinae that are responsible for high acu-
ity and color vision. Here we explain how cones allow us to code for color and how
they transmit information about color to the occipital lobe. First, we review the func-
tion of the three cone systems and then describe how the presence of three cone types is
important in developing the trichromatic theory of color vision.
Most of us have three classes of cone photoreceptors present in the foveae of the
retinae. Each cone type has a different photopigment present and is therefore sensitive
to a different band of wavelengths. The cone that has a maximum response to light at
420 nm is known as the S-cone (because it is sensitive to short-wavelength light). It
is sometimes (and erroneously) called the blue cone because 420-nm light is perceived
as blue. Calling it the blue cone is misleading because, as we discussed with metameric
matches, all three cones are critical to perceiving all colors. The M-cone class has a
maximum response to light at 535 nm, and the L-cone class has a maximum response
to light at 565 nm. Here the M stands for medium, and the L stands for long, even
though the two peaks are surprisingly close to each other. For the M-cone, 535-nm light
is a yellowish green, and for the L-cone, 565-nm light is still to the yellow side of red.
When these cone systems are combined together, we can see color over a range of 400
to 700 nm, from the S-cone’s sensitivity to shorter wavelengths to the L-cone’s sensi-
tivity to longer wavelengths of light. This range is approximate—there have been some
studies suggesting that some people can detect very bright light at levels just below 400
nm. Nonetheless, the 400- to 700-nm range is a pretty good estimate. This is illustrated
graphically in Figure 6.13.
The S-cones are distinctive for several reasons. First, there are many more M- and
L-cones than there are S-cones. Indeed, S-cones make up only 5% of the total number of
cones. Second, S-cones are less sensitive to light overall than are M- and L-cones. This
means that they are less important in our perception of brightness, but they are still
S-cone: the cone with its peak
sensitivity to short-wavelength
light, around 420 nm (blue)
M-cone: the cone with its
peak sensitivity to medium-
wavelength light, around 535
nm (green)
L-cone: the cone with its peak
sensitivity to long-wavelength
light, around 565 nm (yellow)
ISLE 6.5
Color-Matching Experiment:
Metameric Matches
161 Chapter 6: Color Perception
very important in our perception of color,
especially when we consider their role in
opponent processes. Interestingly, M- and
L-cones are not all identical. There are
subclasses of each (Mollon, 1992). These
differences may result in subtle differences
in color perception from person to person.
To understand how the cone systems
relate to color perception, consider the fol-
lowing. A monochromatic light at 500 nm
(green) is projected onto a white piece of
paper. When the reflected light strikes the
retina, there will be a very weak response
in the S-cone, a strong response in the
M-cone, and a relatively weak response in
the L-cone (Figure 6.14). It is this pattern
of responses that induces the experience
of the color green. In metameric match-
ing, we duplicate the pattern of responses
of the three cone classes with other pri-
mary wavelengths. Thus, we can dim the lowest wavelength light and strengthen the
higher wavelength lights of three primary colors to create the same pattern of responses
of the retinal cones. If the output of the cones is the same (it does not matter if it is
caused by physically different patches of light), the two patches will look the same. You
can try this for yourself on ISLE 6.6.
We have just reviewed the finding that each cone type has a wavelength to which it
maximally responds. As we can see in Figures 6.12 and 6.13, each cone type responds
to a swath of different frequencies as well. The
M-cone, for example, responds weakly to light at
450 nm, greatly to light at 535 nm, and weakly
to light at 650 nm. If this is the case, how can
the M-cone distinguish between a very bright
light at 450 nm and a dimmer light at 535 nm?
The answer is that it cannot. If this were all the
information provided to the V1, a person could
not see in color. Any cone system, by itself, can-
not determine wavelength and therefore color.
Furthermore, consider the response of the M-cone
to a light equally intense at 500 and 630 nm.
Given that the M-cone responds equally strongly
to these wavelengths, equally intense lights at
these frequencies cannot be distinguished by the
M-cone. Thus, at least two cone types are neces-
sary for any color vision to occur.
Univariance, or Why More Than One
Receptor Is Necessary to See in Color
The principle of univariance means that any single cone system is color-blind in the
sense that different combinations of wavelength and intensity can result in the same
FIGURE 6.13 Peak Sensitivity of Cones
The sensitivities of the S-, M-, and L-cones are given as a function of their response
sensitivities to light of different wavelengths. The rod system’s sensitivity is also shown for
comparison. An object’s color is determined by the joint response of each cone in response
to that object’s reflected wavelength pattern.
420
100
50
0
N
o
rm
a
li
ze
d
a
b
so
rb
a
n
ce
400 500
Wavelength (nm)
600 700
535 565
LMS Rod
498
ISLE 6.6
Trichromatic Theory and
Cone Responses
FIGURE 6.14 The Response of Cones to a 500-nm Light
Note that each cone system responds to this light but with a weaker or stronger
response. Color is partially determined by this pattern of responses of each cone
to any particular wavelength.
R
e
la
ti
ve
s
e
n
si
ti
vi
ty
R
e
la
ti
ve
r
e
sp
o
n
se
r
a
te
Wavelength (nm)
Short Middle
Cones
Long300
0
1.0
0
1.0
LongMiddleShort
750
Univariance: the principle
whereby any single cone system
is color-blind, in the sense
that different combinations of
wavelength and intensity can
result in the same response from
the cone system
162 Sensation and Perception
response from the cone system. This implies that color vision depends critically on the
comparative inputs of the different cone systems. Indeed, we can define the problem of
univariance in the following way: The problem of univariance refers to the fact that
many different wavelength and intensity combinations can elicit the same response
from a single cone system. This means that any individual cone system cannot, by itself,
distinguish colors.
The solution to this problem is that we have three cone systems that allow us to
map any particular wavelength at any particular intensity onto a specific pattern among
responses by the three cone systems. A monochromatic light, for example, will elicit a
unique combination of outputs of the three cone systems that distinguishes it from other
monochromatic light. However, we can still “trick” a three-cone system by adjusting
the intensity of two or more lights so that they elicit the same overall response from the
cone systems. This “trick” is the metameric match created by our television monitors.
In summary, a metamer is the matching of a monochromatic color by manipulating the
intensity of three lights so that their combination of wavelengths and intensities results
in the same net output as that of the monochromatic light.
Recall the women whose retinae possess four cones, introduced at the beginning of
the chapter. The reason these women can perceive more colors than the rest of us is that
the fourth cone has a different spectral sensitivity than do the rest of the cones. Thus,
any pattern of light will elicit a more complex response by the four cones. For these
people, the intensity of four lights must be adjusted to match any particular wavelength.
This leads them to have millions more combinations of settings of their four-cone sys-
tems than do people with three-cone systems.
Finally, the problem of univariance explains why we do not see colors under night-
time lighting conditions. When we are under scotopic conditions (dim light), we use
only our rod system. Because we have one class of rods, we do not see color under these
conditions. You can see a dynamic illustration of viewing colored lights under one-cone
or rod-only vision on ISLE 6.7.
TEST YOUR KNOWLEDGE
1. Diagram the differences between the different cones that we have.
2. Why are three cones necessary to see the colors we do? What evidence is
there that some people have a four-cone system?
THE TRICHROMATIC
THEORY OF COLOR VISION
6.5
Describe the trichromatic theory of color vision and its
relationship to the three classes of cones.
Although there have been many theories of color vision throughout history, the first
modern theory was proposed by Thomas Young, the 19th-century philosopher and
scientist, and later further developed by Hermann von Helmholtz, perhaps the 19th
century’s greatest scientist (Figure 6.15). Both of these scientists advanced a theory that
is similar to what we call today the trichromatic theory (and sometimes the Young–
Helmholtz trichromatic theory). Breaking down the word trichromatic, you have tri,
which means “three,” and chromatic, which means “colored.” This theory proposes that
color vision is based on there being three elements in our visual system that respond
ISLE 6.7
Univariance and Color
Matching in Monochromat
or During Scotopic Vision
163 Chapter 6: Color Perception
differently to different wavelengths. Young and
Helmholtz did not know about cones; the theory
was instead developed to explain how we make
color matches. Now, however, it fits in squarely
with the idea of a three-cone retina. The trichro-
matic theory of color vision states that the color
of any light is determined by the output of the
three cone systems in our retinae.
We have already reviewed much of the evidence
that supports the trichromatic theory. First, col-
or-matching experiments show that it takes a mini-
mum of three primary colors to make a metameric
match to a single monochromatic light. For people
with three-cone vision, mixing two lights will not
always yield a match to a pure monochromatic
light, and four is not necessary (for nearly all peo-
ple). That it takes three lights to make a match sup-
ports the trichromatic theory and was observed by
Helmholtz, though he did not yet have a physiolog-
ical explanation. Second, there is strong evidence
for the trichromatic theory from the overwhelm-
ing data supporting the existence of three classes of cones in human retinae. Third, the
trichromatic theory predicts what happens when individuals lose one of the cone classes
in their retinae. These people—sometimes called color-blind but more accurately called
color deficient—still see in color, but they cannot distinguish between hues as three-coned
individuals can. In the classic form, most color-deficient people cannot distinguish between
reds and greens. There are now ample data showing that red–green color deficiency results
from the loss of either the M-cones or the L-cones. There is also evidence that shows that
blue–yellow color deficiency is the result of loss of the S-cones. Furthermore, a color-defi-
cient individual with only two cones requires a match of only two light sources to match
any one monochromatic light. The bottom line is that the trichromatic theory explains
extremely well the relation of cones in the retinae and our perception of color.
TEST YOUR KNOWLEDGE
1. Explain how the fact that we have three cones is related to the three primaries
of the trichromatic color system.
2. If having three cones is necessary for having three primaries, how many
primaries would be needed to match colors in a person with two cones?
THE OPPONENT-PROCESS
THEORY OF COLOR PERCEPTION
6.6
Illustrate the opponent-process theory of color vision focusing on what this
theory can explain about color vision that trichromatic theory cannot.
The traditional rival of trichromatic theory is the opponent-process theory of color per-
ception. Opponent-process theory is based on a different set of observations and has a
different underlying physiological basis. Of course, we now know that the two theories
N
ational Portrait G
allery, London
©
G
L A
rchive/A
lam
y
Trichromatic theory of color
vision: the theory that the
color of any light is determined
by the output of the three cone
systems in our retinae
FIGURE 6.15 Thomas Young (1773–1829) and Hermann von
Helmholtz (1821–1894)
Thomas Young (a) and Hermann von Helmholtz (b) developed the trichromatic
theory of vision. This theory was a precursor of the modern view of color vision, in
which the cones essentially serve as a trichromatic system.
(a) (b)
164 Sensation and Perception
are not mutually exclusive, and that both explain some
aspects of color vision. But until relatively recently,
they were considered rival theories. Certainly, when the
opponent-process theory was first developed, it chal-
lenged the Young–Helmholtz view.
The historical rival of Hermann von Helmholtz was
Ewald Hering, as discussed in Chapter 1. Helmholtz
proposed his version of trichromatic theory, and Hering
proposed the opponent-process theory of color per-
ception (Figure 6.16). We know now that each theory
explains certain aspects of color perception that the
other theory cannot account for. We have already seen
how trichromatic theory explains what the cones of
the retinae are doing. We will see shortly how oppo-
nent-process theory explains color perception, starting
in the retinal ganglion cells and continuing to the lat-
eral geniculate nucleus (LGN) and the occipital cortex.
For many years, opponent-process theory was discred-
ited, but the work of Russell De Valois on opponent
cells in the LGN led to its revival (e.g., De Valois, 1960,
1965; De Valois, Abramov, & Jacobs, 1966). But before
we discuss the physiological evidence for opponent-
process theory, we will discuss the perceptual data.
Findings That Support Opponent-Process Theory
Findings such as color-naming data and complementary color data (discussed later)
led Hering to propose that color vision was not trichromatic but was organized with
four primaries, or unique hues. These four primaries are organized in two sets of
oppositional pairs (blue–yellow and red–green). Blue and yellow are opposite to each
other, and red and green are also opposite to each other. In Hering’s view, there
were several observations that Helmholtz’s trichromatic theory could not explain.
Nonetheless, in their day, Helmholtz’s view prevailed. But we now have physiological
evidence to support opponent-process theory, in addition to Hering’s perceptual data.
Here are some of the important reasons advanced to support opponent processes in
color perception:
a. Nonprimary colors can look like combinations of two primary colors. For
example, purple looks like a combination of blue and red, and orange looks
like a mix of yellow and red. But no colors look like a mix of blue and yellow
or red and green. That is, our perception of colors supports the idea that red
and green do not combine and that blue and yellow do not combine. It is hard
to imagine what a yellowish blue might look like or what a reddish green might
look like.
b. In color-sorting experiments, people tend to sort colors into four basic groups—
green, red, yellow, and blue—rather than the three colors that might be predicted
from trichromatic theory. This finding has been observed across Western and
non-Western cultures (Rosch, 1973).
c. Color afterimages are visual images that are seen after an actual visual stimulus
has been removed. If you stare at a bright incandescent light bulb for even a
Opponent-process theory
of color perception: the
theory that color perception
arises from three opponent
mechanisms, for red–green,
blue–yellow, and black–white
Afterimages: visual images
that are seen after an actual
visual stimulus has been
removed
Complementary colors:
colors on the opposite side
of the color wheel that when
added together in equal
intensity give a white or gray
or black
FIGURE 6.16 Hering’s Model of Opponent Processes
Hering’s view was that all colors on the color circle (here the inner circle)
can be represented by two pairs of opposing colors: blue–yellow and red–
green. These opponents are represented along the outer circle.
Green
Red
BlueYellow
ISLE 6.8
Color Aftereffect
165 Chapter 6: Color Perception
short time and then close your eyes, you will continue to see
an afterimage of that light bulb for a relatively brief period
of time. But you will notice that although the light bulb has
a yellowish hue, your afterimage will appear somewhat blue.
Afterimages are strong after seeing lights, but they work for
reflected light as well. After staring at a patch of red light for
30 seconds or so, one can close one’s eyes and see a vague
patch of cyan (between green and blue, at about 485 nm).
These afterimages have led to the amusing illustrations you
can see in Figures 6.17 and 6.18. An afterimage is seen as
the complementary color, which are colors on the oppo-
site side of the color wheel. When mixed together in equal
intensity, you get a white or gray or black. Complementary
colors are not the same as an opponent color. Red and
green are opponent colors, but because
when added together you see a yellow,
not a white, they are not complements
(review ISLE 6.4a). Thus, aftereffects
lead to complementary colors, whose
existence is nonetheless a problem for
trichromatic theory. For a demonstra-
tion of afterimages, go to ISLE 6.8.
d. Simultaneous color contrast occurs
when our perception of one color is
affected by a color that surrounds it.
The effect occurs when a color is sur-
rounded by its opponent color and not
by other colors or achromatic back-
grounds. A green square will seem
more green if it is surrounded by a red
background, and a red square will seem
more red if it is surrounded by a green
background. Similarly, a blue square
will seem more blue if it is surrounded
by a yellow background, and a yellow
square will appear more yellow if it
is surrounded by a blue background
(Figure 6.19). Notice how the appearance of the central square color changes
toward the complementary color of the surrounding color. You can explore an
interactive illustration of simultaneous color contrast on ISLE 6.9.
In a series of important experiments, Hurvich and Jameson (1957) described the
phenomenon of hue cancellation, which led to a rebirth in the idea that opponent pro-
cessing does explain color vision. We turn to this experiment next.
Hue Cancellation
In this classic experiment, the husband-and-wife team of Hurvich and Jameson rein-
troduced Hering’s view on opponency. Hurvich and Jameson (1957) developed a new
way to empirically examine this view. In this experiment, participants saw a mono-
chromatic light at a wavelength between two particular primary colors. For example,
ISLE 6.9
Simultaneous Color Contrast
Simultaneous color contrast:
a phenomenon that occurs
when our perception of one
color is affected by a color that
surrounds it
Hue cancellation: an
experiment in which observers
cancel out the perception of a
particular color by adding light
of the opponent color
FIGURE 6.17 Afterimage of Vivid Pink
Rhododendron Flower and Blue Sky
FIGURE 6.18 Stare at one flag for roughly 30 seconds without moving your
eyes. Then look at a blank space on the page. You should see the correct flag as an
afterimage. Note that complementary colors of afterimages are not the same as
opponents. To get the red in each flag, you need a cyan, not a green.
FIGURE 6.19 Simultaneous Color Contrast
Opponent colors can enhance the experience of each other. Thus, a green square
surrounded by red looks more green than if surrounded by a neutral color. Similarly,
a yellow square looks more yellow when surrounded by a blue background than a
neutral background.
166 Sensation and Perception
a participant might see a cyan light with a wavelength at 485 nm.
Then the participant was given control over the amount of a second
light that could be added to the first, through additive color mixing.
The instructions were to cancel out the blue so that the light appeared
only as green. The participant could do this by adding a yellow-wave-
length light, but if she tried to do it with red light, she could never
succeed. Only yellow light could cancel out the blue light (and vice
versa). However, if you have a light between red and yellow, green must
be added to cancel out the red. You can see the procedure illustrated
in Figure 6.20. You can do a dynamic illustration of this principle on
ISLE 6.10.
We discuss one last bit of psychophysical data on opponent-process
theory before turning to the underlying physiology. Most colors can
be described in terms of combinations of other colors. Orange, for
example, feels like a mix of yellow and red. Pink feels like a mix of
red and white. However, four colors can be described only in terms
of themselves. These four colors are the four opponent colors: blue,
yellow, red, and green. In this way, these colors can be thought of as
unique colors. Interestingly, these unique colors feel basic to us, but
none of them reflects the peak sensitivity of one of our cones. Even
the S-cone’s peak wavelength sensitivity would not be described as an
iconic blue. Rather, 420 nm appears violet, as if there were a bit of red
to it. The peak sensitivity of the M-cone is a yellowish green, and the
peak sensitivity of the L-cone is an orange-yellow. Thus, these unique
colors must arise from a different level of the nervous system than the
cones in the retinae.
Opponent Cells in the LGN and V1
In Chapter 4, we discussed center-surround cells in V1. These are
cells that respond best to a spot of light in the center surrounded by
a darker circle. There are also cells that respond to darkness in the
center surrounded by an annulus of light. We discussed how such a
system was important for edge detection and discriminating shapes. A
similar system exists for color that also supports the opponent-process
view. Researchers have also found opponent cells in V1 that respond
to a particular color in the center and respond best when that center
color is surrounded by an annulus of its opponent color. We can see the first oppo-
nent cells in the retinal ganglion cells, but we focus here on opponent cells in the
LGN and in V1.
In the LGN, one finds color-sensitive cells called cone-opponent cells. These cells
respond best when they are excited by the input from one cone in the center but inhib-
ited by the input from another cone type in the surround. For example, in the LGN, one
can find cells that are excited by L-cones in the center but inhibited by M-cones in the
surround. There are also cells that are excited by S-cones in the center but inhibited by
both L- and M-cones in the surround. These cone-opponent cells are likely the building
blocks of the color-opponent system (De Valois, 2004).
In V1, we find cells that are specific not to cones but to colors themselves. The
difference is that cones are linked to wavelength responses, whereas the perception of
color is affected by adaptation and the area around them. Review color aftereffects
ISLE 6.10
Hue Cancellation
Unique colors: colors that
can be described only with a
single color term—red, green,
blue, and yellow
Cone-opponent cells:
neurons that are excited by
the input from one cone type
in the center but inhibited by
the input from another cone
type in the surround
FIGURE 6.20 Hue Cancellation
In a hue cancellation experiment, a participant
starts off with a given color (in the figure, a greenish
blue). Then the participant must add another color to
eliminate any experience of one of the colors (e.g.,
the blue). Thus, the participant must add yellow to
eliminate blue (or red to eliminate green). In these
studies, only the opponent-process theory predicts
how participants match the colors.
Start with green
(a)
Add blue to cancel yellow
Still yellowish
Just right
Add more blue
Add even more blue
Too bluish
Start with green
(b)
Add red to cancel green
Still greenish
Just right
Add more red
Add even more red
Too reddish
167 Chapter 6: Color Perception
Color-opponent cells:
neurons that are excited by
one color in the center and
inhibited by another color in
the surround, or neurons that
are inhibited by one color in
the center and excited by
another color in the surround
Double-opponent cells: cells
that have a center, which
is excited by one color and
inhibited by the other; in the
surround, the pattern is reversed
ISLE 6.11
Single- and Double-
Opponent Cells
FIGURE 6.21
Color-Opponent Cells
(a) A single-opponent cell’s receptive
field is shown. It responds best when
one color (red) is seen in the middle
and its opponent (green) surrounds it.
(b) Different types of cone-opponent
cells get inputs from different types
of cones. There is also a pathway
for lightness. It gets inputs from the
M and L wavelength cones. (c) The
center of each double-opponent cell
is excited by one color (green) and
inhibited by the opponent color (red).
In the surround, the cell is excited
by red and inhibited by green. When
we put this cell just along the edge
of a green–red barrier, it will respond
maximally, whereas when it is in an
open green or red field, the excitation
and inhibition will cancel out. Thus,
the cell along the edge will respond
robustly, whereas the cell in the open
field will not. Thus, opponent cells
serve as color-edge detectors.
and simultaneous color contrast if this distinction is not apparent. These neurons are
called color-opponent cells. Color-opponent cells are excited by one color in the center
and inhibited by its opponent color in the surround. A color-opponent cell may also be
inhibited by one color in the center and excited by its opponent color in the surround
(Figure 6.21). Color-opponent cells are red–green and blue–yellow but never, for exam-
ple, red–yellow or green–blue, consistent with Hering’s opponent-process theory. That
is, these cells work in opponent pairs. There will be a cell that responds to red in the
center and inhibits green in the surround, the presumed basis of simultaneous color
contrast. There is also a set of cells that track lightness, the difference along the gray
scale, from black to white. Figure 6.21b shows how the different types of cones connect
to these different color-opponent cells.
In V1, there is also a class of color-sensitive cells called double-opponent cells.
Double-opponent cells have a center, which is excited by one color and inhibited
by the other. In the surround, the pattern is reversed. Thus, if the center is excited by
green and inhibited by red, the surround will be excited by red and inhibited by green.
Double-opponent cells are useful for detecting color edges, that is, where one colored
object ends and a differently colored object begins, by enhancing color divisions at
the edges of objects (Johnson, Hawken, & Shapley, 2001). Think of red berries sur-
rounded by green leaves. Double-opponent cells sharpen the boundaries where the red
berries end and the green leaves begin, making it easier for the observer to home in
on some delicious raspberries. This type of information is useful to the visual system.
For a demonstration of how single-opponent and double-opponent cells work, go to
ISLE 6.11.
TEST YOUR KNOWLEDGE
1. Survey the evidence in support of opponent-process color theory.
2. What are afterimages? Why do they support opponent-process color
theory?
Panel b Source: Adapted from Karen K. DeValois and Michael A. Webster (2011), Scholarpedia, 6(4):3073. http://
www.scholarpedia.org/article/Color_vision
R+
G− S M L S
S vs LM L vs M L+M
M L S M L
Opponent Opponent Non-Opponent
− − −+ + + +
R−/G+ R−/G+
R−/G+
R+/G−R+/G−
R+/G−
Double-
opponent cell
Neutral
Worst
Neutral
Best
R−/G+
R+/G−
R−/G+
R+/G−
(a) (b)
(c)
http://www.scholarpedia.org/article/Color_vision
http://www.scholarpedia.org/article/Color_vision
168 Sensation and Perception
THE DEVELOPMENT OF COLOR PERCEPTION
6.7
Explain what we know about color vision in infancy
and how it changes as we age.
Color Perception in Infancy
Infants are born with all three types of cones already present in each eye (Xiao &
Hendrickson, 2000). But the presence of the proper receptors does not guarantee com-
plete color perception. From the discussion earlier, it is clear that it takes
more than a complete set of cones to see in full color. The cones are only
the start of the process. We briefly discuss here the processes whereby
infants develop the ability to see and distinguish colors. The first question
is how we get a nonverbal infant to report on differences in something as
subjective as color.
One way to study color perception in infancy is to use a method that
relies on habituation. As humans, we do not like repetition, and this applies
to young infants as well. When stimuli are repeated, we start to ignore a
stimulus, but more than that, we have learning mechanisms that lead us
to stop responding to a repeated stimulus. Think of a neighbor having a
car that backfires. The first time it happens, you might jump. If the car
continues to backfire over time, eventually you will stop responding. This
lack of responding to a repeated stimulus is call habituation. Infants are
like adults in this way; they also stop responding to a repeated stimulus.
When a stimulus is changed, both adults and infants will respond again,
a process known as dishabituation. So, if, after you are used to the car
backfiring, your neighbor decides to start up target practice and fires off
a rifle, you will probably jump again.
In the habituation research paradigm, a stimulus is presented repeatedly
to the infant. Usually the first time the stimulus is presented, the infant will
respond by widening her eyes and staring intently. Over time as the same
stimulus is presented, the infant will stop looking at the stimulus. At this
point, the infant has habituated. The critical part comes next. A new stim-
ulus is presented. If the infant can perceive the difference in the stimulus,
she will again look. If the difference in the stimulus is not perceived, the
infant will continue to ignore the stimuli. This can be used to determine if
color—when all other dimensions are held equal—causes dishabituation.
Bornstein, Kessen, and Weiskopf (1976) used this method to examine color per-
ception in 4-month-old infants. The researchers presented a stimulus of a particular
wavelength, say 510 nm, to the infants repeatedly, 15 times to be exact. A trichromat
would see this as green. Over time, the infants stopped responding. Then, immediately
after these trials, the infants were then presented more trials. The crucial trials are those
that had stimuli with wavelengths that were different from the original. In the condi-
tion with the 510-nm light, the new wavelengths were 480 nm and 540 nm. The two
wavelengths differed the same number of nanometers of wavelength from the 510-nm
stimulus, but perceptually that is not the case. A 540-nm light still appears green (but
with a bit of yellow in it), but the 480-nm light appears blue to adults. To restate this,
510-nm and 540-nm wavelength lights appear similar and might be called green or
greenish, but a 510-nm wavelength light and a 480-nm wavelength light appear very
different: One appears green (510 nm) and one appears blue (480 nm).
Fr
ed
B
ur
re
ll/
Sc
ie
nc
e
So
ur
ce
FIGURE 6.22
Infants Have All Three Types of Cones
Infants are born with all three types of cones. The
question is whether having these cones gives
newborns color vision.
Habituation: the learning
process in which animals
stop responding to a repeated
stimulus
Dishabituation: the process
in which, after habituation
has occurred, changing the
stimulus causes the organism
to respond again
169 Chapter 6: Color Perception
The question then becomes whether infants see these colors in the same way that
adults do. If they do, then the infants should show much stronger dishabituation to the
480-nm stimulus than to the 540-nm stimulus, and that is exactly what Bornstein and
colleagues found. In their study, they also tested the color boundaries between green to
yellow and yellow to red, and infants gave responses that suggest that they have similar
color distinctions to adults. The interesting nature of these findings, combined with
findings from other studies (Brown & Tellar, 1989), suggests that infants have more
than just operating cones; they also have opponent processes for color vision operating.
It should not be taken that infants have completely adultlike color vision at birth. In
fact, the retinae and foveae are quite immature, but the basics of color vision are pres-
ent as early as we can study, and the way their color vision operates is similar to how
adults’ color vision operates.
Aging and Color Perception
So, what happens to color vision as we age? Adults do not lose cones with normal
aging, so the basic mechanisms of color vision seem intact, but that does not mean that
color vision does not change as we age. One way that color vision changes in aging,
even in healthy aging eyes, is through changes to the transparency of the lens. As we
age, light does not pass as easily through the lens. It is not a great change, and if the
loss of transparency were the same at all wavelengths, then the change would be of
little interest. However, the lens loses transparency to short wavelengths more than
for other wavelengths, lessening our ability to see blue colors. The change is not great
in healthy eyes, but there is an increase in confusion of blues and yellows as would be
expected from opponent-process theory (Pinckers, 1980). The loss of the sensitivity to
blue is slow and usually unnoticed as we age. However, if a person develops the need for
an artificial lens, the change can be noticed because, usually, only one eye gets the lens
implant at a time. So, for a period of time, a person will have the artificial lens in one
eye, which will transmit the short wavelengths clearly, and their aging lens in the other
eye. By opening and closing each eye, the differences in seeing color can be very clear.
Granville (1990) had the procedure done and both described his experience and tested
his eye on various color-matching tests. The differences were dramatic in the blue color
range, greatly enhancing his enjoyment of a clear blue sky and even the color of a gas
jet. Granville’s experience was greater than for those who do not require implants, but
the type of changes would follow the same pattern.
TEST YOUR KNOWLEDGE
1. Describe how the process of habituation is used to determine if infants have
color vision.
2. Diagram how the loss of transparency to short wavelengths causes yellow–blue
confusions in older adults.
COLOR DEFICIENCY
6.8
Diagram the different types of color deficiency and explain why this
term is, almost always, a better term than color blindness.
Color deficiency refers to the condition of individuals who are missing one or more of
their cone systems. Color deficiency is often called color blindness, but the latter term
Color deficiency: the
condition of individuals who
are missing one or more of
their cone systems
170 Sensation and Perception
is rarely appropriate. The vast majority of color-deficient individuals do see colors,
just not as many colors as trichromatic people do. Color deficiencies are usually the
result of genetic variations that prevent the development of one or more cone systems.
Thus, in general, color deficiencies are present at birth and seldom develop later in life.
Interestingly, because of the nature of those genetic issues, color deficiencies are much
more common in men than they are in women.
The genetic information for forming cones in fetal development travels on the
X chromosome in a region of that chromosome disproportionately likely to have a
variation (Woods & Krantz, 2001). These genetic variations are of different types, and
it is the type of genetic information present that determines the type of color deficiency.
It is important to remember that males have only one X chromosome and females have
two. Because the genes that lead to color deficiency are on the X chromosome, males
need only one of these color-deficient genes to be color deficient, but females need two
of these genes, one on each chromosome, to be color deficient. As a result, males are far
more likely than females to have a color deficiency. Such types of traits are known as
sex-linked traits. Other sex-linked traits include male pattern baldness and hemophilia,
both much more common among men than women.
Color deficiency is quite common in humans. Usually, in a college class of 100 stu-
dents or so, there is at least 1 young man who admits to being color deficient. Indeed, it
is estimated to occur in as many as 8% of males and 0.4% of females (Birch, 2001). The
most common diagnosed form is red–green color deficiency. These individuals see colors
in a general spread from dark blues to light blues to dim yellows to bright yellows. The
frequencies three-cone people see as green and red are just part of the blue-to-yellow con-
tinuum for individuals with this form of color deficiency. However, there are really two
separable types of red–green color deficiency, one caused by the loss of the M-cone system
and one caused by the loss of the L-cone system. In the past, a simple way to identify color
deficiency was to show potential patients Ishihara plates
(Figure 6.23). In these plates, trichromatic people can see
the numbers created by the dots because they are different
colors than the surrounding dots. The dots, however, are
isoluminant dots; that is, they reflect light at the same
intensity, even though the wavelengths are different for
the dots that make up the number and the background.
Because of this, trichromatic people will see the number,
because they can detect the color differences. But a red–
green color-deficient individual will see only dots and not
be able to tell them apart because of intensity differences.
Because the dots are isoluminant and chosen to be meta-
mers for color-deficient individuals, a red–green color-de-
ficient person cannot see the number in an Ishihara plate.
Thus, these plates allow for easy identification of color
deficiency. Another way of identifying color-deficient
individuals is to have them do metameric matching tasks.
Their matches will be very different from those of people
with three-cone vision. You can try some different tests
for color deficiency in ISLE 6.12. It is important to note
that because these tests are run under a monitor and not
the conditions called for in the test, their results are only
approximate.
To best be able to understand the different types
of color deficiencies, we start by reminding you about
trichromatic color vision and then how the different
ISLE 6.12
Color Deficiency Tests
©
P
RI
SM
A
A
RC
H
IV
O
/A
la
m
y
FIGURE 6.23 An Ishihara Plate
These figures are used as a quick test for color deficiencies. The dots are
all isoluminant, regardless of color, so the number cannot be determined
by differences in brightness. Only color allows you to see the number. For
the plate shown, a red–green color-deficient individual would not be able
to see the number.
171 Chapter 6: Color Perception
color deficiencies differ from it. People with trichromatic color vision have three func-
tioning cone systems. Such a trichromatic person could match any pure wavelength by
varying the intensity of three colors, such as red, green, and blue. Across trichromatic
people, these matches will be nearly identical. Then there are color-deficient people,
who come in a number of varieties.
Rod Monochromacy
Rod monochromacy is a very rare form of color deficiency, affecting only 1 in every
30,000 people (Carroll, Neitz, Hofer, Neitz, & Williams, 2004). Rod monochromats
have no functioning cones of any kind and therefore can be described as truly color-
blind. As a result, they see the world in shades of gray—high-reflectance objects are
white, low-reflectance objects are black, and intermediate-reflectance objects are vari-
ous shades of gray. In metamer matching, only one color is required to match another,
as all a rod monochromat will be doing is adjusting the percentage of reflected light,
that is, how gray the surface is.
Because they have no cones, rod monochromats have many other visual problems
in addition to color blindness. Rod monochromats are dependent on their rod vision in
both bright and dim light. This has serious disadvantages during daylight conditions, as
these individuals are highly sensitive to light but have poor visual acuity. Because they
are using scotopic vision all the time, rod monochromats are extremely sensitive to bright
lights. For example, in a room that would be considered normally illuminated for people
with intact cone systems, a rod monochromat will find it too bright. As such, rod mono-
chromats often must wear sunglasses indoors. Going outside on a bright sunny day can
be overwhelming and requires very strong eye protection. In reality, most rod monochro-
mats will avoid bright outdoor conditions even with very strong sunglasses. Moreover,
because the rods do not support acuity, rod monochromats have very poor visual acuity
and must wear very strong lenses in order to read. Even then, most rod monochromats
require large typefaces in order to read normally. To summarize, unlike those with color
deficiencies, rod monochromats are at a serious disadvantage relative to people who have
cones as receptors as well as rods (you can see the world as a rod monochromat might on
ISLE 6.13). You can read about the experience of people with this disorder in a book, The
Island of the Colorblind, written by famed neurologist Oliver Sacks (1998), who visited
a Pacific Ocean island where this disorder is relatively common.
Cone Monochromacy
There are extremely rare cases of individuals known as cone monochromats. These
people lack two cone types but have one present. S-cone monochromats have been
found; they have the S-cone system but lack the M- and L-cone systems (Alpern, Lee,
Maaseidvaag, & Miller, 1971). S-cone monochromacy is an X-chromosome-linked trait
and thus is more common in men than women, though it has been observed in women.
However, S-cone monochromacy is still extremely rare in men, as only 1 in 100,000
men will exhibit it. Because of the low overall sensitivity of the S-cone system, cone
monochromats exhibit many of the symptoms seen in rod monochromats, although
the symptoms tend to be less severe in S-cone monochromats than in rod monochro-
mats. Cone monochromats also have poor acuity and high sensitivity to bright light.
Wavelength discrimination is poor in S-cone monochromats, and subjectively, the world
appears in blacks, whites, and grays. One of the authors (JHK) took his sensation and
perception class years ago with a fellow student who had this type of color deficiency.
Despite taking the class in the evening and night (6 pm to 9 pm once a week), the fellow
student wore sunglasses and the lights were kept as low in the room as the class could
ISLE 6.13
Rod Monochromat Vision
172 Sensation and Perception
tolerate. As night came on, the student became more comfort-
able and sometimes took her sunglasses off. Interestingly, in
twilight conditions, in which both the rod and the cone sys-
tems are at work, S-cone monochromats can distinguish some
colors, essentially using the one cone system and the one rod
system as might a dichromat.
Dichromacy
Dichromats have only two working cone systems. Thus, they
can see colors, though a much lesser range of colors than
do trichromats. There are three major forms of dichromacy
depending on which cone is absent: protanopia, deuterano-
pia, and tritanopia (Table 6.1). Dichromats require only two
colored lights to match any monochromatic light, compared
with trichromatic individuals, who require three. Dichromats
see in color, but they cannot make some of the discriminations
that are easy for trichromats. Protanopia and deuteranopia
are linked to the X chromosome and are therefore inheritable
and more common in men than women. Protanopia and deuteranopia are also more
common than tritanopia.
Because men have only one X chromosome (and one Y chromosome), if they have
a deficiency gene on the X chromosome, they will express the deficiency. However,
women have two X chromosomes. The same deficiency gene must be present on both X
chromosomes for a woman to be a protanope or a deuteranope. If a woman has only
one color-deficient X chromosome, she will see colors as a trichromat, as the single
trichromatic X chromosome is enough to structure her retinae correctly. However, she
is still a carrier, and thus there is a 50% chance that she will pass that gene on to an
offspring. A son inheriting the carrier X chromosome would be color deficient, and a
daughter would have a 50% chance of being a carrier. Thus, the only way a woman can
be color deficient is if she has a color-deficient father and either a color-deficient mother
or a mother who is a carrier.
Protanopia
Protanopes lack L-cones in their retinae, as a function of a deficient gene. Protanopia
can occur in as many as 1% of males but is very rare in females, roughly 0.02%.
Because protanopes do not have L-cones, they are classified as red–green color-blind
(the common name for the condition). An approximation of what they see as a function
of wavelength is depicted in Figure 6.24a. At short wavelengths, protanopes see blue.
As wavelength increases, the blue becomes less saturated until it eventually becomes
gray (at 492 nm), and then as the wavelengths continue to increase, the color is per-
ceived as a more and more saturated yellow. The yellow fades at the high end of the
visual spectrum (Figure 6.25). This 492-nm light is called the crossover wavelength for
protanopes.
Deuteranopia
Deuteranopes lack M-cones in their retinae, as a function of a deficient gene.
Deuteranopia has about the same frequency as protanopia, and in many contexts, they
are indistinguishable and are both referred to as red–green color blindness. However,
Protanopia: a lack of
L-cones, leading to red–green
deficiency; this trait is sex-
linked and thus more common
in men
Deuteranopia: a lack of
M-cones, leading to red–
green deficiency; this trait
is sex-linked and thus more
common in men
Tritanopia: a lack of S-cones,
leading to blue–yellow color
deficiency; this trait is rare
and is not sex-linked
Anomalous trichromacy: a
condition in which all three
cone systems are intact, but
one or more has an altered
absorption pattern, leading to
different metameric matches
than in the most common type
of trichromatic individuals
TABLE 6.1
A Description of Different Types of Color Vision
Type of Color
Deficiency
Cone System
Absent
Color
Experience
Rod
monochromacy
All No color
Tritanopia S Lack green and
yellow
Deuteranopia M Lack green and
red
Protanopia L Lack green and
red
Anomalous
trichromacy
All present, but
one is different
from standard
Near standard
color vision
Common
trichromacy
None Standard color
experience
173 Chapter 6: Color Perception
FIGURE 6.24 The World as It Looks to Color-Deficient Individuals
This is how these colored displays look to (a) protanopes, (b) deuteranopes, and (c) tritanopes.
FIGURE 6.25 The Visual Spectrum as It Appears to Color-
Deficient Individuals
400
492
700
400 700
400 700
400 500 600 700
Protanope
Deuteranope
Tritanope
498
570
the crossover wavelength from blue to yellow occurs at a different wavelength (498
nm). For an approximation of how deuteranopes perceive color, inspect Figure 6.24b.
Tritanopia
Tritanopes lack S-cones in their retinae. This is the
rarest form of dichromat color deficiency, occurring
in just about 1 in 100,000 people. Because this defi-
ciency is not sex-linked, it is just about as common
among women as it is among men. Tritanopes see
blue at short wavelengths, which becomes less sat-
urated as the wavelength increases. At higher wave-
lengths, tritanopes see red. The crossover point for
tritanopes is 570 nm. For an approximation of how
tritanopes perceive color, inspect Figure 6.24c. You
can explore a set of interactive illustrations of dichro-
macy on ISLE 6.14. You can examine the cones
missing and how that impacts color matching in dif-
ferent types of dichromacy, and you can simulate the
appearance of images for dichromats. You can try
your own photographs in the ISLE demonstration.
There is also a form of color deficiency called
anomalous trichromacy. In anomalous trichro-
mats, all three cone systems are intact, but one or
more of the cone systems has an altered absorp-
tion pattern, leading to different metameric
matches than in the most common form of cones
in trichromatic individuals. The most common
form of anomalous trichromacy is an abnormality
in the M-cone system (Smith & Pokorny, 2003).
However, it can also occur with the L- or the
S-cone system. In general, anomalous trichromats
ISLE 6.14
Dichromacy
(a) (b) (c)
174 Sensation and Perception
are not as good at discriminating similar wavelengths as the more com-
mon type of trichromats. You can see the different forms of anomalous
trichromacy and their incidence in Table 6.2.
A question that may have occurred to you is how we can be sure of
the colors dichromats and anomalous trichromats are seeing. After all,
because they have missing or abnormal cone systems, their perception of
color may not be imaginable by people with trichromatic color vision. If
this were the case, the perceptual spectra in Figures 6.24 and 6.25 would
not be accurate. In other words, when looking at the sky, a deuteranope
may know to say “blue” as trichromatic individuals do, but is the col-
or-deficient person really seeing the same color?
The answer to this question comes from a small class of color-
deficient persons known as unilateral dichromats. A person with unilateral dichromacy
has dichromacy in one eye but trichromatic vision in the other. This is an extremely rare
condition. However, the existence of unilateral dichromacy allows researchers to discover
the nature of the experience of dichromacy. A unilateral dichromat can observe a colored
figure with one eye at a time and describe the color both as a person with trichromatic
color vision would and as a person with dichromacy would (Alpern, Kitahara, & Krantz,
1983; Graham & Hsia, 1958). When viewing objects with both eyes, they see color essen-
tially as a trichromat would, but when they close their trichromatic eye, they become
dichromats. Thus, such a person would describe a 520-nm light as green with her trichro-
matic eye but as yellow with her dichromatic eye. When she reopens her trichromatic eye,
she again sees it as a fully trichromatic person would. It is based on the experiences of
these unilateral dichromats that we know the color experience of dichromats.
As we discussed at the beginning of the chapter, some women seemingly have four-
cone systems. Interestingly, these women are usually related to men with anomalous
trichromacy, so one theory that accounts for the existence of this condition is that the
same mutation that results in anomalous trichromacy in men can occasionally result
in tetrachromacy in women (Jordan et al., 2010). According to this research, roughly
10% of women may carry the gene for anomalous trichromacy. But in Jordan et al.’s
(2010) study, only 1 in 24 women with this gene showed any evidence of being a tetra-
chromat. Such women require four separate colors to match a monochromatic light and
presumably see countless shades of color that trichromatic individuals do not (Jameson
et al., 2001). To tetrachromats, all of us trichromatic individuals are effectively color
deficient. Tetrachromacy is extraordinarily rare, but it has been documented.
Cortical Achromatopsia
In cortical achromatopsia, loss of color vision occurs because of damage to the occip-
ital lobe. Cortical achromatopsia is extremely rare and is much less common than the
color deficiencies caused by cone problems in the retinae. Cortical achromatopsia usually
comes about from damage to area V4 (also involved in shape perception, as discussed in
Chapter 5). Cortical achromatopsia usually involves a perceptual experience of seeing
only in black and white (and shades of gray) or the impression that colors seem washed
out. In some cases, the perception is of shades of gray, but patients can still discriminate
by wavelength even though they do not experience the colors. These patients still have
all their cone systems intact, and the problem is at a higher level of processing. This may
be why they can discriminate wavelengths but still not see colors. In addition, in some
cases, patients with achromatopsia lose the ability to remember color. That is, they do
not remember what it was like to experience color. In contrast, a person who becomes
blind because of eye damage still remembers his or her experience of color. In some cases,
patients with cortical achromatopsia can no longer put color into mental images and may
fail to be able to remember objects by their colors. Thus, a banana is no longer yellow in
TABLE 6.2 Percentages of Different
Anomalous Color Deficiencies
Type of
Anomalous
Trichromacy
Males Females
Protanomalous
(L-different)
1% 0.02%
Deuteranomalous
(M-different)
5% 0.04%
Tritanomalous
(S-different)
0.005% 0.01%
Unilateral dichromacy: the
presence of dichromacy in
one eye but trichromatic vision
in the other
Cortical achromatopsia: loss
of color vision due to damage
to the occipital lobe
175 Chapter 6: Color Perception
memory, nor is a ripe tomato red. Even in memory, these objects lose their colors. Finally,
in some cases, individuals may not even be aware that color vision has been lost (von Arx,
Müri, Heinemann, Hess, & Nyffeler, 2010). Again, all of this symptomatology has been
linked to damage in V4 (Wade, Augath, Logothetis, & Wandell, 2008).
TEST YOUR KNOWLEDGE
1. Diagram the different types of color deficiencies.
2. What is the difference between a rod monochromat and a cone monochromat?
What differences are there in their vision?
CONSTANCY: LIGHTNESS
AND COLOR CONSTANCY
6.9 Assess the term constancy and how it applies to color vision.
Constancy refers to our ability to perceive an object as the same
object under different lighting and environmental conditions. For
example, we want our visual system to recognize a barracuda
whether it is swimming directly toward us or away from us, in
murky water or clear water, at an angle or coming straight at us.
The image on the retinae may be quite different in each of these
cases, but we still need to recognize the same object. This is a vital
goal of the visual system. We want to be able to tell if an object is
the same object across changes in lighting, shading, distance, move-
ment, and orientation. For another example, we want to be able to
detect a banana as being a banana whether we are seeing it close up
or from far away. We want to be able to judge if the banana is ripe
regardless of whether we are viewing the fruit in broad daylight, by
the light of a light bulb, or even by twilight. For this reason, we have
evolved many processes that enact constancy in different domains
of perception. Lightness constancy refers to our ability to perceive
the relative reflectance of objects despite changes in illumination.
Color constancy refers to our ability to perceive the color of an
object despite changes in the amount and nature of illumination.
Before we delve into the science of color constancy and then
lightness constancy in depth, consider Figure 6.26. We see a pleasant
garden scene. Look at the grass. We see a light green field of grass
with a few scattered small white flowers. In the background, some pretty yellow flowers
adorn a bush. Across the foreground, a tree, which is not visible in the photograph, casts a
shadow over the grass. The core idea of constancy is that we see the grass as green, and the
same green, despite the changes in illumination caused by the shade. We perceive correctly
that there is a shadow present and infer that there is differential illumination on the grass, but
the grass’s color does not change as a function of illumination. This is an illustration of color
constancy, the fact that we see an object as the same color across changes in illumination.
Color Constancy
We consider color constancy first. Color constancy refers to the observation that we
see the same color despite changes in the composition of the wavelengths of light that
Constancy: the ability
to perceive an object as
the same under different
conditions
Lightness constancy: the
ability to perceive the relative
reflectance of objects despite
changes in illumination
Color constancy: the ability
to perceive the color of an
object despite changes in
the amount and nature of
illumination
FIGURE 6.26 Color Constancy
We want to be able to recognize the grass here as one
continuous object of one continuous color, even though some
of the grass is shaded by trees and therefore reflects less light
back to the viewer. That we see the grass as one color despite
the differences of illumination is an example of constancy.
176 Sensation and Perception
is striking that object. Thus, a green mug appears to be the same color regardless of
whether the light illuminating it is natural sunlight, a fluorescent light bulb, or an
incandescent light bulb. This is true even though the object is now reflecting different
absolute amounts of light at different wavelengths under each illumination condition.
Color constancy serves an important perceptual function. The properties of objects
seldom change as a function of changes in the source of illumination. Thus, a system
that sees an object as a constant color across such changes leads to accurate perception.
Interestingly, the distribution of wavelengths in sunlight changes across the day. Evening
light has more long-wavelength light than light earlier in the day. Although we might
enjoy the colors of twilight, we do not normally see objects as changing colors, though
we are aware of general changes in illumination when we attend to them. We can see
this in Figure 6.27. The statues of the presidents appear to be the same color despite
the change from peak sunlight to twilight. You can explore an interactive illustration of
these principles on ISLE 6.15.
Color constancy is not perfect. There are a number of situations in which color con-
stancy fails; that is, we see the same object as being differently colored under different
lighting conditions. One such situation is when we use a monochromatic light. Shining
a monochromatic light on an object and not the area around the object will allow that
object to reflect only that wavelength. Thus, depending on how much of that wave-
length is reflected by the object, the object will appear the color of the light regardless
of its reflectance characteristics. What we will see is a different level of saturation,
depending on how much the object reflects the wavelength being shined on it. Another
situation occurs when an object is viewed in front of a pure black background. This
makes it difficult for the visual system to get the context to see the object as the right
color. Simultaneous color contrast illustrates another way we can fool color constancy
(see Figure 6.19 and ISLE 6.9).
The mechanism whereby our visual systems control color constancy is not well
understood. Seemingly, the visual system is able to compare the reflectance patterns
of different wavelengths from one object with those from another to determine which
object is reflecting more blue, yellow, and so on. However, because the visual system
cannot intrinsically measure the wavelength distributions in the illuminant light, it must
infer this as well (Foster, 2011). Data support the idea that the visual system automati-
cally determines the ratio of wavelengths in a scene by comparing across many objects
in that scene. That is, the color of an object is determined not just by the wavelengths
©
iS
to
ck
ph
ot
o.
co
m
/S
un
Ch
an
©
iS
to
ck
ph
ot
o.
co
m
/j
ov
an
ni
g
ISLE 6.15
Illumination and Color Constancy
FIGURE 6.27 Color Constancy on Mount Rushmore
We see the monument as being the same color despite the change in illumination from day to night.
(a) (b)
177 Chapter 6: Color Perception
coming off of that object but also by the wavelengths of the light coming
from neighboring objects.
One of the classic demonstrations of color constancy has been called
Mondrian experiments by Edwin Land (1977), after the Dutch painter
Piet Mondrian (Figure 6.28). In these experiments, a surface with a ran-
dom collection of rectangles of different sizes and colors of matte paper
(much like Mondrian’s paintings) is presented to participants. Each rect-
angle is surrounded by rectangles of different colors. The illumination
of the surface is provided by three projectors, each of which projects a
different narrow band of wavelengths. One projector emits long wave-
lengths, the second emits middle wavelengths, and the third emits short
wavelengths. When all give light with the same level of illumination,
these three projectors are a match for white light.
The method for these experiments is complicated. First, a partici-
pant is asked to look at one square, say a red one. Once the participant
is focused on the red square, the experimenter changes the illumination
by adjusting the three projectors so that the light coming from the red
square reflects twice as much middle-wavelength light as long-wave-
length light. The question for the participant is what is the color now
for this red square? The square itself reflects more long-wavelength
light than others (hence its red color). But now, it is being differentially
illuminated by more light shorter in wavelength. After the adjustment
of the projectors, the reverse is true; it is reflecting more middle-wave-
length light than long-wavelength light. Still, participants say that the
rectangle they have been focused on the whole time looks red. Within
wide ranges of the bands of illumination, the wavelength coming from
the square does not change its color appearance. Once red, always
red. And of course, the same is true for squares of other colors on
the Mondrian image as well. This is important because the other
squares have changed their reflectance as a function of the incoming
lights. The fact that each square is surrounded by squares of differ-
ent colors is important to the outcome of this experiment. Thus, the
comparison of each area with the varied colors around it is critical to
maintaining color constancy. This supports the idea that color constancy is achieved
by an implicit comparison across different objects in a scene, each object reflecting
a different wavelength, allowing the visual system to extract the illumination from
known reflective properties.
Lightness Constancy
Lightness constancy refers to our ability to perceive the relative reflectance of objects
despite changes in illumination. The easiest way to think of lightness constancy is to
think of it along the continuum from black to gray to white. These achromatic colors
simply refer to the amount of white light an object reflects. A black object absorbs most
light, whereas a white object reflects most light, with gray objects being in between.
Lightness constancy refers to the observation that we continue to see an object in terms
of the proportion of light it reflects rather than the total amount of light it reflects. That
is, a gray object will be seen as gray across wide changes in illumination. A white object
remains white in a dim room, while a black object remains black in a well-lit room.
In this sense, lightness constancy serves a similar function as color constancy in that it
allows us to see properties of objects as being the same under different conditions of
lighting (Adelson, 1993).
©
iStockphoto.com
/hohl
FIGURE 6.28 Building Painted in the
Style of Piet Mondrian (1872–1944)
This building painted in the style of Mondrian shows a
pattern of color. Stimuli such as this have been used for
experiments on color constancy. In the experiments,
the wavelengths of the light illuminating the stimuli are
altered. As long as viewers can see all the different
boxes of color, they maintain color constancy. But if
they only see one square, its color will change as a
function of illumination.
178 Sensation and Perception
Consider an object that reflects 25% of the light that hits its surface.
This object will be seen as a rather dark gray (Figure 6.29). If we leave it in
a dim room that receives only 100 units of light, it will reflect 25 units of
light. However, if we place it a room that is better lit, it will still reflect the
same 25%. If there are now 1,000 units of light, it will reflect 250 units of
light. But we still see it as the same gray, despite the fact that the object is
reflecting much more light. Similarly, an object that reflects 75% of ambi-
ent light will be seen as a light gray in the dim room, even though it reflects
less total light than it does in the bright room. Thus, lightness constancy
is the principle that we respond to the proportion of light reflected by an
object rather than the total light reflected by an object. You can explore an
interactive illustration of these principles on ISLE 6.16.
As with all constancies, there are conditions that create illusions that
overwhelm the processes that create constancy. The Gelb effect is an
exception to the principle of lightness constancy. The Gelb effect is a
phenomenon whereby an intensely lit black object appears to be gray
or white in a homogeneously dark space. Think of a cat caught in the
headlights of a car at night. The headlights illuminate only a small space
in front of the car, dark pavement in addition to the cat. Because there is
nothing to compare the object to, the cat appears white, because it is reflecting a lot of light
in an otherwise dark space. However, if we suddenly place a white object next to the cat,
the cat now appears black, its actual color, as our visual systems now have something with
which to compare it. For an illustration of the Gelb effect and related illusions, go to ISLE
6.17. The Gelb effect neatly shows the importance of the ratio principle in explaining light-
ness constancy (Gilchrist et al., 1999).
The ratio principle states that the perceived lightness of an object is explained by
the ratio of light it reflects rather than the absolute amount of light it reflects, assuming
even illumination across the visual scene. As long as illumination is constant across
the field of view, the ratio captures the properties of reflectance. In an illusion such
as the Gelb effect, the constant illumination requirement is violated—the cat is more
illuminated than its surroundings, and lightness constancy is compromised. Of course,
situations such as the Gelb effect are rare in the real world, and for the most part, the
ratio principle allows us to correctly interpret the lightness of objects.
TEST YOUR KNOWLEDGE
1. Why is it important to have color constancy in the real world? What function
does it serve?
2. What is the difference between color constancy and lightness constancy?
ISLE 6.16
Lightness Constancy
ISLE 6.17
Gelb Effect
Gelb effect: a phenomenon
whereby an intensely lit black
object appears to be gray or
white in a homogeneously
dark space
©
E
dw
ar
d
H
. A
de
ls
on
FIGURE 6.29 Lightness Constancy
In this illustration, we see a checkerboard being shaded
by a peculiar cylinder. Because we infer that there is less
illumination on the shaded part of the checkerboard, we
see square A as being the same shade as square B, even
though objectively B is a darker gray than A.
EXPLORATION: The Color Purple
Purple has, in the West, long been associated with royalty
and religiosity. Perhaps because of its rarity in nature and
the difficulty in generating purple dyes, purple has always
been a regal and expensive color. We find this from our
earliest recorded records to recent history. In the Hebrew
Bible, God tells Moses that the Israelites should bring
Him offerings of purple cloth. In both ancient Greece and
Rome, purple was the color worn by kings and royalty, a
tradition that continued in Europe through the centuries.
Roman Catholic bishops wear purple to this day. This
regard for purple is also seen in other cultures—purple
is a symbol of royalty in Japan and of piety in China.
179 Chapter 6: Color Perception
Even today, purple dyes made from murex snails can cost
hundreds of dollars. Because purple pigments are also rare
in nature, we value plants and flowers that are purple as
well. Purple flowers are a staple of gardens everywhere
(Figure 6.30).
Following Livingstone (2002), we make a distinction
between violet and purple. In practice, these colors are
very similar perceptually, but technically, they refer to
different kinds of color. Violet is a spectral color that we
see at the very shortest wavelengths of the visual spec-
trum, shorter even than blue. We see violet from 400 to
about 440 nm, at which point, wavelengths become blue.
Purple, by contrast, is a nonspectral color that cannot be
generated by a single wavelength of light. Purple is a mix
of red light and blue light. Most dyes and pigments are
purple, reflecting both red and blue light, rather than vio-
let (Figure 6.31). We now describe why these colors look
similar (see Monnier, 2008).
At 440 nm and under (i.e., until about 400 nm, below
which we cannot see), colors look blue but also a little
red. That is why these colors are called violet. Although
they are spectral colors, they look like a mix of red and
blue. There is a clear physiological explanation for this
phenomenon. At 440 nm, our S-cones are nearly at their
peak. However, the L-cone system is also active. Although
these cones are sensitive mainly to long-wavelength light,
they have this minor peak for short-wavelength light.
Thus, these very short wavelengths activate both blue
and red responses in our cones, resulting in the percep-
tion of violet.
Purple is a nonspectral color that results from the combi-
nation of red and blue light. A more bluish purple may be
metameric to violet, but purple is a mixed color, not a spec-
tral color. Thus, purple objects need to have an odd pattern
of reflectance. To be purple, an object must absorb light in
the central or green part of the visual spectrum but reflect
light in the red and blue portions at the ends of the visual
spectrum. This particular arrangement—absorbing wave-
lengths in the middle of the spectrum but not at the end-
points—is particularly difficult for chemical compounds to
achieve. Hence, the rarity of purple in nature. You can see
that for purple plants, the surface reflects the long and short
wavelengths but absorbs the middle ones. Because purple is
rare in nature, it also makes it more difficult for people to
generate purple dyes, which, in the past, led to high prices
for purple dyes and paints. Long live purple!
©
iStockphoto.com
/O
G
photo
FIGURE 6.30 Purple Flowers
Purple flowers are especially valued by gardeners everywhere.
FIGURE 6.31 How to Make Purple
To be purple, an object must absorb light in the central or green part of the visual spectrum but reflect light in the red and blue portions at the ends of
the visual spectrum.
Source: From Livingstone, 2002, p. 31.
700650600550
Wavelength (nm)
African violet
African violet
Purple cabbage
R
e
la
ti
v
e
r
e
e
ct
a
n
ce
500450400
0
0.5
1
700650600550
Wavelength (nm)
Ultramarine Blue
Cobalt violet
Ultramarine
violetR
e
la
ti
v
e
r
e
�
e
ct
a
n
ce
500450400
0
0.5
1
180 Sensation and Perception
APPLICATION: Color Deficiency
and Our Colorful Information
A major technological innovation that was first proposed
in 1931 has changed our world, even if it does not get
the attention that other innovations have. In that year,
an international organization, the Commission inter-
nationale de l’éclairage (International Commission on
Illumination), thankfully, CIE for short, proposed a set
of equations to allow for automatic color reproduction
(Silverstein & Merrifield, 1985). In some ways, color
reproduction has been going on since ancient times, but
before this innovation, to reproduce a color in nature
required a human eye, an artist. With this set of equa-
tions, it was possible to start specifying primary values,
like the red, green, and blue elements on a television
screen, to make a metamer for another color. It no longer
required a person but could be done automatically by
a machine. It was not long after this time that movies
started being produced in color, for example, Gone With
the Wind, Fantasia, and The Wizard of Oz, which came
out by the end of the 1930s, and these films depended on
these equations. To color a movie before this innovation,
artists would have to hand paint each and every frame
of a movie, which did occur, but very rarely. With time,
we got color printing, color television, and all the other
ways that color is part of our lives now. But this advance
has come at a cost. The CIE equations work for trichro-
mats but not dichromats or other people with color
deficiencies. Let us take a look as some of the difficulties
raised for dichromats.
Conventionally, stoplights all around the world use red
for stop and green for go. How do deuteranopes and pro-
tanopes, who are “red–green color-blind,” know to stop
at a traffic signal or drive through, if they cannot discrim-
inate between red and green? This is more of a practical
question than one related to the nature of their visual
experience. In the past, traffic signals were a significant
problem for color-deficient drivers. However, they are no
longer a major problem because it is now standard to
put the red light at the top of the series of lights (three if
there is a yellow light) and the green light at the bottom.
In addition, they use a red and green that will appear
different lightnesses to dichromats as well (Proctor &
Van Zandt, 2008). So, color-deficient individuals can stop
and go by attending to vertical position rather than color.
Those of us with trichromacy do not pay attention to this
feature, but color-deficient people learn it quickly and
use it to respond to traffic signals. Although this posi-
tioning helps, many dichromats still report some trouble
with traffic lights, and some authors argue that automo-
bile drivers should meet some level of color vision ability
before being allowed to drive (Cole, 2016). This argu-
ment would add driving to those jobs that require a cer-
tain level and type of color vision present to be able to
be hired, such as pilots and railroad engineers. In both
of these cases, although trichromatic color vision is not
required, at least anymore, the applicant must be able to
discriminate between certain colors easily. For example,
railroad engineers must be able to discriminate red, green,
and yellow—a requirement that rules out most prota-
nopes and deuteranopes.
The news is not all bad for dichromats, though. In fact,
it is surprising there are so many of them given all of the
difficulties we have outlined in this chapter. Perhaps they
have some sort of advantage that helps them evolutionarily.
Morgan, Adam, and Mollon (1992) discovered that dichro-
mats can see through some forms of color camouflage
that completely mask objects to color trichromats. There
had been anecdotes since World War II about color-defi-
cient people seeing objects hidden by camouflage, but this
study was the first to demonstrate this ability in the lab.
Participants had to locate a square of horizontal rectan-
gles in a field of vertical rectangles. If the dots are all one
Ro
be
rt
B
ro
ok
/S
ci
en
ce
S
ou
rc
e
FIGURE 6.32
Color Deficiency and Our Colorful Information
View through a car windscreen by someone with color blindness, in
particular, deuteranopia or protanopia.
181 Chapter 6: Color Perception
color (Figure 6.33a), the square is easy to find for all of us.
When the figure is camouflaged with a random array of red
and green dots (Figure 6.33b), trichromats perform prac-
tically at chance, whereas dichromats still perform quite
well. You can try a version of this experiment in ISLE 6.18.
You might be asking why this works. Remember the CIE
equations. It works for trichromats and is used to develop
the camouflage. If your color vision is not trichromatic,
the metamers that are being developed for the camouflage
do not work for you. You might recall from your biology
classes that camouflage coloring occurs not just in human
warfare but also in nature as well. It could be the ability
to see through this natural camouflage is an advantage
for dichromats. No, not an
advantage that makes up for
all of the disadvantage, but
enough of one for them to sur-
vive in reasonable numbers.
ISLE 6.18
Color Camouflage
and Dichromacy
FIGURE 6.33
Color Camouflage
(a) It is easy in this version of the
image to find the small box of
horizontal rectangles. (b) With the
addition of a color camouflage,
finding the square becomes much
harder. Try it when the stimulus is
only briefly presented. However,
dichromats have much less trouble
seeing through this camouflage.
CHAPTER SUMMARY
6.1
Examine the relation of the wavelength of light to
perceived color.
The visible spectrum is the band of wavelengths from
400 to 700 nm that people with trichromatic vision can
detect. We see different wavelengths as different colors.
However, wavelength is not the only property that governs
color vision.
6.2
Diagram the perceptual principles of hue, satu-
ration, and brightness and the role they play in
our perception of color.
Hue refers to the color quality of the light and corre-
sponds to the color names we use. Saturation refers
to the purity of the light or the amount of white light
mixed with the colored light. And brightness refers to
the amount of light present. Additive color mixing is the
creation of a new color by a process that adds one set
of wavelengths to another set of wavelengths. When
we add all of the different wavelengths of sunlight,
we see white light rather than many individual colors.
Subtractive color mixing is the creation of a new color
by the removal of wavelengths from a light with a broad
spectrum of wavelengths.
6.3
Formulate the idea of a metamer in additive and
subtractive color mixing in terms of what we
learn from color-matching experiments.
A metamer is a psychophysical color match between
two patches of light that have different sets of wave-
lengths. To create a metamer, there are two types of
color mixing, additive and subtractive. In additive color
mixing, wavelengths from two or more sources of light
are placed close to make the new color. In subtrac-
tive color mixing, wavelengths from a light source are
removed to yield the color match. From color-matching
experiments, we learn that any three wavelengths can
be adjusted to match a single-wavelength light in people
with trichromatic color vision.
(a) (b)
Sensation and Perception182
6.4
Examine the role of our having three cone classes
for our perception of color.
Color vision starts off with the cones of the retina. We
have three cone systems, responsible for different parts
of the visual spectrum. The S-cones have peak sensitiv-
ity to short-wavelength light, at around 420 nm (blue). The
M-cones have peak sensitivity to medium-wavelength
light, at around 535 nm (green), and the L-cones have
peak sensitivity to long-wavelength light, at around 565
nm (yellow).
6.5
Describe the trichromatic theory of color vision
and its relationship to the three classes of cones.
The existence of these three cone types supports the
trichromatic theory of color vision, which states that the
color of any light is determined by the output of the three
cone systems in our retinae.
6.6
Illustrate the opponent-process theory of color
vision focusing on what this theory can explain
about color vision that trichromatic theory cannot.
There is also evidence that supports the opponent-
process theory of color vision, which states that color
perception arises from three opponent mechanisms, for
red–green, blue–yellow, and black–white. Four primaries
are organized in two sets of oppositional pairs (blue–
yellow and red–green). Blue and yellow are opposite to
each other, and red and green are also opposite to each
other. Evidence for this theory comes from color after-
images and hue cancellation studies. Neuroscience has
also shown that there are cone-opponent cells in the
LGN and color-opponent cells in V1. In particular, double-
opponent cells seem to be specialized for detecting
edges, where one color ends and another color starts.
6.7
Explain what we know about color vision in
infancy and how it changes as we age.
Infant vision can be tested using the process of habitu-
ation, which is where we stop responding to repeated
stimuli. Bornstein and colleagues used this procedure
to determine that infants seem to have color categories
similar to the ones that adults do. In other words, infants
dishabituate, that is, respond again, when a color bound-
ary is crossed, say from blue to green, and the boundaries
are similar to those found for adults. In aging, one way
color vision changes is that the lens loses its transpar-
ency to short wavelengths more than other wavelengths,
which causes us to be less able to see blue than other
colors. The change is slow and not great in healthy eyes.
6.8
Diagram the different types of color deficiency
and explain why this term is, almost always, a
better term than color blindness.
Color deficiency refers to the condition of individuals
who are missing one or more of their cone systems. Rod
monochromats have no functioning cones of any kind
and therefore can be described as truly color-blind. Cone
monochromats are people lacking two cone types but have
one present in addition to their rod systems. Protanopia
(red–green color deficiency) is a lack of L-cones, a con-
dition that is sex-linked and therefore more common in
men. Deuteranopia (red–green color deficiency) is a lack
of M-cones, a condition that is sex-linked and more com-
mon in men. Tritanopia (blue–yellow color deficiency) is
a lack of S-cones; this condition is much rarer than the
others and is not sex-linked. Anomalous trichromats
have all three cone systems intact, but one or more has
an altered absorption pattern, leading to different meta-
meric matches than in trichromatic individuals. A unilat-
eral dichromat is a person with dichromacy in one eye but
trichromatic vision in the other. Cortical achromatopsia is
a loss of color vision that occurs because of damage to
the occipital lobe.
6.9
Assess the term constancy and how it applies to
color vision.
Constancy refers to our ability to perceive an object as
the same object under different conditions. Lightness
constancy refers to our ability to perceive the relative
reflectance of objects despite changes in illumination.
Color constancy refers to our ability to perceive the color
of an object despite changes in the amount and nature of
illumination. The Gelb effect or Gelb illusion is an excep-
tion to lightness constancy in which we see as white a
dark object when it alone is illuminated and we cannot
see other objects.
REVIEW QUESTIONS
1. What is the range in nanometers of the human visi-
ble spectrum? What is the difference between het-
erochromatic light and monochromatic light?
2. What is meant by the terms hue, saturation, and bright-
ness? What does each contribute to our perception of
Chapter 6: Color Perception 183
color? Give an example of two colors that differ with
respect to saturation.
3. What are additive color mixing and subtractive color
mixing? How do the two processes differ? When
would you use each one?
4. What are the three cone systems? What kind of mono-
chromatic light is each cone sensitive to? Why do the cone
systems support the trichromatic view of color vision?
5. What is the problem of univariance? How does it
relate to metameric matching? How does it relate to
color blindness under scotopic conditions?
6. What is the opponent-process theory of color vision?
Describe three perceptual phenomena that demon-
strate the reality of opponent processing.
7. What is the difference between cone-opponent cells
and color-opponent cells? Where do you find each
kind of cell? Describe the visual field of a double-
opponent cell.
8. What is meant by the term color deficiency? What
is the difference between a rod monochromat and
a cone monochromat? What are the three types
of dichromats? Describe the physiological issue
and the perceptual consequences for each kind of
dichromat.
9. What is meant by the term constancy? What are
lightness constancy and color constancy? How do
we infer the nature of the illuminant in each case?
10. What is the difference between violet and purple?
What is the physiological explanation for why purple
looks like a mix of red and blue?
PONDER FURTHER
1. Color vision adds a great richness to our visual life.
It also adds a great deal of complexity to our visual
system as you can tell by this chapter. So, what advan-
tages, other than enriching our experience, does
having color vision add to our survival? Recall from
earlier, that most of our fellow mammals have limited
or no color vision.
2. Use ISLE 6.14c and see if you can describe how dif-
ferent types of dichromats will experience the world.
What scenes would a protanope find the most differ-
ent from a trichromat versus a dichromat?
KEY TERMS
Additive color mixing, 156
Afterimages, 164
Anomalous trichromacy, 173
Brightness, 156
Color constancy, 175
Color deficiency, 169
Color-opponent cells, 167
Complementary colors, 165
Cone-opponent cells, 166
Constancy, 175
Cortical achromatopsia, 174
Deuteranopia, 172
Dishabituation, 168
Double-opponent cells, 167
Gelb effect, 178
Habituation, 168
Heterochromatic light, 153
Hue, 155
Hue cancellation, 165
L-cone, 160
Lightness, 156
Lightness constancy, 175
M-cone, 160
Metamer, 159
Monochromatic light, 153
Opponent-process theory
of color perception, 164
Protanopia, 172
Quality, 155
Saturation, 155
S-cone, 160
Simultaneous color contrast, 165
Spectral reflectance, 153
Subtractive color mixing, 156
Trichromatic theory of color
vision, 163
Tritanopia, 172
Unilateral dichromacy, 174
Unique colors, 166
Univariance, 161
Visual spectrum (visible
spectrum), 153
Sensation and Perception184
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
6.1 Examine the relation of the wavelength of light to perceived color. How We See Color
6.2 Diagram the perceptual principles of hue, saturation, and
brightness and the role they play in our perception of color.
Focal Colors and Unique Hues
6.3 Formulate the idea of a metamer in additive and subtractive
color mixing in terms of what we learn from color-matching
experiments.
6.4 Examine the role of having three cone classes for our
perception of color.
Color Vision, Cones, and Color-Coding in the Cortex
6.5 Describe the trichromatic theory of color vision and its
relationship to the three classes of cones.
Cone Contributions to Color Constancy
6.6 Illustrate the opponent-process theory of color vision focusing
on what this theory can explain about color vision that
trichromatic theory cannot.
Synesthesia for Color Is Linked to Improved Color
Perception but Reduced Motion Perception
6.7 Explain what we know about color vision in infancy and how it
changes as we age.
6.8 Diagram the different types of color deficiency and explain why
this term is, almost always, a better term than color blindness.
For One Artist, Colorblindness Opened Up a World of Black
and White
6.9 Assess the term constancy and how it applies to color vision. Lightness Constancy Illusion
These X’s Are the Same Shade, so What Does That Say
About Color?
Checker Shadow Illusion by Edward H. Adelson
Optical Illusions Show How We See—Beau Lotto
David Parker/Science Source
7Depth and Size Perception
Tim Flach/Iconica/Getty Images
LEARNING OBJECTIVES
7.1
Explain monocular depth cues and how they work to
allow us to perceive depth with one eye.
7.2 Compare the different oculomotor curves in their effectiveness as depth cues.
7.3
Summarize the principle of stereopsis and how it
applies to human depth perception.
7.4 Sketch the correspondence problem and how it must be solved for stereopsis.
7.5
Explain the concept of size perception and the
inferential nature of its determination.
7.6 Diagram the concept of size constancy and how it functions in our visual system.
7.7
Demonstrate your understanding of illusions of size and depth and
how they help us understand the operation of our visual system.
INTRODUCTION
Our ability to see depth and distance is a skill we take for granted, as is the case for
much of perception. Like other perceptual processes, it is an extremely complex process
both computationally and physiologically. The problem our visual system starts off
with is simple. How do you extract information about a three-dimensional (3D) world
from the flat two-dimensional (2D) surface known as the retina (Figure 7.1)? As we
will see, our visual system uses a complex combination of various cues or clues to infer
depth, which often results in vivid perceptual experiences, such as when the monster
lunges out at us from the movie screen while we’re watching that notoriously bad 3D
movie The Mummy (2017). As most readers know, an important part of depth percep-
tion comes from the fact that we have two eyes that see the world from slightly different
angles. We know that people blind in one eye may not see depth as well as others, but
they still have depth perception and can judge distances quite well. In the course of this
chapter, we discuss how single-eyed people perceive depth and explore the reasons why
binocular (two-eyed) vision enhances our depth perception.
Our visual system processes visual information, including a comparison between
what the two eyes see, to determine depth, but that is not the only way to see in depth.
Other animals’ visual systems achieve depth perception in very different ways. What
would it be like to see the world through a completely different visual system? We
ISLE EXERCISES
7.1 Depth Perception
and Adanson’s Jumping
Spider
7.2 Monocular Depth
Cues
7.3 Motion Depth Cues
7.4 Accommodation
7.5 Vergence
7.6 Stereopsis
7.7 Binocular Disparity
7.8 The Construction
of Visual Depth With
Binocular Disparity
7.9 Anaglyph
Stereograms
7.10 Random-Dot
Stereograms
7.11 Retinal Image Size
and Distance
7.12 Müller–Lyer Illusion
7.13 Ponzo Illusion
7.14 Ames Room
7.15 Moon Illusion
7.16 Virtual Reality
Photographs
7.17 Virtual Reality and
Therapy
188 Sensation and Perception
cannot necessarily experience what this would
be like, but we can study the mechanisms
involved and compare them with our own
visual system. Consider spiders, a class of ani-
mals that have eight eyes in addition to their
famous eight legs. Do eight eyes give spiders
a more complex system to see depth, just as
some of the four-coned animals we spoke of in
Chapter 6 see more colors? Interestingly, there
have been a few studies on how this class of
spiders see depth, and the system is incredibly
different from our own. We’ll consider one of
these studies examining depth perception in
spiders. Nagata et al. (2012) examined the use of depth information in jumping accu-
racy in a species of spiders known as Adanson’s jumping spiders (Hasarius adansoni).
These spiders have eight eyes; the four frontal eyes are used for hunting (Figure 7.2).
As their name suggests, Adanson’s jumping spiders catch their prey by jumping onto
small insects and eating them. To be effective at this hunting strategy, their jumps must
be precise, which requires good depth perception. If they land in front of or behind their
insect prey, the prey is likely to escape. So, good depth perception is necessary if the
spider is going to eat and survive. Nagata et al. (2012) were interested in what neural
mechanisms the spiders use for depth perception, given the large number of eyes but the
small brain in these spiders. So that they could focus on the two largest eyes, known as
the principal eyes, they rendered the spiders’ other eyes temporarily blind by dabbing
them with black paint. They set out insects for the spiders to catch and then assessed
the accuracy of the spiders’ jumps.
Unlike a human eye, which has only one layer of photosensitive cells on the retina,
the retinae in the principal eyes of these jumping spiders have four distinct photo-
sensitive layers. Each layer is sensitive to a different range of wavelengths, much as
our cones are sensitive to different ranges of wavelengths. When an image is in focus
on one layer of the spider’s retina, it is out of focus on the other layers. Although
you might think this would make their vision blurry, the spiders use the extent to
which the second image is out of focus to determine
the distance they are from objects. Nagata et al. (2012)
showed that the spider’s eyes focus a sharp image on
the first layer of the retina, leaving blurred images on
the subsequent layers. The spider then compares the
sharpness of the first image to the blurriness of subse-
quent images to compute an estimate of depth. Thus,
these spiders use information from different layers of
each retina to compute depth. This fascinating way
of determining depth is quite different from how our
visual system determines depth. (See ISLE 7.1 for a
demonstration of how spiders use this system to deter-
mine depth.) In our visual system, we use the compari-
son of the two images’ positions across the two eyes to
determine depth, so it is a very different way of using
the two eyes to see in depth.
Returning to our own depth perception, look around
your current environment. You probably have your book
(or e-book) about 12 to 20 inches away from your eyes.
FIGURE 7.1 Our Visual Systems Must Re-Create the 3D World
Using an Essentially Flat, 2D Retina
This figure shows the equivalence of size of objects at different distances from the
retina. Everything along this cone projects the same-size image onto a flat retina. The
visual system must then determine relative size and relative distance (depth).
FIGURE 7.2 Adanson’s Jumping Spider
This spider has eight eyes but uses the multiple layers in its retinae to
determine depth. In this photograph, its four frontal eyes, used for hunting,
are easily visible.
©
iS
to
ck
ph
ot
o.
co
m
/e
lth
ar
20
07
ISLE 7.1
Depth Perception and
Adanson’s Jumping Spider
189 Chapter 7: Depth and Size Perception
Beyond that, you may see a table, a window, and clouds drifting in the sky outside
your room. It seems almost trivial that the book is closer to you than the window, and
the window is closer to you than the clouds. All of these observations serve to hide a
rather interesting feature of depth perception. The retina is essentially flat. Although
it is curved along the back of the eye, it is all one layer and can be flattened out very
easily. There is only one layer of receptors (unlike in those pesky spiders). Regardless of
the distance an object is from the eye, light is imaged by the same receptors, so at this
point in the visual system, there is no information about depth. In other words, which
receptors serve to transduce the light into action potentials does not depend on how far
an object is from the eye. Thus, other sources of information about distance must be
used for 3D perception. This information must be found primarily in the visual scene
itself. In addition, for the first time, the role of having two eyes will become apparent, in
terms of both the advantages and the complications that having two eyes cause for us.
The solution that our visual system evolved is to rely on a system of cues or clues for
depth perception. This view of how humans see depth is sometimes known as the cue
approach to depth perception. This approach focuses on the observation that because
information on the retina is 2D, we must infer the third dimension from other cues our
visual system provides. As we discuss shortly, these cues include monocular cues such
as occlusion and relative size, oculomotor cues such as convergence and accommoda-
tion, and, most famously, binocular cues from comparing images from each retina. In
this chapter, we consider the three major factors in depth perception: monocular cues
(including motion cues), oculomotor cues, and binocular cues. We start this survey with
the monocular cues.
It is important to make explicit what we mean by a cue or a clue. In this discus-
sion, we essentially use the terms cue and clue interchangeably. A cue is a factor that
aids you in making a nonconscious and automatic decision. Cues tell us about which
objects are closer and which are farther away. Thus, the cue approach to depth per-
ception emphasizes that we combine information we can use to infer depth given that
we cannot compute it directly. Let us go through different types of cues that we use to
see depth.
MONOCULAR DEPTH CUES
7.1 Explain monocular depth cues and how they work to allow us to perceive
depth with one eye.
Monocular depth cues are the information in the retinal image that gives us informa-
tion about depth and distance but can be inferred from just a single retina (or eye). In
everyday life, of course, people with two functioning eyes can also perceive these cues
with both eyes, but they are just as usable with only one functioning eye. That is, these
are cues that tell us about depth even if we are looking at the world with only one eye.
Try it—close one eye. You can still use vision to distinguish between objects near and
far. Some people describe the world as seeming a bit flatter when using only one eye
than when using two, but we still judge distances accurately. Monocular cues include
pictorial cues, those cues from which we can judge depth from static or nonmoving pic-
tures like a photograph, and movement-based cues, in which moving objects or our
own motion allow us to make inferences about depth and distance, as in a traditional
non-3D movie (Figure 7.3).
We start with the pictorial cues.
Cue approach to depth
perception: the system
whereby depth perception
results from three sources of
information, monocular cues
to depth present in the image,
binocular cues from the
comparison of images in each
eye, and cues from focusing
the eyes, such as vergence
and accommodation
Monocular depth cues:
depth cues that require only
one eye
Pictorial cues: information
about depth that can be
inferred from a static picture
Movement-based cues: cues
about depth that can be seen
with a single eye in which the
inference of distance comes
from motion
190 Sensation and Perception
Occlusion (or Interposition)
Occlusion occurs when one object partially
hides or obstructs the view of a second object.
We infer that the hidden object is farther
away from us than the object that obstructs
it. Consider the whitewater kayakers in Figure
7.4a. In the photograph, the blue helmet of
one kayaker partially occludes the view of the
other kayaker’s boat. From this, we know that
the blue-helmeted kayaker must be in front
of the black-helmeted kayaker. Similarly, the
blue-helmeted kayaker’s paddle occludes the
view of his own lifejacket. From this, we infer
that the paddle is in front of the lifejacket. Such
a scene as this makes the cue of occlusion look
obvious. However, it is still an inference, based
on knowledge we bring to the act of viewing
scenes as can be seen by examining Figure
7.4b and 7.4c, where perceived occlusion is
used to create a powerful illusion on an impossible box. Occlusion provides infor-
mation about only relative position, not absolute distance. In the kayaking photo-
graph, we cannot determine with much accuracy how far apart the two kayakers are.
You can explore an interactive illustration of occlusion and all other monocular cues
on ISLE 7.2.
FIGURE 7.3
A Graphical Depiction of the Different Types of Depth Cues
Each class of depth cues is labeled in a box, with the specific depth cues listed below it.
• Binocular
Disparity
• Accommodation
• Vergence
• Occlusion
• Relative Height
• Relative Size
• Familiar Size
• Linear Perspective
• Texture Gradient
• Atmospheric
Perspective
• Shadowing
• Motion Parallax
• Deletion and
Accretion
• Optic Flow
Monocular BinocularOculomotor
Pictorial Motion
Depth cues
FIGURE 7.4 Occlusion
(a) We know that the kayaker in the yellow boat is in front of the kayaker
in the red boat because the head of the closer kayaker occludes the boat
of the kayaker farther away. What other cues for depth are present in this
photograph? (b) How is this box possible? Some of the edges seem to be
in front but also cross edges that are in the back. (c) The impossible box
revealed. The edges do not cross behind each other. From this angle it is clear
that there are gaps in the front edges making it seem that they go behind the
other edges. This illusion shows how we infer depth from occlusion.
(b) (a)
(c)
ISLE 7.2
Monocular Depth Cues
191 Chapter 7: Depth and Size Perception
Relative Height
Relative height means that objects closer to the horizon are seen as more distant. In
a picture, this means that objects below the horizon are seen as nearer to the viewer
if they are closer to the bottom of the picture, but objects above the horizon are seen
as nearer if they are closer to the top of the picture. To understand relative height,
think of the horizon dividing the world into two roughly equal portions, the ground
below and the sky above. Think about paintings you may have seen. Usually, the
horizon is somewhere near the middle in Western perspective painting. The distant
part of the sky is painted near the middle of the picture, near where the sky and
ground meet at the horizon. The part of the ground and sky near the viewpoint of
the painter, then, occurs at the extremes of the painting, the close part of the ground
near the bottom and the close part of the sky near the top of the painting. Examine
the photograph in Figure 7.5a. The horizon here is where the ocean meets the sky
and is very clear in this photograph. This places the conch shell and the coral rocks
in front of the ocean, relatively close to the viewer (or camera). The rocks closest to
the bottom of the photograph are closest to the viewer. However, look at the clouds
above the horizon. The clouds nearest to the top of the photograph are viewed as
closest to the viewer.
We see the same pattern in the painting depicted in Figure 7.5b. The water in the
river is close to us and is depicted as such by being at the bottom of the painting. At
the top of the painting are clouds looming over us. The horizon is in the center of the
painting, where the blue sky and white clouds meet the distant green hills and more
distant buildings.
Relative Size
Relative size refers to the fact that the more distant an object is, the smaller its image
will be on the retina. Therefore, if there are two identical objects, the one that is far-
ther away will be the one that has a smaller image on the retina. For example, if we
assume that the two kayakers in Figure 7.4a are approximately the same size (the one
in the front is actually slightly shorter than his companion), then the one who has a
Occlusion: a visual cue that
occurs when one object
partially hides or obstructs the
view of a second object; we
infer that the hidden object is
farther away from us than the
object that obstructs it
Relative height: a visual cue
in which objects closer to
the horizon are seen as more
distant
Relative size: the fact that the
more distant an object is, the
smaller the image will be on
the retina
©
iStockphoto.com
/D
enKuvaiev
FIGURE 7.5 Relative Height
(a) The horizon here is where the ocean meets the sky and is very clear in this photograph. This places the conch shell and the coral rocks along
the bottom of the image as relatively close to the viewer. However, above the horizon, objects closer to the horizon are judged as farther away, and
objects toward the top of the image are judged to be closer. (b) An illustration of how an artist uses this rule to create depth in a painting.
(a) (b)
192 Sensation and Perception
smaller image on the retina must be farther away from the viewer. As the image of the
blue-helmeted kayaker is larger in the picture than that of his companion, we assume
that he is closer to the viewer. Take your fingers out and measure the actual size of
the two kayakers. Note that the kayaker in the background does not look abnormal
in any way. Despite creating a smaller image on the retina, the person does not look
oddly small. The normal size of the more distant person is due to a mechanism called
size constancy, which we discuss later, after more of the depth cues have been covered.
Because we infer that this person is farther away, we do not mistake his smaller size on
the retina for his being a smaller person. You can explore an interactive illustration of
relative size on ISLE 7.2a.
Familiar Size
Related to relative size is the cue of familiar size. Familiar size comes into play when
we judge distance on the basis of our existing knowledge of the sizes of objects. Thus,
if we know that a particular object is smaller than another object, but it is taking up
more space on our retina, we assume that the smaller object must be nearer to us and
that the larger object is farther away. Thus, in Figure 7.6a, each object occupies the
same amount of space on the retinae, but the watermelon is judged to be farthest away
because we know that this is the largest fruit. Similarly, in the photograph in Figure 7.6b,
familiar size allows us to perceived that the building is much bigger than the planter
even though the planter takes up more room on the photograph.
FIGURE 7.6 Familiar Size
(a) Familiarity can be used as a cue for distance of depth. In this image, there are
three objects that are familiar to most of us, all of which take up the same space on
the retinae. But because we know that strawberries are smaller than oranges and
oranges are smaller than watermelons, we unconsciously infer that the strawberry is
closest and the watermelon is farthest. (b) Here is a real-world example. The height
of the building is smaller in the photograph than some of the flowers. However, our
experience with buildings and flowers helps us see that the building is larger.
Retinal image
(a)
(b)
Familiar size: the cue
whereby knowing the retinal
size of a familiar object at a
familiar distance allows us to
use that retinal size to infer
distance
193 Chapter 7: Depth and Size Perception
The cue of familiar size is often eclipsed by other cues. For example, in Figure 7.7a,
the presence of children climbing on the lobster informs us that the lobster in this fig-
ure is no ordinary lobster. In Figure 7.7b, we find a gift shop inside a lobster trap, and
finally, in Figure 7.7c, the building in the background informs us that this is no ordinary
boot. We might well wonder whether people in Maine and eastern Canada don’t have
better things to do.
Linear Perspective
Linear perspective is the pictorial depth cue that arises
from the fact that parallel lines appear to converge as
they recede into the distance. From the point of view of
a human observer, parallel lines seem to get closer and
closer to each other as they get farther away. Of course,
you may remember from your high school geometry
class that parallel lines never meet. But perceptually
they do, at the edge of the horizon. To see what this
cue looks like, examine the photograph in Figure 7.8a.
The railroad tracks are parallel, and in this scene, they
go straight through the desert landscape. The linear
perspective cue is that the parallel lines of the railroad
tracks seem farther apart when close to the viewer,
as they take up more space in the image and on our
retinae. They get smaller and closer together higher in
this image, and we extract from this information that
the tracks go off into the distance. This linear perspec-
tive serves as a cue to depth. The larger the distance is
between parallel lines (the tracks), the closer those lines must be. Of course, in Figure
7.8a, there are other monocular depth cues in addition to linear perspective. Figure 7.8b
shows another good example of linear perspective. The numbers all look the same size
to us, even though the lower numbers, seen toward the top of the photograph, are much
FIGURE 7.7 When Familiar Size Is Unhelpful
(a) The presence of children informs us that this is an abnormally large lobster. It is possible that the lobster is normal size, and the children are the
size of shrimp, but this is a less likely scenario, so the presence of the children immediately informs us of the nature of the lobster. (b) Note the normal
lobster traps in front of the building. Various cues here tell us that the restaurant is normal size and the lobster trap that surrounds it is unusually large.
(c) The famous L.L. Bean boot, with various amounts of context that tell us about the boot’s size.
©
D
av
id
R
. F
ra
zi
er
P
ho
to
lib
ra
ry
, I
nc
./
A
la
m
y
©
V
is
io
ns
o
f A
m
er
ic
a,
L
LC
/A
la
m
y (c) (b) (a)
Linear perspective: the
pictorial depth cue that arises
from the fact that parallel lines
appear to converge as they
recede into the distance
FIGURE 7.8 Linear Perspective
In these images, parallel lines appear to converge in the distance.
(a) We infer that the train tracks are parallel and thus must be getting
more distant as they converge toward the top of the photo. (b) In the
photo of the finish line, how many depth cues can you see?
©
D
ig
ita
l V
is
io
n/
Ph
ot
od
is
c/
Th
in
ks
to
ck
©
iS
to
ck
ph
ot
o.
co
m
/m
ur
en
gs
to
ck
ph
ot
o
(a) (b)
194 Sensation and Perception
smaller in terms of their retinal image size, but because
they are farther away, they do not look smaller.
For painters who wish to convey a 3D scene on a 2D
canvas, linear perspective is an important technique. Look
at the painting in Figure 7.9, which is called Paris Street:
A Rainy Day, by Gustave Caillebotte (1848–1894).
Look at the building in the background. The separation
between the floors is clearly indicated. The walls appear
to diverge and give the indication that the building is
angled and larger in width toward the back, and that the
surfaces recede in depth. In fact, the lines that make up
this building are essentially parallel. Thus, parallel lines
indicate a flat surface, and converging lines that we see
as parallel indicate a surface that recedes in depth. Note
also that we assume that the people are roughly the same
size. Thus, the smaller images of people serve as a cue that
those people are farther from the point of the viewer.
Texture Gradients
A texture gradient is a monocular depth cue that occurs
because textures become finer as they recede in the dis-
tance. Texture gradients as a monocular cue are clearly
related to relative size. In both cases, we use existing
knowledge about sizes or patterns of objects and assume
that smaller images closer to the horizon are the same size,
but farther away. Most surfaces, such as walls and roads
and a field of flowers in bloom, have texture. As the sur-
face gets farther away from us, this texture gets finer and
appears smoother (Gibson, 1950). Another way of say-
ing this is that common elements that are evenly spaced
in an image appear more close together in the distance
than they do in the foreground. For example, the tulips
in Figure 7.10 represent a texture gradient. We assume
that the flowers are about the same size and the same
distance apart in the field. That the images are smaller
and closer together toward the top of the image suggests
that these tulips are farther away. We can also see texture
gradients in the cobblestones in the painting depicted in
Figure 7.9. The cobblestones get progressively smaller as
the road recedes in depth, until the stones are not clearly
distinguishable from one another. In the distance, only the
general roughness of the street is noticeable.
Atmospheric Perspective
Atmospheric perspective is a pictorial depth cue that arises from the fact that objects
in the distance appear blurred and tinged with blue. When we look at a visual image,
close objects are clear and well defined, and objects farther away are more blurred.
Moreover, because the atmosphere scatters light, more distant objects will also have a
blue tinge. This feature of depth perception can be seen in Figure 7.11. In the photograph
in Figure 7.11a, the road in the foreground is clear and sharp. The distant mountains at
FIGURE 7.9 Linear Perspective in Art
This painting by Gustave Caillebotte (1848–1894), titled Paris Street:
A Rainy Day, was painted in 1877. Notice how Caillebotte used linear
perspective to show depth and distance in the painting. There is a
progression of people painted large and up close toward the bottom
of the painting and smaller and farther toward the top of the canvas to
indicate their distance from the painter. Notice also the odd building in
the distance. The lines that make up the walls appear to diverge and give
the indication that the building is angled and larger toward the back,
and that the surfaces recede in depth. In fact, the lines that make up this
building are essentially parallel.
G
oo
gl
e
Cu
ltu
ra
l I
ns
tit
ut
e
Texture gradient: a
monocular depth cue that
occurs because textures
become finer as they recede
in the distance
FIGURE 7.10 Texture Gradients
This field of tulips demonstrates how texture gradients show depth. As
with apparent size, as the tulips get farther away from us, their size on
the retinae becomes smaller. This helps create the experience of depth.
©
iS
to
ck
ph
ot
o.
co
m
/K
ar
en
M
as
si
er
195 Chapter 7: Depth and Size Perception
Atmospheric perspective: a
pictorial depth cue that arises
from the fact that objects in
the distance appear blurred
and tinged with blue
Shadows: a depth cue arising
because an object is in front
of its shadow; the angle of
the shadow can provide
information about how far
the object is in front of the
background
FIGURE 7.11 Atmospheric Perspective
Very distant objects tend to have a blue tinge to them. (a) The mountains in the Chilcotin region of British Columbia, Canada, take on a blue tinge. (b)
The mountains in the distance along the Blue Ridge Parkway in North Carolina also take on a distinct blue tinge. Because the atmosphere scatters
light, more distant objects will also have a blue tinge.
©
iS
to
ck
ph
ot
o.
co
m
/v
ix
te
rd
©
iS
to
ck
ph
ot
o.
co
m
/G
ib
so
nP
ic
tu
re
s
(a) (b)
the horizon have a clear blue tinge. The photograph in Figure 7.11b was taken along the
Blue Ridge Parkway in North Carolina showing how the parkway gets its name from
this depth cue.
If we were standing on the moon, which has no atmosphere, faraway objects would
appear neither blurred nor blue. But our atmosphere scatters light, and it scatters blue
light more than other wavelengths (which is why our sky appears blue). This is related
to how rainbows are formed. Blue light bends more easily than other wavelengths.
Indeed, that the atmosphere scatters light also plays a role in our depth perception.
The short or blue wavelengths of light are most easily scattered by the particles in the
atmosphere. In addition, the scattering occurs for all light, regardless of the direction
it comes from, giving us a blue sky. Thus, light coming from a distant object should
have some of its light scattered. That will have two effects on the light reaching our
eyes: (a) Because blue is scattered more, more distant objects should appear bluish, and
(b) because not all of the light is traveling in a straight line to us, more distant objects
should appear a bit fuzzy.
Shadows and Shading
Shadows may also enhance the perception of depth in images. Shadows provide a
depth cue because the object is in front of the shadow, and the angle of the shadow
can provide some information about how far the object is in front of the background.
Objects that are in shadow must be farther from the light than objects that are not in
shadow. In particular, on a curved surface, light falling on an object will create a pattern
of light and shadow. This gives us information about the relative depths of different
parts of a surface. The perception of shadow and the role it plays in determining depth
and shape is interesting because it depends on the assumption our perceptual system
makes about the direction of the sun. Shadows fall differently on an indentation, like
a hole, versus something that sticks up, like a hill (Figure 7.12). In Figure 7.13, we see
two different views of what really is the same image. In the first image, in Figure 7.13a,
the lighting appears to be coming from above and to the right. In the second image, in
Figure 7.13b, the picture is upside down, but we still assume the light is coming from
above and to the right. Note how this flipping of the picture changes our perception of
196 Sensation and Perception
FIGURE 7.12
Shadows
Shadows depend on assuming the
sun is in the sky. However, if the
object is an indentation, the shadow
will be toward the sun, whereas on
a bump or hill, the shadow is away
from the sun.
FIGURE 7.13 Shadows and Shading
We see two views of the same image. (a) The lighting appears to be coming from above and to the right.
(b) The picture is merely flipped, so that the light appears to be coming from below and to the left. Note how
this changes our perception of whether the circles in the rock art are bumps or indentations.
©
F
ro
ar
in
gu
s/
W
ik
im
ed
ia
C
om
m
on
s/
CC
-B
Y-
SA
-3
.0
/G
FD
L
©
F
ro
ar
in
gu
s/
W
ik
im
ed
ia
C
om
m
on
s/
CC
-B
Y-
SA
-3
.0
/G
FD
L
(a) (b)
whether the circles in the rock art are bumps or indentations. In Figure 7.13a, we see
the circles as indentations in the rock, but in Figure 7.13b, we see the circles as bumps.
In this way, shadows can cause different perceptions of the 3D structure of an object.
TEST YOUR KNOWLEDGE
1. Create a diagram that illustrates the different monocular depth cues.
2. Assess the relative contributions of relative size and familiar size as depth cues
and how they might work together to disambiguate perception.
Motion Cues
The monocular cues we have been discussing so far can be extracted from stationary
images. These are the pictorial cues to depth. However, once you start to move or
objects are set in motion, a number of other monocular cues to depth emerge; these are
the motion-based cues. From an observer’s point of view, objects moving at different
speeds can reveal information about relative distance. We discuss three motion cues to
depth here: (a) motion parallax, (b) accretion and deletion, and (c) optic flow. Each of
these motion cues is considered monocular because it can be seen with only one eye.
However, motion parallax and optic flow can create visual experiences that are similar
to those produced by the binocular cue of stereopsis.
Motion Parallax
Motion parallax is a monocular depth cue arising from the relative velocities of objects
moving across the retinae of a moving person. The term parallax refers to a change in
position. Thus, motion parallax is a depth cue caused by the movement of the viewer. In
this way, it is similar to the binocular cues, because binocular cues rely on two images
across space (one to each eye), whereas motion parallax depends on multiple images
across time (i.e., multiple images in a single eye). It is perhaps easier to think of what
motion parallax is by imagining yourself as a passenger in a car looking out the side win-
dow. The car is moving very fast down the highway. The objects very close to the window,
such as the small trees planted by the highway, seem to rush by. Beyond the small trees,
you can see a distant farmhouse. The farmhouse appears to move more slowly relative
to you in the car. You know that the trees and the farmhouse are standing still; you are
Motion parallax: a monocular
depth cue arising from the
relative velocities of objects
moving across the retinae of a
moving person
Deletion: the gradual
occlusion of a moving object
as it passes behind another
object
Accretion: the gradual
reappearance of a moving
object as it emerges from
behind another object
197 Chapter 7: Depth and Size Perception
the object that is moving. But your constant speed (of, say,
60 mph) creates the illusion that the trees are rushing by
but the farmhouse is not. Farther off, you see the tiny
image of a commercial jet airplane moving across the sky.
Although you know this plane is moving in excess of 500
mph, it does not look nearly as fast as the trees whizzing
close by. Thus, we can use this movement relative to the
viewer as a cue for depth. Those objects that appear to
move more quickly by are closer to us. Objects that appear
to move more slowly by are farther away. This is illustrated
in Figure 7.14. We also highly recommend that you view
the interactive animations of motion parallax on ISLE 7.3a.
A more technical description of motion parallax
involves considering one’s fixation point. If you are look-
ing directly at the farmhouse from your car window,
that farmhouse can be said to be your fixation point.
(Fixation points are also important when discussing ste-
reopsis.) We can then divide the world into points closer
to you than your fixation point, such as the trees, and
objects farther away from your fixation point, such as
the parked tractor beyond the farmhouse or the more
distant airplane. Objects closer to your position on the
highway will appear to move in a direction opposite to
your motion. Thus, even though the trees are station-
ary and it is the car you are in that is moving, the trees
appear to move very quickly in the opposite direction. In
contrast, objects farther than the point of fixation, such
as the parked tractor beyond the farmhouse, appear to
move in the same direction as you do. This movement
opposite to your own by near objects and in the same
direction as your own by far objects is motion parallax.
You can examine this effect in motion by watching the
interactive animation of motion parallax on ISLE 7.3a2.
Deletion and Accretion
Deletion is the gradual occlusion of a moving object as
it passes behind another object. Accretion is the grad-
ual reappearance of a moving object as it emerges from
behind another object. Think about being in a library.
You watch someone emerge from behind one bookshelf
and then disappear behind another bookshelf. When the
person first becomes visible, you note that the bookshelf
was not moving, but the person suddenly emerged. This
provides information about relative depth. The person
must be behind the shelf. Similarly, when the person is
“deleted” as she moves behind the next shelf, you again see from her movement the
relative positions of her and the furniture. We can formalize this in the following way:
The object that is being deleted and then later accreted is the object that is farther
away than the object we can see continuously, which is therefore closer. This can be
seen in Figure 7.16. You can also examine this effect in motion by watching the inter-
active animation of deletion and accretion on ISLE 7.3b.
MoveMove
Position 1
(a) (b)
Position 2 Position 1 Position 2
FIGURE 7.14 Motion Parallax
As you move, objects closer to you appear to move faster, whereas objects
farther away appear to move more slowly. This is because the closer
objects move a greater amount on your retinae from Position 1 to Position 2
than do the more distant objects. (a) Motion parallax to a close object.
(b) Motion parallax to a distant object. (c) You can experience motion
parallax a bit in an anaglyph stereogram. Put on your anaglyph glasses and
move your head from side to side while looking at the image. You will see
the finger of the front figure move more than the faces in the background.
ISLE 7.3
Motion Depth Cues
(c)
198 Sensation and Perception
FIGURE 7.16 Deletion and Accretion
As we watch an object move relative to another object, we judge the
object that disappears (deletion) and reappears (accretion) as being
farther away from us than the object that is continually visible.
Time 1 Time 2 Time 3 Time 4
Optic flow: a motion depth
cue that involves the relative
motion of objects as an
observer moves forward or
backward in a scene
Optic Flow
Optic flow is the motion depth cue that refers to the relative motions of objects as
the observer moves forward or backward in a scene. Optic flow is related to motion
parallax. However, optic flow refers to our perception of objects as we move forward
or backward in a scene (Gibson, 1950) (Figure 7.17). Imagine now that you are driv-
ing down a straight country road. As you move forward, the world rushes by you
in the opposite direction. In front of you, however, the world is still coming toward
you and getting larger as it does. We can determine depth from optic flow because
faraway objects appear to move more slowly relative to closer objects, which appear
to rush toward us more quickly. Indeed, extremely large faraway objects may appear
essentially fixed in position. And the objects that are most close in front of you rush
by you at high speeds. Optic flow is often used to convey depth information in mov-
ies. Think of the stars expanding outward from a point when the Millennium Falcon
enters hyperspace in a Star Wars movie. The moving stars create an optic flow and
it can help you feel as if you are moving with the ship. Car chases in movies also use
optic flow to get you to feel as if you are in the car chasing the bad guys at high speed.
You can also examine an interactive animation of optic flow on ISLE 7.3c.
Now imagine you are driving a car on a winding country road. The motion cues
for depth are a combination of optic flow, relative movement coming directly at you,
and motion parallax, relative movement at a 90-degree angle from you. Add in hills for
Focus of
expansion
FIGURE 7.17 Optic Flow
Consider being in the driver’s seat and
seeing the view in front of you. As you
move forward, the world moves toward
you and then disappears behind you.
Your fixation point remains constant in
the distance, but objects flow toward
you and spread out as they do, relative
to your position. The arrows in the figure
on the right side represent this relative
movement as you drive down the road.
iS
to
ck
ph
ot
o.
co
m
/k
av
ra
m
FIGURE 7.15 Aerial Views of New York
An American Airlines plane flies over a highway September 13, 2009,
in the Queens borough of New York City.
M
ar
io
T
am
a/
G
et
ty
Im
ag
es
N
ew
s/
G
et
ty
Im
ag
es
199 Chapter 7: Depth and Size Perception
up-and-down motion, and even more depth cues become available. The amazing thing
about our visual system is that it computes all these relative distances and speeds fast
enough for us to make sense of the world, even at 65 mph.
TEST YOUR KNOWLEDGE
1. Compose a passage for a friend describing how motion parallax works to
contribute to the perception of depth.
2. Relate deletion and accretion as depth cues to occlusion.
OCULOMOTOR CUES
7.2 Compare the different oculomotor curves in their effectiveness as depth cues.
Rest your index finger on the tip of your nose and look at your finger. Then, without
moving your head or the direction of your gaze, adjust your focus so that you are look-
ing at an object farther away, such as the wall of the room in which you are reading.
As you adjust your eyes, you can feel the movements involved in your focus. These
adjustments that your eyes make as they look from objects near to objects far away or
from objects far away to objects closer can serve as cues to depth in and of themselves.
The movements involved come from two sets of muscles, one that controls the shape of
the lens (accommodation) and one that controls the rotation of the eyes relative to each
other (vergence). We look at each in turn.
Accommodation
Accommodation is the process of adjusting the lens of the eye so that you can see
both near and far objects clearly. We discussed this process in Chapter 3. To focus on
a more distant object, we relax the ciliary muscles that contract the lens, and to focus
on an object close to our eyes, we contract the ciliary muscles. These contractions and
relaxations take place automatically as we change our focus. However, we can sense
these muscle movements. And it is the sensing of these movements that could give
us information about depth. However, the narrowness of the pupil during the day
makes accommodation imprecise in day vision, and the poor acuity at night makes
accommodation imprecise then as well. So, accommodation probably does not play
a large role in depth perception except as related to vergence (Kapoula, Bernotas, &
Haslwanter, 1999).
Vergence (or Convergence)
Vergence (also known as convergence) occurs when the eyes rotate inward to see a near
object and then bend outward (diverge) when we look at a more distant object. When
you are looking at your finger resting against your nose, your eyes are rotated inward
to place the image of this very close object on the foveae of both eyes. Essentially, to see
your finger, your gaze must become “crossed.” When you shift your gaze to the window
or wall beyond your eyes, your eyes rotate outward from each other (Figure 7.18).
As with accommodation, this process is automatic, but our brain can sense the move-
ments, and this feedback gives us information about the relative distance of objects.
Convergence is probably a more useful cue than accommodation, and it can provide the
Vergence: the inward bending
of the eyes when looking at
closer objects
200 Sensation and Perception
visual system with reliable depth information to about 2
meters (m) in distance, at which point there is no appre-
ciable difference in eye angle (Schachar, 2006). You can
explore an interactive illustration of accommodation
and vergence on ISLE 7.4 and 7.5, respectively.
TEST YOUR KNOWLEDGE
1. What is accommodation, and how might it be used
to infer depth?
2. Describe vergence as a depth cue and assess
its relative contribution to depth perception with
accommodation.
BINOCULAR
CUES TO DEPTH
7.3
Summarize the principle of stereopsis and
how it applies to human depth perception.
At the beginning of the chapter, we introduced jumping
spiders, amazing creatures with eight eyes (and eight
legs). Human beings are not fortunate enough to have
eyes at both the front and the back of our heads. But
we do have two eyes, located adjacent to each other at
the front of our heads. Because our eyes are next to each
other at the front of our heads, each eye sees mostly the
same objects in the visual world as does the other eye
but from a slightly different angle (review Figure 3.5).
This contrasts with animals such as horses, which have
eyes on the opposite sides of their heads, such that there
is almost no overlap in what each eye sees. This gives
horses a greater ability to see completely around them.
Horses essentially have a panoramic view. However,
because the fields of view of the eyes do not overlap,
horses cannot take advantage of the binocular depth cues that we do. That we humans
have two eyes that see the world from slightly different angles provides us with an
important cue to depth. The reason our two eyes both look in the same ways is that we
pick up information about depth perception from the overlap of the two visual fields.
In the area where both eyes see the same part of the world, we have binocular vision.
We define stereopsis as the sense of depth that we perceive from the visual system’s
processing of the comparison of the two different images from each retina.
Focus your gaze on some nearby object. If there is nothing readily available, hold
one hand out at arm’s length and look at your own index finger. First look at that index
finger with your left eye and then with your right eye. You get an illusion that your hand
has shifted somewhat as you go back and forth from one eye to the other. This quick
test allows us to see the slightly different perspective on the world that each eye gives
us. If you have an object to look at just beyond your index finger, you can see that the
object may appear closer to your index finger through one eye than through the other
(a) (b) (c)
33˚ 3.5˚ <1˚
10 cm
from eyes
1 m from eyes
4 m or more from eyes
FIGURE 7.18 Vergence
Your eyes cross to focus on a nearby object. People can “feel” this
movement, and that gives them information that objects are close by.
When looking at an object farther away (more than 4 m), there is no
vergence at all. This, too, provides information about depth.
ISLE 7.4
Accommodation
ISLE 7.5
Vergence
Stereopsis: the sense of depth
we perceive from the visual
system’s processing of the
comparison of the two different
images from each retina
201 Chapter 7: Depth and Size Perception
(Figure 7.19). What is important to binocular vision is this area of
overlap. We see the same objects in the area of overlap, but it is not
the same image. Binocular vision involves comparing the two images.
The sense in which stereopsis changes the experience of depth
perception is apparent to anyone who has seen a 3D movie, which
recently have become quite popular again (this technology also relies
on vergence). In 2017, movies as varied as Star Wars Episode 8: The
Last Jedi, The Lego Batman Movie, and Spider-Man: Homecoming
were available in theaters in 3D format. The sense of objects coming
out of the screen toward you in the audience can often distract from
plot development and good acting, but it is a perceptually unmistak-
able phenomenon. The sense of Spider-Man flying out of the screen
toward you in three dimensions is a perceptually very different expe-
rience than watching the same movie in standard format (Figure
7.20). We see both 2D and 3D movies on flat screens, whether they
are movie screens or smaller television screens. But the 3D glasses
one wears while watching a 3D film create a situation in which a
slightly different image is sent to each eye. This allows the use of bin-
ocular cues to extract depth from the images. To see how 3D movies
work, refer to Figure 7.21. You can also examine a demonstration of
3D movies on ISLE 7.6.
Binocular Disparity
Binocular disparity arises because our two eyes are in different
locations in our head and therefore have slightly different views of
the world. The explanation of how disparity allows us to extract
depth information is quite complex. So, read through this section
slowly, make sure you understand the diagrams, and review it until
you know it well. After you are certain that you know it well, draw
yourself a diagram of how the two eyes perceive through stereopsis
and explain it to someone who is not taking your sensation and
perception class. Only after you have done that can you be sure that
you understand the explanation of stereopsis. You can see a demon-
stration of binocular disparity on ISLE 7.7.
Line of gaze
from left eye
Line of gaze
from right eye
View from left eyeView from right eye
FIGURE 7.19 Binocular Disparity
Each eye has a slightly different view of the world. If you
hold your finger out at arm’s length and then look at it
alternately with your left eye only and then your right eye
only, the image of your finger relative to the world behind
it will shift somewhat. This is binocular disparity, which
helps provide the basis for the determination of depth.
ISLE 7.6
Stereopsis
ISLE 7.7
Binocular Disparity
Binocular disparity: a
binocular depth cue because
our two eyes are in different
locations in our head and
therefore have slightly
different views of the worldFIGURE 7.20 Spider-Man: Homecoming
Pi
ct
or
ia
l P
re
ss
L
td
/
A
la
m
y
St
oc
k
Ph
ot
o
202 Sensation and Perception
FIGURE 7.21
Three-Dimensional Movies
(a) A traditional 2D movie. In these
movies, each eye sees the same
information, and depth is inferred
from monocular and motion cues.
(b) A 3D movie. In this situation,
each eye receives a different image,
allowing stereoscopic vision to
occur.
Left eye image Right eye image Left eye image Right eye image
Perception = 2D
(a) Same image to left and right eyes (b) Different images to left and right eyes
Perception = 3D
2D image on flat screen 3D information on flat screen
3D glasses
Corresponding points:
refers to a situation in which
a point on the left retina and a
point on the right retina would
coincide if the two retinae
were superimposed
Noncorresponding points:
refers to a situation in which
a point on the left retina and a
point on the right retina would
not coincide if the two retinae
were superimposed
Horopter: the region in space
where the two images from an
object fall on corresponding
locations on the two retinae
Panum’s area of fusion:
the region of small disparity
around the horopter where the
two images can be fused into a
single perception
Diplopia: double images, or
seeing two copies of the same
image; usually results from the
images of an object having too
much disparity to lead to fusion
Corresponding and Noncorresponding Points
Look around you and find some reference points to use when following this argu-
ment. If you are in a room in your house, a dorm room, or a library, there is likely a
lamp nearby. Position yourself so that you are about 10 feet (3 m) from that lamp.
Hold your thumb out in front of you. Notice how you can use convergence and
accommodation to change your focus from looking at your thumb to looking at the
lamp. When you focus on the lamp, you may also notice that you see a double image
of your thumb. When you focus on your thumb, you may notice two images of the
lamp in the background. So, let us see what is going on with your visual system as
you do this.
For this next discussion, imagine taking out your two retinae and overlapping them
such that the two foveae are on top of each other. Corresponding points refers to a sit-
uation in which a point on the left retina and a point on the right retina would coincide
if the two retinae were superimposed; that is, if you put a pin straight through these two
overlapping retinae, it goes through corresponding points. In contrast, noncorrespond-
ing points refers to a situation in which a point on the left retina and a point on the
right retina would not coincide if the two retinae were superimposed. For example, when
looking at your thumb with your hand held out at arm’s length, the image of your thumb
falls on corresponding points on your left and right retinae. The lamp beyond it does not.
This is why you have the illusion of seeing two lamps (see Figure 7.22). Now imagine a
semicircle in front of you, with all the points at the same distance from your eyes as your
thumb. This imaginary line is the horopter. Thus, if you stretch out your other arm along-
side the one you are fixated on, your other thumb is not your fixation point, but lies along
the horopter. Technically, the horopter is the region in space where the two images from
an object fall on corresponding locations on the two retinae. If you switch your focus
203 Chapter 7: Depth and Size Perception
from your index finger to the lamp, you now have established a new horopter. Because
you are now fixating on the lamp, the horopter is now an imaginary semicircle of points
that is the same distance from your eyes as is the lamp. Please see Figure 7.22 and go to
ISLE 7.8 for a demonstration of this phenomenon.
Objects that lie along the horopter are perceived as single
unified objects when viewed with both eyes. We can also fuse
into a single object the images from the left and right eyes
for objects that fall inside Panum’s area of fusion (see ISLE
7.8b). Inside Panum’s area, including the horopter, we see
images as singles. Outside Panum’s area, either in closer or
farther, we see double images. As we move from the horopter
toward our eyes, we are looking at objects closer and closer
to ourselves. At some point, we lose the perception of these
objects as being single unified objects and we see instead two
images of the same object. Thus, when looking at the lamp
3 m away, the image of your index finger appears as a double.
This double vision is known as diplopia.
Examine Figure 7.23a. We can see schematically the retinae
of the left and right eyes. In the diagram, the eyes are fixated
on Object A, depicted in red in the diagram. The image of A
falls on Points A and Aʹ on the left and right retinae, respec-
tively. Because we are fixated on Image A, it defines the horop-
ter for our visual world. Object B, for example, lies along the
horopter. Thus, Object B falls along Points B and Bʹ on the
retinae. We perceive Object B as being in the same plane or
the same distance from us as Object A. Now consider Object
C. Object C lies closer to us than does Object A and falls on
Points C and Eʹ on the retinae. Notice how Point C is closer to
B than Eʹ is to Bʹ. Because it does not lie along the horopter, its
image falls on noncorresponding points. Object D lies farther
from us than Object A and falls on Points D and Fʹ on the ret-
inae. Again, notice how Point D is closer to Point A than Fʹ is
to Aʹ. Because it does not lie along the horopter, its image falls
on noncorresponding points.
Points that are nearer to us than the horopter have crossed
disparity, and points farther away have uncrossed disparity.
You can see this in the diagram.
Bear with this example, as we introduce a little more ter-
minology necessary to understanding binocular vision. Yes,
the visual world does get much more complicated because of
binocular vision. Consider Object C in Figure 7.23b. Object
C is closer to the observer than the horopter line. Its image
falls on Points C and Eʹ on the retinae. Look closely at these
points. You see Object C to the right of the fixated Object
A with the left eye, but to the left of the fixated Object A
with the right eye. Because of this differential position along the retinae, we call this
crossed disparity. Crossed disparity refers to the direction of disparity for objects
closer to the viewer than the horopter (the image in the left eye is to the right of the
image of the object in the right eye). This disparity is often given a positive sign. You
can also see this interactively on ISLE 7.8c.
Fovea
Horopter
Horopter
FIGURE 7.22
The Horopter and Corresponding Points
When we look at an object, that object defines our horopter—all points
equally distant from us form the horopter. Technically, the horopter is the
region in space where the two images from an object fall on corresponding
locations on the two retinae. Points that are closer to us than the horopter
have crossed disparity, and points farther away have uncrossed disparity.
ISLE 7.8
The Construction of Visual
Depth With Binocular Disparity
Crossed disparity: the
direction of disparity for objects
closer to the viewer than the
horopter (the image in the left
eye is to the right of the image
of the object in the right eye)
204 Sensation and Perception
Next consider Object D in Figure 7.23b. Object D is farther from the viewer than
the horopter line. The image of Object D falls on Points D and Fʹ of their respective
retinae. Note that the image of Object D falls to the left of Object A (the fixated object)
on the left retina, but to the right of Object A on the right retina. Because of this posi-
tioning along the retinae, we call this uncrossed disparity. Uncrossed disparity is the
name given to the direction of disparity for objects that are farther from the viewer
than the horopter (the image of the object in the left eye is to the left of the position
of the image of the object in the right eye). This type of disparity is often given as a
negative value.
Finally, consider Object A itself. Its image falls on corresponding points on the left
and right retinae. Similarly, Object B, though not the focus of our fixation, also falls
along the horopter, so its image falls on corresponding points on the left and right reti-
nae. Points along the horopter are said to have zero disparity. Zero disparity means that
retinal images fall along corresponding points.
So, now let us examine Figure 7.24. We now consider the magnitude of reti-
nal disparity between the two images. We can see here that the amount or magni-
tude of disparity increases as the distance of an object from the horopter increases.
Consider Figure 7.24a. This figure shows two objects with crossed disparity, that
FIGURE 7.23 Corresponding and Noncorresponding Points and the Horopter
(a) Corresponding points are for objects that fall on the horopter. (b) Crossed disparity is for objects (C) that are in front of the horopter and uncrossed
disparity is for objects (D) that are behind the horopter.
Horopter
Fixation point
AB
D
C
Left eye
D A B C F´ A´
B´
E´
Right eye
(a)
Horopter
Fixation point
A
D
C
Left eye
C A D
E´A´F´
Right eye
(b)
Uncrossed disparity: the
direction of disparity for
objects that are farther from
the viewer than the horopter
(the image of the object in
the left eye is to the left of the
position of the image of the
object in the right eye)
Zero disparity: the situation
in which retinal images fall
along corresponding points,
which means that the object is
along the horopter
205 Chapter 7: Depth and Size Perception
is, two objects that are closer to the viewer than the object being fixated on. You
can see that Object C is closer to the viewer than Object B. Therefore, Object C has
a greater crossed disparity than Object B. Now consider Figure 7.24b. This figure
shows two objects with an uncrossed disparity, that is, two objects that are farther
from the viewer than the object being fixated on. You can see that Object D is farther
from the viewer than Object E. Therefore, Object D has a greater uncrossed disparity
than Object E.
We now have the cue people use to determine relative distance of objects by compar-
ing the relative positions of the images of objects on the two eyes. The degree of retinal
disparity gives us information about objects near and far. Indeed, retinal disparity can
give us information about depth distances as small as 4 mm at a distance of 5 m. It is
also useful at distances of up to 200 m (roughly an eighth of a mile) (Howard & Rogers,
2002).
Horopter
Fixation point
Left eye view
Fovea
C
B
A
F
E
D
Fovea
Right eye view Left eye view Right eye view
Larger
crossed
disparity
Smaller crossed
disparity
(a) (b)
Horopter
Fixation point
Fovea Fovea
Smaller uncrossed
disparity
Larger uncrossed
disparity
FIGURE 7.24 Magnitude of Binocular Disparity
The farther away an object is from the horopter, the larger the disparity will be. (a) This figure shows two objects with crossed disparity, that is, two
objects that are closer to the viewer than the object being fixated on. You can see that Object C is closer to the viewer than Object B. Therefore,
Object C has a greater crossed disparity than Object B. (b) This figure shows two objects with an uncrossed disparity, that is, two objects that are
farther from the viewer than the object being fixated on. You can see that Object D is farther from the viewer than Object E. Therefore, Object D has a
greater uncrossed disparity than Object E.
206 Sensation and Perception
Think again about 3D movies. The plane of the screen becomes the horopter. The
manipulation of images to the left and right eyes allows the filmmaker to create images
that go to noncorresponding points along the retinae of the left and right eyes. If the
filmmaker creates an image with uncrossed disparity, we see that image as being behind
the plane of the screen. If the filmmaker creates an image with crossed disparity, we see
that object as being in front of the screen. Indeed, if we perceive an object with increas-
ing crossed disparity, this object appears to come out of the screen toward us. Think
of the shark in the 1983 movie Jaws 3-D. The approaching image of the deadly shark
is caused by increasing crossed disparity. If you have not seen this movie, don’t bother.
It is awful, but the image of a giant shark coming out of the screen to attack you is a
powerful illustration of stereopsis.
In everyday vision, our brain automatically uses binocular disparity as a cue for depth.
Although the monocular cues provide good estimates of depth and distance, binocu-
lar disparity provides strong subjective cues. When watching a regular movie, we have
no problem judging distances between characters and objects. However, the binocular
cues available in 3D movies create a strong experiential boost to our perception of three
dimensions. Seeing objects move into and out of the screen, much as they do in real life,
reinforces the importance of binocular disparity in creating the perception of a 3D world.
The Correspondence Problem
As we just described, the brain uses crossed and uncrossed disparity to determine if
objects are in front of or behind the horopter and the magnitude of disparity to deter-
mine how far the object is from the horopter. But there is an important task our visual
system must accomplish that must be examined. How does our visual system know
which image in the left eye matches up with which image in the right eye? In simple
scenes, this may be relatively obvious. Because we know a lot about objects, in some
cases, matching the image in the left and right eyes should be easy. For example, when
looking at the lamp, that the “finger-shaped object” about a meter away from your
eyes is your index finger in both your left and right eyes is not surprising. But in many
complex scenes, matching images to the left and right eyes may be more difficult. Real
scenes often involve complex textures, similar objects in motion, and many other vari-
ations that may cloud an easy linking of an image in one eye to an image in the other.
Imagine watching a raft of ducks swimming by. Some ducks are closer than others,
but they all look identical to the untrained eye. How do our eyes match up the cor-
rect image of ducks in the left and right eyes? What happens if we match the wrong
ducks together across eyes? This is the correspondence problem. The correspondence
problem (depth perception) is the problem of determining which image in one eye
matches the correct image in the other eye. How our visual system solves the correspon-
dence problem has been an area of some fascinating research, which we discuss shortly.
But to understand how our visual system solves the correspondence problem, we must
describe the techniques researchers have used to investigate the issue. This means we
will have to take a quick look at the nature of 3D images called stereograms so that we
can discuss how random-dot stereograms help us understand how our brain solves the
correspondence problem.
TEST YOUR KNOWLEDGE
1. What is the difference between crossed and uncrossed disparity? Which
corresponds to points closer than the horopter, and which corresponds to
points farther away than the horopter?
2. How does binocular disparity arise? What aspects of the placement of the eyes
are important?
Correspondence problem
(depth perception): the
problem of determining which
image in one eye matches the
correct image in the other eye
207 Chapter 7: Depth and Size Perception
STEREOGRAMS
7.4 Sketch the correspondence problem and how it must be solved for stereopsis.
Charles Wheatstone (1802–1875) was an English inventor during the 19th century.
Among his inventions were a concertina (a small handheld accordion-like instrument),
devices necessary for the creation of the first telegraph networks, and his famous
Wheatstone stereoscope, invented before the first photographs. In the Wheatstone ste-
reoscope, you looked at the two mirrors and one image was presented in each mirror
giving the two images needed to create disparity (Figure 7.25a). This was a cumbersome
instrument, and it was quickly replaced by the Brewster stereoscope, which became
very popular in the 19th century. The Brewster stereoscope is a small instrument (see
Figure 7.25b) that presents one image to one eye and a second image to the other eye
using prisms to help the viewer. The pictures presented to each eye are images slightly
offset from each other in order to replicate the phenomena of crossed and uncrossed
disparity. When one looks through a stereoscope, one sees a single 3D image of the
scene. Originally, Wheatstone used drawings for his stereograms, as photography was
still a year away from being invented and thereafter was expensive, but with the advent
of photography, stereoscopic photographs happened very quickly.
It is fairly easy to take stereographic pictures. A photographic stereogram can be
made by taking a photograph of a scene. First, select a “still-life” type scene, perhaps
a bowl of fruit. Take a photograph and then move the camera 4 inches (6 cm) to the
right and take a second photograph. Keep in mind that the first photograph is the
left-eye photo and the second photograph is the right-eye photograph. Print out the
photographs and place them in an object like the stereoscope above. Such an image
is presented in Figure 7.26. When we look at the stereogram through a stereoscope,
one image goes only to the left eye, and one image goes only to the right eye. Because
the images are so similar, they are combined by the visual system, and the result is the
illusion of depth.
Some people can examine stereograms without the use of a stereoscope, a skill known
as free fusion. The way to do so is to control the convergence movements of one’s eyes.
If one relaxes one’s gaze and imagines that one is looking at a distant point, the left and
right eyes may diverge sufficiently such that the left eye is seeing only the left-eye image,
and the right eye is seeing only the right-eye image. If this is difficult, you may be able to
free-fuse the images by crossing your eyes. This means maximally converging your eyes
as if you were looking at an object very close. This usually involves reversing the pho-
tos, because when you cross your eyes, you will be seeing the left-eye image with your
FIGURE 7.26 An Old-
Fashioned Stereogram
FIGURE 7.25
Stereoscopes
(a) A Wheatstone stereoscope.
The viewer looks at the mirrors
and the images for each eye are
off to the side. (b) The Brewster
stereoscope. This simple device
projects one image to each eye. If
there is disparity in the images, a 3D
image will jump out at the viewer.
(c) A Brewster stereoscope as an
anaglyph stereogram. Use your
anaglyph glasses.
©
Brand X Pictures/
Stockbyte/Thinkstock
(a)
(b)
(c)
By Creator:Life G
roups [CC0], via W
ikim
edia Com
m
ons
208 Sensation and Perception
right eye and the right-eye image
with your left eye. So, if you copy,
cut out, and reverse the photos as
usually depicted, you can see the
correct depth relationship with
a crossed-eye approach. In both
forms of free fusion, one is usually
left with the odd perception of see-
ing three pictures. You can still see
each of the original pictures, but
you now see a third picture in the
middle from the combination of
your two eyes. It is this third (and
essentially illusory) picture in which you can see the depth relations (see ISLE 7.9 for
some really fun examples of stereograms).
The anaglyph is another form of stereogram and the technique generally used in
older 3D movies. Like traditional stereograms, anaglyphs are made by taking two pho-
tographs of a scene from cameras separated by about 6 cm. However, one photograph
is then printed in a shade of one color, such as blue, whereas the other photograph
is printed in a shade of another color, such as red. The two photographs are then
integrated into a common image. The common image looks a bit fuzzy under normal
viewing. However, when viewed through special color-coded anaglyph glasses, each
of the two images goes to one eye, allowing for the stereoscopic image to emerge. The
current convention is for the red lens to cover the left eye, and the cyan (blue) lens to
cover the right eye. If you look at Figure 7.27 first without anaglyph glasses, you see a
fuzzy image. But then put on a pair of anaglyph glasses and look at Figure 7.27 again.
As with the stereograms, your left eye now sees one image and your right eye another
image, and your visual cortex extracts the 3D information from the photograph. In one
photograph, we see two students studying in their science classroom, but the anaglyph
glasses give us a stunning illusion of depth. Similarly, the masks seem to pop out of the
book when you look at them through the glasses. Make sure to keep your anaglyph
glasses handy. There are other anaglyphs scattered throughout the text. Go to ISLE 7.9
if you want to see more of these.
Random-Dot Stereograms
Earlier, we introduced the correspondence problem, that is, how the visual system
determines which object’s image in one eye matches the same object’s image in the
other eye. Here we explain how stereograms can be used to study the correspondence
problem and potentially derive some solutions. How the visual system is able to solve
the correspondence problem is quite complex computationally. The specifics of this
computation were the subject of a debate that took place about the nature of stereop-
sis. On one side was the view that the visual system must bring to bear knowledge of
objects and use that knowledge to match images. The other view was that the visual
system matches the left and right images before bringing knowledge of the objects to
bear on the situation.
To distinguish these hypotheses, Hungarian American vision researcher Béla Julesz
invented random-dot stereograms (Julesz, 1971). Random-dot stereograms are stereo-
grams in which the images consist of a randomly arranged set of black and white dots.
The left-eye and right-eye images are arranged identically, except that a portion of the
dots is moved to the left or the right in one of the images to create either a crossed or an
uncrossed disparity. This creates the experience that part of the image is either in front
ISLE 7.9
Anaglyph Stereograms
FIGURE 7.27 Anaglyph
This is another form of stereogram and the technique generally used in recent 3D movies. Use a pair
of anaglyph glasses to look at these images.
(a) (b)
Random-dot stereograms:
stereograms in which the
images consist of a randomly
arranged set of black and
white dots, with the left-eye
and right-eye images arranged
identically except that some
of the dots are moved to
the left or the right in one of
the images, creating either
a crossed or an uncrossed
disparity
ISLE 7.10
Random-Dot Stereograms
209 Chapter 7: Depth and Size Perception
of or behind the rest of the dots. Such a stereogram is
seen in Figure 7.28. Figure 7.29 shows random-dot ste-
reograms as anaglyphs. A graphic on how random-dot
stereograms are made can be seen in Figure 7.30. You
can explore an interactive illustration of random-dot
stereograms on ISLE 7.10.
When you view a random-dot stereogram without
a stereoscope or without free fusing, all you see is a
grid of white and black dots. There is no shape appar-
ent other than this uninteresting field of dots. Thus, if
we can extract depth information from such images, it
must come from depth perception processes that pre-
cede object recognition, because there are simply no
objects to perceive in such figures until after stereopsis
has occurred. Thus, the argument Julesz (1971) made is
the following. Correspondence between points in the left
image and right image is necessary for the perception of
binocular disparity. If object recognition is necessary for
matching correspondence, then random-dot stereograms
will not result in a 3D perception. However, if correspon-
dence matching occurs before object recognition, then
it should be possible for people to extract
binocular depth cues from random-dot
stereograms. Inspect Figure 7.28 through
a stereoscope or Figure 7.29 or ISLE 7.10
with a pair of 3D glasses. What do you
see? Do any patterns jump out of the page
at you? The majority of people with nor-
mal stereopsis will see a square made up
of many random dots jump out in front of
the page. If you are free fusing by crossing
your eyes, the figure will appear behind the
plane of the page. Thus, because people do
see depth information in random-dot ste-
reograms, we know that correspondence
precedes object recognition.
The Anatomy
and Physiology
of Binocular Perception
The next question we can ask about stereopsis is how it is achieved in the human visual
cortex. We already touched on the answer to this question in Chapter 4. We review
these issues and expand on them here. As discussed in Chapter 4, there are cells sensi-
tive to binocular disparity in V4 and also in V1 of the occipital cortex (Hubel & Wiesel,
1962). These binocular cells have two receptive fields, one for each eye. These cells are
also usually similar with respect to their preferred orientation and motion sensitivity,
suggesting that the main function of these cells is to match the images coming to each
eye. Moreover, many binocular cells in the cortex respond optimally when the images
are on corresponding points on each retina. Interestingly, there are also binocular cells
that respond best to varying degrees of disparity, that is, when similar images lie in front
FIGURE 7.28 Random-Dot Stereograms
When these images are viewed through a stereograph, you can see
patterns floating in front of the black and white dots.
FIGURE 7.29 Random-Dot Stereograms as Anaglyphs
Use a pair of anaglyph glasses to examine the image. You should see
patterns floating in front of the pattern of black and white dots.
1 2 1 2 1 2 2 1 2 1
1 2 1 1 2 1 2 2 2 2
2 1 1 2 1 2 1 1 1 2
1 2 2 2 2 1 2 1 2 1
1 2 1 1 2 1 2 2 2 1
2 1 2 2 2 2 1 2 1 2
1 2 1 1 1 2 1 2 1 1
1 2 2 1 2 2 2 1 2 2
1 2 1 2 1 2 1 1 1 1
2 1 2 1 1 1 1 2 1 2
1 2 1 2 1 2 2 1 2 1
1 2 1 1 2 1 2 2 2 2
2 1 1 2 1 2 1 1 1 2
1 2 2 2 1 2 2 1 2 1
1 2 1 2 1 2 1 2 2 1
2 1 2 2 2 1 1 2 2 1
2 1 2 2 2 1 2 2 1 2
1 2 1 1 2 1 1 2 1 1
1 2 2 1 2 2 2 1 2 2
1 2 1 2 1 2 1 1 1 1
FIGURE 7.30 How Random-Dot Stereograms Are Made
To make a random-dot stereogram, you make a random grid of black and white dots. Each
number in the figure represents either a black (1) or white (2) dot. You then copy the image
to make two such images. But in the second image, you shift a central section of the first
image to the right or left. Thus, the same pattern is represented in each image, but part of it
is shifted. When we look at this through a stereograph, the shifted part will appear either in
front of or behind of the rest of the dots, depending on which direction it was shifted.
Binocular cells: cells with
two receptive fields, one for
each eye; their main function
is to match the images coming
to each eye
210 Sensation and Perception
of or behind the horopter (Barlow, Blakemore, & Pettigrew, 1967). This arrangement is
depicted in Figure 7.31. Indeed, different binocular cells are tuned to different dispari-
ties. For example, a neuron may be tuned to crossed disparity of a particular magnitude,
whereas another cell might be tuned to an uncrossed disparity of another magnitude.
Moreover, such disparity-tuned cells are found throughout the visual cortex, including
along both the ventral pathway (what) and the dorsal pathway (where and when).
For both systems, depth information can play an important role in visual perception
(Parker, 2007).
Developmental Issues in Stereopsis
Are human beings born with stereopsis, or is it a visual skill that requires experience in
the environment to learn? If it does develop, what are the perceptual and physiological
processes that allow infants to learn stereopsis? Research suggests that newborn infants
are blind to binocular depth information and continue to show no stereopsis until the
age of about 4 months. At about 4 months of age, stereopsis develops rapidly in human
infants (Teller, 1983). Indeed, a number of studies have found that 3-month-old infants
do not detect disparity at all, but by 5 months of age, infants perceive depth from dis-
parity as well as normal adults (Birch, 1993).
Testing infants at this age is tricky because they cannot make verbal responses,
nor are they yet in control of all their muscular movements. Thus, researchers must
be clever in designing tasks on which infants can provide measurable responses. It
turns out that most infants like novel stimuli. When presented with an image they
have seen before or a completely new one, infants will direct their gaze toward the
new stimulus. This is often called a novelty preference. Gaze direction and novelty
preference can be measured by
researchers. Thus, we can habit-
uate an infant to a 2D stimulus.
Once the stimulus is no longer
novel, we can show the infant an
alternative stimulus that has the
same structure in two dimensions
but has a 3D interpretation if the
infant can use binocular cues.
Thus, if the infant prefers the 3D
image to the 2D image, it demon-
strates stereopsis, as only with the
3D information is the image novel.
Preferential looking tasks show
that infants start becoming sensi-
tive to disparity at about 5 months
of age (Birch, 1993).
One explanation for this phe-
nomenon is that binocular cells
in the cortex are not mature and
not yet functioning. (It also could
be infants’ poor acuity and lack
of vergence.) The current research
suggests that the area in the brain
that is not yet mature is found not
in V1 but in higher areas of the
occipital cortex. Chino, Smith,
Fixation point
Binocular neurons
in striate cortex
(a) (b) (c)
FIGURE 7.31 Binocular Cell Receptive Fields
These are simplified illustrations of what a receptive field for disparity-tuned neurons in the
occipital cortex look like. (a) Both the red cell and the blue cell are not responding, as the only
object is the fixation point, to which disparity-tuned neurons do not respond. (b) There is an object
closer than the fixation point. A crossed disparity neuron (red) is firing in response to this object.
(c) There is an object farther away than the fixation point. A blue uncrossed disparity neuron is
firing in response to this object.
211 Chapter 7: Depth and Size Perception
Hatta, and Cheng (1997), for example, found that binocular cells of 1-week-old
monkeys were responding to disparity in the same way that binocular cells of older
monkeys were doing. Ocular dominance columns also appear to be mature at birth.
At this point, it is not clear where the locus of origin in the brain for stereopsis to
emerge is, but some evidence points to area V2 (Zheng et al., 2007). Nonetheless, as of
yet, there is no ready explanation for the sudden development of stereopsis at around
4 months of age.
TEST YOUR KNOWLEDGE
1. What is a random-dot stereogram? How is it made? What issue does its study
address?
2. What do random-dot stereograms tell us about how the visual system solves
the correspondence problem?
SIZE PERCEPTION
7.5 Explain the concept of size perception and the
inferential nature of its determination.
Size and depth are deeply intertwined. Think of watching a professional basketball
game from the seats at the top of the coliseum. One knows the players are taller than
normal people, but at that distance, it is hard to perceptually distinguish just how tall
they are. Contrast this with the experience of finding yourself next to Shaquille O’Neal
at the deli counter of your supermarket. At close range, his extreme tallness is appar-
ent, whereas at a distance, we use familiar size cues to perceive people, any people, and
thus, the basketball player’s height is underestimated. This is similar to the experience
we have looking at the ground from airplanes. Intellectually, we understand that we are
2 miles above the surface of the earth and the cars and houses we see are really quite
large. But at that vertical distance, our sense of size is problematic, and we perceptually
experience what look like toy cars and houses. In both of these cases, we misjudge size
because we are at unfamiliar distances. We are more familiar with interacting with peo-
ple, houses, and cars at closer distances. At these familiar distances, we can scale size
better. Indeed, at most distances, we can judge the sizes of objects quite well, despite
the changes in size these objects make on our retinae as they approach us or recede
from us. Think of watching your friends leave your house. As you watch their car speed
away down the street, you do not see your friends’ car getting smaller. You perceive the
car at the same size but moving farther away from you. This leads us to the concept of
size–distance invariance.
Size–distance invariance refers to the relation between perceived size and per-
ceived distance and simply states that the perceived size of an object depends on
its perceived distance, and the perceived distance of an object may depend on its
perceived size. In a classic experiment, Holway and Boring (1941) looked at this
relation. (College students may not make jokes about the second author’s name.
He was a famous psychologist.) They placed disks at various distances from the
observers in such a way that the disks all took up the same amount of space on the
observers’ retinae. If there were no depth cues, the observers judged the objects to
be of the same size, a natural judgment given that the objects were equivalent on the
retinae. But when depth cues were provided, the observers correctly distinguished
the smaller objects up close from the larger objects farther away. That is, as soon
Size–distance invariance:
the relation between
perceived size and perceived
distance, whereby the
perceived size of an object
depends on its perceived
distance, and the perceived
distance of an object may
depend on its perceived size
212 Sensation and Perception
as distance was clear, the observers’
visual systems used the size–distance
invariance principle to scale the sizes
of the objects consistent with their
distance.
Important to studying size–distance
invariance is the concept of a visual
angle. A visual angle is the angle of an
object relative to an individual’s eyes.
That is, if we drew lines from the top
and bottom of an object and extended
those lines to your eyes, we would have
the visual angle of that object (Figure
7.32). Smaller objects close up can
have the same visual angles as larger
objects farther away. Classic examples
of this are the sun and the moon. Each
appears approximately the same size
in the sky and makes a similar visual
angle to our eyes (by sheer coinci-
dence). However, the moon is much
smaller than the sun, and the moon
is also much closer to Earth than the
sun is. Similarly, an index finger held
at arm’s length also makes approximately the same visual angle as do the sun and the
moon (although, again, your index finger is obviously much smaller and closer than
either the sun or the moon). We perceive the index finger as smaller than these faraway
objects because of size–distance invariance. However, we cannot perceptually deter-
mine the distances or the sizes of objects as massive and as distant as the sun and the
moon, and therefore, we do not see the size differences between the sun and the moon.
For another example, the actor Peter Dinklage standing close to you might make the
same visual angle as the retired basketball player Shaquille O’Neal would standing
some distance from you. Similar visual angles from objects of different sizes and differ-
ent distances is also the point of Figure 7.33. The point of Holway and Boring’s (1941)
experiment was that depth provides information that allows us to appropriately scale
the size of an object. Go to ISLE 7.11 for a demonstration of the relation of visual
angles and size perception.
TEST YOUR KNOWLEDGE
1. What is size–distance invariance? How is it used by the visual system to
determine size?
2. Diagram what happens to the visual angle of an object as it gets farther
from you.
SIZE CONSTANCY
7.6
Diagram the concept of size constancy and how it functions in our
visual system.
Visual angle
Size of
retinal
image
Size of
retinal
image
(a)
(b)
Visual angle
FIGURE 7.32 Visual Angle and Size
Visual angle is a function of the size of an object and its distance from the observer. When the
object moves closer, its visual angle on the retina increases. When the object moves more
distant, its visual angle decreases. If we know the object, we will see these differences not as
changes in size but as changes in distance.
Visual angle: the angle
of an object relative to the
observer’s eye
ISLE 7.11
Retinal Image Size and Distance
213 Chapter 7: Depth and Size Perception
Size constancy is the perception of an object as having a fixed size, despite the
change in the size of the visual angle that accompanies changes in distance. That is,
we have a tendency to see an object as the same size regardless of the size of its image
on our retinae. As we have seen, there are limits to size constancy. Shaquille O’Neal
does not look so tall when we see him from far away. However, at the range of normal
viewing, size constancy allows us to see objects as the “right” size even as they move
away from or toward us (Figure 7.34). For example, consider talking to a friend. You
see her as the same size if she is standing 6 feet away from you or if she is standing 3
feet away from you. If she is standing 6 feet away and suddenly takes a step closer to
you, you do not see her grow, even though her visual angle is now twice as large on
your retina. Thus, size constancy usually allows us to see objects as not changing in
size, but there are also exceptions to it. Consider the boot in Figure 7.7c. If we saw
this boot in isolation, we might think it was an ordinary boot. Only in the context of
all the cues that tell us that it is an enormous boot do we see it as such. We now turn
to a set of illusions that occur when depth and size information are not well specified
in a visual image.
TEST YOUR KNOWLEDGE
1. Describe size constancy and why it is important for perception.
2. Under what circumstances might size constancy result in illusions rather than
the perception of reality?
VISUAL ILLUSIONS OF
SIZE AND DEPTH
7.7
Demonstrate your understanding of illusions of size and depth and
how they help us understand the operation of our visual system.
Visual illusions fascinate us because they cause us to see that which is not really there. We
see colors when no colors exist, we see spots of light where no such spots exist, and we
FIGURE 7.33 Size and Visual Angle Illusions
(a) Is the author (JHK) really a giant and as tall at the pyramid in front of the Louvre? The lack of cues for distance suggest
that he’s as tall as the pyramid and standing right next to it. (b) The effect is similar in the picture of the woman “kissing”
the sphinx. She is really much closer to the camera than to the sphinx, but the lack of depth cues makes it appear that she
is even with the sphinx and big enough to kiss it.
M
ar
ga
re
t K
ra
nt
z
RE
U
TE
RS
/J
am
al
S
ai
di
FIGURE 7.34
Size Constancy at the
Range of Normal Viewing
Shaquille O’Neal talks to the crowd
during the 2015 March Madness
Music Festival, April 5, 2015, in
Indianapolis, Indiana.
Scott Legato/W
ireIm
age/G
etty Im
ages
Size constancy: the
perception of an object as
having a fixed size, despite
the change in the size of the
visual angle that accompanies
changes in distance
(a) (b)
214 Sensation and Perception
see shapes that cannot be. Illusions of size and depth are no exception. By manipulating
the depth cues we have discussed in this chapter, it is possible to get viewers to see depth
relations that are really not present in an image.
The Müller–Lyer Illusion
In the Müller–Lyer illusion (Figure 7.35), we see the left line as longer than the
right line, even though both lines are exactly the same length. If you do not believe
this assertion, measure the two lines with a ruler. They are the same length. We will
not distort illusions in this textbook, but please do not trust us. Measure our illu-
sions objectively, and you will discover how your perception can be tricked. With
respect to the Müller–Lyer illusion, the smaller lines that split off from the main
line create the illusion that the main line is longer or shorter. An obvious question is
why would these additional lines affect our perception of the length of the longest
line? Most explanations of the Müller–Lyer illusion focus on the relation of size
and depth. For example, Gregory (1966) advanced the view that the Müller–Lyer
illusion is the result of misapplied size constancy. What this means is that the
visual system wants to keep objects of the same size looking the same size, but in
the case of the Müller–Lyer illusion, we mistakenly see size differences when the
size is actually the same.
The argument works as follows. Consider the left image in the Müller–Lyer illu-
sion. Think about what this might look like in three dimensions. We may see the
Müller–Lyer image as a corner in a wall. If the corner comes toward us, then the little
projections at the top and bottom will move toward the middle of the line similar to
receding parallel lines in linear perspective, as the walls lead away (see the left-hand
image of Figure 7.36). In the image on the right of Figure 7.36, we see the corner
pointed away from us, and the little projections that mark the corner are coming
toward us. To draw them, they will go away from the line. Here we see the corner as
being at a distance and the walls coming toward us. Because we see the line as being
farther away in the right-hand image than we do in the left-hand image, we see the
line in the right-hand image as longer. Why? Because it takes up the same space as
the left-hand line on our retina, but we perceive it as being more distant. Objects that
take up the same amount of space on our retina, but are more distant, are necessarily
larger. Hence, we see the line as longer. You can see how this looks in real life by
examining the corners in Figure 7.36.
However, the previously stated explanation stemming from Gregory’s (1966)
work is not the only explanation for the Müller–Lyer illusion. Some researchers
have questioned whether an implicit assumption of depth is required to see the
Müller–Lyer illusion. Day (1990) proposed a simpler explanation of the Müller–
Lyer illusion. Day claimed that because the extending lines reach up and out in
the right-hand image of Figure 7.36, the overall figure is longer in that image than
the one on the left-hand side. Thus, we perceive components as longer as well. This
view accounts for the Müller–Lyer illusion without recourse to a depth illusion.
Another interesting observation about the Müller–Lyer illusion that suggests that
Gregory’s account might not be complete is that you still get the illusion when
done by active touch (haptically). You can demonstrate the Müller–Lyer illusion in
both blindfolded and even congenitally blind participants. You build the Müller–
Lyer stimulus using rods, with a central rod whose length is to be estimated and
rods at the end forming the wings like in Figure 7.36. Now you have them esti-
mate the length of the central rod by moving their hands along the rod stimulus
FIGURE 7.35
The Müller–Lyer Illusion
We see the vertical line as longer in
the right figure than the left figure
even though the vertical lines are
the same length in both.
Müller–Lyer illusion: the
illusion where a line that has
two lines going away at an
angle looks longer than a line
of the same length but the end
lines angle back across the
main line
Ponzo illusion: the illusion
in which two horizontal lines
are drawn one above the
other; both lines are on top of
two inwardly angled vertical
lines; the top line, where the
two vertical lines are closer
together, looks longer
215 Chapter 7: Depth and Size Perception
and people still have the illusion. There are
no depth cues here (Heller et al., 2002). Go
to ISLE 7.12 for interesting variants on the
Müller–Lyer illusion.
The Ponzo Illusion
The Ponzo illusion is a strong example of
misapplied size constancy via the influence of
linear perspective (a monocular cue to depth)
on size perception. The Ponzo illusion is illus-
trated in Figure 7.37. The two cows are the
identical size (indeed, the identical animal).
They take up exactly the same amount of size
on the page or screen. If you do not believe
this, you can measure them. However, the
cow closer to the top of the page looks bigger.
This is because there are a number of cues in
the photograph that give clear indications of
depth relations. We see the roughly parallel
lines of the side of the road receding into the
distance. We see a texture gradient of flowers
and grasses. We see that the trees at the top of
the photo are a bit hazy. Familiar size cues suggest that
the trees, despite their smaller retinal image than the
grass, must be larger but more distant. As a function
of all this, we see the upper cow as farther away from
the viewer than the lower cow. Because the cows take
up the same amount of space on the retina, and the
upper cow is farther away, the visual system makes the
inference that the upper cow must be larger, leaving us
with the strong perception of a big cow and tiny cow
in front of her. The Ponzo illusion is so called because
it was discovered by the Italian psychologist Mario
Ponzo (1882–1960). For more on the Ponzo illusion,
go to ISLE 7.13.
The Ames Room Illusion
The Ames room is a neat illusion because it can be instan-
tiated in real space, as has been done in numerous sci-
ence museums, such as those in Melbourne, Australia;
Keswick, England; and Jerusalem, Israel. It also works on
paper (Figures 7.38 and 7.39). In the Ames room, we put two people of normal size into a
room that is anything but normal. When viewed through a peephole on the side of one of
the walls, the perception is of a very large person in one corner and a very small person in
the other corner. The room, however, looks normal. But the room is not normal. Indeed,
it defies almost all conventional rules of rooms. Its walls (except the wall people are look-
ing through) are trapezoids, as are the windows in the room. In versions in which there
are floor tiles in the room, these are also trapezoids (see Figure 7.38). However, when we
FIGURE 7.36 The Müller–Lyer Illusion in the Real World
Note in the first picture that the angled lines indicate an outside corner, whereas the
angled lines in the second picture indicate an inside corner. The inside corner with
the walls coming toward us suggests that the straight line is farther away from us,
and thus we perceive it as bigger.
ISLE 7.12
Müller–Lyer Illusion
FIGURE 7.37 The Ponzo Illusion
Even though both cows take up the exact same space on the retina,
the one higher on the image looks bigger because it appears
farther away.
ISLE 7.13
Ponzo Illusion
216 Sensation and Perception
look through the viewing hole, we cannot distinguish the trapezoids,
and we use our cues of familiar sizes and shapes to infer a normal room.
Our visual systems convert the trapezoids into squares, so that we can
perceive the room itself as normal. Because we perceive a normal room,
we must therefore infer that the people are abnormally short or tall. To
make the illusion fun, you can find twins who are dressed alike and put
one at each end of the room, making for a very tall twin and a very short
twin. You can see a video of people moving through the Ames room in
ISLE 7.14.
The Moon Illusion
The moon illusion is another powerful illusion related to size–depth
relations. What is interesting about this illusion is that we can see it in
the night sky several times each month, which makes it a rare illusion
in that it happens in nature. Find out when the next full moon is, or
a day before or after the full moon. Then find out when sunset will
occur, and watch the moon rise at sunset and then look at it again a few
hours later. When we see the full moon on the horizon (such as when
it rises at sunset and sets at sunrise), we perceive it as being larger than
when it is higher up in the sky. This perceptual fact is seen in countless
romantic movies, in which a love-struck couple stares at an abnormally
large full moon. The moon illusion is depicted in Figure 7.40. As you
can see, in Figure 7.40, the moon looks bigger at the horizon than at
zenith. However, the moon does not change size across the night. Its size
remains constant, and its distance from the Earth remains constant. If
you do not believe this, take a photograph of the full moon as it rises
and then again a few hours later. Print out the photograph and cut out
the image of the moon. You will see that the zenith moon fits perfectly on top of the hori-
zon moon. The moon does not change size; only our perception of it does.
FIGURE 7.38 The Ames Room Illusion
The people in the photo are the same size, but the person
on the left appears much larger than the other because
of the shape of the room. Note that the person on the left
in one photograph is the person on the right in the other
photograph. Did she shrink while her friend grew?
ST
EP
H
A
N
IE
P
IL
IC
K/
St
af
f/
G
et
ty
Im
ag
es
Ames room: a specially
constructed room where
two people of the same size
standing in the two back
corners will look very different
in height
Moon illusion: the illusion
where the moon looks larger
when it is near the horizon
than it does when overhead
Peephole
Twice as far from observer
as the man on the left
FIGURE 7.39 The Ames Room Revealed
You can see in this drawing what an Ames room looks like. When you look through the peephole, as the
observer is doing, it looks like Figure 7.38, but you can see here that the person on the right is approximately
twice as far away from the observer as the person on the left. But for the observer, this difference is not
seen, and instead the person on the left is seen as much bigger.
ISLE 7.14
Ames Room
ISLE 7.15
Moon Illusion
217 Chapter 7: Depth and Size Perception
FIGURE 7.40 Moon Illusion
You can see here that the moon looks bigger when we see it on the horizon (a) than when it is higher in the sky (b). But if you match the moons, you
will see that they are the same size.
©
iS
to
ck
ph
ot
o.
co
m
/k
ei
ic
hi
hi
ki (a)
©
iS
to
ck
ph
ot
o.
co
m
/k
la
gy
iv
ik (b)
The explanation for the moon illusion is similar to other size–depth illusions: a
misperception of distance causes a change in the perception of size. We see the sky
as a giant dome overhead, and objects in the sky as all at the same distance, that is,
“painted” on the dome (though intellectually we know this to be untrue). As such, on
this dome, the horizon is farther away from you than is the zenith, directly overhead.
Because we perceive the horizon as being farther away than the zenith overhead, an
object that takes up the same amount of space on our retina must be larger. At zenith,
the moon looks smaller because the same-size object is now thought to be closer. This
explanation is illustrated in Figure 7.41. You can explore an interactive illustration of
the moon illusion on ISLE 7.15.
TEST YOUR KNOWLEDGE
1. Assess the role of depth perception in the Müller–Lyer, Ponzo, Ames room,
and moon illusions.
2. What is the Ames room? How does it illustrate the cue approach to depth and
size perception?
FIGURE 7.41
The Moon Illusion Explained
We view the sky as a dome, and the moon
and stars as “painted” on the dome, even
though we know intellectually that this
is not true. Thus, because the horizon is
perceived as farther away than the zenith,
the same-size object is viewed as larger on
the horizon than at the zenith.
Actual path
of moon
Horizon
(not drawn to scale)
Apparent path
of moon
Apparent size and
distance of moon
directly overhead
Apparent size
and distance
of moon
near horizon
Same visual angle
218 Sensation and Perception
EXPLORATION: Stereopsis and Sports:
Do We Need Binocular Vision in Sports?
In everyday life, we can get by with monocular cues, but
the binocular cues add to our perception of depth and
give us additional invaluable cues, which in some cases
may help us perceive depth. But are there situations in
which having binocular vision is absolutely essential, and
are there situations in which binocular vision gets in the
way? Sports provide one of these situations—competing
in sports requires finely honed senses and close coordina-
tion between what one is seeing and what one is doing.
Think of the coordination between quarterback and wide
receiver in football. The quarterback must time his pass at
just the right time to avoid the hands of oncoming defend-
ers and in such a way as to bring the football into contact
with the wide receiver’s hands at just the right moment.
Similarly, the wide receiver must be aware of the positions
of defenders, the pattern he is supposed to run, and the
exact arrival of the football at a particular point in time.
Moreover, the wide receiver must do this while running
nearly 20 mph (32 km/h). One would think that such
activities require excellent depth perception (and periph-
eral vision), and yet the former football player Wesley
Walker succeeded at being a wide receiver despite being
legally blind in one eye. However, Walker was a runner as
fast as Olympic sprinters, which gave him an advantage
despite his monocular vision.
However, in target sports, the conventional wisdom is that
it is desirable to eliminate binocular cues. Archers and tar-
get shooters are usually instructed to close one eye. The
thinking here is that good shooting means focusing on
lining up a close point, such as your gun’s sight, and a
far point, the target. Because the close point may be on
noncorresponding points on your left and right retinae, it
may not be possible to line up the sight using both eyes,
especially if firing a handgun. Given that shooters in com-
petitions are usually aiming at targets that are largely out
of the range of binocular depth cues anyway, there is no
real advantage to using both eyes, but there is this one big
disadvantage. Unfortunately, there has been no published
empirical research on the advantages or disadvantages of
stereopsis in target sports.
But are there any empirical data athletes could rely on?
Do we know that quarterbacks, for example, use binoc-
ular cues of depth to judge distance, and do we know if
archers would shoot better if they kept both eyes open? In
this section, we discuss some of the existing literature on
stereopsis and sports.
Much of the research has been done with respect to the
batter in baseball. Consider the perceptual-motor task a
baseball batter is confronted with. A pitcher is throwing
a ball with a 9-inch circumference (230 mm) at more than
90 mph (145 km/h) from a distance of 60 feet (18 m).
Baseball hitters must react extremely quickly; indeed,
they often initiate their swing even before the pitcher has
released the ball. As the ball approaches the batter, there
are a number of depth cues that the batter may attend to,
including familiar and relative size, linear perspective, shad-
ing, optic flow, and binocular disparity. So, our question
is this: To what extent do baseball batters use binocular
disparity information?
In one study, Hofeldt and Hoefle (1993) compared profes-
sional baseball players in the highest professional league
(the major leagues) with professional baseball players who
had not made the highest professional league (the minor
leagues) (Figure 7.42). Hofeldt and Hoefle looked at the
players’ ability to do a stereo matching task that measured
individual differences in the ability to use stereoscopic
cues. The researchers found that the major league play-
ers were more accurate at the stereoscopic task than the
minor league players and that ability in the task predicted
batting average (a measure of baseball performance) in
the major leaguers. This suggests that baseball batters do
use stereo cues to time their swings. However, this study
is still correlational in nature. We do not know if batters
are better because they have better stereopsis, or if better
stereopsis is the result of working harder to be good at
baseball. So Hofeldt and his colleagues next designed an
experimental procedure to look at baseball batting and
depth perception.
Hofeldt, Hoefle, and Bonafede (1996) examined ama-
teur baseball players hitting in batting cages under con-
trolled conditions, including a constant speed of pitches.
Again, they were interested in the interaction of the
two eyes in timing the swing of a baseball bat. Baseball
batting success was measured by looking at the rate of
hits (contact with the ball into play), fouls (contact with
219 Chapter 7: Depth and Size Perception
the ball, but out of play), and misses (not making con-
tact with the ball). They then used filters to impair one
eye or the other during swinging. These filters reduced
the amount of light reaching the filtered eye. When one
eye receives less light than the other, that filtered eye
essentially perceives more slowly, making it harder to
match corresponding points. This effect can also change
the apparent depth of object in an illusion called the
Pulfrich effect. The researchers found that when both
eyes were filtered, the decrease in hitting success was
negligible and nonsignificant. However, when one eye
was filtered, but not the other, motion-for-depth cues
were interrupted, and hitting success decreased dramat-
ically, from 87% hits to 36% hits. However, this was
when the dominant eye was filtered. The effect was
smaller (80%) when the nondominant eye was filtered.
Scott, van der Kamp, Savelsbergh, Oudejans, and Davids
(2004) also found that participants were better able to
hit a foam object thrown at them if they had access to
binocular cues than when they only had monocular cues.
Hofeldt et al. concluded that (a) binocular information
is important for baseball batting and (b) baseball batters
really do have a dominant eye, consistent with the con-
ventional sports wisdom.
In baseball, players must be able to catch balls as well as
hit them. Outfielders must judge the distance and direction
a ball is going to go after the batter hits it, and they must
also time their running speed to meet the ball in an antici-
pated location. We can ask to what extent baseball players
use stereopsis to judge where they must run to intercept
the ball. Mazyn, Lenoir, Montagne, and Savelsbergh (2004)
looked at the ability of people to catch a tennis ball with
one hand. They compared performance under binocular
viewing conditions as well as monocular viewing conditions
at a variety of ball speeds. People with normal stereo vision
caught more balls under binocular conditions than under
monocular conditions, and this effect was more pronounced
the faster the ball was thrown at them. Thus, binocular cues
are used in catching balls, contrary to some earlier notions
of how baseball players intercept fly balls (see Mazyn et al.,
2004). Mazyn et al. also looked at people who do not see
well in stereo. These individuals were no better in the bin-
ocular condition than the monocular condition and were
somewhat lower in their overall ability to catch tennis balls.
Along similar lines, Isaacs (1981) found that people with
better stereo vision were also better at shooting foul shots
in basketball than people with weaker stereo vision. Thus,
across an assortment of athletic tasks, we see that stereo
vision is useful in performing athletic tasks.
APPLICATION: Virtual Reality and Therapy
Although not all that common yet, views like Figure
7.43a are becoming increasingly common. People are
sticking their phones into strange head pieces, putting
these head pieces on, and craning their heads all around.
These head pieces or goggles use phones to create what
is called virtual reality (see Figure 7.43b for an anaglyph
of a couple of examples of different goggles that can
be used). Virtual reality refers to a computer-generated
three-dimensional photograph, image, or environment
that can be interacted with in an apparently authentic
way. To create convincing virtual reality, all the depth
and size cues that we have discussed in this chapter
have to be understood and reproduced accurately. For
example, panoramic photographs are becoming quite
popular, but what if you could put yourself back inside
the photograph and turn around to see the different
FIGURE 7.42 Binocular Vision in Baseball
A batter must be able to accurately time an incoming baseball in a
fraction of a second in order to hit it. Batters hit better with binocular
vision than with monocular vision.
©
Shutterstock.com
/sirtravelalot
Virtual reality: a computer-generated photograph, image,
or environment that can be interacted with in an apparently
real way
220 Sensation and Perception
directions in the original location? With virtual reality
goggles, that is possible. Phones will draw two versions
of the image and the headsets use the same technique
as in Brewster stereoscopes to help you fuse the images
so you can have the full range of monocular and bin-
ocular depth cues. You can try some in ISLE 7.16. If
you are on a laptop you can scroll the images around
with your mouse. If you have a tablet, make the image
full screen and as you turn around you will see dif-
ferent views of the photographs. If you have gog-
gles that can run Google Cardboard images, you
can fully put yourself into the image which will be pre-
sented stereoscopically. You look around by turning your
head and body as if you were there. In a fully computer-
generated version of virtual reality, the programmer
must implement cues such as relative size. That is, if all
of the people in a scene are drawn the same size, instead
of smaller for more distant figures, then our size con-
stancy will make those figures in the background loom
as giants like this version of the Ponzo illusion (Figure
7.44), which might be interesting but violates what real-
ity looks like.
Virtual reality goggles are making commonly available
what has been discussed in
research for a long time in
terms of the principles dis-
cussed in this chapter. Virtual
reality is also now available
to anyone with a smartphone, and the price for the head-
sets is dropping fast. As such, new ways to experience
locations and play games will continue to emerge as the
technology matures. Think of revisiting your vacation by
putting on some goggles and being able to look around a
scene just like when you were there. It appears that these
goggles might be useful for more than reliving experi-
ences or playing games. One interesting development is
the use of virtual reality for psychological therapies.
One area of therapy in which virtual reality is being
explored as a tool is relief from anxiety and phobic
(fear) disorders. All of us have anxiety from time to time.
However, in people who have an anxiety disorder, anxi-
ety persists and can interfere with day-to-day functioning.
An anxiety disorder refers to a broad class of disorders
in which anxiety persists and is greater than the situation
seems to warrant. In a phobic disorder, the person has a
fear of a situation or object. A common method of treat-
ment, under various names and guises, can be called expo-
sure therapy. In brief, the client is exposed in a controlled
manner to the stimulus that is causing the anxiety or fear.
The exposure starts at a level that the patient finds easy to
handle and then as each level of exposure is handled with-
out any increase in anxiety or fear, a more intense level of
the phobic stimulus is presented.
Virtual reality creates the possibility of controlled
exposure to the anxiety or fear-inducing stimulus
FIGURE 7.43 Virtual Reality Goggles
(a) A photograph of one of the authors wearing virtual reality goggles and looking around. A smartphone provides the stimuli. (b) An anaglyph of a
couple of different types of virtual reality goggles. Use your glasses to see them in depth.
(a) (b)
ISLE 7.16
Virtual Reality
Photographs
221 Chapter 7: Depth and Size Perception
through computer generation. When virtual reality
is used, the therapy is called virtual reality exposure
therapy (VRET). The idea here is that in a computer
environment, the exposure can be much more carefully
controlled.
One anxiety disorder is post-traumatic stress disor-
der (PTSD) in which people experience symptoms of a
trauma long after an experience occurred. PTSD occurs
not only for many battle-tested soldiers but also for civil-
ians who have suffered trauma as a result of having expe-
rienced assault, rape, or a natural disaster. Although still
in pilot stages of testing, these virtual reality therapies
have shown promise. In one study, Portuguese veterans
were placed in a jungle setting where triggers for their
PTSD were presented, such as a mortar explosion. Over
repetitions, the strength of the trigger could be increased
very precisely, thereby controlling the exposure (Gamito
et al., 2010). In another study, elderly American veterans
of the Vietnam war were flown over a virtual Vietnam
and landed in a clearing in the jungle (Rothbaum
et al., 1999). In both cases, the clients showed signifi-
cant improvements, and Rothbaum and colleagues found
that the improved symptoms lasted at least 6 months.
However, the number of participants in both cases is
small and the results are considered preliminary. You can
learn more about the use of virtual reality therapy for
PTSD in ISLE 7.17.
Specific phobic disorders, such as arachnophobia (intense
fear of spiders), is another area where the use of virtual
reality has shown promise. In traditional therapies, it often
requires starting with something that distantly suggests
the phobic stimulus and gradually getting ever closer to
the dreaded arachnid. Several studies have recently exam-
ined using VRET for specific phobias, including arach-
nophobia (e.g., Bouchard, Côté, St-Jacques, Robillard, &
Renaud, 2006). There are a sufficient number of studies on
this topic that it is possible to see if different researchers
are finding consistent results (Opriş et al., 2012). It seems
that these virtual reality therapies are at least as effective
as the best traditional therapies on several measures, such
as reduction of symptoms and dropout rate. The question
then arises, why do the virtual reality therapy? Bouchard
and colleagues (2006) might have an answer to this
question. Developing virtual
reality programs is quite
expensive. However, so, too,
are traditional therapies.
Overcoming a phobia such as arachnophobia might even-
tually require having to deal with spiders. Virtual spiders
are easier to maintain and don’t require lots of mosquitos.
Bouchard used an existing virtual reality game to help in
the treatment of arachnophobia. Using an existing game
can reduce cost, and if these emerging goggles continue to
reduce in cost as well, this form of therapy might become
cost-effective. You can see more about the use of virtual
reality in treating phobic disorders in ISLE 7.17. All in
all, it appears that these funny-looking goggles might be
more than toys.
FIGURE 7.44 Watching Out for Relative Size
In virtual reality, all of the depth cues in the real world have to be
accurately reproduced. For example, if you do not make more distant
figures smaller, they become giants as in this version of the Ponzo
illusion.
ISLE 7.17
Virtual Reality and Therapy
Sensation and Perception222
CHAPTER SUMMARY
7.1
Explain monocular depth cues and how they
work to allow us to perceive depth with one eye.
The problem our visual systems must solve is that we rep-
resent the world on flat, 2D retinae. However, we live in
and therefore must perceive a 3D world. Our visual system
seems to do this in classic Helmholtzian fashion—by using
unconscious inference from myriad clues that inform us of
relative depth. We divide these cues into three groups—
the monocular cues, the oculomotor cues, and the binoc-
ular cues. The monocular cues include information about
depth that we can infer with just one eye. These tend to be
characteristics of the scene itself or motion-based cues.
Monocular cues include occlusion, relative height, relative
size, familiar size, texture gradients, linear perspective,
atmospheric perspective, shading, and shadows. Included
in the monocular cues are the motion-based cues of motion
parallax, accretion and deletion, and optic flow.
7.2
Compare the different oculomotor curves in their
effectiveness as depth cues.
The oculomotor cues are convergence (or vergence)
and accommodation. Convergence means that the eyes
rotate toward each other when looking at closer objects.
We sense this motion, and it informs us about whether we
are looking at a near or a far object. Accommodation is the
process of adjusting the lens of the eye so that both near
and far objects can be seen clearly. Again, we can sense
the muscles that make this adjustment, and this informs us
about the proximity of the objects that we are looking at.
7.3
Summarize the principle of stereopsis and how it
applies to human depth perception.
Stereopsis is the strong sense of depth we perceive from
the visual system’s processing of the comparison of the two
different images from each retina. Stereopsis arises from
binocular disparity. Binocular disparity occurs because our
two eyes are in different locations in our heads and there-
fore have slightly different views of the world. For stereop-
sis to work, the visual system must match the image on the
left retina to that on the right retina.
7.4
Sketch the correspondence problem and how it
must be solved for stereopsis.
Corresponding points refers to a situation in which a point
on the left retina and a point on the right retina would coin-
cide if the two retinae were superimposed. In contrast,
noncorresponding points refers to a situation in which
a point on the left retina and a point on the right retina
would not coincide if the two retinae were superimposed.
Corresponding points lie along the horopter, the region in
space where the two images from an object fall on corre-
sponding locations on the two retinae. We use disparity
information to determine if an image is in front of the horop-
ter or behind it. Crossed disparity means that an object is in
front of the horopter, whereas uncrossed disparity means
that an object is behind the horopter. The correspon-
dence problem is the problem of determining which image
in one eye matches the correct image in the other eye.
Stereograms and anaglyphs are specially designed pictures
in which the photograph or film replicates the binocular dis-
parity and therefore creates a pop-out phenomenon that we
see as depth. Random-dot stereograms have been used to
show that object recognition is not necessary for disparity
cues, thus placing the solution to the correspondence prob-
lem as something that occurs prior to object recognition.
Physiological studies demonstrate that there are binocular
cells in the visual cortex. These cells are tuned to disparity
information, thus allowing the neurons to extract informa-
tion about depth. Infants do not develop stereopsis until the
age of about 4 months, though the physiological reasons for
this are unclear.
7.5
Explain the concept of size perception and the
inferential nature of its determination.
Size and depth are deeply intertwined. Size–distance
invariance refers to the relation between perceived size
and perceived distance, and simply states that the per-
ceived size of an object depends on its perceived distance,
and the perceived distance of an object may depend on its
perceived size.
7.6
Diagram the concept of size constancy and how
it functions in our visual system.
Size constancy is the perception of an object as having
a fixed size, despite the change in the size of the visual
angle that accompanies changes in distance.
7.7
Demonstrate your understanding of illusions of
size and depth and how they help us understand
the operation of our visual system.
A number of illusions demonstrate violations of size–distance
invariance and size constancy. In the Müller–Lyer illusion,
we see a line that looks longer than an identical-length line
Chapter 7: Depth and Size Perception 223
because the ends of one line suggest a corner moving away
in depth. The Ponzo illusion is a strong example of misap-
plied size constancy as well as the influence of linear per-
spective (a monocular cue to depth) on size perception. In
the Ponzo illusion, we see two objects that take up the same
amount of space on our retinae as different in size because
of their perceived differences in depth. In the Ames room,
we put two people of normal size into a room that is anything
but normal. When viewed through a peephole on the side of
one of the walls, the perception is of a very large person in
one corner and a very small person in the other corner. The
room, however, looks normal. The moon illusion is another
powerful illusion related to size–depth relations. When we
see the full moon on the horizon (such as when it rises at
sunset and sets at sunrise), we perceive it as being larger
than when it is higher up in the sky.
REVIEW QUESTIONS
1. How do jumping spiders use their multilayered ret-
inae to perceive depth? How is this different from
mammalian depth perception?
2. What are the oculomotor cues to depth? How do they
work, and how do they give us depth information?
3. Describe three pictorial monocular depth cues. How
does each one provide us information about depth or
distance?
4. What is motion parallax? How is it used as a cue for
depth?
5. What is meant by the term stereopsis? Why does
stereopsis require two frontally placed eyes?
6. What is the horopter? How do crossed and uncrossed
disparity relate to the horopter? What is meant by
zero disparity? Where would such a point lie along
the horopter?
7. What is the correspondence problem? How do ran-
dom-dot stereograms address the theoretical issues
raised by the correspondence problem?
8. What evidence suggests that stereopsis is not
innate? What areas of the brain appear to be involved
in stereopsis?
9. What is meant by size–distance invariance? What is
size constancy? Describe one illusion that illustrates
each principle.
10. What data exist to support the idea that stereop-
sis can help athletic performance? Choose a sport
not considered in this chapter (e.g., volleyball) and
describe how depth perception might be critical to
perform well in that sport.
PONDER FURTHER
1. In many ways artists are our first developers of virtual
reality. On flat canvases and other surfaces, they cre-
ate the impression of depth, and yet they are restricted
to monocular depth cues. Survey artwork online, or by
any other way you have access to it, and determine
the depth cues that artists use to create the percep-
tion of depth.
2. Review ISLE 7.8, all parts but particularly ISLE 7.8b.
Panum’s area of fusion suggests that we get our best
depth perception from binocular disparity in a very nar-
row range around the horopter. Large differences in
depth do not benefit nearly as much from our having
binocular disparity. So, consider 3D movies that use
binocular disparity. You are giving advice to the director
on the most effective use of binocular disparity for a
3D movie. What would you tell this director?
KEY TERMS
Accretion, 197
Ames room, 215
Atmospheric perspective, 194
Binocular cells, 209
Binocular disparity, 201
Correspondence problem
(depth perception), 206
Corresponding points, 202
Crossed disparity, 203
Sensation and Perception224
Cue approach to depth
perception, 189
Deletion, 197
Diplopia, 203
Familiar size, 192
Horopter, 202
Linear perspective, 193
Monocular depth cues, 189
Moon illusion, 216
Motion parallax, 196
Movement-based cues, 189
Müller–Lyer illusion, 214
Noncorresponding points, 202
Occlusion, 190
Optic flow, 198
Panum’s area of fusion, 203
Pictorial cues, 189
Ponzo illusion, 215
Random-dot stereograms, 208
Relative height, 191
Relative size, 191
Shadows, 195
Size constancy, 213
Size–distance invariance, 211
Stereopsis, 200
Texture gradient, 194
Uncrossed disparity, 204
Vergence, 199
Virtual reality, 219
Visual angle, 212
Zero disparity, 204
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
7.1 Explain monocular depth cues and how they work to allow us
to perceive depth with one eye.
7.2 Compare the different oculomotor curves in their effectiveness
as depth cues.
Extremal Edge: A Powerful Cue to Depth Perception and
Figure-Ground Organization
7.3 Summarize the principle of stereopsis and how it applies to
human depth perception.
Seeing in 3-D With Just One Eye: Stereopsis Without
Binocular Vision
Going Binocular: Susan’s First Snowfall
Losing Stereo Vision and Depth Perception—a Personal
Account From Oliver Sacks
Jumping Spiders
7.4 Sketch the correspondence problem and how it must be solved
for stereopsis.
7.5 Explain the concept of size perception and the inferential
nature of its determination.
Distance Perception
7.6 Diagram the concept of size constancy and how it functions in
our visual system.
7.7 Demonstrate your understanding of illusions of size and depth
and how they help us understand the operation of our visual
system.
Dynamic Müller Lyer Illusion
The Dynamic Ebbinghaus
Tim Flach/Iconica/Getty Images
8Movement and Action
Mads Perch/Stone/Getty Images
LEARNING OBJECTIVES
8.1
Explain the concept of a motion threshold and what
variables influence that threshold.
8.2 Describe the anatomy of the visual system dedicated to motion perception.
8.3 Discuss how we infer form from the perception of biological motion.
8.4 Summarize the concept of an affordance.
INTRODUCTION
A number of major world cities, such as Los Angeles, San Francisco, Port-au-Prince
(Haiti), Tokyo (Japan), Reykjavik (Iceland), Ankara (Turkey), and Wellington (New
Zealand), to name just a few, lie in earthquake zones. Anyone who has ever lived
through an earthquake understands how motion can induce fear. Once the earthquake
starts, things that are not supposed to move, like walls and floors, may start shaking,
undulating, and cracking. Other things start falling—books, jars, glasses, and televi-
sions. People outside their homes may see bridges sway and roads crumble. Cities heav-
ily fortified against earthquakes (e.g., San Francisco, Tokyo) design their buildings to
sway in an earthquake, so as to avoid cracking and crumbling. However unnerving
this may be for residents of these cities, it saves countless lives when these highly popu-
lated cities are struck by earthquakes. But simply watching swaying buildings is rather
unnerving. Only when all this motion subsides can people relax. What many find strik-
ing about perceiving motion during an earthquake is that objects we generally perceive
as stable—walls, roads, and buildings—move. This type of motion induces fear. Clearly,
perceiving motion is important and vital for human beings.
Imagine now that you are on an airplane, perhaps one bound from San Francisco
to Tokyo on your way to a conference on sensation and perception research. You are
7 miles above the Pacific Ocean, traveling at nearly 1,000 km/h (621 mph). A seren-
dipitous error on the airline’s part bumped you up into first class. Therefore, you are
sitting in a comfortable reclining chair, eating warmed nuts and drinking champagne,
completely unaware that you are moving at nearly the speed of sound (which is 1,236
km/h). Why is it that you are not perceiving the incredible motion that is occurring
in this situation? With the shades drawn shut, you do not see your motion relative to
the ground below. You see only the tranquil scene of people relaxing in their first-class
seats, feeling smug that they are comfortable while the rabble behind them is not. Your
world is stable and not moving.
ISLE EXERCISES
8.1 Relative Motion
8.2 Time-Lapse Motion
8.3 Motion Thresholds
8.4 Apparent Motion
8.5 Correspondence
Problem in Motion
(Wagon Wheel Effect)
8.6 Induced Motion
8.7 Reichardt Detectors
8.8 Corollary Discharge
8.9 Eye Movements
8.10 Correlated Motion
8.11 Motion Aftereffect
8.12 Structure From
Motion
8.13 Biological Motion
8.14 Cat and Laser
Pointer
8.15 Optic Flow
8.16 Rotating Snakes
8.17 Spiral Staircase
8.18 Illusory Rotation
8.19 The Furrow Illusion
228 Sensation and Perception
You may remember from physics class that all motion is relative. In the case of the
airline passenger, everything around her is moving at the same speed. The comfortable
chair, the champagne glass, the magazines, the flight attendant, and the passenger are all
moving together at the exact same speed. We may feel the rumbling of the engines and the
rumbling in our stomachs when the plane encounters turbulence. But we feel this motion
rather than see it. Unless you look out the window, you will not perceive motion visually
under these circumstances. It is not all that dissimilar to why we do not perceive the
rotation of the Earth itself (see ISLE 8.1). Everything around us, including us, is rotating
with the Earth, so we do not perceive the motion. In this sense, we can define motion as
a relative change in position over time.
Our visual systems must be able to attend to motion. Perceiving motion allows us to
move ourselves as well as to time the arrival of incoming objects, whether they are cars,
baseballs, cheetahs, or falling coconuts. One can imagine that motion perception evolved
to help our distant ancestors perceive incoming predators and fleeing prey. Nowadays,
motion detection is important in driving cars, crossing city streets, playing sports, and
watching movies. Thus, at its basic level, there are a number of features our visual system
must be able to perceive. First, we need to know if moving objects are approaching us or
heading away from us. In many cases, such as a fast-moving train, we need to know if an
object is heading toward us so that we can get out of its way. In other cases, we need to
know if an object is moving away from us, so that we can slow it down, as in the case of a
child trying to catch an ice cream truck. Thus, the direction of motion, toward us or away
from us, is critical. But we must be able to perceive this motion across three dimensions—
directly ahead of us, to our sides, and above (or below) us. An object going straight up
may not represent a danger, but an object coming down, and being accelerated by gravity
as it does so, may represent a danger. Finally, we must also be able to estimate the speed
of moving objects. A woman and child walking may not constitute a danger, but speeding
race cars may very well be a danger (Figure 8.1). You can work with an interactive illus-
tration of relative motion and frame of reference on ISLE 8.1a.
HOW DO WE PERCEIVE MOTION?
8.1
Explain the concept of a motion threshold and what
variables influence that threshold.
Motion Thresholds: How Slow and How Fast?
Think about watching a spinning bicycle wheel. When the rider first starts peddling, we
see the motion of the spokes of the wheel. As the bicyclist pedals faster, the spokes start
spinning faster and faster. We can see this motion, but eventually, the wheel is moving
ISLE 8.1
Relative Motion
Motion: a change in position
over time
©
iS
to
ck
ph
ot
o.
co
m
/m
ev
an
s
(b)
©
iS
to
ck
ph
ot
o.
co
m
/m
on
ke
yb
us
in
es
si
m
ag
es (a) FIGURE 8.1
Motion Is Relevant
(a) We see this woman and her
child approaching us. Their
speed, however, probably does
not cause concern. (b) These race
cars bearing down on us would
cause concern and, hopefully, a
sudden leap off the road.
229 Chapter 8: Movement and Action
so fast that we can no longer track the
individual spokes. Instead, we see a
blur of motion. There are two points
to be made here. First, some motion is
so slow that we cannot perceive it, and
other motion is so fast that we cannot
perceive it. Think of a plant bending
its leaves toward the direction of sun-
light. Most plants move their leaves
extremely slowly, so slowly in fact
that human eyes do not perceive the
motion. Only when we view a plant
through time-lapse photography do we know that it is actually moving (Figure 8.2)
(ISLE 8.2). Similarly, movements that are extremely fast, such as the spinning of an
automobile’s wheel, may simply be too fast for us to perceive. Many sources of light
flicker, such as our computer screens, but they do so at such a rapid rate that we do not
perceive the change.
Motion thresholds are a function of what parts of the retinae are seeing the motion.
Interestingly, we have rather poor motion thresholds in the foveal regions of our ret-
inae. But our motion thresholds are much lower (i.e., better) than our acuity in the
periphery of our retinae. You may occasionally become aware of this, when you detect
motion to your side and move your eyes and head to engage with the oncoming motion.
Motion thresholds also nicely illustrate the importance of peripheral vision. Most of
the functions of the visual system already discussed in this book have involved the
region of the visual field near and around the fovea. Color and much of the discussion
of form relate to the fovea and near it. Yet motion is a function that does very well at
the periphery. It is tempting to think of our peripheral vision as merely poor vision, or
a poor version of how vision operates in the fovea. However, that would be a mistake.
Vision at the periphery is not so much poorer as it is different. The relative importance
of acuity and motion in the fovea and at the periphery gives some insight into this
difference. A moving stimulus at the periphery seems to grab the attention, and it may
direct the fovea over to this stimulus.
As with any other perceptual feature of vision, we can ask a few basic psychophys-
ical questions about motion thresholds. For example, how slow can motion be if we
are to still perceive it as motion? Do we see snails moving or plants shifting their leaves
toward the sunlight? The answer may be yes for the snails but no for the plants. Because
snails are small objects that move slowly, their motion has few consequences for us, so
we may not ordinarily attend to snails in motion. But if we do, we can probably detect
their motion as they slime their way up the sides of our houses. We know that for us to
detect movement, an object must move at least 1 minute of 1 degree across the retina
to be detected (that’s 1/60 of 1 degree of visual angle). Thus, our absolute threshold for
motion detection will be a function of the speed of the moving object and its distance
from us.
At the other end of the spectrum, we can ask, at what high speed do we lose the
ability to track motion? Can we follow the motion of a supersonic jet? Can we follow
the individual rotations of a car’s wheels spinning when the car is moving at 70 mph?
We know that such thresholds will be context dependent, so specific answers cannot
be given. The brightness of an object, the size of the object, and the amount of time the
object is visible will influence motion thresholds. In general, we can usually perceive fast
motion, even if we cannot track it. Nonetheless, some objects move at such high speeds
that we just cannot see them (e.g., a bullet shot at 1,500 feet per second). You can
examine your own motion thresholds at different locations on your retina in ISLE 8.3.
FIGURE 8.2 Blue Hyacinth Blooming
©
iStockphoto.com
/nickp37
ISLE 8.2
Time-Lapse Motion
ISLE 8.3
Motion Thresholds
230 Sensation and Perception
Real and Apparent Motion
Motion in the world is created by the con-
tinual change in position of an object rela-
tive to some frame of reference. That is, we
watch the cat run across the kitchen tiles.
We watch the leaves of the trees bend back
and forth with the sky in the background.
We watch ducks swim across the pond.
This is real motion. However, human
beings also perceive a number of forms of
illusory motion, that is, situations in which
we perceive motion when none actually
occurs. One form of this illusory motion is
apparent motion. Apparent motion is the
appearance of real motion from a sequence
of still images (Figure 8.3; also see ISLE
8.4 to explore apparent motion). Apparent
motion occurs whenever stimuli separated
by time and location are actually perceived
as a single stimulus moving from one loca-
tion to another. Apparent motion is the
basis of our sense of motion in watching
videography and animation, and it forms
the basis for much of our entertainment in
the form of television, movies, and com-
puter games. When we watch Iron Man
flying across the sky in the movies, what
we are seeing is apparent motion. The pat-
tern of lights on your screen creates an illu-
sion that an object is moving.
Apparent motion includes beta motion
(optimal motion), in which an object is perceived as realistically moving on the basis of what
is actually a series of stationary images being presented sequentially (Figure 8.4). Beta motion
is the basis of motion seen in movies. It is similar to but different from phi motion, the basis
of motion in the displays in Las Vegas. In beta motion, the perceived motion is indistinguish-
able from real motion, while in phi motion, you perceive motion but can see that the ele-
ments, like the individual bulbs in the Las Vegas displays, do not move. In both beta motion
and phi motion, the images are turned on and off quickly to induce the perception of motion.
You can see both types of motion in ISLE 8.4 by changing how fast the dots go on and off.
Phi motion forms the basis of billboard displays, such as the famous Times Square
signs that depict stock market information. You can work with an interactive illus-
tration of apparent motion, both beta and phi, on ISLE 8.4. Indeed, all the motion
FIGURE 8.3 Kinetoscopic Record of a Man Sneezing
Filmstrip of a man sneezing for Thomas Edison’s Kinetoscope.
Jo
hn
S
pr
in
ge
r C
ol
le
ct
io
n/
Co
rb
is
H
is
to
ric
al
/G
et
ty
Im
ag
es
Real motion: motion in the
world created by continual
change in the position of an
object relative to some frame
of reference
Apparent motion: the
appearance of real motion
from a sequence of still
images
ISLE 8.4
Apparent Motion
Flash FlashDark
FIGURE 8.4
Apparent Motion Illustrated
(Beta Motion)
When these two lights are
flickered on and off at just the
right rate, it will look like a single
light is jumping from one location
to the other.
231 Chapter 8: Movement and Action
illustrations on ISLE make use of apparent motion. This is true for any movement one
perceives on a television or computer screen.
If you recall from Chapter 7, we discussed the correspondence problem with respect
to depth perception. In that case, the correspondence problem pertains to how the
visual system knows how to match objects perceived in the left eye with objects per-
ceived in the right eye. We discussed how the visual system matches objects in the
left and right eyes before object recog-
nition, as indicated by successful depth
perception in random-dot stereograms.
In this chapter, we briefly describe the
correspondence problem as it applies to
motion perception.
In motion perception, the correspon-
dence problem refers to how the visual
system knows if an object seen at Time
1 is the same object at Time 2. In most
normal vision settings, we know that an
object is the same because most objects
do not go through rapid changes across
time when they are in motion. Moreover,
we may use eye movements to track that motion across
time. But consider watching a flock of birds move across
the sky. In this case, it may be difficult to track a par-
ticular bird, but we do not see some birds flying out of
existence and others coming into existence. We see a
pattern of birds flying. This means that there must be a
way in which we keep coherence in motion perception.
The correspondence problem is illustrated in Figure 8.5.
You can see an illustration of the issues involved in the
correspondence problem on ISLE 8.5, which shows the
wagon-wheel effect. In the wagon-wheel effect, we per-
ceive the direction of motion in the opposite direction of
the actual motion.
Another motion-based illusion is induced motion.
Induced motion means that one moving object may
cause another object to look like it is moving. The classic
example of induced motion is the movement of clouds at night, which may make it
seem as if the moon is moving (Figure 8.6). The clouds moving in one direction induce
a perception that the moon is moving in the opposite direction. Similarly, the movement
of your car makes it look as if the world is rushing by you, when in fact it is you in
the car who is rushing by the world, and the surroundings are relatively motionless.
Induced motion is illusory because we misperceive what is moving relative to the other
object. Your car is really moving relative to the surface of the road, but you perceive the
road as moving relative to your stable position in the car (ISLE 8.6).
How different is apparent motion from real motion? When we watch a movie, we
suspend our knowledge that we are just looking at a screen and we feel as if we are
actually watching speeding planes and talking people. How close is it to real motion?
One question we can ask is whether there are different neurocognitive systems
involved in the perception of real and apparent motion. That is, does apparent motion
look like motion because it activates the same neural networks as real motion does?
This question was put to the test by Larsen, Madsen, Lund, and Bundesen (2006).
Larsen et al. (2006) compared the neural responses to real and apparent motion by
ISLE 8.5
Correspondence Problem in
Motion (Wagon Wheel Effect)
??
A
B C
(a) (b) (c)
FIGURE 8.5 The Correspondence Problem
How do we know that what we see at Time 1 corresponds to what we see at Time 2? The
pictured square moves up and to the left. To detect the motion, the visual system must match
points along the square at Time 1 with points along the square at Time 2.
Correspondence problem
(motion perception): how
the visual system knows if an
object seen at Time 1 is the
same object at Time 2
Induced motion: an illusion
whereby one moving object
may cause another object to
look as if it is moving
ISLE 8.6
Induced Motion
FIGURE 8.6
Cloud Movement Makes the Moon Appear to Move
©
iS
tockphoto.com
/kdshutterm
an
232 Sensation and Perception
recording brain activity with functional magnetic resonance imaging (fMRI) tech-
nology. In the apparent motion condition, participants watched a standard apparent
motion display of lights flashing back and forth such that it looked as if one light
was moving from one location to the other. In the real motion condition, participants
watched an actual light move from one location to the other. And in a control con-
dition, participants also saw two lights flashing, but the lights did not appear to be
moving. Larsen et al. then compared the areas of the brain that were active during each
stimulus. The fMRI brain scans found that the areas of the primary visual cortex that
were responsive to apparent motion were the same as those responsive to real motion.
These areas within the visual cortex were active during both forms of motion but not
during the control condition. Therefore, the region in the cortex was responding to
movement, not to flashing lights. For this reason, we can be reasonably certain that the
apparent motion participants view in experiments generalizes to motion perception of
actual moving objects.
TEST YOUR KNOWLEDGE
1. What is the correspondence problem as it applies to motion? How is it best
solved?
2. What is the difference between phi movement and beta motion?
THE NEUROSCIENCE OF
VISION AND MOTION
8.2 Describe the anatomy of the visual system dedicated to motion perception.
Motion Detection in the Retina
The retinae play an important role in early motion detection. We know that some types
of amacrine cells in the retina are sensitive to motion (Masland, 2012). Thus, the begin-
nings of analyzing motion occur quite early in the human retinae. We also see, in the
optic nerve that leaves the retina, the beginning of the M pathway, which codes for
motion in V1 and along the dorsal stream of vision (Tapia & Breitmeyer, 2011). The
P pathway also contributes to motion perception, as we see moving objects in color.
Thus, both pathways at the level of the retina contribute to motion perception.
Some studies have looked at motion perception in other animals. In a series of clas-
sic papers, Barlow and his colleagues investigated motion perception in the retinae of
frogs. Barlow (1953), for example, found cells in the retinae of frogs that responded
to the transition from light to dark and then to the opposite transition. Later, Lettvin,
Maturana, McCulloch, and Pitts (1968) called these cells bug detectors because they
were particularly good at identifying the movements of flies, a primary food of frogs.
The Complexity of Motion
As we often repeat in this book, perceptual processes are complex, even if we do them
effortlessly. The neuroscience of the perception of motion is no exception. First of
all, our bodies are constantly in motion—we must be able to discriminate our own
motion, both intended and unintended, from the motion of other people, animals, and
objects. Consider an eye blink—every so often we mistake our own eye blinks for
233 Chapter 8: Movement and Action
moving objects, but not very often. Usually, our visual systems take into account our
own motions and do not project them onto the perception of other objects. Even when
we are perfectly still and watching a moving object, such as a bird flying across the sky,
our visual system has a complex task. Think of a simple case of motion—a single object
moving in a straight line across the visual field. This might be a bird flying across the
sky or a person walking down the street. As we mentioned earlier, we must be able to
judge the direction, in each of the three dimensions, and the speed of this object. As we
discussed in the opening chapter, we must also be able to judge the time to impact, that
is, how long it will take before the moving object smashes into us. A bird flying fast
directly at you is not usually a desirable state of affairs, whereas a bird flying past you
is harmless. Thus, the two elements of motion detection—direction and speed—must be
coded at the neural level.
Now consider how this might be done in the visual system. We start off with the
simplest case. Your eyes are not moving. They are looking straight ahead and not track-
ing a moving object. The object is passing in front of you, moving from left to right in
a straight line, without dipping or wobbling (Figure 8.7). The visual system must be
able to correlate an object at one time (T1) in one position (P1) with the same object
at another time (T2) in another position (P2). It must also be able to distinguish this
motion from motion going in the opposite direction, that is, starting at P2 at T1 and
reaching P1 at T2. And to reiterate, we also want to know the approximate speed and
direction of the moving object.
Now think about this in terms of a neural circuit. We need to have neurons that have
receptive fields that include the points P1 and P2 in the visual world. But we need these
neurons to respond temporally as well. That is, we want neurons that are sensitive to
an object at P1 at T1 and then at P2 at T2, some specific later time point. We need other
neurons that fire when objects are at P1 at T1 and at P2 at T2 at a range of differences
in (T2 – T1), that is, different speeds. We also need neurons sensitive to movement
in the other direction, that is, if an object moves from P2 to P1 at a particular speed.
This allows us to track motion in the other direction. One possible model for motion
detection in neurons is shown in Figure 8.8. The neurons in this model have been called
Reichardt detectors after the German psychophysicist who first hypothesized them
(Reichardt, 1969).
If you inspect Figure 8.8 carefully, you will notice a few important features of
Reichardt detectors. In the model, you can see motion-sensitive neurons (labeled M for
motion). These M neurons are tuned to activity first in receptive field P1 and then in
receptive field P2, if there is a specific delay between the activity in the two receptive
fields. The delay specifies the speed to which this neuron is sensitive. If the delay is too
short or too long, the M neuron will not make as large a response. Similarly, if the mov-
ing object is going the other way, this neuron will not respond. Thus, this simple model
can account for both speed (as measured by delay) and direction (as measured by which
receptive field is activated first). Of course, there will be other motion-sensitive neurons
that will respond to different delays and different directions of motion. Motion-sensitive
neurons with longer delay times are sensitive to slower motion, whereas motion-sensi-
tive neurons with shorter delay times are sensitive to faster motion. We find these cells
in the magnocellular tract. You can work with an interactive illustration of Reichardt
detectors on ISLE 8.7.
Are there neurons like this in the human visual system? It turns out that there are
many neurons in V1 that show these characteristics. V1 neurons, in addition to the
features already discussed, seem to be tuned to specific directions and speeds of motion
(Orban, Kennedy, & Butler, 1986; Wang & Yao, 2011). In nonprimate species, such as
cats, there are also motion-sensitive neurons in the lateral geniculate nucleus (Wang &
Yao, 2011).
Moving spot of light
Motion in retinal image
d
d
FIGURE 8.7
Motion on the Retina
A moving object (here moving
from left to right) moves a certain
distance across the visual field. The
distance correlates with a distance
across the retina.
Reichardt detectors: neural
circuits that enable the
determination of direction and
speed of motion by delaying
input from one receptive field,
to determine speed, to match
the input of another receptive
field, to determine direction
ISLE 8.7
Reichardt Detectors
234 Sensation and Perception
Corollary Discharge Theory
Reichardt detectors work well when the eyes are stationary, but consider a situation in
which the viewer is tracking motion across a scene. What happens when our eyes are
moving? Think about watching that bird fly across the sky. Perhaps it is an eagle, and
you want to watch it soar on the wind.
As you follow its motion, your eyes and
head move as the eagle flies. Indeed,
while tracking motion, your eyes make
movements (called smooth-pursuit move-
ments) to keep the image of the eagle on
the foveae of your retinae (Figure 8.9). In
another setting, consider a tennis player
tracking a tennis ball as it approaches his
racket. His eyes track the movement of
the ball from the moment her opponent
hits the ball as it approaches his side of
the court. His eyes, head, and body must
be in continual movement to maintain
alignment with the speeding tennis ball (Figure 8.10). This continual tracking of move-
ment allows another method of detecting direction and speed of motion.
This brings us to the corollary discharge theory, an important concept in under-
standing how our visual system detects and tracks motion. The corollary discharge
theory states that the feedback we get from our eye muscles as our eyes track an object
FIGURE 8.8 Reichardt Detectors
A simple neural network for detecting motion. The signals arrive at neuron M below receptors A and B at the same time, from a neuron with a
receptive field at P1 and then from a neuron with a receptive field at P2. Depending on the time course of arrival, neuron M will determine motion
and speed.
A B
P1 P2
(a)
M
Time 1
P1 P2
Neural
signal
M
Time 2
A B
P1 P2
M
Time 3
Receptive
Field
Retinal
Detectors
A B
P1 P2
M
Time 4
Motion-
Sensitive
Neurons
A B
P1 P2
(b)
M
Time 1
A B
A B
P1 P2
Delay
in signal
M
Time 2
A B
P1 P2
M
Time 3
Receptive
Field
Retinal
Detectors
A B
P1 P2
M
Time 4
Motion-
Sensitive
Neurons
No
neural
signal
FIGURE 8.9 Smooth-Pursuit Eye Movements
As the bird soars across the sky, smooth-pursuit eye movements allow you to track the motion
of the bird. Smooth-pursuit movements are possible only in the presence of movement.
©
iStockphoto.com
/PeopleIm
ages©
iS
to
ck
ph
ot
o.
co
m
/m
ic
ha
el
m
ill
Corollary discharge theory:
the theory that the feedback
we get from our eye muscles
as our eyes track an object is
important to the perception of
motion
235 Chapter 8: Movement and Action
is important to the perception of motion. Corollary dis-
charge theory starts off quite similar to the Reichardt
detector model, with neurons that are sensitive to
movement across the retina. However, when we wish
to track an object such as a tennis ball, a command
signal must be sent from the brain to the muscles that
control eye movements. Corollary discharge theory
states that, in addition to the muscles of the eye, this
signal will be sent to areas of the brain responsible
for motion detection. This signal, or corollary discharge,
provides the brain with updated information about
the locations and speeds of moving objects (Sommer
& Wurtz, 2008). In other words, we use the fact that
we are moving our eyes and heads as a means to detect
motion in the world. It is as if our visual systems were
interpreting the situation as follows: We are making
smooth-pursuit movements with our eyes; therefore, we
must be tracking motion. This logic then allows the feed-
back from the eye movements to assist our visual system
in seeing and timing the motion.
One source of evidence for the corollary discharge theory comes from the movement
of afterimages. If you look directly at a bright light and then close your eyes, you will
see an afterimage of that light. When you move your eyes, the afterimage stays on the
exact same part of the retina. However, you sense motion. Why is this the case, if the
afterimage has not moved across your visual field? It must be because of feedback from
a corollary discharge loop. Similarly, experiments have shown that people can keep
their eyes fixated on a central point even when their eyes are being physically pushed.
Here too, even though there is no movement of objects across the visual field, we sense
motion, stemming from a corollary discharge feedback system (Bridgeman & Stark,
1991). For a demonstration of corollary discharge and how afterimages move when the
eyes move, see ISLE 8.8.
Physiological evidence for this theory comes from the discovery of real motion neu-
rons, which respond only to movements of objects but not movements of eyes. To deter-
mine the difference, these neurons must first get feedback from eye movement signals
so that they can “know” the difference. Experiments with monkeys show that these real
motion neurons in the extrastriate cortex respond when an object is moving across the
monkeys’ visual field but not when their eyes are moving and the object is stationary
(Galletti & Fattori, 2003). Corollary discharge, therefore, allows our visual system to
integrate the movements of objects with our own basic motility.
The corollary discharge theory means that one of the cues to detecting motion is the
movement of our own eyes. Thus, it is important to understand how and why our eyes
move in order to understand the nature of motion perception. We turn our attention
next to eye movements.
Eye Movements
Our visual system can perceive objects in the world that move, but, of course, we move
as well. We can move our eyes, our heads, and our bodies. We can track motion just
by moving our eyes, or we can follow the direction of a moving object by walking or
running. In this section, we are concerned with eye movements that direct our eyes
from one location to another in the visual world. This contrasts with the discussion
of eye movements with vergence, discussed in Chapter 7. Vergence refers to the eye
FIGURE 8.10 Using Smooth-Pursuit Eye Movements
While playing a sport such a tennis, our eyes and head move to track the
movement of the ball using smooth-pursuit eye movements.
©
iStockphoto.com
/PabloBenitezLope
ISLE 8.8
Corollary Discharge
236 Sensation and Perception
movements that cause our eyes to resolve a particular object or bring it into focus.
Here we are concerned with changing our gaze from one object to another or tracking
a moving object. We have already discussed how feedback from eye movements helps
our visual system sort out different forms of motion. Eye movements serve a great
many other functions as well, the most significant being the ability to direct the gaze of
our foveae on whatever stimulus in the world attracts our attention. Eye movements
allow us, for example, to read. We make small discrete movements along the page to
ensure that our foveae are directed at whatever it is we want to read right now. When
we watch moving print, such as the credits at the end of a movie, we make small eye
movements from left to right and up and down. There is a simulation of eye movements
on ISLE 8.9.
Saccades
Saccades are the most common eye movements. They are used to look from one object
to another. Saccades are very rapid—we make them in less than 50 milliseconds (ms),
and we can make approximately three saccades each second. In other circumstances,
we may need up to 1 second to plan a saccade, but once initiated, the movement is very
rapid. What characterizes saccades is the quick jump from the focus on one object to
another. When you read, you make a series of saccades along the page. When you look
up from what you are reading to see who is looking in the window, you make a saccade
from your book to the window. Then, when you change your gaze from looking at a
stationary tree to your car parked outside your house, you are also making a saccade.
Interestingly, vision is suppressed during the actual movement. That is, during the 50 ms
it takes to make the eye movement, we essentially cannot see anything new. Only when
our saccade lands at the new location do we again see.
Smooth-Pursuit Eye Movements
Smooth-pursuit eye movements are the voluntary movements we use to track moving
objects. We can make smooth-pursuit eye movements only when there is an actual mov-
ing object in the environment. In an environment without movement, we can make only
saccades. Feedback from our visual system, however, allows our eyes to continuously
follow motion. Thus, our eyes move gradually as we follow an airplane across the sky
or a tennis ball back and forth across a tennis court.
TEST YOUR KNOWLEDGE
1. What are Reichardt detectors? What aspect of motion do they account for?
2. What are the differences between saccades and smooth-pursuit eye
movements?
MT: The Movement Area of the Brain
MT, also known as V5, is an area in the occipital cortex critical to motion perception.
MT stands for “medial temporal,” because MT is adjacent to the medial temporal lobe,
although it is itself within the extrastriatal areas of the occipital lobe. In Figure 8.11,
you can see where MT and other important motion perception areas are located in
the brain. Recall that extrastriate refers to an area in the occipital lobe, but not in V1.
MT receives input from both V1 and V2, as well as from the superior colliculus, an
important area in controlling eye movements. From the research we review shortly,
we know that MT is sensitive to both direction of motion and speed of motion. In
contrast, MT neurons are not tuned to other perceptual characteristics, such as color
or orientation. We also know that it integrates motion-sensitive cells from across V1 to
ISLE 8.9
Eye Movements
237 Chapter 8: Movement and Action
detect large-scale motion (such as a walking person). We
can consider MT a region of the brain critical to the visual
perception of motion.
Some of the most important work on the func-
tion of MT was done by the neurophysiologist William
Newsome and his colleagues (Hedges et al., 2011;
Newsome, Shadlen, Zohary, Britten, & Movshon, 1995).
They were interested in how and why neurons in MT
respond to motion, particularly larger scale motion, such
as a dog running in a park. They set out to understand
motion perception in rhesus monkeys, which have visual
brains similar to our own. We now describe some of
their experimental work linking MT to motion percep-
tion in rhesus monkeys. The logic of the experiment is
as follows. Newsome and his team trained rhesus mon-
keys to respond to particular forms of motion with spe-
cific behaviors. That is, if a visual pattern was moving
in one direction, the monkeys made one response, but
if the visual pattern was moving in the opposite direction,
the monkeys made another response. Once the monkeys
were trained, Newsome could lesion MT in the mon-
keys’ brains and see what behavioral deficits the monkeys
developed or, somewhat more humanely, conduct single-cell recordings of individual
cells within MT while the monkeys were watching movement.
In an important first experiment, Newsome and Paré (1988) trained monkeys to
respond to a pattern of dots all moving in the same direction (Figure 8.12). However,
they added an interesting manipulation. In some trials, all of the dots were moving in
the same direction (100%), but in other conditions, only 50% or 20% of the dots were
moving in sync, whereas the rest of the dots were moving randomly. As such, in these
conditions, no dot, in and of itself, could determine the large-scale motion seen in the
pattern, as any particular dot might just be going in the opposite direction. However,
clearly our visual systems must be tuned to this kind of motion. (Fish swimming in a
school or cattle in a herd provide real-world examples of this situation.) In essence, this
experiment was looking at the physiological basis of the gestalt principle of common
fate. Do we see motion when a pattern of dots is moving in a particular direction, even
if an individual dot is not? The visual system must pull information across many dots to
determine the pattern of motion in the 50% and 20% conditions (see Figure 8.12). By
the time the monkeys were fully trained,
they could detect the general pattern of
motion even when only 3% of the dots
were moving in the same direction (and
the rest were moving randomly). That is,
MT neurons integrate across any number
of local detectors to infer the general pat-
tern of motion in the display. You can see
these patterns in motion on ISLE 8.10.
Newsome and Paré (1988) then sur-
gically lesioned MT in these monkeys.
Following recovery from surgery, the mon-
keys’ performance on the direction-of-mo-
tion task was severely impaired. However,
the monkeys were not impaired at visual
Primary
visual
cortex
(V1)
Middle temporal and
middle superior
temporal areas (V5)
Superior temporal sulcusLateral fissure
Lingual
gyrus
(V3)
Motion-processing
parietal cortex
Postcentral sulcus
Central sulcus
FIGURE 8.11 Motion Areas in the Brain
In this map of the brain, you can see V1 at the back of the occipital
lobe. MT (also known as V5) is anterior in the occipital lobe, located just
above the temporal lobe. This map also shows motion-sensitive areas in
the parietal lobe.
ISLE 8.10
Correlated Motion
100% 50% 20%
FIGURE 8.12 Stimuli Used in Newsome and Paré’s (1988) Experiment
In the 100% condition, all the dots were moving in the same direction. In the 50% condition,
half the dots were moving in a consistent direction. And in the 20% condition, only one fifth
of the dots were moving in a consistent direction.
238 Sensation and Perception
tasks that involved stationary objects—only motion tasks were affected. Thus, for exam-
ple, color identification was fine, but the direction-of-motion task showed strong decre-
ments in performance. Thus, because these monkeys had been able to do motion tasks
prior to the lesioning but were impaired afterward, Newsome and Paré concluded that
MT is involved in this kind of motion discrimination.
In another experiment (Newsome, Britten, & Movshon, 1989), Newsome and his
colleagues found through single-cell recording that MT neurons fired more strongly the
more coherent or correlated the motion was. That is, there was more activity in MT
when all the dots were moving in the same direction than when only 20% of the dots
were moving in the same direction. This was the case even though the 20% motion is
salient when humans view it and presumably similarly salient to the monkeys. Thus,
these studies provided strong evidence that MT is not just a motion area but one that
is sensitive to larger scale motion.
There have also been studies using neuroimaging that confirmed the role of MT
in humans. For example, fMRI studies with human participants have confirmed the
role of MT in such large-scale movement, similar to Newsome’s studies. In humans,
as with monkeys, MT responds more to
moving stimuli than to stationary stimuli,
and more to complex movement than to
simple movement. For example, Weigelt,
Singer, and Kohler (2013) looked at the
human MT by recording activity with
fMRI technology. Weigelt et al. showed
participants moving stimuli. In some tri-
als, participants attended to the locations
of certain objects, whereas in other trials,
participants attended to the direction of
motion of certain objects. In this case, the
stimuli were identical—the difference was
what the person was attending to, either
the locations of objects or the direction of
motion. Weigelt et al. found that attention
to motion resulted in a bigger response in
MT than did attention to location. In con-
trast, they found no difference in the neural responses in V1 between the two attention
conditions. Thus, as in monkeys, the human MT is responsive to large-scale motion.
Weigelt et al.’s results can be seen in Figure 8.13.
Weigelt and her group have also found evidence that MT is active during visual
imagery that involves motion (Kaas, Weigelt, Roebroeck, Kohler, & Muckli, 2010).
That is, even when there is no actual movement present, but participants are imagining
moving objects, MT is active. In the study, participants were asked to imagine objects
moving without actually seeing the motion of those objects. They compared this with
a visual imagery condition that did not involve motion as well as an auditory imagery
task. Relative to the control conditions, when participants were engaged in motion
visual imagery, larger responses were recorded from MT. These results can be seen
in Figure 8.14. Here too, we can see how important MT is to higher order aspects of
motion perception.
Last, we turn to neuropsychology and its role in understanding the function of area
MT. Neuropsychology provides us with some of the most convincing and, at the same
time, bizarre evidence for the role of MT in motion perception. When MT is damaged,
FIGURE 8.13 Weigelt et al.’s (2013) Results
In this fMRI study, Weigelt et al. found that activity in MT was associated with attention to
movement. In these fMRI pictures, the activity in MT is highlighted in color. The results are
averaged across 15 participants.
239 Chapter 8: Movement and Action
a condition called akinetopsia or motion blindness
can arise. Akinetopsia is a rare condition in which
a patient is unable to detect motion despite intact
visual perception of stationary stimuli. Patients with
this disorder no longer see objects in motion. Rather,
their perception resembles a series of still photographs
moving one to the next. It occurs without any loss of
object recognition, color vision, or visual acuity, but
nonetheless, it can have profound effects on a person’s
vision and ability to function in a visual world.
What would the world be like for someone with
no perception of visual motion? A potential metaphor
in normal experience is being in a dark room illu-
minated by a stroboscope flickering slowly, as might
occur in some dance clubs. The room is dark except
for brief flashes in which it is illuminated. Under these
conditions, normal people may feel as if they have
motion blindness.
Several patients have been tested and shown to
have motion blindness. One of the most widely tested is a patient labeled L.M. (Zihl,
von Cramon, & Mai, 1983). Patient L.M. described the difficulty of pouring water into
a glass, because she could not see the movement of the water from the pitcher into the
glass and therefore could not tell exactly when the glass was full. Similarly, crossing a
street is difficult for L.M., because she does not know if her current image of the world
is recent and therefore how close the cars actually are to passing in front of her. From
this testimony of L.M., we can see how important it is to be able to perceive motion as
it is happening.
Schenk, Mai, Ditterich, and Zihl (2000) showed that a patient with akinetopsia had
difficulties with simple action tasks as well. When instructed to grasp moving objects,
the motion-blind patient took more time and was less accurate at grasping objects than
age-matched controls. Thus, the deficit in motion blindness extends to control of the
motor system as well as the profound perception deficits it causes. In another rare but
documented case, epileptic seizures induced temporary akinetopsia in at least one patient
(Sakurai, Kurita, Takeda, Shiraishi, & Kusumi, 2013). In summary, damage to MT in
human patients can cause a terrible motion perception deficit.
Interestingly, akinetopsia can be simulated in normal human brains. A technique called
TMS allows researchers to temporarily disable selective areas of the human brain. TMS
stands for “transcranial magnetic stimulation.” In some cases, it can increase activity in
the area of the brain to which it is applied, but it also can decrease activity. It depends on
the kind of stimulation that is applied and what behavior is being measured. Interestingly,
when TMS is applied to area MT, temporary akinetopsia results (Beckers & Zeki, 1995).
These participants will experience a temporary inability to perceive motion, which, fortu-
nately, wears off shortly after the TMS is no longer being applied.
Motion Aftereffects
One of the illusions we see quite commonly in everyday life is the motion aftereffect. Motion
aftereffects are also called the “waterfall illusion” because they occur when we stare at a
waterfall (Figure 8.15). After we have watched the falling of the water for about a minute, if
we look at a blank surface, such as a white wall, we will get a sense of motion going upward,
a. Individual hMT/V5+ regions of interest
b. Regions in�uencing left hMT/V5+ during motion imagery
1. Left anterior caudate nucleus 2. Left inferior parietal lobule
ImageryImagery
y = −38y = −10
t(11) = 2.2
p < 0.05
ControlControl
FIGURE 8.14 fMRI Results From Kaas et al. (2010)
These diagrams illustrate how MT is activated when people imagine perceived
motion, particularly 8.14a.
Akinetopsia (motion
blindness): a rare condition in
which an individual is unable
to detect motion despite intact
visual perception of stationary
stimuli, caused by damage to
area MT
240 Sensation and Perception
that is, in the opposite direction of the falling water. Perhaps
today, the most common experience of motion aftereffects
comes when we watch the credits at the end of a movie. If
you want to know where the movie was filmed, for exam-
ple, you may dutifully watch the names of the actors and
actresses scroll up the screen (apparent motion, not real
motion), the stunt staff, and the camera staff, until finally,
the credits reach the spot where they tell what town and in
what state or country the movie was filmed. At this point,
you may pause your DVD player or your mobile device’s
video player to read the information about where the movie
was filmed. When you pause the apparent motion, you
may get a definite sense of the words on the screen moving
upward after watching them scroll downward for a couple
of minutes. This illusion of a nonmoving surface moving
opposite to the movement just watched is called the motion
aftereffect or waterfall illusion. For a demonstration of
motion aftereffects, go to ISLE 8.11.
We can define a motion aftereffect as a motion-based visual illusion in which a sta-
tionary object is seen as moving in the opposite direction of real or apparent motion just
observed. Aristotle wrote about the waterfall illusion around 350 BCE. He described
watching the water tumbling down the falls for several entranced minutes. He then
fixed his gaze on a stationary object and experienced the illusion of that object’s moving
upward, opposite the direction of the waterfall (see Figure 8.15).
The motion aftereffect suggests that motion neurons in the occipital cortex may
have an opponent system, similar to that for color vision. Because we see movement
opposite the direction of the motion we were just watching, the motion aftereffect
suggests that movement in one direction is linked to movement in the opposite direc-
tion. Thus, upward and downward motion is an example of motion contrast, just
as red and green are color contrasts. Consider two motion-sensitive neurons in area
MT of the occipital cortex. One neuron, N-l, is sensitive to motion in the upward
direction, whereas N-r is sensitive to downward motion. Activity in N-l may prompt
inhibition in N-r, but when N-l is no longer activated and the inhibition is turned off,
we will sense the downward motion that has been inhibited. Of course, neurons are
sensitive to many features in addition to the one under discussion. Thus, N-l might
also have particular brightness, orientation, and speed preferences. For example, N-l
might be stimulated by a dim object moving in the neuron’s preferred direction or by
a very bright object moving in a less than optimal direction for that neuron. On the
basis of this cell’s response alone, we cannot tell the difference between these two
possibilities. However, if N-r is tuned to the opposite direction of motion, but perhaps
other features, the inhibition it gets as a function of movement in the opposite direc-
tion is enough to disambiguate the N-l stimulation. Thus, motion aftereffects are an
illusory consequence of a system that allows neurons to pick out specific directions
of motion.
TEST YOUR KNOWLEDGE
1. What were Newsome and Paré (1988) interested in? What methodology did they
use to address this issue?
2. What is akinetopsia, and what does it result from?
FIGURE 8.15 The Waterfall Illusion: Motion Aftereffects
A beautiful waterfall in Tennessee. If we stare at the downward motion
of a real waterfall, we can see the aftereffect when we look at another
surface afterward.
©
iS
to
ck
ph
ot
o.
co
m
/B
am
bi
G
ISLE 8.11
Motion Aftereffect
Motion aftereffect: a motion-
based visual illusion in which
a stationary object is seen
as moving in the opposite
direction of real or apparent
motion just observed
241 Chapter 8: Movement and Action
FORM PERCEPTION AND
BIOLOGICAL MOTION
8.3 Discuss how we infer form from the perception of biological motion.
Scared animals instinctively know to stay perfectly still, especially those species that
wear camouflage on their skin or fur. Think of an arctic hare hiding in the snow from
wolves or polar bears (Figure 8.16). Its white fur allows it to blend in perfectly with the
winter snow. However, keeping still is also critical to an animal or a person attempting
to hide via camouflage. Once prey is in motion, predators can detect the motion, despite
the camouflage. Indeed, we demonstrate in this section that we are often able to detect
form directly from the perception of motion when motion cues are the only cues to
what an object is. See ISLE 8.12.
Motion perception provides us with information about what object we are observing.
Think about someone you know with a distinctive style of walking. You may know some-
one who always appears to have a hop in her step, and you may know someone else who
seems to be trudging around all the time. These motion cues may help you recognize that
person. Consider running into one of these people at night, when you cannot get a good
view of the person’s face. Detecting the style of walking may allow you to recognize the per-
son. An ingenious technique allows researchers to assess whether these assertions are true.
Johansson (1973) developed a method called the point-light walker display to
examine this phenomenon. A point-light walker display is one in which small lights
are attached to the body of a person or other animal, which is then filmed moving
in an otherwise completely dark environment. In Johansson’s experiment, small lights
were placed on a person’s body, including the wrists, elbows, shoulders, ankles, knees,
and hips. He then video recorded the person walking, running, and dancing in total
darkness. Thus, the only thing visible to viewers were the lights, and not the person’s
body (Figure 8.17). It is absolutely necessary to view the demonstration and experiment
on this topic on ISLE 8.13a. You can also go to http://www.biomotionlab.ca/Demos/
BMLwalker.html (also linked to in ISLE 8.13a) to view a demonstration.
When Johansson (1973) showed participants still photographs of the light patterns,
the participants were unable to extract any form information from the photographs.
However, when participants viewed videos of the light patterns, they were able to detect
the human form when it was walking or running. Moreover, the participants were able
to distinguish between forms of motion, including walking and running. Other studies
using similar methods have shown that human observers can distinguish between dif-
ferent animals on the basis of the patterns of their movements in point-light displays
(Blake & Shiffrar, 2007). In addition, human participants can judge age, gender, and a
person’s emotional state solely on the basis of point-light displays (Blake & Shiffrar,
2007). Finally, human observers can learn distinctive walking patterns of individuals in
point-light displays and later recognize those individuals when they see them moving in
a normal video (Westhoff & Troje, 2007). Point-light displays also allow human beings
across cultures to infer the emotional state of the person in the display (Parkinson,
Walker, Memmi, & Wheatley, 2017). Thus, these studies support the notion that pat-
terns of motion can allow us to see or infer the presence of form.
It is also possible to disrupt our usual good perception in point-light displays.
Troje and Westhoff (2006), for example, showed videos of biological motion through
point-light displays of people walking, but the videos were inverted. Under these
FIGURE 8.16 A Well-
Camouflaged Arctic Hare
As long as it stays still, it is hard to
detect.
© iStockphoto.com/photos_martYmage
ISLE 8.12
Structure From Motion
ISLE 8.13
Biological Motion
Point-light walker display:
an experiment in which small
lights are attached to the
body of a person or an animal,
which is then filmed moving in
an otherwise completely dark
environment
242 Sensation and Perception
circumstances, it was very difficult for participants to detect
the biological motion. Breaking down the coordination
between the lights on various parts of the body can also
interfere with perception under these circumstances (Troje,
2013). Interestingly, children with autism are impaired at
inferring form in point-light displays relative to matched con-
trols (Swettenham et al., 2013). Thus, variables or situations
that affect our perception of patterns can render form-from-
motion extraction more difficult. To see some of these
exceptions, go to ISLE 8.13b.
As with most successful experimental paradigms in sen-
sation and perception (and all of psychology), the point-light
display procedure has now been used while participants are
monitored by fMRI technology. The perception of biological
motion in these point-light displays is associated with activ-
ity in the posterior superior temporal sulcus in the temporal
lobe (Troje, 2013). In studies using point-light displays in
which neural activities have been monitored by fMRI, there
is more activity in the posterior superior temporal sulcus
for biological motion than nonbiological motion. Thus, this
region is not motion specific—it does not rise above base-
line activity for nonbiological motion. Rather, it seems to be
involved in the recognition of particular forms of motion,
consistent with the idea that we can use motion perception
to infer forms. In another study, Grossman, Battelli, and
Pascual-Leone (2005) interfered with the posterior supe-
rior temporal sulcus with a pulse from a TMS device. While
under the influence of TMS, normal individuals showed a
severe deficit in the perception of biological motion. As you
can see, this methodology has been enormously successful in
examining higher order levels of movement.
TEST YOUR KNOWLEDGE
1. What information does motion perception provide that
is not present in static images?
2. What is a point-light walker display? What does it tell
us about how motion contributes to form perception?
ACTION
8.4 Summarize the concept of an affordance.
Young cats existed for millions of years before the invention of the laser pointer. In
those bygone days, kittens found lots of things to play with. But with the laser pointer,
the young cat has found the ultimate human–cat interface. Even though laser pointers
were invented for less exciting reasons, including allowing professors to point to over-
head screens, laser pointers afford playing in young cats. And for lazy cat owners, laser
pointers afford play sessions with their cats without their having to get off the couch
(Figure 8.18). We will see that the concept of an affordance is critical in understanding
Person wearing
point lights
Point-light
walker display
FIGURE 8.17 Point-Light Walker Display
Lights are attached to a person’s joints. The person is filmed walking
or running in a completely dark room except for the lights on his
joints. Then the point-light displays are shown to participants. In
general, most participants can determine the type of and direction of
motion from these point-light displays alone. We can even determine
the gender of the walker from the lights alone.
243 Chapter 8: Movement and Action
the theory of the interplay between perception and
action that we are about to develop. If you are a bit tired
of studying and need a laugh, you can watch Dr. Krantz
playing the laser game with his cats on ISLE 8.14.
An affordance is the information in the visual world
that specifies how that information can be used. For
example, seeing a piano affords playing music. Seeing
an elevator affords being able to go up or down in a tall
building. For a track athlete, seeing a hurdle affords jump-
ing over it. And for a kitten, seeing the laser light of a
laser pointer affords high-speed chases across the floor.
According to the prominent vision theorist J. J. Gibson
(1979), perception is about finding these affordances in
the world. Perception, according to Gibson, is not about
whether a person can detect a very dim spot in an oth-
erwise completely dark room, but rather about percep-
tion in everyday life and how we use perception to guide
action. Animals, including people, see in an ever-changing world while constantly moving
themselves. As such, Gibson argued, we should pay more attention to the complexity of
stimuli in vision. Moreover, he argued, the goal of perception itself is to afford action, that
is, movement of the organism.
Affordances mean that perception is determined partially by meaning or function.
We see objects as stimuli with particular characteristics not just of color, depth, width,
size, and shape but also of function. An object that has no function may also not draw
our attention, whereas we seek out objects that we need at the moment. Not seeing
where your eyeglasses are, for example, may elicit some search behavior, but you are
not likely to search for an object with no apparent use. Similarly, we may judge bean-
bags to be more similar to regular chairs than we might expect on the basis of their
similarity in shape. This is because beanbags and chairs share a common function: They
afford sitting in comfort. Gibson (1979) emphasized that function drives perception.
One of Gibson’s chief contributions was to the understanding of optic flow. We discussed
optic flow in Chapter 7 as one of the motion cues to depth. We defined optic flow as a motion
depth cue that refers to the relative motions of objects as the observer moves forward or
backward in a scene. In this chapter, we focus our attention on how we perceive motion in
optic flow patterns and how they influence our action in motion. To see an optic flow pattern
of driving along a road or landing a plane, go to ISLE 8.15 (also see Figure 8.19).
FIGURE 8.18
For a young cat, a laser pointer affords hours of fun.
©
iStockphoto.com
/borzyw
oj
ISLE 8.14
Cat and Laser Pointer
Affordance: information in
the visual world that specifies
how that information can be
used
FIGURE 8.19 Optic Flow
As we move in one direction, objects appear to get bigger as they approach us. In addition to this being a
cue for depth, it also indicates motion. A driver can judge her speed by the rate at which objects are flowing
toward her.
©
C
an
S
to
ck
P
ho
to
In
c.
/n
ac
ro
ba
ISLE 8.15
Optic Flow
244 Sensation and Perception
Optic flow provides information about distance and consequently can be used to aid
in our own movement. As we discussed in the previous chapter, objects closer to us seem
to move faster past us, whereas more distant objects appear to move slowly as we move
toward them. This pattern is called the gradient of flow. In simulations, if we increase
the speed at which the observer is moving, this gradient of flow accelerates. If the speed
of the observer decreases, the gradient of flow lessens. The horizon or destination point
is the distant point at which the gradient of flow comes to zero. This point is called the
focus of expansion. As we voluntarily change directions in an optic flow pattern, this
focus of expansion will shift.
In this section, we are interested in how action and perception interact. At a sim-
ple level, knowing where you are going means that you can assess if you are actually
going in the intended direction. If your goal is to pilot your small Cessna plane from
Fort Lauderdale, Florida, to Bimini, in the Bahamas, decisions about slight deviations
in course will occur with respect to both the goal and your present position. A strong
wind starts blowing out of the east, slowing your speed, and you may seek to fly at
a different altitude. In a virtual reality experiment, Warren, Kay, Zosh, Duchon, and
Sahuc (2001) controlled the optic flow pattern that participants were viewing while
walking in a specially designed room. Participants were asked to walk toward a goal:
a red line visible in the virtual reality setup. When Warren et al. slowed or sped up the
optic flow pattern, participants adjusted their walking to be consistent with their goal
of making it to the red line. Thus, optic flow patterns can change the actions we are
engaged in. This result is consistent with many others demonstrating that optic flow
plays an important role in adjusting our movements as well as allowing us to perceive
depth (Chrastil, 2013).
In the modern world, driving a car is an important and frequent activity. Ensuring
safe driving should be—even if it is not—a national concern. Thus, examining how
drivers use optic flow is also relevant. Do drivers use optic flow patterns to ensure that
they are driving safely and in the correct direction? Some research suggests that optic
flow is one way in which drivers maintain their positions on the road. For example,
Kandil, Rotter, and Lappe (2010) were interested in what information drivers use when
driving on bends or turns. While rounding a turn, which is quite normal for drivers,
the focus of expansion will not be obvious to the driver’s visual system. Thus, Kandil
and colleagues were interested in what other cues drivers use to keep their cars on
the road and going in the correct direction while driving on curves. In their exper-
iment, people drove real cars on real roads, while their eye movements were being
recorded. The investigators recorded these eye movements as drivers drove through
a series of bends. They found that drivers kept their eyes on the focus of expansion
during straight-ahead driving. But as drivers approached bends, they took their eyes
off the focus of expansion and instead directed their eyes to the straight road segments
that were coming up. This focus on the goal of rounding the turn—the straight stretch
of road ahead—allowed the drivers to direct their cars’ movement in a smooth pattern
around the bend. New drivers tend to focus on the curve itself rather than the straight
stretch ahead, leading to more adjustments and less smooth driving. Thus, optic flow
information is one source, but not the only source, of information drivers use to adjust
their motion.
Visually Guided Eye Movements
The anatomical bases for the interaction between action and perception emerge from
the parietal lobe. The parietal lobe appears to have critical networks for integrating
Gradient of flow: the
difference in the perception of
the speeds of objects moving
past us in an optic flow display
Focus of expansion: the
destination point in an optic
flow display, from which point
perceived motion derives
245 Chapter 8: Movement and Action
muscle systems, somatosensory systems, and the visual sys-
tem. This interaction allows the smooth transition from
visual perception to guided action. The parietal lobe itself is
divided by the postcentral sulcus, which divides the anterior
parietal lobe from the posterior parietal lobe (Figure 8.20).
The anterior parietal lobe is concerned with the somato-
sensory system, a topic for a later chapter. However, the
posterior parietal lobe contains regions that are specific to
visually guided action (Snyder, Batista, & Anderson, 2000).
Studies with monkeys reveal an area known as the lateral
intraparietal (LIP) area, which is involved in the control of
eye movements. There appears to be an equivalent area in
human brains. (You can see where this region is located in
Figure 8.20.)
Colby, Duhamel, and Goldberg (1996) performed some
interesting experiments on the role of the LIP area using sin-
gle-cell recording with rhesus monkeys. In these experiments,
a monkey is required to hold fixation on a central point
(Figure 8.21). Once the monkey has started to maintain fix-
ation, the experimenters flash another point at the
near periphery relative to the fixation point. The
monkeys are trained to not move their eyes to this
new point until after it disappears. When the point
disappears, the monkeys make a saccade to this sec-
ond point, even though the light is no longer pres-
ent. The researchers were interested in what the LIP
area was doing during the original appearance of the
signal at the periphery and when the monkey actu-
ally made the eye movement. Colby et al. found that
neurons within the LIP area, which had a receptive
field corresponding to the area where the second spot
appeared, became active as soon as the spot appeared
on the screen. Activity in the LIP area then continued
as the monkey made its saccade to this spot and then
diminished afterward. Thus, the LIP area of the pari-
etal lobe is involved with both the anticipation of the
eye movement and the eye movement itself. Studies
using fMRI with humans have found an equivalent
area in the human brain that also shows activity that
reflects intended eye movements (Quiroga, Snyder,
Batista, Cui, & Andersen, 2006).
Visually Guided Grasping
As we have emphasized in this chapter, the visual system functions to provide us with
information, which we can then use to guide our actions. Toward this end, our visual
systems and our motor systems have coevolved to allow us precise control over move-
ment on the basis of continual feedback from our visual system. This aspect of vision–
action interaction can be seen in research on the control of grasping in humans and
other primates. Primate hands, especially human primate hands, are instruments of fine
Postcentral sulcusCentral sulcus
Superior
parietal lobe
Intraparietal
sulcus
Occipital
lobe
Inferior
parietal
lobe
Frontal
lobe
Lateral
fissure
Temporal lobe
A
nt
er
io
r
pa
rie
ta
l l
ob
e
Po
ste
rior
parietal
lobe
M
IP
LIP
AIP
FIGURE 8.20 The Parietal Lobe Serves
Important Functions in the Perception of Action
Studies with monkeys have revealed an area known as the lateral
intraparietal (LIP) area, which is involved in the control of eye
movements. This area is marked on the human brain shown here.
Lateral intraparietal (LIP)
area: an area of the primate
parietal cortex involved in the
control of eye movements
Receptive field
of LIP neuron Target spot
Monkey looks at
fixation point
Target spot
appears
Time = t 0 Time = t1
Target spot
disappears
Time = t 2
Saccade
Fixation point
disappears
Time = t 3
Fixation
point
Direction
of gaze
FIGURE 8.21 Experiment Showing the Function of the
LIP Region of the Parietal Lobe
Monkeys are expected to keep their eyes on a central fixation point. The
researchers can then look at the receptive field of a particular neuron in the
LIP area. A target then appears in the receptive field of that neuron. When the
target disappears, the monkey must make a saccade to that location. Activity
in the LIP area precedes the saccade.
246 Sensation and Perception
motor control. Think of all the tasks you do that require fine motor control of your
hands, from typing on your computer keyboard to knitting a sweater to changing the
spark plugs on your car. Each of these tasks requires fine motor control of the hand
combined with complex feedback from the visual system.
If you refer back to Figure 8.20, you will see an area of the posterior parietal
lobe identified as the medial intraparietal (MIP) area. This area of the parietal lobe
is involved in the planning and control of reaching movements of the arms. The
MIP area seems to be critical in guiding the movement of the arms toward a visu-
ally selected location. MIP area neurons also seem to be involved in goal-directed
arm movements (Swaminathan, Masse, & Freedman, 2013). Nearby is the anterior
intraparietal (AIP) area, a region of the posterior parietal lobe involved in the act
of grasping. Once your arms are close enough to an object that your fingers can
start picking the item up or grasping it, activation shifts from MIP area neurons to
AIP area neurons. Gallivan, McLean, Flanagan, and Culham (2013), using fMRI,
showed that the AIP area was active during visually guided movements to grasp
at specific objects. Moreover, like the LIP area, which controls eye movements, the
AIP area was also active during the planning of grasping motions. Gallivan et al.
had participants plan to grasp either small or large objects, which would require
different hand movements. Activity occurred in the AIP area before the participants
were given instructions to actually move their hands. These experiments elegantly
demonstrate the interaction between visual and motor systems in subserving percep-
tually guided action.
TEST YOUR KNOWLEDGE
1. What is meant by the term optic flow? What does it tell us about how we use
visual information to inform our own motion?
2. What is the lateral intraparietal area? Where is it in the brain, and what function
is it linked to? What is the function of the anterior intraparietal (AIP) area and
the medial intraparietal (MIP) area?
Medial intraparietal (MIP)
area: an area of the posterior
parietal lobe involved in
the planning and control of
reaching movements of the
arms
Anterior intraparietal (AIP)
area: a region of the posterior
parietal lobe involved in the
act of grasping
EXPLORATION: Motion Illusions
Illusions can be thought of as glitches in the system. At
some level, they are errors—we misperceive what is actu-
ally out there. In a perfect visual system, there would be
no illusions. But our visual system, however effective it is,
is not perfect—its mechanisms occasionally lead to errors,
which we call illusions. We have made the point that illu-
sions often occur because of unusual situations that our
visual systems were not designed to handle, but that our
visual systems are very good at handling natural percep-
tion. While viewing an illusion, we do not see what is really
present, and we do see what is not. However, illusions can
be fun. We often pay to see professional magicians enter-
tain us with illusions. And more important, illusions can
reveal to us how our perceptual systems work. By finding
when and where these mechanisms fail, we can figure out
how the perceptual system is working in the first place.
Inspection of the various motion-based illusions is no
exception to this rule.
Take a look at Figure 8.22. There is no actual movement
in this figure—how could there be, especially if you are
looking at a piece of paper in a textbook? Yet the illu-
sion of movement is powerful. When you look at the
center of one of the snakes, that snake appears station-
ary, but all the others in the figure appear to be rotating.
Dr. Kitaoka’s website (http://www.ritsumei.ac.jp/~akitaoka/
index-e.html) shows many variations on this theme. We
have already discussed the famous waterfall illusion or
247 Chapter 8: Movement and Action
motion aftereffect. This adaptation effect tells us much
about how neurons are organized in area MT of the occip-
ital cortex. It also tells us about the nature of saturation
of motion channels. Watching movement at a particular
speed exhausts the neurons tuned to motion at that speed,
leading to the characteristic sense of motion going the
opposite direction when we look away from a steadily
moving object. In this Exploration section, we address
several interesting and important motion illusions and
discuss what they tell us about motion perception. Keep
your access to the ISLE system handy. As with all illusions,
seeing them is usually necessary to understand them, so
reading this section without viewing the illusions is not
advised. And because a static book cannot show move-
ment, you will certainly need to access your electronic
resources for this section.
Illusion 1: Rotating Snakes
The illusion of rotating snakes (see Figure 8.22) was
developed by Akiyoshi Kitaoka (2005), a psychologist in
Kyoto, Japan. Because this illusion creates an illusion of
motion from a static display, you can see the motion in
Figure 8.22. It is also in ISLE 8.16. You can also visit Dr.
Kitaoka’s website (http://www.ritsumei.ac.jp/~akitaoka/
index-e.html) to view not only this illusion but many
other striking motion illusions that occur with static dis-
plays. The rotating snakes illusion is based partially on
the earlier Fraser-Wilcox spiral staircase illusion (Fraser
& Wilcox, 1979), which you can see on ISLE 8.17.
Kitaoka, however, has multiplied the effect. If you look
at the center of any particular “snake,” you can see that
the snake you are looking at is stationary. However, you
will notice that the rest of the “snakes” are in motion.
The motion is illusory—the figure is completely static.
You can test this by changing your gaze and looking at
another “snake.” Now the new snake is stationary and
the one you were just looking at appears to move. And
if you are looking at the illusion on paper rather than
on a computer screen, you know it is impossible for that
paper to move in the way you are perceiving motion. If
you are viewing the illusion on a computer screen, con-
sider printing out the illusion to convince yourself that
the motion is illusory.
The explanation of the motion induction revolves around
eye movements. As we discussed earlier, saccades are eye
movements we make in which we direct our gaze from
one location to a new location. Some of these saccades
may involve very small changes in focus. These micro-
saccades are sometimes so small that we do not even
notice them as we make them. A micro-saccade can be as
small as changing one’s focus from the first “hump” in the
letter m to the second one. According to Otero-Millan,
Macknik, and Martinez-Conde (2012), the explanation
for the rotating snakes involves these micro-saccades.
In their study, participants were shown the rotating
snake illusion and asked to indicate when the perceived
motion was at a maximum and to indicate when the
figure appeared to be not rotating. The perception of
motion was highly correlated with the micro-saccades,
which they measured via
eye tracking. Apparently, we
make small saccades along
the figure but do not notice
them. Instead, the change of
position of our eyes relative
to the figure induces an illu-
sion of motion.
Knowing this, you can focus your gaze on the center of
one snake and focus really hard on keeping your eyes still.
What you will notice when you do this is that the motion
tends to stop. Then move your eyes to a new location, and
the snakes will start to spin again. Prior to Otero-Millan
et al.’s (2012) work, it was assumed that the illusion was
caused by random drift movements of the eyes. But Otero-
Millan et al. showed that it was saccade eye movements
that induce the perceived motion.
Micro-saccades have an important function. They pre-
vent visual fading during fixation. Visual fading refers
to the loss of visual experience that occurs when nei-
ther the visual world nor our eyes are moving. What
this means is that if an image were perfectly aligned
with our retina for even a short time, there would be
FIGURE 8.22 The Rotating Snakes Illusion
©
A
.Kitaoka 2003
ISLE 8.16
Rotating Snakes
ISLE 8.17
Spiral Staircase
248 Sensation and Perception
rapid adaptation, and the image would quickly fade.
Although this never happens in the real world, in the
lab, it is possible to create a stabilized image. In a stabi-
lized image, whenever and however we move our eyes,
the visual world moves with them. That is, no matter
how we move our eyes, we are still looking at the exact
same static picture. Under these conditions, unless the
picture we are viewing changes, the image quickly fades
(Troncoso, Macknik, & Martinez-Conde, 2008). Micro-
saccades prevent this from happening in the real world
but also lead to the induction of these motion illusions
from static stimuli.
Illusion 2: Illusory Rotation
As with most illusions, you must see this one first to appre-
ciate the effect and then to understand its cause. Because
it involves apparent motion, you must go to either ISLE
8.18 or the website of this illusion’s creator, Dr. Stuart
Anstis (http://anstislab.ucsd
.edu/illusions). A static view
of this illusion is shown in
Figure 8.23. Anstis calls this
one the “spoked wheel” illu-
sion (Anstis & Rogers, 2011).
When you watch the pattern
in the illusion, you see what looks like a bicycle wheel. The
spokes of the disk are thin gray lines. These lines do not
move, nor do they change their brightness. The apparent
movement comes from the wedges between the spokes.
The movement comes from the clockwise rotation of the
gray of the wedges. Once the illusion is set in motion,
people see both the clockwise motion of the wedges and
what looks like counterclockwise motion of the spokes.
This motion is both apparent and illusory, because these
lines do not move. That is, the spokes remain absolutely
immobile, whereas the gray wedges shift position from
one frame to the next. Moreover, if you stare at the
pattern long enough and then look at a clear white screen
or sheet of paper, you will see a subtle counterclockwise
motion aftereffect. Evidently, the apparent motion of
the wedges interacts with the edge detection system to
create the backward motion of the spokes (Anstis &
Rogers, 2011).
The spoked wheel display likely arises from the inter-
action of edge contrasts that the visual system is tuned
to perceive and the detection of motion in the appar-
ent motion display. Because the motion system is very
sensitive to time, when we introduce factors that influ-
ence the visual system’s ability to discriminate stimuli
quickly, we can see illusions. In this case, it is likely that
the different grays are processed at different speeds, with
lighter grays being processed more quickly. This creates
differences in the speed of processing, which, in this
case, we perceive as the counterclockwise movement of
the spokes.
Illusion 3: The Furrow Illusion
This is another illusion developed and studied by Anstis
(2012). You can view this illusion either on ISLE 8.19
or on Dr. Anstis’s website. A static image of it appears
in Figure 8.24. Take a minute to view the illusion before
continuing to read this section. When you are looking at
the static image (Figure 8.24), you see a circle with an odd
pattern of gray and white inside it. You also see a small
yellow circle along the top and another yellow circle in the
bottom half of the larger circle. When the image is set in
motion, the yellow circles move from left to right or right
to left across the larger circle. When you look at the top
yellow circle, it moves straight across the field from left
to right and back again. However, when you look at the
top yellow circle, the lower yellow circle appears to zigzag
back and forth as it makes its way across the screen. But if
you shift your gaze and now look at the lower circle, that
circle appears to move in a straight line, and it is the top
FIGURE 8.23 The Spoked Wheel Illusion
When you see the static image in the figure, you see what looks like
a bicycle wheel. Once the illusion is set in motion, people see the
clockwise motion of the wedges, but can also see what looks like
counterclockwise motion of the spokes.
A
ns
tis
w
eb
si
te
ISLE 8.18
Illusory Rotation
ISLE 8.19
The Furrow Illusion
249 Chapter 8: Movement and Action
yellow circle that appears to zigzag back and forth. Thus,
the same image causes a different perception of motion
depending on whether we are viewing it with our foveal
vision or with our peripheral vision. Anstis argues that the
intersections between the grating within the circle and the
moving colored circles cause the illusion, revealing differ-
ences in the way in which motion is perceived in the fovea
and at the periphery.
What do these illusions tell us about motion percep-
tion? In general, we could make the case that motion
perception interacts with other aspects of visual process-
ing. In these illusions, we have seen how motion can be
seen in nonmoving displays (rotating snakes) and that
motion can be induced by the interaction of apparent
movement and edge detection (illusory rotation). We
also saw how motion perception can be induced when
what is actually moving is our eyes (rotating snakes).
Because motion perception may be different in the fovea
and at the periphery, it is clear that motion perception
interacts with other aspects of visual perception. We also
hope you found looking at these illusions to be a “wow”
experience.
FIGURE 8.24 The Furrow Illusion
When the image is set in motion, the yellow circles move from left to
right or right to left across the larger circle. When you look at the top
yellow circle, it moves straight across the field from left to right and
back again. However, when you look at the top yellow circle, the lower
yellow circle appears to zigzag back and forth as it makes its way
across the screen.
http://w
w
w
.journalofvision.org/content/12/12/12 - via CCC
APPLICATION: Motion Perception
in Airplane Pilots
Airplanes are a ubiquitous part of modern human life.
Estimates suggest that on any given day, there are 1.7 mil-
lion people on airplanes in the United States and as many
as 8 million worldwide (http://www.transtats.bts.gov). Air
travel is remarkably safe with an average fatality rate in
the United States of less than one person per year. In the
United States alone, nearly 600,000 people have licenses
to pilot planes of one kind or another. In many cases, pilots
can use “autopilot” and have various computer assistance,
but in the end, most planes are flown by human percep-
tual processes. Therefore, it is of interest to examine the
processes involved in perception during flying and if there
are technological adjustments that can be made to make
pilots even better at avoiding danger and getting their pas-
sengers safely to their destinations.
Pilots and the people who train pilots must understand
perception. Pilots are trained to think about the limitations
imposed by our perceptual systems and what they can and
cannot see, hear, or feel. They are also introduced to the
malleable nature of perception, namely that pilots, like
others, are subject to illusions. In some situations, if a pilot
decides to continue on a current path based on erroneous
information from misperceiving certain factors, such as
weather conditions, runway distances, and aircraft perfor-
mance, there may be situations in which accidents occur.
Thus, finding out what perceptual errors pilots make and
how best to correct them is paramount.
Think of some of the decisions a pilot must make based
on the visual perception of moving objects. First and fore-
most, at take-off and landing, a pilot must judge his speed
relative to the lift of the airplane. Landing at a relatively
short runway means judging the angle between the air-
plane and the runway to make a smooth and safe touch-
down. For example, a pilot approaching a long runway
250 Sensation and Perception
may perceive that her plane is too high on the approach
and therefore descends too close to the ground. Pilots usu-
ally have redundant systems to determine such factors as
altitude, forward speed, vertical speed, direction, and so
forth. These are crucial to any pilot. But pilots must also
develop an ability to “feel their plane.” One such factor
is judging approximate speed by watching the plane’s
optic flow pattern on the ground (Yasuaki & Seno, 2015).
Yasuaki and Seno have shown that topographical features
on the ground can affect a pilot’s judgment of speed in the
air. For example, if there are no hills or other features, a
pilot may judge the ground to be moving faster than when
there are hills.
While flying, pilots must avoid other flying objects. Being
able to determine the difference between a small object
flying at low speeds nearby and a larger object flying at
higher speeds farther away is an important issue and one
that involves both the perception of movement and the
size constancies discussed earlier. Some accidents in air
travel occur when a pilot misjudges the distance between
his own plane and that of another. Modern pilots, of
course, have electronic traffic collision avoidance sys-
tems, but pilots must also be able to make these decisions.
Indeed, commercial airplanes have a system, the traffic
collision avoidance system (TCAS), that monitors other
aircraft near the plane and displays this information to
the pilots. This display both plots the positions and rela-
tive motions of other airplanes and changes the colors of
other airplanes on the display if their position and motion
indicate that the two planes will get too close (Livadas,
Lygeros, & Lynch, 2000).
Consider this situation described by Hershenson and
Samuels (1999). Samuels, a professor at the U.S. Air Force
Academy, was watching a plane from his office window,
a not uncommon experience when working at the Air
Force Academy. The plane, in particular, was doing very
fast maneuvers, which gave Dr. Samuels pause. No human
pilot could withstand such tight turns. This reoriented
Dr. Samuels, and he realized that he was watching a
smaller drone that was much closer to him rather than a
larger plane at some distance. Motion-in-depth is judged
by its approximate distance. An object seen moving will
be perceived as slower and smaller up close but faster and
larger when farther away. Thus, according to Hershenson
and Samuels, when the smaller craft or drone is perceived
as a larger airplane flying at a farther distance, the percep-
tion will be of fast speed for that airplane. So, consider
the situation of the observer. This illusion of speed occurs
because the larger airplane appears to travel a greater
distance in the same time that it takes the smaller craft
to travel a much shorter distance. Thus, a relatively small
plane subjectively appears to be a much larger airplane.
In addition to appearing like a larger airplane, the illusion
projects the large plane to be much farther away than is its
actual distance from the observer.
This illusion also interacts with familiarity. If we expect
to see a large plane and not a small plane, our initial per-
ception will be biased toward the larger object farther
away. Recall the role of familiar size in depth perception
from Chapter 7. Additional cues must be put in place
before we switch our perception to a smaller object mov-
ing more closely by. Because of this, the perception of the
speed of the airplane is affected, and the speed is judged
to be less than it actually is. In this illusion, the perceived
size and distance depend on an assumption of what the
object is, that is, whether it is a small or large aircraft.
This leads to the conclusion that familiarity with size
affects our perception of speed of motion (Hershenson &
Samuels, 1999).
When planes experience technical trouble, the safety of
the pilots and passengers is then most dependent on the
pilot’s ability to perceive accurately. Consider a small
plane being buffeted by powerful winds on a very dark
night. Typically, a pilot can maintain the plane’s balance
by instruments on his panel. These instruments measure
the pitch and roll and help keep the wings straight despite
the buffeting wind. However, if these instruments were to
be lost due to technical problems, the safety of that plane
would depend on the pilot’s ability to keep the plane
from rolling too much during flight (Nooij & Groen,
2011). Although this perception is more vestibular (see
Chapter 14) than visual (given it’s a dark night), proper
training allows pilots to sense the correct orientation of
the plane even without their instruments. Repetition of
this task in simulators during training also allows pilots
to be less affected by motion sickness. Indeed, spatial dis-
orientation has been linked to many airplane accidents,
and thus such training is necessary (Kallus, Tropper, &
Boucsein, 2011).
We count on our pilots to safely transport millions of peo-
ple at high speeds across long distances every day. In most
airports (e.g., Atlanta, Chicago, or Dallas), multiple planes
may be taking off or landing at any single moment. Thus,
studies that can reduce pilot error are critical. One such
pilot error is illusory perceptions, including the size–dis-
tance illusion discussed here. Luckily, there is an active
research program in many countries that helps pilots fly
more safely.
Chapter 8: Movement and Action 251
CHAPTER SUMMARY
8.1
Explain the concept of a motion threshold and
what variables influence that threshold.
Motion is a change in position over time. We need to know
if moving objects are approaching us or heading away
from us. We must be able to perceive motion across three
dimensions—directly ahead of us, to our sides, and above
or below us. We must also be able to estimate the speeds
of moving objects. Motion thresholds are a function of what
part of the retina is seeing the motion. We have rather poor
motion thresholds in the foveal regions of our retinae. But
our motion thresholds are better at the periphery of our reti-
nae. Apparent motion is the appearance of real motion from
a sequence of still images. We see apparent motion every
time we watch a movie. Induced motion means that one
moving object may appear to make another object look like it
is moving. Using fMRI, Larsen et al. showed that the areas of
the primary visual cortex that were responsive to apparent
motion were the same as those responsive to real motion.
8.2
Describe the anatomy of the visual system dedi-
cated to motion perception.
The retinae play an important role in early motion detec-
tion. We know that some types of amacrine cells in the
retina are sensitive to motion. In frogs, we find motion
detectors, known as bug detectors, built right into the
retinae. Reichardt detectors are hypothetical neurons
that are sensitive to motion. They respond to activity in
one receptive field at Time 1 and in another receptive
field at Time 2. The corollary discharge theory states that
the feedback we get from our eye muscles as our eyes
track an object is important to the perception of motion.
Thus, in addition to being sensitive to motion in receptive
fields, we use our own eye movements to help us perceive
motion. Saccades are the most common and rapid of eye
movements. They are used to look from one object to
another. Smooth-pursuit eye movements are the voluntary
tracking eye movements that allow us to slowly move our
eyes in concert with the motion of an object. MT (V5) is an
area in the occipital cortex critical to motion perception.
Newsome and his colleagues have shown that the mon-
key’s MT is responsive to large-scale movement, that is,
the movement of many objects together. Weigelt et al.
showed that the human MT is active when we are attend-
ing to motion in a moving display and even when we are
just imagining movement. Akinetopsia (motion blindness)
is a rare condition in which an individual is unable to
detect motion despite intact visual perception of station-
ary stimuli. It is caused by damage to area MT. A motion
aftereffect is a motion-based visual illusion in which a sta-
tionary object is seen as moving in the opposite direction
of real or apparent motion just observed.
8.3
Discuss how we infer form from the perception
of biological motion.
A point-light walker display is one in which small lights are
attached to the body of a person or another animal, which
is then filmed as it moves in an otherwise completely dark
environment. Even when we can see only the lights, we can
see the form of the human just from the pattern of move-
ment. Thus, we can infer form from motion perception.
8.4 Summarize the concept of an affordance.
Affordances are the information in the visual world that
specifies how that information can be used. One important
aspect of visually guided action is optic flow. Optic flow is
the relative motion of objects as an observer moves for-
ward or backward in a scene. The gradient of flow is the
difference in the perception of speed of objects moving
past us in an optic flow display. The focus of expansion is
the destination point in an optic flow display, from which
point perceived motion derives. The lateral intraparietal
(LIP) area is an area of the primate parietal cortex involved
in the control of eye movements. The medial intraparietal
(MIP) area is an area of the posterior parietal lobe involved
in the planning and control of reaching movements of the
arms. The anterior intraparietal (AIP) area is a region of the
posterior parietal lobe involved in the act of grasping.
REVIEW QUESTIONS
1. What is meant by the term motion threshold? How
would you go about measuring the speed threshold
at which we perceive motion?
2. What is real motion? What is apparent motion? Why
would a visual system evolve to perceive appar-
ent motion as real motion? What common brain
Sensation and Perception252
mechanisms underlie the perception of both forms
of motion?
3. What is a Reichardt detector? How might the visual
system use Reichardt detectors to perceive motion?
4. What is the corollary discharge theory? How does it
link eye movements to the perception of motion?
5. What is MT or V5? What area of the brain is it in?
Describe one study using single-cell recording and
one study using fMRI that support the role of this
area in motion processing.
6. What are motion aftereffects? How are they experi-
enced? What areas of the brain are involved in pro-
ducing them?
7. What are point-light displays? How have they been
used to examine the relation of form and motion per-
ception? Describe an experiment that supports that
role.
8. What is an affordance? How does the concept of an
affordance serve to bridge the gap between percep-
tion and action?
9. What is the lateral intraparietal area? Describe a
study that links this area of the brain to its role in the
relation of perception and action.
10. What is the rotating snakes illusion? Why are
micro-saccades critical in perceiving this illusion?
Why do we make micro-saccades?
PONDER FURTHER
1. Anyone who has ever watched a cat play with a laser
pointer or chase a lizard or mouse knows how sensitive
to movement a cat’s visual system is. If you were design-
ing a cat visual system from scratch (pun intended),
what variables would be different from human motion
perception?
2. In ISLE 8.8, there is a demonstration of corollary dis-
charge. What is corollary discharge? And why is it
important for a person to be able to perceive motion in
the world?
KEY TERMS
Affordance, 243
Akinetopsia (motion blindness), 239
Anterior intraparietal (AIP) area, 246
Apparent motion, 230
Corollary discharge theory, 234
Correspondence problem
(motion perception), 231
Focus of expansion, 244
Gradient of flow, 244
Induced motion, 231
Lateral intraparietal (LIP) area, 245
Medial intraparietal (MIP) area, 246
Motion, 228
Motion aftereffect, 240
Point-light walker display, 241
Real motion, 230
Reichardt detectors, 233
Chapter 8: Movement and Action 253
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
8.1 Explain the concept of a motion threshold and what variables
influence that threshold.
A Window on Reality: Perceiving Edited Moving Images
Van Gogh’s “Starry Night” Optical Illusion
8.2 Describe the anatomy of the visual system dedicated to motion
perception.
The Woman From Munich Who Is Motion Blind
8.3 Discuss how we infer form from the perception of biological
motion.
8.4 Summarize the concept of an affordance. Action’s Effect on Perception
9Visual Attention
Victor Habbick Visions/Science Source
LEARNING OBJECTIVES
9.1
Explain selective attention and divided attention, which
help us understand our scanning of the world.
9.2
Illustrate how we move attention around a scene both by using
eye movements and by using our peripheral vision.
9.3
Assess the nature of attentional capture and how it works in
our visual system to have stimuli capture attention.
9.4
Examine attentional blink and change blindness as ways of
helping us understand how attention changes over time.
9.5
Explain the differences between the orienting attention network and the
executive attention network and their roles in directing visual attention.
9.6 Identify what factors lead to the development of visual attention as we grow up.
INTRODUCTION
In 2008, the classical violinist Joshua Bell brought his $3 million, 300-year-old
Stradivarius into a busy Metro station in Washington, D.C. Bell, a renowned soloist
who has toured the world playing the most complex pieces in the classical repertoire,
plays to packed concert halls. A front-row seat can cost upward of $200. But on
that Friday morning, Mr. Bell took out his violin near an escalator in a busy sta-
tion and played his finest pieces for 45 minutes (Figure 9.1). Amazingly, few people
stopped to listen, and only one person recognized him. Most people walked right
by him, not realizing that a rock star of classical music was performing in a place
where lesser known street musicians often play. What had happened? People were
busy rushing to work, making sure they caught their trains on time, and presum-
ably were more focused on their own lives than the beautiful music emanating
across the train station. It is reasonable to guess that what had occurred was not
a failure of music appreciation but rather an illustration of the critical nature of atten-
tion. Because no one was attending to the musician in their midst, no one realized who
he was (see Chabris & Simons, 2009).
A major social concern in many countries is the scourge of texting while driving
(Figure 9.2). People lead busy lives, and in many places, such as big cities, many people
spend an inordinate amount of time stuck in traffic. The temptation to use that time to
ISLE EXERCISES
9.1 The Stroop Effect
9.2 Scanning
9.3 Spatial Cuing
9.4 Inattentional
Blindness Examples
9.5 Stimulus Salience
9.6 Feature vs.
Conjunction Search
9.7 Change Blindness
9.8 RSVP
9.9 Attentional Blink and
Repetition Blindness
9.10 Hemifield or
Unilateral Neglect
9.11 Bálint’s Syndrome
9.12 Perceptual
Bistability
9.13 Navigation in
Blindsight
256 Sensation and Perception
text to friends, family, or colleagues is strong. But research
shows that texting (and talking on cell phones) is a major
distraction and strongly impairs the ability to drive, result-
ing in many accidents and many deaths. Drivers are slower
to respond to dangers while texting and consequently get
into more accidents. This outcome for cell phone use has
been demonstrated both on the road and in the lab (Strayer,
Watson, & Drews, 2011). But why? Why can’t we drive and
text at the same time? Of course, part of the answer is that
you are looking at a small screen and not at the road, so
you can hardly make responses to objects on the road if you
cannot see them. Recall from Chapter 3 that we have good
acuity only in and near the fovea. So if the road is in the
periphery, you cannot make it out clearly. But even if you
are looking out over your cell phone so that you can direct
your vision back and forth, you are still putting yourself and
others at risk, because you have only a limited amount of
visual attention, which, when directed to your phone, is not
being directed to the potential hazards on the road. Thus,
the reason why we cannot drive well and text at the same
time revolves around the concept of attention. The question
we concern ourselves with in this chapter is the nature of
visual attention, its limits, how attention can be selected and
divided, whether we are justified in thinking about atten-
tion as unified or whether it must be considered multiple
phenomena, and, finally, the neurological underpinnings of
visual attention.
Right up front, it is important to make a distinction
among three psychological terms, which are all sometimes
called attention in everyday life. We will see that each one
has different psychological traits and different psychological
functions. The terms are alertness, attention, and awareness.
Alertness refers to a state of vigilance. When alert, we are
awake, mindful, and scanning our surroundings. Alertness,
however, implies that we are not attending to any particular
stimulus; rather, we are waiting to find out what we should be paying attention to. For
example, we want a security guard to be alert, looking out for any kind of danger at any
time. A security guard asleep at his station is not providing much security. However, we
do not want him focusing too much on one screen on his bank of monitors, because an
intruder may be coming in through another entrance. We want our security guard to be
alert but not directing his attention too much to any one source. Attention, the main
focus of this chapter, is the allocation of our limited cognitive resources to one of many
potential stimuli. This term implies selection. Thus, while visiting the zoo, you may
see many individual animals of many species within one enclosure. But you attend to
the cute baby giraffe following its mother around. At a restaurant, there may be many
people and voices, but you attend to the person with whom you are dining. Moreover,
once the security guard detects an intruder on one camera, we want him to attend to
what the intruder is doing, as he notifies the police. Finally, awareness is active thought
about something, which can be either physically present or just in our imagination.
Thus, you are aware that the bright blue sky outside indicates a pleasant day. In general,
we are aware of our surroundings whenever we are awake, but there are also bizarre
disturbances of awareness. In this chapter, we discuss patients who have lost their
awareness of their visual world, even though their eyes are still functioning (blindsight).
FIGURE 9.1 Violinist Joshua Bell
The violin soloist Joshua Bell played in a Washington, D.C., train
station for 45 minutes, and most people passed by without attending
to his artistry.
©
Z
U
M
A
P
re
ss
In
c.
/A
la
m
y
FIGURE 9.2 Texting While Driving
A major social concern is texting while driving. An important question
is, Why can’t we safely text while driving?.
©
iS
to
ck
ph
ot
o.
co
m
/n
yc
sh
oo
te
r
257 Chapter 9: Visual Attention
Because issues of awareness are close to issues of consciousness, we devote some time
to visual awareness at the end of the chapter.
Reading a textbook on sensation and perception requires your complete attention.
To understand psychophysical methods, neurophysiological techniques, and the termi-
nology of brain anatomy, you must stay focused on your reading. If you let your atten-
tion wander, you may find that you do not remember or understand the last sentence
you read. The lead pipe transformed into a feckless pecan. Did you catch that last sen-
tence, or has your attention already drifted to the person sitting near you in the library
or the chattering voice on the television? Distraction is the negative side of attention.
When we are attending to an object in the world, we gather much information about it,
but it means that we are distracted from other stimuli in our world. In some cases, this
distraction has interesting consequences. We will discuss inattentional blindness, which
describes how we miss potentially important stimuli when our attention is directed
elsewhere. And worry not—neither the lead pipe nor the pecan will be on the exam.
Why is it that we cannot attend to more stimuli at any point in time? There is some
evidence to suggest that the human brain just does not have the computing power
to follow more than one possible incoming stream of information (Dewald, Sinnett,
& Doumas, 2013). To compensate for this inability, our visual system (and cognitive
systems) have evolved to pay attention to some stimuli but not others. In this chapter,
we use the term attention to refer to several mechanisms that allow us to direct our
perceptual processes to some stimuli but not others. That is, attention is not a single
process but many processes (Chun, Golomb, & Turke-Browne, 2011). We start with
the following definition of attention: a set of processes that allow us to select or focus
on some stimuli.
There are a few features of attention worth noting at the outset. First, our focus in
this chapter is visual attention. But attention can be directed to any of our senses, such
as auditory sources or somatosensory sources. Indeed, when we are enjoying a good
meal, we can direct attention to our taste senses. Second, attention can be directed
externally to perceptual features of the world, but we can also direct attention inter-
nally to our thought processes or imaginal processes (Raymond, Shapiro, & Arnell,
1992). Thus, for example, when you think about the Mona Lisa, you may attend to
your internal imagery, which conjures up a picture of the da Vinci painting. Can you
see the landscape in the background of your mental image of the Mona Lisa? (After
conjuring up your image, have a look at Figure 9.3.) In this chapter, as in this book, our
focus is on external attention, that is, our attention to stimuli in the perceptual world.
Attention can also be sustained or temporary. Sustained attention, which often
requires sustained alertness as well, is required in many transportation-related jobs. An
airline pilot may spend 10 or 11 hours in control of a plane carrying many hundreds of
people. She must be alert but also ready to attend to any problem that surfaces either
with the plane or with the weather. Changes have been made in recent years to give
pilots time off so that their attention does not have to be engaged continuously for
hours, but in some cases, such as a trans-Pacific flight, pilots must be able to deploy
attention to their jobs for many hours straight.
Temporary attention is an everyday phenomenon as well. We may pay attention to
some stimuli for short time periods and then direct our attention to other stimuli. For
example, you may look up from your reading to see if your dog is in need of food or
a walk. For that moment, your attention is directed toward your dog rather than your
book. You pat his head and then go back to the book. Now your attention is back on
your reading. Attention can be overt. For example, when we are looking directly into
someone’s eyes, we are telling that person that we are paying attention to him. But
attention may be covert as well. We may be looking at our conversational partner but
attending to news coming from a distant radio. Our first topic is selective attention, the
how and why of focusing attention processes on one, and only one, visual input.
Attention: a set of processes
that allow us to select or focus
on some stimuli
FIGURE 9.3 Attention
to Internal Sources
How well were you able to focus on
your internal representation of the
Mona Lisa? Could you attend to the
background in your visual image?
Is it harder to attend to stimuli in
imagery than it is when we can
actually see the stimuli?
M
usée du Louvre
258 Sensation and Perception
SELECTIVE ATTENTION
9.1 Explain selective attention and divided
attention, which help us understand
our scanning of the world.
Consider the following situation. You are sitting in your
family’s living room. Your father is watching a base-
ball game on the television, your brother is playing a
video game, your mother is talking on the telephone,
and you are trying to study. Obviously, this is not an
ideal scenario for you to concentrate on your studying.
However, what you are trying to do is engage in selec-
tive attention. You are trying to focus on your sensation
and perception textbook and block out the competing
distractions. This is the essence of selective attention, in
which we direct our perceptual and cognitive resources
to one stimulus among many potential stimuli. Selective attention can be defined as
the processes of attention that allow us to focus on one source when many are present.
Selective attention can be compared with divided attention. Divided attention occurs
when we try to attend to competing sources of information (Figure 9.4). Thus, in the
example, you may be trying to study and pay attention to the balls and strikes in the
baseball game. To the extent that you are successful at this, your attention is divided.
Thus, we can define divided attention as the process of attending to multiple sources
of information.
Sometimes we cannot seem to prevent stimuli from intruding on our cognitive
processes. Some responses to stimuli seem to be automatic. Responses just jump out
regardless of where we want to direct our attention. This situation is best described
once we have an example under our belt. Try ISLE 9.1 before you continue. Your task
will be to name colors. Let us see how you do.
Make sure you have done the experiment in ISLE 9.1 before you continue reading.
In this famous task, the Stroop task, you are asked to name the colors (e.g., red or blue)
of things you see, some of which happen to be letters arranged in patterns called words.
The problem is that it is not a square or circle of color you are naming but a word and
not just a word but a word that is a color word. Sometimes the word and the color are
the same (e.g., the word green displayed in the color green), but sometimes the color
of the word is not the same as the color word (e.g., the word yellow displayed in the
color blue). You are trying to name colors, so the word should not matter. You have
directed your selective attention to the color and you should be able to ignore the word.
Right? J. Ridley Stroop (1935) tried this task and found that people could not ignore
the meaning of the words. Think of your own experience. It took longer to respond
when the words and colors did not match, and you probably made more mistakes. You
might even have gotten a bit frustrated. This study is the classic example of automa-
ticity. Automaticity refers to those cognitive processes that do not require attention.
They happen automatically. These automatic processes, both innate and learned, can
extend what we can handle in the day, but they can also interfere because we have a
harder time controlling them. Just try the Stroop task again. This chapter will focus on
attention, but it is good to remember that some perceptual and cognitive processing can
occur without attention. If you want to make a learned task automatic, it takes a lot of
practice. If you are a musician or athlete, think of all of the drills you have done to learn
basic skills, such as playing scales or dribbling a basketball.
ISLE 9.1
The Stroop Effect
FIGURE 9.4 Divided Attention
Modern life requires us to constantly divide our attention, as this family
seems to be doing.
©
S
hu
tt
er
st
oc
k.
co
m
/Y
ul
ia
Y
as
Pe
Selective attention: the
processes of attention that
allow us to focus on one
source when many are
present
Divided attention: the
process of attending to
multiple sources of information
Automaticity: refers to those
processes that do not require
attention
259 Chapter 9: Visual Attention
TEST YOUR KNOWLEDGE
1. Figure out what it might be like to not have selective attention.
2. Predict what advantages and disadvantages a person without selective
attention would have.
SPATIAL LIMITS OF ATTENTION
9.2
Illustrate how we move attention around a scene both by using eye movements
and by using our peripheral vision.
Attention and the Direction of Gaze in Space
Typically, we attend to a particular location in space by directing our gaze to that location.
Thus, when reading, you are directing your gaze at the words on the page, and when you
glance up at the baseball game, you direct your gaze to the
television screen. In almost all situations, what is being rep-
resented in our foveae is what we are attending to. If our
attention shifts, so does our gaze. When one changes one’s
attention from the textbook to the baseball game, it is usually
accompanied by a change in the direction of gaze. This move-
ment of our eyes makes sense given that the best acuity is
found on our foveae (recall Chapter 3). It is only in and near
the fovea that we have enough detail to support many of the
demands of attention. Even within a scene, we usually move
our eyes around the scene, or scan the scene, to take it all in.
For example, find the small blue flower in this photograph
(Figure 9.5). It is small, so unless you are lucky, you need
to move your gaze around the picture to find it. The main
way you look around the image is to make saccades (recall
Chapters 4 and 8). Researchers use sophisticated methods
to track eye movements. They look for where the eyes pause
between saccades, the fixations, because during saccades,
the eyes move too fast to see clearly (e.g., Zanos, Mineault,
Guitton, & Pack, 2016). In ISLE 9.2, you can simulate what an eye tracker might find as you
searched for the flower in this image. You can try other images or load your own.
An intriguing question we can ask, however, is whether it is possible to attend to
locations in the world other than our gaze direction. That is, can I be looking at my
textbook, but actually attending visually to the presence of the baseball slugger, Miguel
Cabrera, at home plate? That is, is it possible to direct our attention to an object not on
the fovea but in our periphery?
The assumption in sports is that we are capable of directing our attention to places
other than our direction of gaze. Think of the “no-look” pass in basketball. A basket-
ball player may be running down the court looking to the left at a teammate ahead
of him. Instead, he passes the ball to a player moving to his right. This may catch the
opposing team off guard, and the no-look pass results in a score, thanks to what is
called covert attention (Figure 9.6). Covert attention is when your visual attention
does not line up with your direction of gaze. The opposing player assumes that atten-
tion is directed toward the location at which the player with the ball is looking, but that
ISLE 9.2
Scanning
FIGURE 9.5 Scanning
Try to find the small flower in this photograph.
Covert attention: when your
visual direction does not line
up with your direction of gaze
260 Sensation and Perception
player is actually attending to another location, allowing
the recipient of the pass a better chance at making a bas-
ket. These passes work because attention is usually asso-
ciated with our direction of gaze, which lines up with the
foveae. Covert attention is opposed to the more normal
situation, overt attention, where our attention lines up
with where we are looking.
Michael Posner and his colleagues investigated this
phenomenon in a series of interesting experiments in the
late 1970s and early 1980s (see Posner, 1980). In this
paradigm, a participant is directed to look at a central
fixation light. In many experiments, the participant’s
eyes are monitored to ensure that she is looking at the
central fixation point. Trials will not start until the par-
ticipant’s eyes are still and focused on the fixation point
(Hughes & Zimba, 1985). The participant then sees an
arrow pointing to either the right or left of the fixation
mark. This arrow is a cue, which directs the participant’s
attention in visual space (Figure 9.7). The task of the
participant is to maintain fixation on the center point but direct her covert attention
in the direction of the arrow. Then a light appears on either the same side or the side
opposite the one to which the arrow pointed. When the light occurs on the same side
as the cue, it is said to be a valid cue, but when it occurs opposite the cue, it is said to
be an invalid cue. In Posner’s original experiment, the cues were 80% valid and 20%
invalid. With an 80/20 mix, when the cue pointed to the left, the target occurred on
the left 80% of the time (valid), whereas it occurred 20% on the right (invalid). When
the cue pointed to the right, the target occurred on the right 80% of the time (valid),
whereas it occurred 20% on the left (invalid). There were also neutral trials in which
the cue did not point to a particular side and the target occurred 50% of the time on
each side. In the neutral condition, the participant did not have a hint as to the side on
which the target would occur. The task for the participant was to respond as quickly as
possible when the target light came on. Posner’s question was, would covert attention
to the cued location facilitate the response to that location, and would covert attention
to the cued location inhibit the response in the opposite location? The investigators
measured this by recording the reaction time to indicate that the participant had seen
the target. In general, most young adults are quite fast at this task and can make their
responses in about 250 milliseconds (ms; a quarter of a second) (see Figure 9.7 for an
illustration of the procedure).
Posner (1980) varied one other feature in this experiment. Sometimes the cue
appeared at the exact same time as the target, but in other conditions the cue occurred
at set intervals, up to 400 ms before the target. Thus, Posner could also look at the time
course of any cuing effect. This variable was called stimulus onset asynchrony. Stimulus
onset asynchrony refers to the difference in time between the occurrence of one stim-
ulus and the occurrence of another, in this case, the cue and the target. If the stimu-
lus onset asynchrony is zero, there is no difference between the occurrence of the cue
and the target; that is, they occur at the same time. If the stimulus onset asynchrony is
200 ms, the target occurs 200 ms after the cue is presented. This variable turned out
to predict the results. First, when there is zero stimulus onset asynchrony, there is no
difference in reaction time between the valid and invalid signals. However, if the cue
occurs 200 ms before the target, there is a distinct advantage, with faster reaction
times for targets in the valid location than targets in the invalid location. This is also true at
longer stimulus onset asynchronies. Neutral trials were of intermediate speed (Figure 9.8).
Later work on this paradigm showed that relative to an appropriate neutral trial, most
Overt attention: when your
visual attention lines up with
your direction of gaze, that is,
your foveae
Stimulus onset asynchrony:
the difference in time between
the occurrence of one
stimulus and the occurrence
of another, in this case, the
cue and the target
D
av
id
L
ia
m
K
yl
e/
N
at
io
na
l B
as
ke
tb
al
l A
ss
oc
ia
tio
n/
G
et
ty
Im
ag
es
FIGURE 9.6 Covert Attention
Stephen Curry of the Golden State Warriors may be looking ahead, but he
may also make a no-look pass to the right or the left. Thus, his attention is
somewhere other than the direction of his gaze.
261 Chapter 9: Visual Attention
of the effect was inhibition of invalid trials rather
than facilitation of valid trials (Hughes & Zimba,
1985). This means that, relative to the neutral tri-
als, the disadvantage for invalid trials was bigger
than the advantage for valid trials. You can try a
demonstration of this experiment on ISLE 9.3.
What does this study tell us about attention?
First, it tells us that we can devote attention
covertly, that is, direct attention to a location in
space that we are not looking at directly with our
foveae. Thus, our intuition that we can be looking
at our computer screen, but attending to the cute
girl or boy at the other table in the library, is con-
firmed. Similarly, it confirms that athletes can look
one way but attend in the opposite direction, as in
the aforementioned no-look pass. But we should
not forget the loss of acuity in the periphery.
Posner (1980) likened attention to a spotlight
that we can shine on particular locations in space;
that is, there is a spatial limit to attention. Visual
attention has a size. In that spotlight, we can pro-
cess what we see there in a more efficient manner
than if the spotlight were not directed there. Much
as a spotlight on a stage directs your attention to
that location, your internal spotlight makes it eas-
ier to process information in that location, while
making other locations more difficult to pro-
cess (Figure 9.9). On the basis of the previously
described experiments, Posner also thought the
spotlight could be directed away from the region
a person is actually looking at. The spotlight met-
aphor makes a good general model of selective
attention in space, but we will see shortly how the
spotlight is not always perfect, and we can make
errors in processing even when we are attending to
a particular location in space.
An interesting extension of Posner’s paradigm
was conducted by Egly, Driver, and Rafal (1994).
As in Posner’s paradigm, a cue was given to indicate
FIGURE 9.7 The Posner Cuing Paradigm
The participant maintains fixation at the central point. Cues indicate whether the
target will appear on the left or the right. In most trials, the cue is valid; that is, the
target appears on that side. But in some trials, the cue is invalid; that is, the target
appears on the opposite side of the cue. The experimenters measure the reaction
time to indicate that the target is present.
Start *
*
*
*
*
*
*
*
Time 1
Time 1 Tim
e
Time 2
Time 2
Time 3 X
X
X
Time 3
Test probe
Response Keys
This cue is valid
This cue is invalid
Tim
e
Tim
e
220
Invalid
cues
Neutral
cues
R
e
sp
o
n
se
t
im
e
(
m
se
c)
Valid
cues
240
260
280
300
320
FIGURE 9.8 Results of
Posner’s (1980) Experiment
Valid cues result in faster reaction times
to the target than do neutral (control)
trials or invalid trials. This figure depicts
the reaction time with a stimulus onset
asynchrony greater than zero.
ISLE 9.3
Spatial Cuing
262 Sensation and Perception
where a target light would occur. However, the setup was
a little different (Figure 9.10). A target could occur at
any of four locations, as seen in Figure 9.10. A cue indi-
cated where the target was likely to occur. The target then
occurred most often in the cued location (valid cues) but
occasionally in other locations. As in Posner’s paradigm,
the target was responded to faster in the valid than the
invalid locations. However, there was also an advantage for
the invalid cue when the target appeared in the same object
as the cued location. Notice that in Figure 9.10, locations
A and B sit on the same object in the display, even though
they are in different spatial locations. That is, we can see
that Location B has a faster response time than Location C
when it is Location A that is cued. This has been called the
same-object advantage. Why? The attentional spotlight is
focused on Location A, but it travels to B more easily than
C because there is no boundary between B and A, but there
is a boundary between A and C. Thus, response times to
Area B also show some enhancement. It is also called the
same-object advantage because a location of C is equal dis-
tance from A as is B, but C is not physically connected to A
as is B, and, thus, it would not benefit from the attentional
focus. That is, Location C resides in a different object.
Thus, Egly et al.’s (1994) experiment extends the con-
cept of spatial attention. Areas in the object we are attend-
ing to will benefit even if we are not directly attending
to that area. Where might this finding apply in the real
world? Think about two wrestlers competing with each
other. One wrestler may be watching his opponent’s eyes
for any clue as to what move he will make next. Attending
to the wrestler’s eyes may allow that wrestler to more
quickly sense his opponent’s hands moving in a particu-
lar way than the hand movements of a spectator sitting
nearby. The opponent’s hands are attached to his eyes, and
thus it makes good sense if the attentional focus spreads
easily to other areas along the same object.
However, unless we are playing competitive sports,
engaging in international espionage, or participating
in Posner-paradigm experiments, we are usually not
engaged in covert attention but in overt attention. This
means that we are looking directly at what we are attending to, or when our attention
is shifted, we direct our attention and our gaze to the new stimulus. It is this overt atten-
tion, or rather failures of overt attention, that we examine next.
Inattentional Blindness
Inattentional blindness refers to a phenomenon in which people fail to perceive an
object or event that is visible but not attended to. This refers to situations in which
a well-above-threshold event or object is not seen because the person’s attention
is directed elsewhere. In the 1963 movie Cleopatra, during one scene, an airplane is
passing overhead. Given that the movie was supposed to take place in 48 BCE, this
is clearly an error on the part of the filmmakers. However, most viewers will not notice
FIGURE 9.9 The Spotlight Model of Attention
The spotlight model argues that, much like a spotlight on a stage, attention
focuses on one location in visual space and allows us to process
information better there.
©
iS
to
ck
ph
ot
o.
co
m
/j
gr
ou
p
FIGURE 9.10 Experimental Setup From Egly et al. (1994)
Participants look at the central fixation marker, but the target can occur
in any one of four locations. The researchers found that cues to the left or
right would have a faster reaction time even when the cue was directed
to either the top or the bottom of the same object (same side).
Cue
Present cue Present targetCue off
374 msC
+
D
A
B
C
+
D
A
B
324 ms
358 ms
Inattentional blindness: a
phenomenon in which people
fail to perceive an object or
event that is visible but not
attended to
263 Chapter 9: Visual Attention
the passing airplane, as it is irrelevant to the storyline and certainly not expected. Even
if you watch it now, alerted to this anachronism, you will likely miss it. Movie directors
who miss these goofs definitely benefit from inattentional blindness! Try an example.
Read Figure 9.11. What is wrong in it? Did you find the extra the? Inattentional blind-
ness is a counterintuitive finding. Most people would not predict it to occur and are
quite surprised when they find that they are susceptible to it as well.
Perhaps the most famous demonstration of inattentional blindness comes from a
study conducted by Simons and Chabris (1999), which builds on an earlier example
shown first by Neisser (1979). Before you continue reading, take a moment to view
their video of this demonstration, which can be found at Chabris and Simons’s website
(http://www.theinvisiblegorilla.com/videos.html) (see also ISLE 9.4). Like many of the
illusions and phenomena we describe in this book, seeing is believing for this demon-
stration. On Chabris and Simons’s website, the demonstration we are about to describe
is the first video provided and it is also found on ISLE 9.4. Take the time now and view
this video. It will definitely be worth it.
In the experiment, Simons and Chabris (1999) asked participants to watch a video that
shows three young college-age adults wearing white T-shirts, passing a basketball, and three
young college-age adults wearing black T-shirts, passing another basketball. The six people
are weaving among one another. The participants watching the video are instructed to count
the number of times the team with white shirts passes the basketball among themselves. Less
than a minute into the video, a person wearing a gorilla suit walks into the scene, contin-
ues through, and then walks off camera. The “gorilla” is visible at the center of the video
for about 5 seconds. Once the video is over, participants are asked how many passes they
observed, and then they are asked if they saw the gorilla. Nearly half (46%) of participants
failed to notice the “gorilla” walking across the field of view. Simons and Chabris describe
the surprise that many participants experienced when they rewatched the video to determine
that yes, the “gorilla” was visible and salient while they were attending to the basketball
passes.
In Simons and Chabris’s (1999) experiment, participants are focused on a challeng-
ing perceptual task, counting the white team’s basketball passes while ignoring the black
team’s basketball passes. It is actually quite a difficult task, and many participants were
not able to count the number of passes correctly, regardless of whether they noticed the
“gorilla.” Because of this, their attention was narrowly
focused, which then caused them to ignore other stimuli
to the extent that they did not even notice the very odd
appearance of the “gorilla” (Figure 9.12).
Inattentional blindness can be demonstrated under more
traditional laboratory conditions as well. Mack and Rock
(1998), for example, showed that participants were unable
to see a perfectly visible stimulus when their attention was
drawn to another aspect of the display. Participants main-
tained fixation on a central point (Figure 9.13). They then
saw a large cross somewhere in the parafoveal region, that
is, near the fovea. The participants’ task was to determine
if the horizontal or vertical lines of the cross were larger. In
some trials, but not all, the fixation point transformed into
a diamond shape at the exact instant the cross appeared.
Remember that the term fixation point refers to the point
at which participants’ eyes were supposed to be focused.
In trials in which the fixation point changed, participants
were asked if they had seen anything change when the cross
appeared on the screen. A majority of the participants did
ISLE 9.4
Inattentional Blindness Examples
FIGURE 9.11
Read This Sentence
Read this sentence. Did you find
the error? Read the text for more
information.
Flowers bloom
in the
the spring.
FIGURE 9.12
Inattentional Blindness (Simons & Chabris, 1999)
When viewed as a static photograph, it is hard to imagine that participants
do not see the gorilla.
264 Sensation and Perception
not report seeing the diamond, even though it
was being presented directly onto the foveae.
Thus, even when we are looking at some-
thing directly, we may not notice a change
when our attention is directed elsewhere.
Is it important that people are unable
to detect crosses changing to diamonds in
simple displays or even fail to see a person
dressed up as a gorilla in a contrived video?
The question, of course, is, does inattentional
blindness occur in real-world situations? The
answer is yes. In a stunning demonstration
of this phenomenon, Drew, Võ, and Wolfe
(2013) used expert radiologists as their test
participants. The stimuli were computed
tomographic (CT) scans taken to determine if
patients had dangerous nodules on their lungs.
The radiologists in the study had many years
of experience analyzing CT scans of lungs,
looking for these lung nodules. Embedded
in one of the CT scans was a small image of
a gorilla, about the same size a radiologist
would expect a lung nodule to be (Figure
9.14). Eighty-three percent of the radiolo-
gists failed to detect the image of the gorilla,
even though eye-tracking software showed
that many of them were looking right at the
image. The radiologists were better than the
nonexperts. Not one of the nonradiologists
in the study noticed the gorilla. Nonetheless,
even experts, operating within their sphere of
expertise, show inattentional blindness.
TEST YOUR KNOWLEDGE
1. Classify the different ways that we can direct our attention around the world.
2. Evaluate what inattentional blindness tells us about how we use attention.
STIMULUS FEATURES
THAT DRAW ATTENTION
9.3
Assess the nature of attentional capture and how it works in our
visual system to have stimuli capture attention.
We have discussed a failure of attention, inattentional blindness. Part of the explana-
tion for inattentional blindness is that our attention is directed elsewhere. We are not
attending to the stimulus an experimenter thinks is relevant, just something else. In this
section, we will discuss some of the features of stimuli that draw our attention.
FIGURE 9.13
Inattentional Blindness: Stimuli From Mack and Rock (1998)
In critical trials, the fixation point changed from a cross to a diamond. In many critical trials,
participants failed to notice the change.
Noncritical trial
Critical trial
Fixation point
Cross with arms of
different lengths
Fixation
1,500 msec
Stimulus
200 msec
Time
Time
Mask
500 msec
Fixation
1,500 msec
Stimulus
200 msec
Mask
500 msec
Critical stimulus
265 Chapter 9: Visual Attention
Stimulus Salience
You are driving down the road, and one of those new elec-
tronic billboards flashes to the next advertisement. You
look up at the billboard; that is, it is taking your atten-
tion. The billboard captured your attention using what is
called stimulus salience. Stimulus salience refers to the
features of objects in the environment that attract our
attention. Salience can be any number of features—bright
colors, fast movement, personal relevance, or, in the non-
visual domain, a loud or distinctive sound or smell. From
the auditory domain, think about nodding off during a
boring lecture in class, and then the professor calls your
name. Hearing your name is a salient stimulus, and you
are immediately paying attention—why has she called on
me? Another example might be seeing a person streak-
ing by without clothes in your university library. Because
this image (positive or negative) is novel, surprising, and
potentially important, your attention is immediately diverted from your calculus homework
to the sight of the person streaking by. In general, stimuli that are novel or unexpected will
act to divert our attention to them. The process by which a stimulus causes us to shift atten-
tion is called attentional capture (Anderson & Yantis, 2013). In Figure 9.15, we illustrate
attentional capture. Here we have a novel situation—a dog wearing reading glasses. Your
attention is captured by the dog’s glasses because this aspect of the photograph is unusual.
Most dogs indeed prefer chasing cats and ducks to reading the newspaper. You can also try
the images in ISLE 9.5, which uses the simulation of eye tracking from ISLE 9.2. Look around
the images and see what features of the image grab your attention, that is, what parts of the
image have stimulus salience. They should be where you spend the most time with your eyes.
Brian Anderson and Steven Yantis have explored the notion of attentional capture.
They found that one feature that captures our attention is a stimulus that has been previ-
ously associated with reward. Rewards are generally considered positive experiences, and
we seek them out. Thus, a stimulus associated with a reward ought to attract our attention.
Think about those “guns” or launchers that shoot T-shirts at sporting events, which are
now nearly ubiquitous at American sporting events. Fans get free T-shirts if they are lucky
enough to have one shot in their direction. Because these T-shirt launchers are associated
with rewards, they may capture our attention if we see them in a different context later.
Anderson, Laurent, and Yantis (2013) conducted an experiment in which they paired
particular colored stimuli with specific amounts of monetary reward. The participants
learned to associate these stimuli with their linked rewards. Later, participants engaged in
a different task using different objects in different colors. However, Anderson et al. peri-
odically presented a nonrelevant stimulus in a color associated with the highest reward in
the earlier task. They found that when participants saw this reward-associated object, it
captured their attention and slowed their performance on the intended task. Thus, stimuli
that have value can also capture our attention.
FIGURE 9.14
Inattentional Blindness in the Real World
In this intriguing but frightening study by Drew
et al. (2013), most radiologists failed to notice a small
image of a gorilla on a CT scan they were asked to
inspect for evidence of lung disease.
Slice 1 Slice 2 Slice 3 Slice 4 Slice 5
50% 75% 100%
Gorilla Opacity
75% 50%
Stimulus salience: refers to
the features of objects in the
environment that attract our
attention
Attentional capture: the
process whereby a salient
stimulus causes us to shift
attention to that stimulus
ISLE 9.5
Stimulus Salience
FIGURE 9.15 Attentional Capture
A dog wearing reading glasses may attract your attention more so than a
less unusual image.
©
iStockphoto.com
/Fly_dragonfly
266 Sensation and Perception
Semantic meaning may also capture our attention in a visual scene, if
that meaning is presented in the fovea. Võ and Henderson (2011) showed
participants pictures such as the ones seen in Figure 9.16. In one version
of the picture, participants saw a kitchen scene with a pot on the stove.
In a second version of the scene, participants saw a kitchen scene with
a computer printer on the stove. In an earlier experiment, participants
could move their eyes freely around the scene (Võ & Henderson, 2009). In
this 2009 study, they found that participants’ attention was drawn to the
printer and that participants spent more time looking at it than when the
object was an expected pot. However, in the later study (Võ & Henderson,
2011), participants’ ability to move their eyes around the scene was lim-
ited by the technology used to present the stimulus. In this study, atten-
tional capture did not work at the periphery. When participants could see
the printer only at the periphery, it did not attract attention in the form
of eye movements. This was true even when the printer was displayed
suspended in space above the stove. Thus, attentional capture works best
when the stimulus evoking capture is processed by the fovea.
Consider the situation described by Võ and Henderson (2011). We are
looking at a common kitchen scene but fail to notice the printer miracu-
lously defying gravity and suspended in the air above the stove. In real life,
of course, we would be moving our eyes about the scene and would pick
up this anomaly with our foveal vision. But nonetheless, this failure to
detect unusual objects constitutes a failure of attention. It should be adap-
tive to notice unusual circumstances, as such circumstances may present
a threat, especially when we see them only peripherally. With stimulus
salience, we have been discussing moving our eyes around to different
parts of a scene. Let us look further into looking around a scene for some-
thing we want to find.
Visual Search
One of the most important attentional tasks in vision is visual search, that
is, looking for and finding one object amid a background of visual distrac-
tion. Think about those security personnel at the airport. They must examine
X-ray screens looking for banned items, such as weapons, among the vast
array of objects that people bring onto airplanes. In this case, screeners must
distinguish between rifles and golf clubs and between knives and flutes. One
can think of few visual searches more important than those airport screen-
ers do countless times every day at airports. But passengers must engage in
visual search, too, when they are at the airport. When you arrive at your
destination, you must be able to distinguish the face of your sister among
a sea of other faces also waiting for passengers. In a more peaceful setting,
away from the airport, a birdwatcher may be looking for the rare eider duck
among a flock of mallard ducks. Finally, young children may spend endless
time engaged in visual search, trying to see “where’s Waldo.” In Figure 9.17,
you can engage in visual search to look for the dead tree and the satellite
dish. How long did it take you to find these objects? We can define visual
search as looking for a specific target among distracting objects.
In the laboratory, we can control many aspects of visual search. We can
control the size, shape, color, and location of the search item as well as
the size, shape, color, location, and number of distracting items. We can
then measure how long it takes a participant to find the target under these
different circumstances. Consider Figure 9.18a. This figure demonstrates a
FIGURE 9.16 Attentional Capture
Participants’ attention was drawn to the printer, and
participants spent more time looking at it than when
the object was an expected pot. However, when it was
presented at the periphery, participants failed to notice
the printer miraculously defying gravity and suspended
in the air above the stove.
267 Chapter 9: Visual Attention
Visual search: looking for
a specific target among
distracting objects
Feature search: the search
for a target in which the target
is specified by a single feature
Conjunction search: the
search for a target in which
the target is specified by a
combination of features
Feature integration theory:
a theory stipulating that some
features can be processed in
parallel and quickly prior to
using attentional resources,
whereas other visual
characteristics require us to
use attention and are done
serially and therefore less
quickly
ISLE 9.6
Feature vs. Conjunction Search
FIGURE 9.17
Visual Search
Can you find the dead tree and the
satellite dish?
feature search. You are looking for the vertical orange bar amid a mix of different stimuli.
Feature searches such as these are very easy. In Figure 9.18b, we see a conjunction search.
Here you are still looking for the vertical orange bar, but now the distractors include both
horizontal orange bars and vertical blue bars. You are searching for a conjunction between
two features—vertical and blue. Because of this, the task gets more difficult with a greater
number of distractors. You can vary the set size (number of distractors) and a host of other
factors in ISLE 9.6.
The feature search in Figure 9.18a is fast, and the number of distractors is irrelevant. We
can pick out the orange bar quickly no matter how many blue bars are shown in the figure.
This kind of sudden visual search is called “pop-out,” because the target seems to jump out
at us from the display. When we are given a feature search, we seem to be able to do the
search in parallel (Wolfe, 2012). The conjunction search in Figure 9.18b is different. Here we
are looking for the vertical orange bar among some stimuli that are also vertical and some
stimuli that are also orange. In this case, we tend not to have a pop-out effect. Instead, we
must engage in a serial search, that is, looking at every object until we find the one we are
looking for. Because of the conjunctions, we can think of these searches as being less efficient.
Feature Integration Theory
One of the prominent theories advanced to account for visual attention is feature inte-
gration theory (Treisman & Gelade, 1980). This theory stipulates that some features
can be processed in parallel and quickly prior to using attentional resources. Other
visual characteristics require us to use attention and are done serially and therefore less
quickly. In this view, there are some characteristics that simply pop out at us, such as the
gross mispelling of this wird. Most of you instantly noticed that word was misspelled,
but you might have missed that misspelling was also misspelled. Treisman and Gelade
(1980) argued that many perceptual characteristics simply pop out, but only those that
do not require attention. Consider the display in Figure 9.18b and 9.18c. The pattern
shows that conjunctions and configurations require attention. We must actively search
in time to determine the mismatched figure. In contrast, the searches that do not require
the finding of a conjunction or configuration tend to pop out at us.
268 Sensation and Perception
(a) Feature search
Find
Set size
Find Find or
(b) Conjunction search (c) Spatial con�guration
search
Correct target present Correct target absent
∼0 ms/item
R
e
a
ct
io
n
t
im
e
(
m
s)
10∼3
0 m
s/ite
m
5∼15 m
s/item
40
∼6
0 m
s/i
te
m
20∼
30 m
s/it
em
FIGURE 9.18 Visual Search Tasks
In a feature search (a), the participant must identify
the object that differs along one dimension (here,
color). In a conjunction search (b), the participant
must find the unique object among two sets of
objects. Finally, in a spatial configuration search
(c), the participant must look for a particular shape
among numerous related shapes. The feature
search takes place in parallel and therefore takes
no longer among several distractors than many
distractors. However, the conjunction search and
the spatial configuration search are done in a serial
self-terminating manner, which requires more time
the more distractors are present.
TEST YOUR KNOWLEDGE
1. Contrast the role of visual salience in capturing attention with how we direct
attention with eye movements and covert attention.
2. Collect data from feature and conjunction searches in ISLE 9.6, and examine
how the reaction times change, or not, as the number of distractors increases.
Examine what it is about the feature search that leads those targets to pop out,
and predict what other visual features might also lead to pop-out.
ATTENTION OVER TIME
9.4
Examine attentional blink and change blindness as ways of helping us
understand how attention changes over time.
Change Blindness
Imagine this situation: You are talking to a person at a party, and a group of people
separate you for a moment. What if the person you had been talking to leaves and you
269 Chapter 9: Visual Attention
end up talking to another per-
son? Would you notice? Change
blindness is the difficulty we
experience in detecting differ-
ences between two visual stimuli
that are identical except for one
or more changes to the image.
Change blindness is a very coun-
terintuitive effect. We usually
think we will notice obvious
changes when they occur, but
change blindness suggests that we
often fail to do so. What is inter-
esting about change blindness is
that even when we have engaged
our attention and are directing our visual search in a very conscious manner, we may still
fail to see the changes in an image. Consider Figure 9.19. Can you find the change? You
probably can, but it does not immediately pop out for most people viewing these images.
In a classic demonstration of change blindness, Simons and Levin (1997) conducted
a field experiment in the city of Ithaca, New York. Participants were chosen at random
on the Cornell University campus. In the experiment, an experimenter posing as a tourist
asked a person on campus for directions. When the participant started giving directions, two
other experimenters, posing as construction workers, passed by carrying a detached door.
The construction workers passed between the experimenter who had asked for directions
and the participant. At this point, Simons and Levin had the first experimenter hide behind
the door and exit the scene, while a second experimenter, the same gender and age as the
first experimenter, replaced the first. The question was whether the participant would notice
that the person to whom he was giving directions had changed. It seems obvious—if you
were just talking to one person, and he was replaced by another person, of course you would
notice the difference. However, this obvious answer turned out to be wrong most of the time.
Simons and Levin (1997) asked both professional researchers and undergraduates to
predict the outcome of this experiment before the results were made public. Both pro-
fessionals and students predicted overwhelmingly that almost all people would notice
the change. After all, the participant finds himself talking to a different person. When
the predictors were asked if they themselves would notice the difference, 95% of people
answered in the affirmative. But this is not what Simons and Levin found in the field. In
the study, nearly 50% of the participants failed to notice the change from one person
to another. Indeed, Simons and Levin have made available video of participants con-
tinuing to explain and point without noticing that they are giving directions to a new
person. Check out a video the researchers have shared online at ISLE 9.7. Let us repeat:
Nearly half of the participants failed to notice that the people they were talking to had
changed from before the workers passed by to after the workers had passed by.
Do these findings generalize to events in the real world? One such situation might be
detecting errors or “goofs” in movies. Hollywood has professional staffers who, during
postproduction, go through films to detect inconsistencies. However, invariably, some
of these inconsistencies get through and make it into the movie. Fans and aficionados
look for these errors and catalog them on websites, but most of us casual moviegoers
never notice them. Of course, nowadays, it is rather easy to look up these goofs online
before we go to movies and then annoy our friends by pointing them out, but most of
us watch these movies originally without ever noticing these errors. For example, in the
movie Iron Man 3 (2013), the characters of Tony Stark and Colonel Rhodes are talking
together via cell phone to the vice president. The vice president’s cell phone is different
from one shot to the next. Most of us, including the editing staff of the movie, failed
Change blindness: the
difficulty we experience in
detecting differences between
two visual stimuli that are
identical except for one or
more changes to the image
ISLE 9.7
Change Blindness
FIGURE 9.19 Change Blindness
Can you detect the difference between the photographs? If you cannot find the difference and give up
looking, go to the end of the Chapter Summary for the answer.
270 Sensation and Perception
to notice this when seeing the movie. Consistent with the concept of change blindness,
such errors abound in movies, but we almost always fail to notice them.
In a more typical experiment on change blindness, Rensink, O’Regan, and Clark
(1997) showed photographs of a variety of scenes, one image at a time. After a set period
of time the photograph would disappear and be replaced by a nearly identical image. In
the new photo, one aspect of the image would be different, as in Figure 9.19. The partic-
ipants’ task was to identify what had changed. If they could not immediately detect the
change, then participants were given a set amount of time to flip between the two images
and detect the change. Here, too, some participants never found the change between one
image and the other. You can try a change blindness similar to this study in ISLE 9.7.
Thus, particularly if the change from one photograph to the other is not to an
important aspect of the meaning of the photograph, we often fail to notice the change.
Moreover, the Good Samaritan giving directions is not all that concerned with what
the lost person looks like. She is simply doing the right thing by giving directions and
may not really be paying attention to the person making the request, especially if the
directions are complicated. She may be focusing on a mental map of the area. Thus, we
can think of change blindness as a deficit in attention.
One can ask what is going on at the neural level when we fail to notice these changes. After
all, we are looking at different images but perceiving them as the same. Can we see different
patterns of brain activity when we are blind to changes and when we actually recognize the
changes? This topic was investigated in an experiment by Busch (2013). Busch showed par-
ticipants a photograph of a real-world object and then showed a second photograph later
in which one of the objects in the photograph had been switched, similar to Figure 9.19.
As in all other work on change blindness, many participants failed to recognize the change
between the photographs. In Busch’s study, the participants did a final recognition task in
which they had to identify objects as being part of the study task or new to the study. Some
of these were the original object, some were changed objects, and some were entirely novel.
This part of the study was done while participants were undergoing electroencephalographic
(EEG) recording. Busch found that the EEG patterns were different for old objects and new
objects, but also that the EEG patterns were similar for items whose change had been detected
and those whose change had not been detected. Thus, some aspect of the change was being
encoded, as the changes led to neural changes, even if they did not lead to the participants’
perceiving the pictures as “different.”
Beck, Muggleton, Walsh, and Lavie (2006) used transcranial magnetic stimulation to
examine change blindness. They inhibited the right parietal lobes of some partici pants
and the left parietal lobes of other participants while those
participants were doing a change blindness task, similar
to the ones just described. They found that interrupting
the function of the right parietal lobe increased change
blindness in the sense that participants were less able to
detect the differences between photographs. On the other
hand, interrupting function of the left parietal lobe had
no effect on change blindness. This result suggests that the
right parietal lobe may be critical in this form of attention.
As we will see later, the right parietal lobe is critical in
many aspects of attention in addition to change blindness.
Attentional Blink and Rapid
Serial Visual Presentation
Consider, again, the overworked airport security agent
(Figure 9.20). She is tasked with monitoring the contents of
bags moving through the X-ray detector at the airport. But
FIGURE 9.20 The Airport Security Agent
Consider again the overworked airport security agent. Dozens of bags
pass through this machine every minute. This worker is attending to one
location but looking for changes in that space across time.
Jo
hn
M
oo
re
/G
et
ty
Im
ag
es
N
ew
s/
G
et
ty
Im
ag
es
271 Chapter 9: Visual Attention
dozens of bags pass through this machine every
minute. Essentially, from the perspective of the
agent, she is attending to only a small area of
space, but she must maintain this attention to
particular objects across time. The agent never
knows exactly when the form of a handgun may
attempt to slip past. Also along law enforcement
lines, think of the role of a SWAT team sniper.
She must attend, through the scope of a rifle, to
the people passing before her. The job here is to
locate in time when the terrorist, rather than the
innocent hostage, is in the sight of the rifle. For
a less violent example, think of a line worker
at a factory. He may have to inspect each set of
spark plugs that goes by for any design flaws.
As in airport security, this worker is attending
to one location but looking for changes in the
properties of what is in that space across time.
Attention over time rather than space has
been studied with a paradigm called the rapid
serial visual presentation (RSVP) paradigm.
In RSVP, a series of stimuli appear rapidly in
time at the same point in visual space. Indeed,
the stimuli may appear as fast as 10 items per
second. The stimuli are usually letters or pho-
tographs (Figure 9.21). The task of the partici-
pant is to determine when a particular stimulus
appears and to press a button or key as fast as possible after that stimulus occurs. Thus, the
participant might be following a series of letters flashed 10 per second. The participant’s
task is to press a response button every time the letter S occurs. In another version of the
RSVP task, photographs might be flashing by at 5 photographs per second. The participant
must hit the response button every time a photograph of a guitar player occurs. To try this
task yourself, go to ISLE 9.8.
The RSVP paradigm allows the researcher to ask many questions about what enhances
the attentional focus on the stimulus to be responded to, and the paradigm can also allow
investigation of what factors can distract our attention. For example, Zivony and Lamy
(2014) asked participants to respond when a stimulus was a particular color. The stimuli
to be judged were all presented at the point of fixation so that the images would be main-
tained on the fovea. However, they also presented various distractors at the periphery to
determine if these distractors would affect attention and interfere with performance. In
their study, they found that distractors at the periphery that were the same color as the
intended target attracted attention and reduced accurate performance on the primary
task. Think of it this way. You are driving down the road looking for signs that indicate
dangerous curves. Well, these signs are yellow. You are more likely to be distracted by
other yellow signs like a road closed or stop ahead sign rather than a white speed limit
sign. In another study, Irons and Remington (2013) asked participants to track two simul-
taneous RSVP streams, one on each side of fixation. The participants’ task was to respond
to a conjunction of color and location. Thus, they might be asked to respond to a red
object on the left but a green object on the right. This made the task quite a bit harder, and
therefore, overall errors were relatively high and reaction time was down. But they also
found that red objects presented on the right captured attention and slowed participants’
responses even further. This tendency of red to capture attention could explain the utility
of making the stop sign red.
ISLE 9.8
RSVP
Rapid serial visual
presentation (RSVP)
paradigm: a method of
studying attention in which a
series of stimuli appear rapidly
in time at the same point in
visual space
FIGURE 9.21
The Rapid Serial Visual Presentation (RSVP) Paradigm
In this study, a series of stimuli, here letters, appear rapidly in time at the same point
in visual space. The participant presses a button or key as fast as possible after a
particular stimulus occurs.
Letter on,
15 ms
Letter off,
85 ms
Betw
een 7 and 15 random
letters before T1.
Another 8 random
letters after T1.
Here, T2 is in position 2.
T1, a white letter
Position 1
(after T1)
Tim
e
Position 2
(after T1)T2, the letter X
+
D
M
T1
L
H
X
272 Sensation and Perception
Let us return to our security personnel looking at a stream of stimuli going before
them on their screen. The question here is what finding one gun does to the ability to
find the second gun right after the first gun. If we return to the simpler version of RSVP
in which one must track only one stream of letters, we can examine this question by
varying the time between the presentation of one target and a second target. Thus, if we
are following letters and responding to S, there might be a lag of 4 letters between one
S and the next, or there might be a lag of 10 letters between one S and the next target
(typically another letter). This variation on RSVP allows us to ask our question about if
detecting the first target reduces our ability to detect the second target. It turns out that
it does, if the second stimulus occurs within 500 ms (half a second) of the first stimulus.
This phenomenon is called attentional blink, which refers to the tendency to
respond less reliably to the second target in an RSVP task. Indeed, in some cases, the
participant may not report having seen the second stimulus at all. In a typical study
on attentional blink, the first and the second targets may be different. Thus, the partic-
ipant knows to look for an S and then after the S to look for a K. One can then vary
the lag between the S and the K and determine when and how the participant responds
to the K. To demonstrate that attentional blink is an issue of attention, we merely have
to change the instructions and ask participants to look only for the K. Given the same
stream of stimuli as with the S-K instructions, K-only instructions yield faster and
more accurate identifications of the K. The standard explanation of attentional blink
focuses on an inhibition mechanism that dampens responses to other targets while
processing the first target. When that target is detected, there is a finite amount of time
necessary to “reboot” the attentional mechanism for the next target. Variables that
slow this disengagement of inhibition can therefore strengthen the blink. For example,
simply inducing fatigue in participants increases the intensity and length of the blink
period (Kawahara & Sato, 2013). In contrast, there is some evidence to suggest that
experienced video game players may show reduced attentional blink because of their
training in games that resemble RSVP tasks (Kristjánsson, 2013). Finally, when the
second target is the same stimulus as the first target (e.g., S-S) and occurs right after
the first target, some participants will fail to see it at all. This phenomenon is called
repetition blindness. You can see illustrations of both repetition blindness and atten-
tional blink in ISLE 9.9.
TEST YOUR KNOWLEDGE
1. Identify the role that the attentional blink might have in increasing the problems
associated with using devices while driving.
2. Predict what elements of a scene might be subject to change blindness, and
evaluate why we might be subject to this entertaining, irritating phenomenon.
THE ANATOMY AND
PHYSIOLOGY OF ATTENTION
9.5
Explain the differences between the orienting attention network and the
executive attention network and their roles in directing visual attention.
There are numerous questions that can be asked concerning the interaction of atten-
tional processes in the brain. For example, we could take the standard brain localization
approach and ask the following: What areas of the brain may be involved in the creation
of attentional processes? Are there different brain regions for different forms of attention?
Attentional blink: the
tendency to respond less
reliably or not at all to the
second appearance of a target
in an RSVP task when the
second target occurs within
500 ms of the first target
Repetition blindness: the
failure to detect the second
target in an RSVP task when
the second target is identical
to the first one; like attentional
blink, it occurs when the
second target is presented 500
ms or less after the first target
ISLE 9.9
Attentional Blink and
Repetition Blindness
273 Chapter 9: Visual Attention
This standard approach of correlating anatomy and func-
tion has yielded numerous interesting findings, which we
discuss here. But we can also ask other questions, such
as, when we are attending to one stimulus, how does that
change the neural processing of that stimulus? Put another
way, does attention change the way sensory areas of the
brain respond to a stimulus, or does attention occur after
such processing has occurred? For example, if I am focusing
my attention on the pitcher in a baseball game, how does
that change the neural processing of the visual image of the
pitcher releasing the ball relative to a situation in which I
was focusing my attention on the batter? We can also exam-
ine what happens to the processing of nonattended visual
stimuli. So, if I am focusing on the pitcher, does my percep-
tual processing of the runner on first base change?
We start with the basic anatomy of attention.
The Orienting Attention Network
Much of what we have presented as visual attention in this chapter is a function of a
neural system called the orienting attention network (also called the dorsal attention
network), which allows us to engage in visual search and direct our visual attention to
different locations in visual space. The orienting attention network is based in circuits
in the parietal lobe (Posner & Rothbart, 2013). Damage to this network can cause a
number of neuropsychological conditions, most famously unilateral neglect (hemifield
neglect), which we consider later in the chapter. Anatomical regions associated with the
orienting attention network can be seen in Figure 9.22.
The Executive Attention Network
Beyond the orienting attention network, we need some neural processes to choose the
stimulus to attend to. This function, among others, seems to be the domain of the exec-
utive attention network. The executive attention network focuses on attention by the
inhibition of habitual responses and acts as the top-down control of attention (Posner
& Rothbart, 2013). This network allows us to inhibit auditory stimuli so that we can
concentrate on visual stimuli, or it can allow us to inhibit visual stimuli so that we can
concentrate on auditory stimuli. It also operates on attention directed at memory and
higher order cognition. For example, in the context of texting and driving, this is the
network that directs our attention to the small screens on our cell phones when we
should be attending to the road. It is also the system that must be engaged when we
attend to the color of a word (e.g., green written in red print) rather than its mean-
ing (the famous Stroop effect discussed earlier in this chapter; review ISLE 9.1 for an
example of this effect). The executive attention network is the product of processes in
the prefrontal lobe. In models of memory, the executive attention network is sometimes
called the “central executive,” because it comprises the brain regions by which attention
is directed to the desired stimulus.
Tamber-Rosenau, Esterman, Chiu, and Yantis (2011) conducted a functional mag-
netic resonance imaging (fMRI) study with human participants to examine how these
two attentional networks allocate attention in a visual attention task. Participants
watched an RSVP display, consisting of two streams of letters, one to the left of fixation
and one to the right of fixation. The researchers also used a distractor RSVP display
above and below fixation to increase the difficulty of the task and to ensure that the
participants would need their attentional networks. The above and below streams were
Orienting attention network
(dorsal attention network):
a neural system, located
primarily in the parietal lobe,
that allows us to engage in
visual search and direct our
visual attention to different
locations in visual space
Executive attention
network: a system that
focuses on attention by
the inhibition of habitual
responses and acts as the
top-down control of attention;
found in the frontal lobe
FIGURE 9.22 Attention Networks in the Brain
EAN OAN
274 Sensation and Perception
not to be attended to but rather provided background distraction. However, partic-
ipants had to monitor both the left and right streams. When the letter L occurred,
participants were to shift their attention from the left stream to the right stream of
letters. When the letter L occurred again, participants shifted their attention back to the
left stream of letters. The question Tamber-Rosenau et al. were interested in was what
areas of the brain would show activity during these attentional shifts. Their results con-
firmed involvement of both the executive attention network and the orienting attention
network. They found that areas of the brain in the prefrontal lobe and in the parietal
lobe were active during these attentional shifts. In particular, within the orienting atten-
tion network, the medial parietal lobule was active during shifts of attention. Within
the executive attention network, there was activity in the superior frontal sulcus/gyrus
(Figure 9.23). The changes in these areas reflect these two attentional networks at work.
We discuss shortly a similar study that shows how visual areas of the brain change in
response to attentional changes.
How Attention Affects the Visual Brain
Think about the Posner paradigm described earlier (Posner, 1980). In this task, people
are asked to direct their attention to a spatial location other than the location on which
their eyes are fixated. To engage in this covert attention, participants must inhibit their
tendency to want to move their eyes to the location of the to-be-attended stimuli. They
must also inhibit the tendency to remain focused on the point of fixation. Thus, it is
likely that this task draws on the executive attention network. But how does this net-
work exert its attentional effect on the task? Attention is useful only if it can alter the
efficiency of other cognitive processes. Thus, neutrally, attention must act on other areas
of the brain that are otherwise engaged in the visual task at hand—detecting the target
and making the response. So, attention must show up as both a “command” from an
attention network and a change in perceptual processing in visual areas of the brain.
FIGURE 9.23 Results From Tamber-
Rosenau et al.’s (2011) Study
These fMRI illustrations show activation in both
the prefrontal lobe and the parietal lobe during
attentional shifts. Within the orienting attention
network, the medial parietal lobule was active during
shifts of attention. Within the executive attention
network, there was activity in the superior frontal
sulcus/gyrus.
275 Chapter 9: Visual Attention
This aspect of attention was illustrated elegantly in
an experiment by Moran and Desimone (1985).
Moran and Desimone (1985) conducted a sin-
gle-cell recording experiment with rhesus monkeys.
Monkeys were trained to keep their eyes fixated on a
central point and then, as in the Posner spatial cuing
paradigm, to attend to objects in one of two locations
they were not directly looking at (Figure 9.24). The
question the researchers were interested in was how
attention would affect the physiological response in
cells that were responding to visual characteristics,
such as color and orientation. For this reason, they
recorded cells in area V4 of the brain, which, as you
will recall, is sensitive to both color and orientation.
One of the presented objects was considered the
effective stimulus because it elicited a large response
from the cell in V4 being studied when presented
alone in the receptive field. The second stimulus
was considered ineffective because it did not elicit a
strong response from the same cell in V4 when pre-
sented alone in the receptive field. Thus, when both
stimuli are presented to the visual field, without an
attentional manipulation, one would expect a large
response driven by the effective stimulus. However,
in the study, the monkeys were directed to attend to
either the effective or the ineffective stimulus. Note, of
course, that there are presumably other cells in V4 that respond to the ineffective stimu-
lus. But the cell being recorded from does not. When attention is directed to the effective
stimulus, the V4 cell responds strongly, in fact, more strongly than when attention is not
directed there. However, when attention is directed to the ineffective stimulus, the cell’s
response decreased, despite the fact that the effective stimulus was in the receptive field
as well. Because the effective stimulus was not being attended to, however, the response
of the V4 cell decreased. Thus, this experiment showed that, at a physiological level,
attention can affect the processing of visual information and at a fairly early stage of
visual processing. Here, attention acts to decrease the activity of a cell when the effective
stimulus for that cell is not being attended to.
We can see similar patterns of activity in the human brain. Using fMRI, Chiu and Yantis
(2009) examined shifts in activity within the occipital lobe as a function of attention. In
their study, participants fixated on a central marker and then rapidly shifted attention
from stimuli on the left side of fixation and from stimuli on the right side of fixation. The
stimuli were either letters or digits. When the letter R occurred, it meant to direct atten-
tion to the right and keep it there, until participants saw the letter L, and then they were
supposed to direct their attention to the left. When attention was directed to the left, there
was more activity in areas of the right occipital lobe, and when attention was directed to
the right, there was more activity in areas of the left occipital lobe (Figure 9.25). Note that
the point of this study is to demonstrate that directing attention alters neural processing in
visual areas of the brain. Thus, attention can affect visual processing.
The Neuropsychology of Attention
One of the most fascinating, albeit tragic, neuropsychological conditions arises when
there is damage to the orienting attention network in the parietal lobe. When a stroke
FIGURE 9.24 Attentional Networks and V4
Rhesus macaques fixated on a central marker but attended to stimuli to the left
or right of that marker. Moran and Desimone (1985) found that when attention
is directed to the effective stimuli, the V4 cell responds strongly.
Receptive field
of V4 neuron
Ineffective
stimulus
Direction
of attention
Response of
V4 neuron
Response of
V4 neuron
Effective
stimulus
Fixation
point
Direction
of gaze
276 Sensation and Perception
or some other neurological insult affects the right posterior parietal lobe, a condition
called hemifield neglect or unilateral visual neglect may arise. This condition almost
always occurs when the right parietal lobe is damaged, leading to a deficit in the left
visual world. In a handful of patients, one can see neglect of the right side of the
world from left parietal damage, but this is much less common than a left-field deficit
from right parietal damage. We define hemifield neglect or unilateral visual neglect
as a condition in which a person fails to attend to stimuli on one side of the visual
world (usually the left) as a consequence of neurological damage to the posterior
parietal lobe.
What are the consequences of not attending to half of the visual world? It may not
seem so strange at first, but it has devastating consequences. For example, male patients
may shave only one side of their faces. Patients may neglect the care of the left sides of
their bodies. In one case described by Sacks (1985), a patient with neglect rejected the
fact that the left side of his body belonged to him.
Sensitive tests can show that these patients have not lost the ability to see in their
left visual world, but they no longer attend to stimuli in the left world. When pressed
to respond to an item in the left visual world, they may identify it, but under normal
circumstances, they simply ignore it. It is as if they are no longer interested in the left
world or, more properly speaking, that they can no longer direct attention to objects in
the left visual world.
One of the tests of neglect is to ask patients to copy various drawings. For exam-
ple, when asked to reproduce a clock face, a patient may put all the numbers of the
clock on the right side of the page (Figure 9.26). When shown a picture of a house, the
patient draws only the part of the house on the right side of the paper. When asked to
draw her own face, a participant will draw only the side she sees on the right side of
the mirror.
One striking demonstration that neglect is an attentional problem and not a visual
problem comes from a patient in Italy studied by Bisiach and Luzzatti (1978). Their
patient was the editor of a major newspaper in an Italian city and a highly educated
man. After his initial hospitalization, he was able to resume his duties with the newspa-
per. But he continued to visit the lab to be tested by Bisiach and Luzzatti. Asked to imag-
ine himself walking down the main square from north to south in his native city in Italy,
FIGURE 9.25 Shifts of Attention Within the Occipital Lobe
When attention was directed to the left visual world, there was more activity in the right occipital lobe, and when attention was directed to the right
visual world, there was more activity in the left occipital lobe.
Shift left to right Shift right to left Right hemisphere Left hemisphere
0.30
0.15
−0.15
−0.30
−8 8 12 16−4 4
Time (sec)
Left Extrastriate Right Extrastriate
%
s
in
g
le
c
h
a
n
g
e
%
s
in
g
le
c
h
a
n
g
e
0 −8 8 12 16−4 4
Time (sec)
0
0
0.30
0.15
−0.15
−0.30
0
Hemifield neglect (unilateral
visual neglect): a condition
in which a person fails to
attend to stimuli on one side
of the visual world (usually
the left) as a consequence of
neurological damage to the
posterior parietal lobe
277 Chapter 9: Visual Attention
the patient described the monuments
and buildings only on the west side (his
right). When asked to imagine himself
walking up the main square from south
to north, the patient described the sites
only on the east side (now on his right).
Thus, there was nothing wrong with his
visual memory. He successfully retrieved
the buildings on each side of the main
square during the tests. However, when
engaged in this mental walk, he attended
only to those buildings that would
have been on his right. He consistently
ignored the left side of the square,
regardless of whether “left” meant east
or west. Note that he was doing this in
the lab, not actually in the square. Thus,
he was showing neglect for the left side
of his visual images rather than visual
perception. Thus, the imagery deficit
mirrored the perceptual deficit.
Left untreated, the symptoms of uni-
lateral visual neglect will persist and can
be quite devastating to a patient’s long-
term health and well-being. However,
patients show improvement with inter-
vention and treatment. One of the more successful treatments is to require patients
with hemifield neglect to wear prism glasses, which shift the left visual world into
the right visual world, where they will attend to it. In some cases, one can, using a
series of prisms with different refractive properties, shift the left visual world leftward
and see if the patients continue to attend to it (Jacquin-Cortois et al., 2013). Other
treatments have been tested as well. Pavlovian conditioning has been used to increase
patients’ attention to the left visual world (Domínguez-Borràs, Armony, Maravita,
Driver, & Vuilleumier, 2013), and there are studies showing that listening to music
can also allow some patients to focus more on the left visual world than if they were
not listening to music (Chen, Tsai, Huang, & Lin, 2013). With these treatments, many
patients with unilateral neglect will see a diminishment of the symptoms and a chance
to resume their normal lives. Actual patients with unilateral visual neglect can be seen
in ISLE 9.10.
Bálint’s Syndrome
Bálint’s syndrome is a rare condition in which function in both the left and the right
posterior parietal lobes has been compromised. Patients with this condition have a
limited ability to localize objects in space. This results in difficulty grasping for objects,
probably its most salient symptom. In addition, patients with Bálint’s syndrome seldom
move their eyes. As a consequence of this deficit, they have a condition called simult-
agnosia. Simultagnosia is a deficit in perceiving more than one object at a time. Thus,
they focus on the one object that is presented directly in front of them and ignore other
stimuli. This makes them similar to patients with unilateral neglect, except that patients
with Bálint’s syndrome ignore both the left and the right visual world. Actual patients
with Bálint’s syndrome can be seen in ISLE 9.11.
ISLE 9.10
Hemifield or Unilateral Neglect
ISLE 9.11
Bálint’s Syndrome
Bálint’s syndrome: a
neurological condition caused
by damage to both left and
right posterior parietal lobes
Simultagnosia: a deficit in
perceiving more than one
object at a time
FIGURE 9.26 Hemifield Neglect (Unilateral Visual Neglect)
Patients with this neurological condition ignore one half of the visual world (usually the left).
These pictures show how patients with hemifield neglect interpret the world. They understand
that a clock should have 12 numbers, but because they ignore half of the world, they put all 12
numbers on one side of the clock.
12
11
10
9
8
12
6
111
210
39
48
57
6
1
2
3
4
5
7
278 Sensation and Perception
TEST YOUR KNOWLEDGE
1. Find a diagram of the brain and indicate both the orienting and executive
networks of attention on it.
2. Classify each of the disorders of attention in terms of their deficits and whether
the orienting or executive functions of attention are disrupted.
DEVELOPMENTAL ASPECTS
OF VISUAL ATTENTION
9.6 Identify what factors lead to the development of visual attention as we grow up.
When does the ability to attend develop? Are young infants born with the ability to
select locations in space they wish to attend to, or are newborns caught in a world
of stimuli without this ability, the “blooming, buzzing confusion” of William James
(1890)? Is there an age at which we learn to covertly direct attention to a point in space
other than the one we are looking at? There are many pertinent questions in the devel-
opment of visual attention. We examine only a small sample of the possible answers to
these questions here.
Attention in very young infants is determined by how long they can maintain a gaze
at an interesting stimulus, whether that stimulus is a colorful collage or an image of
their mother (Figure 9.27). As most parents suspect, it turns out that at quite a young
age, infants can maintain the direction of gaze for a considerable time, indicative of
attentional control (Colombo, 2002).
One means of studying attention in young infants is with a technique called the oddball
procedure. In this procedure, an infant is shown a series of related objects (e.g., different
kinds of balls). However, after a number of balls have been shown to the infant, a novel
object from a different category is shown to the infant (e.g., a stuffed animal). In older
children, the novel object attracts attention. In infants, such attention would be called
stimulus orienting, as the infant focuses on the novel
object. This procedure can then be combined with neuro-
imaging techniques such as using the event-related poten-
tial analysis of EEG recording (Richards, Reynolds, &
Courage, 2010). Richards et al. (2010) compared infants
who were alert and those who were not (i.e., sleepy). They
also compared infants at 4, 5, and 7 months of age in an
oddball paradigm. Alert babies and older babies showed
greater activity as measured by electroencephalography.
In addition, alert babies, regardless of age, showed greater
EEG activity when presented with the oddball item. Thus,
infants as young as 4 months orient toward novel stimuli
(Richards et al., 2010).
Other recent neuroimaging studies suggest that ori-
entation in the oddball paradigm is accomplished by the
same areas of the brain that are associated with selective
attention in older children and adults. These brain regions
include areas in the extrastriate cortex as well as the pos-
terior parietal lobe. Richards et al. (2010) superimposed
the EEG activity (discussed in the previous paragraph)
FIGURE 9.27 Infants and Attention
Do young infants have the ability to direct their attention to specific
objects in the environment?
©
iS
to
ck
ph
ot
o.
co
m
/n
m
ax
fie
ld
279 Chapter 9: Visual Attention
on magnetic resonance images of infant brains to con-
firm this (Figure 9.28). Figure 9.28 shows the areas of the
brain active in an infant brain during the oddball task.
Many adults complain that if a television set is play-
ing, they have difficulty concentrating on their jobs or
on their studies. Indeed, we are sure that you have heard
professors advise you not to study with the television on.
However, infants may function a bit differently in this
regard. Setliff and Courage (2011) examined infants at
6 and 12 months of age during play with novel toys. The
infants played with the toys while a television was either
playing or not playing in the background. They found lit-
tle difference in the attention infants gave to the toys and
very little difference in directed glances at the television during the session. Thus, it is
likely that background noise provided by a television is less distracting to infants than
it is to adults. In this one regard, we might conclude that infants are better at selective
attention than their older family members. Certainly, we know from the literature on
aging that older adults have a harder time inhibiting responses to irrelevant stimuli than
younger adults, and it looks as if the youngest members of our species are even better.
TEST YOUR KNOWLEDGE
1. Assess the oddball paradigm and how it can be used to tell us about the
development of visual attention.
2. Track the changes in our ability to block out background stimulation from
childhood through adulthood.
FIGURE 9.28
Neuroimaging Attention in the Infant Brain
Activity includes brain regions such as the extrastriate cortex and the
posterior parietal lobe.
EXPLORATION: Awareness
and Visual Consciousness
For a philosopher, one of the fundamental questions
about perception is the following: How can a physical
system composed of brain, eyes, and neurons and made of
organic materials, such as proteins and fats, produce con-
scious visual experiences, such as the experience of seeing
green or the joy in watching a cat swish its tail when it
wakes up from a nap (Figure 9.29)? Philosophers of mind
argue endlessly whether we can account for awareness
and consciousness with purely material explanations,
even though they acknowledge that without brains and
eyes, no seeing would ever occur. This paradox—that the
neural processes of seeing do not resemble in any way
the subjective experience of seeing—has led neurosci-
ence to examine if we can find the neural correlates of
consciousness.
Vision and attention provide a great laboratory for looking
at the neural correlates of consciousness, because clearly
FIGURE 9.29 A Sleepy Cat
Many cat owners will smile at the relaxed pose and poise of the cat in
this photo. Why does seeing a cat feel the way it does?
©
iStockphoto.com
/chictype
280 Sensation and Perception
when you are looking at and attending to an object, such
as a cup of chocolate mousse, you are conscious of that
object. But as we have seen in this chapter, with phenom-
ena such as change blindness, inattentional blindness, and
unilateral visual neglect, that you are conscious of seeing
the mousse does not mean that you will consciously per-
ceive the moose and the mouse, approaching from different
directions, which just might attempt to eat your mousse.
Thus, in this section, we will examine what two phenom-
enal experiences, perceptual bistability and blindsight, can
tell us about awareness and vision.
Perceptual Bistability
Perceptual bistability is one of those phenomena you
must see before you can believe, understand, or study.
So first go to ISLE 9.12 to see it and experiment with
it. You can also use your pair of three-dimensional (3D)
glasses to inspect Figure 9.30. The anaglyph here pro-
vides an opportunity to see a bistable image. In examining
Figure 9.30, note how first you see the cat’s face, and then
it fades out and is replaced by the flower, only to have
the flower fade out and be
replaced by the face again.
This is the essence of percep-
tual bistability.
We can define perceptual bistability as the phenomenon
in which a static visual image leads to alternating percep-
tions. Perceptual bistability occurs in a number of com-
mon illusions, such as the Necker cube, the rabbit–duck
image, and the faces–vase image, all of which can be seen
in Figure 9.31.
Each of these figures creates a paradox for our visual
system. For example, in the Necker cube, what we really
see are some lines on a two-dimensional surface, namely,
the paper of your book or the screen of your computer.
However, the lines suggest a 3D cube, and we tend to
interpret this figure in three dimensions. However, there
are two possible 3D interpretations of this two-dimen-
sional figure. So, our perceptual systems may flip back and
forth from one to the other. Of interest here is that the
exact same physical stimulus creates two separate percep-
tual experiences.
One of the most striking examples of perceptual bistabil-
ity comes from a phenomenon known as binocular rivalry.
Binocular rivalry occurs when a separate image is presented
to each eye. Figure 9.30 illustrates the perceptual bistability
that arises from binocular rivalry. If you look at the image
through just the red filter of a pair of 3D glasses, you see only
the “red” image, the cat’s face. If you look through only the
blue filter of the 3D glasses, you see only the “blue” image,
the flower. Thus, when you are using both filters, one over
each eye, each eye is getting a separate image. Binocular
rivalry illustrates a number of important points about aware-
ness in vision. First, our visual system is set up to see a single
perception of the world, rather than a separate perception
from each eye. Thus, when each eye is seeing a completely FIGURE 9.30
Perceptual Bistability and Binocular Rivalry
A bistable image anaglyph. Using a pair of anaglyph glasses, you can
look at this image. You should sometimes see one image, sometimes
the other. However, if you close one eye and then the other, while using
the anaglyph glasses, you can clearly see each image.
FIGURE 9.31 Famous Bistable Images
Each of these drawings has two different interpretations. Most people
report seeing one interpretation and then the other but never both
simultaneously.
Perceptual bistability: a phenomenon in which a static
visual image leads to alternating perceptions
Binocular rivalry: a phenomenon that occurs when a
separate image is presented to each eye
ISLE 9.12
Perceptual Bistability
281 Chapter 9: Visual Attention
different image, rather than creating a double image of the
world, it systematically inhibits one perception or the other.
Second, it also demonstrates the top-down processing aspect
of perception. We usually see the more “important” image
more than the less important image. Thus, we usually see a
face longer than another stimulus in the display, in this case
the flower, in Figure 9.30 (Sandberg et al., 2013).
In an early study with fMRI, Tong, Nakayama, Vaughan,
and Kanwisher (1998) examined two regions of the brain
during binocular rivalry. They presented an image that
produces binocular rivalry similar to the image depicted in
Figure 9.30. They then focused their fMRI scanner on two
regions of the brain, the fusiform face area, which we know
is involved in face processing, and another nearby area called
the parahippocampal area, which responds well to specific
objects such as houses. While participants were being mon-
itored by the fMRI scanner, they indicated whether they
were visually conscious of the face or the house. They were
asked to press one button to indicate that they were con-
scious of the face and another button to indicate that they
were conscious of the house. Amazingly, when the partic-
ipants perceived the face, Tong et al. showed that partici-
pants had more activity in the fusiform face area, but when
participants perceived the house, they had more activity
in the parahippocampal region (Figure 9.32). Subsequent
studies showed that lower areas in the visual cortex also
change responses, depending on which image is being
perceived, including V1 and the lateral geniculate nucleus
(Meng, Remus, & Tong, 2005). Thus, activity in these areas
tracked the participants’ visual consciousness rather than
the physical nature of the stimuli (see
Tong, Meng, & Blake, 2006).
Blindsight
Recall blindsight from Chapter 4.
Blindsight refers to the residual ability
to make visual responses when a patient
is subjectively blind in certain regions of
his visual field. This means, paradoxi-
cally, that patients with this condition
are making visual responses to stimuli
they cannot see, that is, to which they
are not aware.
Refer back to Chapter 4 and the story
of Patient T.N., a medical doctor who
had two strokes less than a month
apart in the early 2000s. The strokes
caused permanent and complete blind-
ness (Buetti et al., 2013). He has no conscious awareness of
seeing, yet he can use his vision. You can read more details
about his condition in Chapter 4 and see a video of his navi-
gating a hallway strewn with obstacles in ISLE 9.13. Various
studies have shown he can point in the proper direction
of objects on a computer screen over 75% of the time
(Buetti et al., 2013) and even
distinguish the emotions of
faces presented to him (Pegna
et al., 2005).
So, the question arises, how can someone make visual
responses without having the conscious awareness of seeing?
At this point, you should be quite familiar with the
anatomy of the visual system. You may remember from
Chapter 4 that the retinae of the eyes project to many
different areas in the brain. The majority of retinal axons
project to the lateral geniculate nucleus and from there
to the occipital lobe. It is likely that this is the path-
way that leads to conscious visual experience. Indeed,
it is this pathway that is damaged in T.N. and others
who have blindsight. However, the retinae also project
to other areas of the brain. Weiskrantz hypothesized that
the responses made by patients with blindsight might be
the result of behavior produced by these alternate routes
(see Weiskrantz, 2009). In particular, Weiskrantz focused
on the route from the retinae to the superior colliculus.
The superior colliculus is a region of the brain instru-
mental in making visually guided head movements as
Rivalry
Time from reported perceptual switch (s)
1.0
0.8
0.6
0.4
0.2
0.0
−8 −4 0
House Face
FFA
FFAPPA
PPA
4 8 12
%
M
R
s
ig
n
a
l
1.0
0.8
0.6
0.4
0.2
0.0
−8 −4 0
Face House
4 8 12
%
M
R
s
ig
n
a
l
FIGURE 9.32 Bistability in the Brain (Tong et al., 1998)
When participants perceived the face, there was more activity in the fusiform face area, but
when participants perceived the house, there was more activity in the parahippocampal region.
ISLE 9.13
Navigation in Blindsight
282 Sensation and Perception
well as eye movements. Weiskrantz hypothesized that
because this route is still intact in patients with dam-
age to V1, the superior colliculus can guide their visual
responses, even though the route that produces con-
scious vision, that is, V1, is damaged. Thus, the superior
colliculus can allow visual responses in the absence of
seeing (Figure 9.33).
Interestingly, research now shows that the superior col-
liculus projects axons to higher areas of visual process-
ing in the occipital lobe. So, the visual responding seen
in patients such as D.B. and T.N. may be the result of
this connection between the superior colliculus and the
occipital cortex, rather than just the superior colliculus
alone. However, even if this is the case, this route, though
strong enough to allow visual response, is not sufficient
to create a sense of conscious visual experience in these
patients.
TEST YOUR KNOWLEDGE
1. Interpret what perceptual bistability tells us about
our general apparent stable perception of the
world.
2. Formulate a description for the different functions
of those pathways involved in blindsight and the
visual pathways that travel through the cortex.
Optic chiasm
Optic tract
Superior
colliculus
Lateral
geniculate
nucleus
Damaged
pathway
V1
FIGURE 9.33 The Pathways in Blindsight
In people with blindsight, the route from the retinae to the lateral
geniculate nucleus to V1 has been damaged. It is this route that
supports conscious seeing. However, other routes, such as the link
from the retinae to the superior colliculi, may support visual response
in the absence of visual consciousness.
APPLICATION: Distracted Driving
Driving is a task that demands sustained attention. We
drive for extended periods of time and the situation is
always changing. Some truck drivers, however much it is
discouraged, may drive for more than 15 hours without
stopping. As we drive, we must scan the road for what
other drivers are doing, changes in direction on the road,
and even stoplights going from green to yellow to red.
The task is complicated enough when driving is all that
is required. We can be distracted by other happenings in
the car, such as conversations with passengers, our ste-
reos playing music, and even making sure we do not run
out of gas. But with all of our new devices, especially cell
phones, we have a lot of new ways to be distracted while
we drive. We simply are more distracted during driving
than we used to be. Overall, this distracted driving has
grown into a major cause of accidents, particularly those
that cause injuries or fatalities. In the years from 2005 to
2009, the overall rate of fatalities from car crashes fell
significantly while the rate of fatalities due to distracted
driving increased 22% (Coben & Zhu, 2013). This period
of time witnessed the introduction of our beloved smart-
phones. Beyond crashes, it appears that distracted driv-
ing impedes general traffic flow as well (Stavrinos et al.,
2013). Using a simulator, drivers who were distracted var-
ied speed more, changed lanes significantly fewer times,
took longer to complete the scenario, and were passed
by more (simulated) vehicles. These behaviors indicate a
driver who, even when not making traffic more danger-
ous, is still clogging up the roadway and not helping us
reach our destination.
Several of the concepts that we have discussed in this
chapter can help us to understand why distracted driving
is such a concern. Overt attention tells us that attention
283 Chapter 9: Visual Attention
is usually located on the fovea in the direction of gaze.
While looking at the screen of our phone, we are not
looking at the road, and features of the road and traffic
can easily be missed. Although we can direct attention
to other locations than our gaze (covert attention), it
does not appear to help us in driving. Moreover, cell
phones are highly salient objects, so they draw our atten-
tion. There is even some evidence that merely having
the phone handy serves to draw our attention and
can negatively impact our driving (Thornton, Faires,
Robbins, & Rollins, 2014). Cell phones seem to have a
strong attentional capture.
Even after we finish with the phone, we cannot imme-
diately switch back to processing the road. Attentional
blink tells us that there is a time lag from processing one
stimulus before we can process the next. We learned that
it appears that experienced video gamers might have a
smaller attentional blink (Kristjánsson, 2013). It seems
reasonable that we might find that video gamers might
also do better in distracted driving situations. Rupp,
McConnell, and Smither (2016) examined this very idea
using driving simulators. It is a lot safer to study driving
whenever possible using a driving simulator. Researchers
can control the traffic and any distractions in simulators
without risk to the participant or anyone else. In this
experiment, one of the variables the researchers exam-
ined was the number of times the drivers did not stay in
their lanes, what they called lane deviations. Interestingly,
video gamers showed fewer lane deviations during non-
distracted driving, when there were fewer irrelevant stim-
uli present, than during distracted driving. It seems that
video game experience helps us sustain our attention over
a prolonged period of time but not deal with distractions
(Rupp et al., 2016).
One interesting study examined changes in the brain
during distracted driving. With visual attention, we cov-
ered two types of networks. There is the orienting atten-
tion network, centered in the parietal lobe, that allows
us to direct our visual attention. When we think about
driving, this network will help us study the road to make
sure we follow the upcoming curves or examine the
mirrors to see what is going on behind us. Then there
is the executive action network, which gives top-down
control to attention. When applied to driving, the exec-
utive action network can help us to respond to driving
as opposed to other tasks available. Think about traffic
suddenly becoming busy. You have been having a great
conversation with your fellow passengers in the car and
suddenly you drop out of the conversation. The execu-
tive action network would help you put your driving over
your conversation.
Schweizer and colleagues (2013) asked their participants
to drive in a driving simulator while in a device that mea-
sured fMRI. They used two basic conditions, a normal
driving condition and a distracted driving condition. To
simulate the distraction that cell phones cause, the partici-
pants needed to answer general knowledge questions in the
distracted driving conditions, whereas in the normal driv-
ing condition, this was not required. Schweizer et al. then
compared the fMRI patterns across the driving conditions.
In the normal driving condition, the posterior part of the
brain was most active, largely overlapping with the orient-
ing attention network. However, during distracted driving,
the activity in the brain moved to the forebrain, where the
executive action network is located. It seems that during
distraction we take activity away from those networks that
help us guide our vision where we need it and move it to
areas that suppress habitual driving responses and allow us
to use our cell phone.
There might be some hope in the future. A study by Wang,
Chen, and Lin (2014) used electroencephalography to
measure brain activity during distracted and normal driv-
ing. They were able to identify quite reliably when drivers
were distracted or not by looking at the brain activity over
the frontal lobe and left motor cortex. The frontal area
matches what was observed by Schweizer et al. (2013),
providing nice confirmation for both studies. Perhaps in
the future there might be a device that can help alert us
when we are not properly paying attention to our driving.
Or perhaps driverless cars really are the way to go.
TEST YOUR KNOWLEDGE
1. Classify the attentional functions, for example, attentional blink and visual
capture, that play a role in making distracted driving such a danger.
2. Examine how distracted driving is related to the orienting and executive
networks of attention.
Sensation and Perception284
CHAPTER SUMMARY
9.1
Explain selective attention and divided attention,
which help us understand our scanning of the world.
Alertness is a state of vigilance. When alert, we are
awake, mindful, and likely scanning our surroundings.
Awareness is actively thinking about something, which
can be either physically present or just in our imagination.
Attention is a set of processes that allow us to select or
focus on some stimuli. Attention can also be sustained or
temporary. Selective attention can be defined as the pro-
cesses of attention that allow us to focus on one source
when many are present. Divided attention is the process
of attending to multiple sources of information.
9.2
Illustrate how we move attention around a scene
both by using eye movements and by using our
peripheral vision.
Generally, we align our attention with the direction of our
gaze. A question we can ask, however, is whether it is pos-
sible to attend to spatial locations other than the location
we are looking at. Posner and his colleagues investigated
this phenomenon. A cue is given that a target will occur in a
particular region of space. In most trials, the target appears
in the cued location, but in some it does not. Even though
participants cannot look at the cued area, their response
times are faster when the cues are accurate. This tells us
that we can devote attention covertly, that is, direct atten-
tion to a location in space we are not looking at directly with
our foveae. This helps us understand the distinction between
overt and covert attention. Overt attention is when our atten-
tion is directed with our gaze, and covert attention is when
our attention is directed toward our periphery. Inattentional
blindness is a phenomenon in which people fail to perceive
an object or event that is visible but not attended to. Chabris
and Simons (1999) conducted the famous gorilla experiment
to demonstrate that salient stimuli can actually be missed
when the focus of attention is elsewhere.
9.3
Assess the nature of attentional capture and
how it works in our visual system to have stimuli
capture attention.
Stimulus salience means that some objects in the environ-
ment attract our attention. Attentional capture occurs when
a salient stimulus causes us to shift attention to that stimu-
lus. Both a history of previous reward and relevant semantic
meaning tend to capture our attention. Visual search means
looking for a specific target in an image with distracting
objects. Feature search means searching for a target in
which the target is specified by a single feature. Conjunction
search means searching for a target in which the target is
specified by a combination of features. Feature integration
theory stipulates that some features can be processed in
parallel and quickly prior to using attentional resources.
Other visual characteristics require us to use attention and
are done serially and therefore less quickly.
9.4
Examine attentional blink and change blindness
as ways of helping us understand how attention
changes over time.
Rapid serial visual presentation (RSVP) is an experimental
paradigm in which a series of stimuli appear rapidly in time
at the same point in visual space. Participants must direct
their attention across the time domain rather than the space
domain. Findings show that people can respond quickly to a
particular stimulus when it occurs in time. Attentional blink is
the tendency to respond more slowly or not at all to the sec-
ond target in an RSVP task when the second stimulus occurs
within 500 ms of the first stimulus. Repetition blindness is the
failure to detect the second target in an RSVP task when the
second target is identical to the first one. Like attentional blink,
it occurs when the second target is presented 500 ms or less
after the first target. Change blindness is the difficulty we
experience in detecting differences between two visual stim-
uli that are identical except for one or more changes to the
image. In a surprising finding, Simons and Levin (1997) found
that participants could even be change blind to the substitu-
tion of one person for another.
9.5
Explain the differences between the orienting
attention network and the executive attention net-
work and their roles in directing visual attention.
The orienting attention network (or dorsal attention network)
allows us to engage in visual search and direct our visual
attention to different locations in visual space. The orienting
attention network is located primarily in the parietal lobe.
The executive attention network focuses on attention as
the inhibition of habitual responses and the top-down con-
trol of attention. The executive attention network is found in
the frontal lobe. Moran and Desimone (1985) found that at
a physiological level, attention can affect the processing of
visual information. Attention acts to decrease the activity of
a cell when the effective stimulus for that cell is not being
attended to. Hemifield neglect, or unilateral visual neglect,
is a condition in which a person fails to attend to stimuli
on one side of the visual world (usually the left) as a con-
sequence of neurological damage to the posterior parietal
lobe. Bálint’s syndrome is a neurological condition caused
by damage to both the left and the right posterior parietal
Chapter 9: Visual Attention 285
lobes. Simultagnosia is a deficit in perceiving more than one
object at a time. Perceptual bistability is a phenomenon in
which a static visual image leads to alternating perceptions.
Binocular rivalry occurs when a separate image is pre-
sented to each eye. Binocular rivalry results in perceptual
bistability as viewers see the image presented to one eye
for a while before the perception shifts to what the other eye
is viewing. Blindsight is the residual ability to make visual
responses when a patient is subjectively blind in certain
regions of his or her visual field. Patients will say that they
are blind in regions of their visual fields but make responses
anyway. It is likely that the blindness is caused by damage to
area V1 of the occipital cortex but that the residual vision is a
function of intact structures, such as the superior colliculus.
9.6
Identify what factors lead to the development of
visual attention as we grow up.
Infants show from quite a young age the ability to maintain the
direction of gaze, indicating some attentional control. One way
attention is studied in infants is with the oddball procedure.
If infants are shown a series of objects from the same cate-
gory and then a novel object is presented, the oddball attracts
attention. This procedure has shown that infants as young as
4 months will orient toward the novel object (Richards et al.,
2010). These same researchers also found that some of the
same regions used to direct attention in older children are
used by infants. It has also been found that, compared with
older children and adults, infants do not seem as distracted
by external stimuli, say a television (Setliff & Courage, 2011).
REVIEW QUESTIONS
1. What is the difference between selective attention
and divided attention? What function does attention
serve in perception?
2. How did Posner and his colleagues study covert
attention? Describe their experiment and its results.
What do these results tell us about covert attention?
3. What is attentional capture? Describe an experiment
reviewed in the textbook that examined features of
attentional capture.
4. What is the difference between change blindness
and inattentional blindness? Describe an example of
each. Why are change blindness and inattentional
blindness considered errors of attention?
5. What is feature integration theory? How does it
explain feature searches and conjunction searches?
6. What is the rapid serial visual presentation (RSVP)
paradigm? How is it conducted in the lab, and what
aspect of attention does it measure?
7. What are the orienting attention network and the exec-
utive attention network? What area of the brain is each
located in? What aspects of attention do they serve?
8. What is unilateral neglect? What are its symptoms?
What kind of brain damage causes it?
9. What is binocular rivalry? How is it measured, and
what principles of awareness does it demonstrate?
10. What is blindsight? Describe the deficits and pre-
served function in the patient T.N. What is typically
thought of as the neurological basis for the preserved
function in blindsight?
11. How does our understanding of visual attention help
us explain the safety issues associated with cell
phone use during driving?
PONDER FURTHER
1. You are watching your favorite team playing your favorite
sport. The official (referee, umpire, etc.) makes a call that
you disagree with, vigorously. We have all been there.
Take the material from this chapter and evaluate the
attention of both yourself and the official to consider why
you both see the situation so differently. Without casting
blame, consider why you might see these situations so
differently. Consider your location, stimuli, and internal
factors, and even your orienting and executive networks.
2. You are an advertiser or marketer. How can you apply
the material from this chapter to enhance the chance
of visual capture by your advertisement, announce-
ment, or solicitation? Now imagine you are a person
receiving this information. How does what has been
covered help you to internally choose your stimuli for
attention?
Answer for Figure 9.19 : In one image, there are three yellow and gold flowers in the lower left-hand corner. In the
other image, there are only two yellow and gold flowers in the lower left-hand corner.
Sensation and Perception286
KEY TERMS
Attention, 257
Attentional blink, 272
Attentional capture, 265
Automaticity, 258
Bálint’s syndrome, 277
Binocular rivalry, 280
Change blindness, 269
Conjunction search, 267
Covert attention, 259
Divided attention, 258
Executive attention network, 273
Feature integration theory, 267
Feature search, 267
Hemifield neglect
(unilateral visual neglect), 276
Inattentional blindness, 262
Orienting attention network
(dorsal attention network), 273
Overt attention, 260
Perceptual bistability, 280
Rapid serial visual presentation
(RSVP) paradigm, 271
Repetition blindness, 272
Selective attention, 258
Simultagnosia, 277
Stimulus onset asynchrony, 260
Stimulus salience, 265
Visual search, 266
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
9.1 Explain selective attention and divided attention, which help us
understand our scanning of the world.
The Neural Basis of Selective Attention: Cortical Sources and
Targets of Attentional Modulation
Identifying and Remediating Failures of Selective Attention in
Older Drivers
The Science Behind Sleight of Hand
9.2 Illustrate how we move attention around a scene both by using
eye movements and by using our peripheral vision.
How We Pay Attention
The Invisible Gorilla (Featuring Daniel Simons)
Seeing the World as It Isn’t—Daniel Simons
9.3 Assess the nature of attentional capture and how it works in our
visual system to have stimuli capture attention.
Intersensory Redundancy Guides the Development of
Selective Attention, Perception, and Cognition in Infancy
We See More Than We Can Report: “Cost Free” Color
Phenomenality Outside Focal Attention
What We Really See When We Go See a Movie
9.4 Examine attentional blink and change blindness as ways of
helping us understand how attention changes over time.
The Attentional Blink Reveals the Probabilistic Nature of
Discrete Conscious Perception
Change Blindness: Theory and Consequences
Optical Illusion: Car Wheels Going ‘Round
9.5 Explain the differences between the orienting attention network
and the executive attention network and their roles in directing
visual attention.
The Blind Woman Who Sees Rain, but Not Her Daughter’s
Smile
A Visual Neglect Patient
Excerpt From Through the Wormhole With Morgan Freeman:
Interview With Beatrice de Gelder
9.6 Identify what factors lead to the development of visual attention
as we grow up.
Link Seen Between Babies’ Sight, Language Development
How Do You Ask a Preverbal Infant What She Can See?
Victor Habbick Visions/Science Source
10The Auditory System
DNA Illustrations/Science Source
LEARNING OBJECTIVES
10.1
Discuss the physical nature of sound and how it
correlates with the perceptual nature of sound.
10.2
Describe the basic anatomy of the ear and the difference
between the outer, middle, and inner ear.
10.3
Examine the nature of hearing loss and what can be done
to improve hearing in hearing-impaired individuals.
INTRODUCTION
“Friends, Romans, countrymen, lend me your ears.” So wrote William Shakespeare in
his play Julius Caesar (1599). Of course, Caesar meant for his audience to listen to him,
not actually allow him to borrow their ears. There was some confusion about this in the
mind of one of your authors when he was a young boy and first heard this quotation
from the play. But as is often the case with Shakespeare, he summarized quite a bit in
one clever line. For all but a small population of sign language speakers, sound means
communication and the ability to talk and listen to others. To lend someone your ears
means to listen to the language sounds that he or she is making. Indeed, one of the crit-
ical functions of hearing is to perceive and interpret the sound of the human voice. It is
hard to imagine a world in which we could not hear one another talk, and for billions
of people around the globe, sound and hearing also mean music, which brings us great
enjoyment and peace of mind. Indeed, people who have gone deaf after a lifetime of
hearing most often miss the ability to hear music.
Think of all the sounds you hear at any given moment. You may hear the whirring
of the washing machine, the whining of the air conditioning, the distant buzz of cars on
the road, a lawn mower from down the street, and the gentle lapping sounds of your
cat drinking from its water bowl. Our ears are always open, and thus we hear these
sounds all the time. This contrasts with vision, in that you can close your eyes. In some
cases, sounds such as the ones just described may become distracting. In this case, you
may create your own world of sound by putting on headphones or ear buds. In this
case, listening to your favorite music allows you to concentrate on the sounds you want
to hear, not simply those present in the environment. Alternatively, you may put in ear-
plugs to drown out external sound. Although this may succeed in dampening unwanted
sound, many people find the silence of this to be strange (Figure 10.1). Moreover, sound
comes at us from all directions. We see only in front of us, but we hear from all 360
ISLE EXERCISES
10.1 The Sound Stimulus
10.2 The Speed of Sound
and the Sonic Boom
10.3 The Decibel Scale
10.4 Frequency and Pitch
on a Piano
10.5 Frequency
Response of the Ear
10.6 Timbre and Musical
Instruments
10.7 Fourier Analysis in
Audition
10.8 Missing Fundamental
10.9 Timbre and
Overtones
10.10 Phase and
Cancellation
10.11 The Middle Ear
10.12 The Basilar
Membrane and Sound
Stimuli
10.13 The Traveling Wave
10.14 Place Code Theory
10.15 The Basilar
Membrane and Fourier
Analysis
10.16 Transduction and
Hair Cells
10.17 Temporal Code Theory
290 Sensation and Perception
degrees. This is likely why wailing sounds, such as a siren, and
not flashing lights indicate emergencies that are out of visual
range. In sum, we live in a world engulfed in sound.
As with every perceptual system, the essence of hearing
is transforming information available in the environment, in
this case, sound pressure waves, into a perception we can use
to understand the world and guide our actions. As we work
through the sensory processes involved in hearing and the per-
ceptual processes involved in speech perception and music per-
ception, you can note both the similarities and the differences
between audition and vision. They share similar physiological
mechanisms, but these mechanisms must be modified for the
specific modality they are responsible for.
SOUND AS STIMULUS
10.1
Discuss the physical nature of sound and how it
correlates with the perceptual nature of sound.
In the movie Alien (1979), one of the scariest movies ever made, the tag line is “In
space, no one can hear you scream” (Figure 10.2). As effective as this is in building
tension before you even go into the movie theater (and maybe eliciting screams in the
theater), the statement is true, in the sense that there needs to be a medium, such as air
or water, to conduct sound. In the absence of such a medium, as in the near vacuum of
space, sound cannot exist. So, before we can discuss the physiological and psychological
processes that allow us to hear, we need to understand a little bit about what sound is.
The sound stimulus is the periodic variations in air pressure traveling out from
the source of the variations. That is, these periodic variations in pressure are the sound
wave, and the source of the variations is the object making the sound. Over time, air
pressure will increase and decrease slightly, and these small changes in air pressure con-
stitute sound to our ears if they occur strongly enough and quickly enough. Sound can
also be transmitted through other media, such as water, bones, and train tracks—any-
thing that can vibrate. Water transmits sound faster than air does, making it more dif-
ficult for a scuba diver to localize a sound underwater than for a person on land. Even
someone just swimming in a pool may notice how difficult it is to tell where a sound
is coming from. Mostly, humans hear in an air medium, and occasionally in a water
medium, but really anything that can reverberate or change in pressure over time can
transmit sound. Think of the Old West sheriff listening for the bad guys by putting his
ear to the train track. The iron of the rail transmits sound, which tells the sheriff when
the train is coming and therefore when the train robbers will be coming.
Think of what happens when you clap your hands. The pressure of your hands
against each other compresses the air between them, creating the pressure wave. This
compression of the air between your hands causes the air molecules to collide with other
air molecules in each and every direction around your hands, which then collide with air
molecules farther away from your hands, and so on and so forth. As the air molecules
are compressed in each area of space, just behind them is a small area in which the air
pressure is lower because some of the molecules have been pushed forward. Thus, sound
consists of pockets of higher pressure air followed by pockets of lower pressure air.
Changes in air pressure propagate outward from the original source of the disturbance,
©
iS
to
ck
ph
ot
o.
co
m
/L
es
lie
La
ur
en
FIGURE 10.1 Ear Protection
People who do jobs with a lot of noise nearby are often advised to
wear ear protection. Ear plugs like this can block out loud noise.
Sound stimulus: the periodic
variations in air pressure
traveling out from the source
of the variations
M
ov
ie
st
or
e
co
lle
ct
io
n
Lt
d/
A
la
m
y
St
oc
k
Ph
ot
o
FIGURE 10.2 Alien (1979)
291 Chapter 10: The Auditory System
in this case your hands clapping
(Figure 10.3). For a demonstration
of this, go to ISLE 10.1a.
When you clap your hands, you
disturb the air around your hands
and initiate the pattern of high- and
low-pressure air movements that
move out in all directions from the
source. This pattern is called a sound
wave. Sound waves are the waves
of pressure changes that occur in
the air as a function of the vibration
of a source. Sound waves are like
any kind of wave—the wave moves
through its medium even though
particles within the wave may stay
in the same place, just as a standing
wave stays put on a river. In the case of sound, the source of the sound is your hands
when you clap. The source of the sound could be air blown through a brass instrument
or the vibrating of strings on a guitar. Air molecules do not travel very far. They basically
just move back and forth from high-pressure to low-pressure areas, but
the wave of pressure change moves across space, causing compression
(high pressure) and rarefaction (low pressure) across space, sometimes
at great distances, depending on how forceful the original sound was.
In this wave, there will be a peak high in air pressure and a peak low
in air pressure. Although the physics of light are much more compli-
cated, sound can be measured in an analogous manner, namely, by mea-
suring wavelength and its inverse, frequency. The time between two
consecutive high peaks is the cycle of a sound wave. Cycles can be
measured in their number per second, also known as frequency (Figure
10.4). Finally, the energy in any sound wave will weaken across time
and space. Your clap may sound very loud to you because you are so
close to it. But to your friend in another room, it will be audible but not
loud. By the time the sound wave gets through the door and out into the
street, the energy may have dropped off so much that a person walking
by on the sidewalk may not hear it at all. You can see a demonstration
of this on ISLE 10.1b.
Under normal conditions, at sea level, sound travels very fast, but
much more slowly than light. Sound travels at about 344 m/s (761.2
mph). This is a bit faster than a civilian jet plane (a typical jet on
its way from Chicago to New York travels at a peak speed of 550
mph). However, we have planes, mostly used by the military, that can
equal and exceed the speed of sound. Indeed, the military has planes
that exceed the speed of sound by as much as 3 times (“Mach 3”
in military terms means 3 times the speed of sound). Such high speeds are avoided
for typical civilian aircraft because they leave a tremendous collision of sound, called
a sonic boom, behind them when the plane reaches and exceeds the speed of sound
(Figure 10.5). Interestingly, because the planes are going faster than the sounds they
make, pilots and passengers on such supersonic planes experience an incredibly quiet
ride. And, by the way, the Mach of Mach 3 is the same scientist as the person who first
observed Mach bands (Chapter 3).
ISLE 10.1
The Sound Stimulus
FIGURE 10.3 The Propagation of Sound Through a Medium
When a person claps, air pressure changes are created. The clap creates a compression of air
between the hands, which pushes against the air adjacent to it in all directions. The compression
creates a rarefaction of air next to it, which alternates with the compression and propagates
through the air.
Pressure in small volumes of air molecules
CompressionCompression Rarefaction
Sound waves: the waves of
pressure changes that occur
in the air as a function of the
vibration of a source
Cycle: in a sound wave, the
amount of time between one peak
of high pressure and the next
FIGURE 10.4
Frequency or Wavelength of Sound
The vibrations coming from an object, such as hands
clapping, can be measured by looking at the pattern of
increasing and decreasing air pressure. One cycle is the
amount of time it takes for air to return to the same state
of air pressure as at an earlier point in the wave or, more
technically, the time between two consecutive high peaks.
A
ir
pr
es
su
re
Time
1 2 3 4 50
One
cycle
292 Sensation and Perception
Although the speed of sound is very high, there are times when we may notice a
lag between sound and sight. If the source of a sound is 100 meters (m) away, there
will be a lag of about 0.3 seconds (s) between when we see the hands clapping and
when we hear the sound. Thus, a person watching a sprint race from just behind
the finish line will see the gun go off and then hear it a split second later. When we
shout across a canyon toward a cliff, the echo is not simultaneous with our shout;
it takes time for our shout to reach the distant cliff and for the echo to return. The
lag of sound relative to light also accounts for the delay in hearing thunder after we
see lightning. Thunder and lightning result from the same event: It is simply that
the light reaches your eyes much more quickly than the sound reaches your ears.
Interestingly, in water, sound travels about 4 times faster than it does through air
(1,483 m/s) (ISLE 10.2).
The Relation of Physical and
Perceptual Attributes of Sound
If you recall, we talked about light as a wave. In examining waves, there are two
important measures, their amplitude and their wavelength. Amplitude, for light,
means the intensity or brightness of the light, and wavelength dictates the color.
Sound has similar attributes—amplitude and frequency (the inverse of wavelength).
We also consider the concept of waveform, that is, how different frequencies interact
with one other to create complex sounds, which also affects our auditory perception.
Each of these physical attributes maps onto a perceptual attribute. Amplitude maps
onto loudness, frequency maps
onto pitch, and waveform maps
onto timbre. To start off our dis-
cussion, however, we consider
pure tones, that is, sound waves
in which air pressure changes
follow the basic sine wave for-
mat. A pure tone is heard at a
particular pitch but does not
have the complexity you would
expect when hearing a musical
instrument (or a voice) play (or
sing) that particular pitch. So we
consider each of these attributes
now (Figure 10.6). To listen to
a sample of pure tones, go to
ISLE 10.1c.
Amplitude and
Loudness
The amplitude of a sound is
expressed as the difference
between its maximum and min-
imum sound pressures. Thus, as
with ocean waves, as any surfer
will tell you, taller waves are stronger waves. A strong clap produces a bigger change
in air pressure than a mild, not-quite-excited clap. Dropping a hammer results in a
ISLE 10.2
The Speed of Sound
and the Sonic Boom
FIGURE 10.6 Amplitude, Frequency, and Waveform
(a) Difference between a low- and a high-frequency sound. The perceptual equivalent of frequency
is pitch. (b) Difference between a low- and a high-amplitude sound. The perceptual equivalent of
amplitude is loudness. (c) Difference between a simple waveform or pure tone and a complex sound.
Complex waveforms contribute to our perception of timbre.
Low frequency
(low-pitched tone)
High frequency
(high-pitched tone)
Low amplitude
(soft tone)
Time
A
ir
p
re
ss
u
re
A
ir
p
re
ss
u
re
Time
Simple waveform
(pure tone)
High amplitude
(loud tone)
Complex waveform
(complex sound)
A
ir
p
re
ss
u
re
Time
Normal air
pressure
A
ir
p
re
ss
u
re
Time
A
ir
p
re
ss
u
re
Time
A
ir
p
re
ss
u
re
Time
A
ir
p
re
ss
u
re
Time
A
ir
p
re
ss
u
re
Time
(a) (b) (c)
Frequency
(perceived as pitch)
Amplitude
(perceived as loudness)
Waveform
(perceived as timbre)
Pure tone: a sound wave in
which changes in air pressure
follow a sine wave pattern
FIGURE 10.5 This U.S. Air
Force F-22 Raptor is capable of
exceeding the speed of sound. Its
top speed is Mach 1.8 or nearly
twice the speed of sound.
RE
U
TE
RS
/H
o
N
ew
293 Chapter 10: The Auditory System
greater amplitude sound wave than does drop-
ping a feather. Think about the amount of air
that gets displaced when an airplane rushes
by. This force of the airplane creates large-
amplitude sound waves, which can be heard
for miles in all directions. Amplitude has a very
clear psychophysical correlate. Loudness is
the perceptual experience of amplitude or the
intensity of a sound stimulus. High-amplitude
(high-intensity) sounds will be heard as loud,
and low-amplitude (low-intensity) sounds will
be heard as soft. Thus, a person screaming pro-
duces greater amplitude of the human voice
than does a person whispering.
Amplitude is usually measured in decibels. A
decibel (dB) is 1/10 of a bel, which is a unit of
sound intensity named in honor of Alexander
Graham Bell. The decibel scale is a logarithmic
scale. This means that the intensity (amplitude)
of a sound increases more quickly than the num-
bers along the decibel scale. With every 6 dB, the
sound pressure doubles. A decibel level of 120
is nearly 1 million times greater in terms of sound
pressure than a decibel level of 10. The formula
to determine decibel level is given by (this is
one of the few formulas we actually include in
this book)
dB = 10log(p2/p
r
2),
in which dB is the sound pressure level, p is
the measured sound pressure (in another unit
called micropascals), and p
r
is an agreed-upon
reference sound pressure. Sound measures of
decibels are measures of relative intensity, so it
is important to know what both sounds are. In
the most usual case, p
r
derives from the audi-
tory threshold that is being used as the com-
parison sound. In this case, the measure should
be given as dB SPL, where SPL stands for “sound pressure level.” Figure 10.7 gives
the approximate decibel SPL levels of a number of common sounds.
Sustained exposure to sounds over 85 dB is potentially damaging, and even short
1-second exposures to sounds over 120 dB can result in immediate hearing damage.
What this means in terms of our loudness perception is that we can hear sounds across
a wide range of amplitudes, from really quiet sounds (the proverbial pin dropping) to
sounds so loud that they can damage our ears. In addition, we are remarkably good at
detecting differences in loudness. Under quiet conditions at average frequencies (e.g.,
2,000 Hz), we can discriminate a difference of just 1 dB. For example, if a series of
simple pure tones are played one after the other, at the same frequency, we can detect
the one tone that is 1 dB stronger than the other tones. We can perform similarly with
complex tones as well (ISLE 10.3).
FIGURE 10.7 Amplitude (Loudness) of Common Sounds
Decibels (dB SPL)
Lawn mower at close range;
stereo level of many listeners.
Flushing toilet
Normal conversation
Quiet of�ce level; normal refrigerator sound level
Usually suf�cient sound to awaken a sleeping person
Empty theater; whispered conversation
Sound threshold of a normal young adult
Micropascals
100,000,000
130
120
110
100
90
80
70
60
50
40
30
20
10
0
Immediate and
permanent hearing loss
Jet airplane at takeoff;
deafening if no protection
Prolonged exposure
above 85 decibels
can cause
noise-induced
hearing loss
Sound induces pain;
even short-term exposure
can cause permanent damage.
Very loud; sustained sound at
this level can cause damage.
10,000,000
1,000,000
100,000
10,000
1,000
100
20
140
150
160Handgun �ring
170
180
Amplitude: the difference
between maximum and
minimum sound pressures
Loudness: the perceptual
experience of the amplitude or
intensity of a sound stimulus
Decibel (dB): a physical
unit that measures sound
amplitude
294 Sensation and Perception
Loud sounds can be dangerous. Prolonged contact with sounds above 85 dB can
cause hearing loss in the long run. That is, people who work around such loud sounds
or play loud music frequently run the risk of damaging their hearing. This might include
the 90-dB sounds of airplanes taking off from the perspective of a baggage handler. This
is why people who work on the tarmac are supposed to wear ear protection, to reduce
that 90-dB level to something less harmful. Firearms instructors and other people who
spend extended time at firing ranges may also experience hearing loss in the long run,
even if they wear ear protection. Even with a 30-dB reduction from ear protection, many
firearms will still produce sounds that can damage the shooter’s
ears. Finally, many people listen to car stereos at sound levels
that approach or exceed 100 dB, which can lead to damage in
the long run. Even a hair dryer at close range can exceed 85 dB,
so be careful. There is a moral here: Be mindful of your daily
exposure to such loud sounds.
Sounds louder than 120 dB are decidedly painful, and sounds
louder than 130 dB will generally result in immediate and per-
manent hearing loss. A jet airplane at close range may be 140 dB,
hence the need for tarmac workers to protect their ears at all times.
Similarly, the firing of many guns is usually in excess of 160 dB
at close range, and hence the need for serious hearing protection.
Even small-caliber bullets can fire at nearly 140 dB. Thus, firing a
gun without ear protection can cause immediate damage to one’s
ears, which is a common symptom in veterans of wars. Most stan-
dard ear protection for shooters and tarmac workers results in
only a net reduction of 30 dB, which puts the shooters and workers
out of the range of pain and immediate damage but leaves them high in the zone of sounds
that cause long-term damage.
TEST YOUR KNOWLEDGE
1. What are the physical dimensions of amplitude and frequency, and what
perceptual dimensions do they map onto?
2. Why are loud sounds potentially dangerous to your ears?
Frequency and Pitch
The frequency of a sound stimulus refers to the number of cycles in the sound wave that
occur in 1 second. The perceptual correlate of frequency is pitch. Tones that have low
frequencies are heard as being low in pitch, whereas tones that have high frequencies
are heard as high in pitch (ISLE 10.4). We define frequency as the number of cycles in a
sound stimulus that occur in 1 second. Pitch is the subjective experience of sound that
is most closely associated with the frequency of a sound stimulus.
Remember that frequency and wavelength are inverses of each other. Frequency is the
number of cycles per second, and wavelength is the time course of one cycle. Thus, as the
frequency gets larger, the wavelength gets smaller, and vice versa. For arbitrary reasons, we
use a wavelength measure when discussing vision but a frequency measure when discussing
sound. This is not done just in this book to confuse you; rather, it is the convention in all
fields that concern themselves with physical measurements of light and sound. Frequency
is measured in hertz (Hz), which is a unit of measure indicating the number of cycles per
second, named after the German physicist Heinrich Hertz. A sound that has 200 cycles per
second (i.e., 200 ups and downs per second) is said to be 200 Hz. A sound that has 20,000
cycles per second (i.e., 20,000 ups and downs per second) is said to be 20,000 Hz.
ISLE 10.3
The Decibel Scale
©
iS
to
ck
ph
ot
o.
co
m
/m
ar
cd
uf
FIGURE 10.8
It’s a noisy world out there; ear protection can help save you from
hearing loss.
ISLE 10.4
Frequency and Pitch on a Piano
Frequency (sound
stimulus): the number of
cycles that occur in a second
Pitch: the subjective
experience of sound that is
most closely associated with
the frequency of a sound
stimulus; related to the
experience of whether the
sound is high or low, such as
the two ends of the keyboard
of a piano
Hertz (Hz): a unit of measure
indicating the number of
cycles per second
295 Chapter 10: The Auditory System
The psychological equivalent
of frequency is pitch. Pitch is the
subjective experience of sound
that is most closely associated
with the frequency of a sound
stimulus. Lower frequencies are
heard as lower in pitch, and higher
frequencies are heard as higher
in pitch. Think of the typical
man’s voice and woman’s voice.
Typically, women have voices with
higher pitches than those of men.
You can also think of a piano key-
board. If you play the note farthest
to the left, you are playing a note with a low frequency (27 Hz). Play the note farthest to
the right, and you are playing a note with a high frequency (4,186 Hz). Middle C is 261 Hz
(Figure 10.9). You can hear how frequency relates to pitch in ISLE 10.4.
Children and young adults can hear a range from about 20 to 20,000 Hz (Yost,
2007). As we get into our late 20s and beyond, we lose much of our hearing in the high-
est range. By the time one is 40 years old, it is unlikely that frequencies above 14,000
Hz are heard. By the time one is 50 years old, this upper limit may be down to 12,000
Hz. Dr. Krantz describes an experience in his lab when he was a graduate student in
which the students complained to the professor about loud, high-pitched, unpleasant
sounds being produced by equipment in the lab. The professor, old enough to be deaf
in this range, did not hear the sounds, but they were loud and painful to the younger
people in the lab. The loss of high-frequency hearing is inevitable, but it may be exacer-
bated by exposure to loud sounds when young. The lowest frequencies, however, tend
to remain stable with age. To determine your range of frequencies, go to ISLE 10.5.
Above 20,000 Hz and below 20 Hz, humans are simply deaf no matter how loud
the sound is. Thus, we could play a sound at 30,000 Hz, and we would not hear it,
regardless of the decibel level. However, your dog would hear the 30,000-Hz sound. If
it was loud enough, the dog just might complain about it, too. In fact, dogs can hear up
to about 50,000 Hz. This is the basis of the dog whistle, which makes a sound inaudible
to us but perfectly audible to your dog. This allows you to communicate to your dog
without other people being aware. Other animals can hear even higher frequencies than
that. Bats and dolphins, for example, can hear frequencies up to about 200,000 Hz.
These high frequencies are essential for their biosonar systems, which we discuss later
in the book. Other animals, such as elephants and humpback whales, can hear much
lower frequency sounds than we can. Elephants, for example, use calls as low as 1 Hz
for long-distance communication. These low-frequency sounds can travel farther than
higher frequency sounds, and whales can make very loud low-frequency sounds that
can be heard by other whales many miles away.
Losing these high frequencies has few consequences for understanding speech, as
even the highest soprano’s frequency is about 1,200 Hz. Similarly, music seldom reaches
frequencies higher than 4,186 Hz (the highest note on a piano), which is higher than
instruments noted for their high-pitch notes, such as violins and piccolos, can go. Losing
the high frequencies interferes with the perception of timbre, our next topic.
Waveform and Timbre
Imagine the difference between the sounds of a clarinet and a trumpet. A clarinet and
trumpet may be playing the same note, such as a B-flat in the same octave (i.e., at the
36
9.
99
41
5.
30
34
.6
48
38
.8
91
46
.2
69
51
.9
13
58
.2
70
69
.2
69
77
.7
82
92
.4
99
10
3.
83
11
6.
54
13
8.
59
15
5.
56
18
5.
00
20
7.
65
23
3.
08
27
7.
18
31
1.
13
46
6.
16
55
4.
37
62
2.
25
73
9.
99
83
0.
61
93
2.
33
11
08
.7
12
44
.5
14
80
.1
16
61
.2
18
64
.7
22
17
.5
24
89
.0
29
60
.0
33
22
.4
37
29
.3
29
.1
35
27
.5
00
Frequency (Hz)
N
ot
e
30
.8
63
32
.7
03
36
.7
08
41
.2
03
43
.6
54
48
.9
99
55
.0
00
61
.7
35
65
.4
06
73
.4
16
82
.4
07
87
.3
07
97
.9
99
11
0.
00
12
3.
47
13
0.
81
14
6.
83
16
4.
81
17
4.
61
19
6.
00
22
0.
00
24
6.
94
26
1.
63
29
3.
67
32
9.
63
34
9.
23
39
2.
00
44
0.
00
49
3.
88
52
3.
25
58
7.
33
65
9.
26
69
8.
46
78
3.
99
88
0.
00
98
7.
77
10
46
.5
11
74
.7
13
18
.5
13
96
.9
15
68
.0
17
60
.0
19
75
.5
20
93
.0
23
49
.3
26
37
.0
27
93
.0
31
36
.0
35
20
.0
39
51
.1
41
86
.0
FIGURE 10.9 Frequency and Pitch
A piano keyboard nicely illustrates the relation between frequency and pitch. As one moves to the
right from the keys farthest to the left on a piano, frequency increases. The lowest key on a piano is 27
Hz, whereas the highest is 4,186 Hz. As one moves from left to right on the piano keyboard, the notes
increase from low in pitch to high in pitch.
ISLE 10.5
Frequency Response of the Ear
296 Sensation and Perception
same frequency), and yet they still sound different. A trumpet’s
sound is pointed and comes right after you, even when played
softly. A clarinet seems to have a more subtle sound, which
seems to sneak up on you. Composers will call on trumpets
often for happy or martial music, whereas the clarinet is often
used to express a more sad sound. A piano playing the same
note might sound more neutral than either the trumpet or the
clarinet. How is it that different instruments playing the same
note can sound so different? (To hear the sounds of different
musical instruments, you can go to ISLE 10.6.) The difference
in sound quality when different instruments play the same
note has to do with the concept of harmonics. Harmonics are
higher frequencies present in a complex sound that are inte-
ger multiples of the fundamental frequency (main frequency).
There are a lot of terms in that definition that need explaining.
So we will now take a step back and explain the concepts of
the fundamental frequency, harmonics, and complex sound.
Pure tones are simple sine waves at single frequencies.
However, in nature, pure tones are virtually nonexistent.
Almost all sounds are complex sounds, which consist of
mixes of frequencies. These frequencies combine to form a complex waveform (Figure
10.10). A complex waveform can be broken down into its composite frequencies
through a mathematical formula known as Fourier analysis. Fourier analysis is a
mathematical procedure for taking any complex waveform and determining the sim-
pler waveforms that make up that complex pattern. The simpler waves used are sine
waves. When we do a Fourier analysis, we break down a complex sound into its
fundamental frequency and its harmonics. The fundamental frequency is the lowest
frequency present in the complex sound and the one that determines the perceived
pitch of that sound. The harmonics are all frequencies present in the stimulus that
are higher in frequency than the fundamental frequency. The fundamental frequency
determines the pitch of the sound, but the harmonics provide the timbre that makes
the sound of the clarinet different from that of the trumpet or the piano. See ISLE 10.7
for a Fourier analysis of real sound in real time.
So now we continue to unpack this new vocabulary. The fundamental frequency
determines the pitch. Thus, if the lowest frequency in a complex sound is 440 Hz, we
will hear this note as a pitch at concert-tuning A. However, there may also be frequen-
cies present at 880 Hz, 1,320 Hz, 1,760 Hz, 2,200 Hz, and so on. These additional
frequencies represent the harmonics (Figure 10.11). These harmonics determine the
characteristics that give each instrument (or voice, or any sound) a distinct timbre
when playing the same note. Observe that the fundamental frequency, though usually
louder than its harmonics, need not be the loudest frequency. It is always the lowest
frequency present in a sound. Even if the first harmonic is louder than the fundamen-
tal frequency, as it is in a clarinet, we still hear the pitch at the fundamental frequency.
Indeed, we can remove the fundamental frequency altogether, and we will still hear
the pitch at the missing fundamental. We hear the missing fundamental’s pitch because
the sequence of harmonics implies its presence (Schwartz & Purves, 2004). ISLE 10.8
illustrates pitch both with and without the fundamental frequency.
We hear these differences in the relative strength of harmonics as differences in
timbre. Timbre is the musical term that refers to the perceived sound differences
between sounds with the same pitch but possessing different higher harmonics. Timbre
provides the richness in sound we perceive when we hear a good violinist playing on
Harmonics: higher frequencies
present in a complex sound
that are integer multiples of the
fundamental frequency (main
frequency)
Complex sound: a sound
consisting of a mix of
frequencies
Fourier analysis: a
mathematical procedure for
taking any complex waveform
and determining the simpler
waveforms that make up that
complex pattern; the simpler
waves used are sine waves
Fundamental frequency: the
lowest frequency in a complex
sound, which determines the
perceived pitch of that sound
Timbre: the perceived sound
differences between sounds
with the same pitch but
possessing different higher
harmonics
ISLE 10.6
Timbre and Musical Instruments
FIGURE 10.10 Complex Waveforms
When three notes (green, light blue, and orange) are combined,
the result is a complex waveform (dark blue). Fourier analysis can
be used to determine how the component waves are combined to
create the complex waveform.
60
40
20
−20
−40
−60
0
0 2.5 7.5 10.0
Time (msec)
Complex waveform
A
m
p
li
tu
d
e
(
d
B
S
P
L)
12.5 15.05.0
ISLE 10.7
Fourier Analysis in Audition
297 Chapter 10: The Auditory System
a well-made violin. Well-made violins have a greater
array of harmonics than do cheap violins. The relative
loudness of different higher harmonics contributes to
timbre, but there are other factors that contribute as
well (see Chapter 12). To hear differences in timbre, go
to ISLE 10.9.
Phase
The last characteristic of sound stimuli we consider
is phase. Remember that sound is a change in sound
pressure over time and space. Think about that clap
again. It creates a wave of high-pressure peaks and
low-pressure troughs that propagate across space. If
you examine Figure 10.12, you see a sound wave with
a peak at Time 1 (T1) and a trough at Time 2 (T2). Like
any sound, we will hear this wave at the frequency that
represents twice the distance from T1 to T2, that is,
from one peak to the next one. Now consider Wave
B. This wave has the same frequency as Wave A, but it
is out of phase by 180 degrees. Thus, when the sound
in Wave A is at its peak, Wave B is at its trough, and
when the sound in Wave A is at its trough, the Wave
B is at its peak. In Figure 10.12, we see what happens
when we superimpose these sounds on each other:
They cancel each other out. That is, when these sound
waves are presented at the same time, but 180 degrees
out of phase, we hear neither Wave A nor Wave B, as
the two sounds cancel out. This is the principle behind
noise-canceling headphones, which have become pop-
ular among travelers. Some high-end cars also have
noise-canceling systems to reduce the amount of road
noise that one hears inside the car. You can see and
hear a demonstration of phase and canceling in ISLE
10.10.
TEST YOUR KNOWLEDGE
1. What is the fundamental frequency? Why is it important in sound perception?
2. What is the relation between timbre and harmonics?
G4
G5
392
(Fundamental
frequency)
D6
G6 B7
D7
F7
G7
Frequency (Hz)
A
m
pl
itu
de
0
0 1,000 2,000 3,000 4,000 5,000
Flute G4
G4 G5
392
(Fundamental
frequency)
D6
G6
B7 D7
F7 G7
Frequency (Hz)
A
m
pl
itu
de
0
0 1,000 2,000 3,000 4,000 5,000
Violin G4
FIGURE 10.11 Fundamental Frequency and
Harmonics of Common Musical Instruments
The fundamental frequency is the lowest frequency produced when
playing a particular note, though it need not be the loudest frequency. The
higher harmonics provide overtones that make the sound richer and more
complex; that is, they provide timbre.
ISLE 10.9
Timbre and Overtones
ISLE 10.8
Missing Fundamental
Phase: the position in one cycle
of a wave; there are 360 degrees
in a single cycle of a wave
ISLE 10.10
Phase and Cancellation
FIGURE 10.12 Phase
Phase refers to the position in
one cycle of a wave. The two
waves shown here have the
same frequency but are 180
degrees out of phase with each
other. If played together, they
would cancel each other out,
and we would hear nothing.
Wave B
Wave A
Cancels
sound
298 Sensation and Perception
ANATOMY OF THE EAR
10.2
Describe the basic anatomy of the ear and the difference
between the outer, middle, and inner ear.
We now turn our attention to the anatomy of the ear.
Like the eye, the ear is a complex system whose pur-
pose it is to take energy from the external environment
and render it into meaningful information. The ear fun-
nels sound waves toward specialized hair cells in the
inner ear that transduce the sound from physical sound
energy into a neural impulse, which then travels to the
auditory regions of the brain. Without transduction of
the auditory stimulus, there would be no hearing. Thus,
the question for this section is the following: How does
transduction take place? In this section, we start with
the entrance of the sound stimulus into the side of the
head and follow it until transduction occurs. This pro-
cess takes us through three distinct anatomical regions.
These regions are the outer ear, the middle ear, and the
inner ear. Figure 10.13 gives you an overview of the
anatomy of the ear.
The Outer Ear
The part of your ear that sticks out on the side of your head is called the pinna (plural
pinnae). The pinna collects sound and funnels it into the external auditory canal. The
pinna’s fleshy shape helps gather sound waves and channel them to the ear. The shape of
the pinna also helps in sound localization, that is, determining the direction a sound is
coming from. In other animals, the pinna can be moved in various ways, helping these
animals pinpoint sound in space (Figure 10.14). Think of your dog’s ear perking up as
it hears someone’s car pulling into the driveway. This action helps the dog determine the
source of the sound. A select few humans can also wiggle their pinnae, but it is unclear
if this gives them an advantage in sound localization, although it may be fun at parties.
After sound is collected by the pinna, it is directed into the external auditory canal. The
external auditory canal (also known as the external auditory meatus) conducts sound
from the pinna to the tympanic membrane. In all people, regardless of their height, the
auditory canal is about 25 mm long (just shy of 1 inch). This length helps amplify certain
higher frequencies. The auditory canal also acts to protect the tympanic membrane.
The tympanic membrane is commonly known as the eardrum. The tympanic mem-
brane is a thin elastic sheet that vibrates in response to sounds coming through the
external auditory canal. Thus, sound moving down the auditory canal hits against the
membrane, which vibrates in response to that sound. The tympanic membrane also seals
the end of the outer ear.
Damaging the tympanic membrane can result in hearing loss. A common injury in
scuba diving is the puncturing of the tympanic membrane due to high pressure in the
auditory canal. This injury is very painful but does not cause deafness. Divers may expe-
rience temporary hearing loss until the membrane heals. In most cases, the tympanic
membrane will repair itself. But repeated injury can result in permanent damage due to
scarring, in which case hearing loss will be permanent. The Bajau people, a traditional
diving and seafaring culture in the Philippines, will intentionally rupture their tympanic
membranes as children to reduce pain from free diving (Langenheim, 2010). Not surpris-
ingly, many Bajau people have hearing deficits.
FIGURE 10.13 Overview of the Anatomy of the Ear
Hammer
Anvil
Semicircular canals
Cochlea
Auditory nerve
Stirrup
Tympanic
membrane
(eardrum)External auditory
canal
Pinna
Pinna: the structure that
collects sound and funnels it
into the auditory canal
External auditory canal
(external auditory meatus):
the channel that conducts
sound from the pinna to the
tympanic membrane
Tympanic membrane: a thin
elastic sheet that vibrates in
response to sounds coming
through the external auditory
canal; commonly known as the
eardrum
299 Chapter 10: The Auditory System
The Middle Ear
The tympanic membrane is the last structure of the outer ear. The next part of the ear is
called the middle ear, which consists of three small bones that transmit sound into the
inner ear. When the tympanic membrane vibrates, it causes motion in these three small
bones, called ossicles, which then conduct the sound mechanically. You have probably
heard the old (but true) refrain that the ossicles are the smallest bones in the body, but
we repeat it here anyway. The three ossicles act to amplify sound waves, although most
of the amplification comes from the size of the tympanic membrane relative to the oval
window. The tympanic membrane causes sound transmission in the first ossicle, known
as the malleus. The malleus vibrates and transmits the sound to the next ossicle, known
as the incus. The incus is then connected to the final ossicle, known as the stapes. The
stapes then pushes against the oval window of the cochlea, and sound moves into the
inner ear. Examine Figure 10.15 to see how these bones are connected inside the ear. For
a simulation of how this system works to propagate sound, see ISLE 10.11.
The ossicles are important for the following reason. The cochlea of the inner ear is
immersed in liquid, but sound in the auditory canal is in the form of air-based sound waves.
Why is this relevant? Sound travels well in water, but it does not cross from air to water very
well. In fact, 90% of sound traveling through air will bounce off water rather than penetrate
it. This is why that darn party across the lake seems so loud even though it is quite far away.
In essence, sound just skips off the surface of the water rather than penetrating it. The sound
that heads in the direction of the lake itself echoes off the lake’s surface rather than being
absorbed by the water, leading it to sound much louder farther away than if the same party
were being held at the edge of a field. In contrast, because sound is being transmitted from
an air environment to the watery environment of the inner ear, the sound must be amplified
as much as possible to overcome the loss of sound due to this transition. In the outer ear,
the sound is still traveling through air as it makes its way to the tympanic membrane. Thus,
a system is needed to amplify the sound before its intensity is diminished when it hits the
ISLE 10.11
The Middle Ear
Ossicles: three small bones in
the middle ear
Malleus: the first ossicle
in the middle ear; receives
vibrations from the tympanic
membrane and transmits them
to the incus
Incus: an ossicle in the middle
ear; receives vibrations from
the malleus and transmits
them to the stapes
Stapes: an ossicle in the
middle ear; receives vibrations
from the incus and transmits
them to the oval window of the
inner ear
FIGURE 10.14 Pinnae in Different Mammals
©
iS
to
ck
ph
ot
o.
co
m
/t
et
m
c
©
iS
to
ck
ph
ot
o.
co
m
/m
om
ci
lo
g
©
iStockphoto.com
/TakinPix
©
iS
to
ck
ph
ot
o.
co
m
/J
iri
H
au
re
lju
k
©
iS
to
ck
ph
ot
o.
co
m
/y
es
fo
to
©
iStockphoto.com
/Becart
300 Sensation and Perception
liquid medium of the cochlea. The ossicles serve to amplify the sound.
Interestingly, this is the reason why fish have no need for an outer and
middle ear. Because sound goes directly from the water to their inner
ears, they do not need to amplify the sound.
The ossicles amplify sound in the following way. First, they use lever
action to increase the amount of pressure change. A small amount of
energy at the malleus becomes a larger amount at the stapes. Second,
the ossicles transfer energy from a larger surface area, the tympanic
membrane, to a smaller surface area, the oval window of the cochlea.
Indeed, the tympanic membrane is about 18 times as large as the oval
window. Thus, the bones increase the sound pressure 18 times at the
oval window, critical in the transmission of sound into the liquid envi-
ronment of the cochlea. Thus, most of the amplification is due to the dif-
ference in size between the tympanic membrane and the oval window.
The middle ear has a number of other important functions. One
part of the middle ear is called the eustachian tube. The eustachian
tube is the thin tube that connects the middle ear with the pharynx
and serves to equalize air pressure on either side of the tympanic
membrane. Normally, the eustachian tube is closed, but it opens
briefly when we swallow or yawn, for example. The brief opening
of the eustachian tube is the technical explanation for the phenom-
enon of “popping” your ears. When you hold your nose and blow,
the eustachian tubes open to release the pressure. This is also why
divers must continually equalize as they descend to deeper depths
(Figure 10.16). Failure to do so during diving brings first intense
pain and also potential damage to the tympanic membrane.
The middle ear is filled with air, and except for when the eustachian
tube is open, it is cut off from any changes in air pressure in the out-
side environment. For optimal operation of the tympanic membrane,
it is important for the air pressure on both sides of the tympanic mem-
brane to be equal, but the air pressure outside the tympanic membrane
changes regularly due to weather and altitude. The eustachian tube
opens to allow the two air pressures to equalize. Usually the change
in air pressure in the middle ear is slight, which is why the eustachian
tube does not open very often under normal circumstances. Yet when
you ascend or descend a mountain, especially when you are doing so
rapidly in a car, there can be a large change in air pressure, causing
your ears to pop, particularly as you descend and the air pressure
increases outside your ears relative to inside them. Pressure changes
may occur when we dive in water, as pressure increases more rapidly
as we descend underwater than it does in air. One of the first skills a
scuba diver must master is “equalizing,” that is, forcibly opening the
eustachian tubes to equalize pressure. If you are ascending a moun-
tain, the air pressure outside your ears decreases with each step up
in altitude. If your eustachian tubes stay closed, you will have much
more air pressure on the middle-ear sides of your tympanic mem-
branes than outside, causing them to bow toward the outside of your
head. Being pushed out causes the tympanic membrane to move less effectively in response
to sound stimuli, and in these cases you might find that your hearing is not quite as good
as normal. When you yawn or swallow, in these cases there will be a rapid reduction of
the air pressure inside your middle ear, which you experience as the popping of your ears.
The ossicles also serve a role in attenuating sustained loud sounds. There is a muscle
attached to the malleus called the tensor tympani and a second muscle attached to the
FIGURE 10.15 Anatomy of the Middle Ear
The three bones of the middle ear receive mechanical
stimulation from the tympanic membrane and transmit it to the
oval window. Because the oval window is smaller than the
tympanic membrane, this transmission acts to amplify the sound.
Eustachian tube: a thin tube
that connects the middle ear
with the pharynx and serves to
equalize air pressure on either
side of the eardrum
Tensor tympani: the muscle
that is attached to the malleus
©
iS
to
ck
ph
ot
o.
co
m
/P
op
ar
tic
FIGURE 10.16 The Middle Ear Adapts to
Pressure Changes From Diving
301 Chapter 10: The Auditory System
stapes called the stapedius. Like the bones they are attached to, these are the smallest mus-
cles in the body. Their job is to tense in the presence of very loud noises, thus restricting the
movements of the ossicles and avoiding damage to the inner ear. This acoustic reflex pro-
tects somewhat against chronic loud noises, such as car stereos, but it is too slow for sud-
den loud noises such as the sound of a gun firing. (Have we mentioned that being around
gunfire is not good for your hearing?) Interestingly, these muscles may also tense in response
to sounds generated inside the head, such as the sounds generated by chewing or talking.
TEST YOUR KNOWLEDGE
1. Describe the anatomy of the outer and middle ear.
2. What are the functions of the ossicles?
The Inner Ear
The inner ear contains the parts of the ear that transduce sound into a neural signal. In par-
ticular, the hair cells situated along the organ of Corti in the cochlea act by taking vibrations
and converting them into a neural signal. In this way, the hair cells are equivalent to the rods
and cones of the retinae. The inner ear is an amazing accomplishment of evolution, but it has
lots of parts with hard-to-remember (and seemingly arbitrary) names, and thus it typically
presents a challenge for students learning about it for the first time. Therefore, read carefully,
study the diagrams, and test yourself repeatedly. For a diagram of the inner ear, examine
Figure 10.17. Go to ISLE 10.12 for an interactive model of the workings of the inner ear.
FIGURE 10.17
The Inner Ear
The inner ear is a very complicated
part of the body that contains the
hair cells that transduce sound into
a neural signal. These hair cells are
located along the basilar membrane,
which transmits the mechanical
input of sound. When sound enters
the inner ear, the tectorial membrane
causes the basilar membrane
to vibrate. These vibrations are
detected by the hair cells, starting
the neural signal.
Hammer
(a) Cochlea and middle ear
(b) Section of cochlea
(c) Organ of Corti
Auditory
nerve
Vestibular
canal
Hair cells
Tympanic
canal Cochlear
canal
Tectorial membrane
Hair cells
Basilar membrane
Cochlear
neuron
Oval window
(membrane behind stirrup)
Tympanic
membrane
Stirrup
Anvil
ammer
(c) OrOrgangan of Coorti
AudA itory
nern ve
Vestibulaarr
canal
HaiH r ccelle ss
Tympanic
canal CocC hlear
canc al
Tectorial membrane
HaiHair celll ss
Basilar membrane
Cochlehl arr
neun ronn
Oval window
(meembrmb aneane beb hini d sd tirrup)
mmpanpa icic
mbrane
StiS rruup
Stapedius: the muscle that is
attached to the stapes
Acoustic reflex: a reflex that
tightens the tensor tympani
and the stapedius in response
to chronic loud noise
Cochlea: the snail-shaped
structure of the inner ear that
houses the hair cells that
transduce sound into a neural
signal
302 Sensation and Perception
The cochlea is the snail-shaped structure of the inner ear that houses the hair cells that
transduce sound into a neural signal. The term cochlea derives from the Greek word for
snail, and if you look at the cochlea depicted in Figure 10.17, you will see that its spiral
indeed looks like a snail. The cochlea is a coiled tube, coiled 2.74 times. As a coiled tube,
it takes up just about 4 mm of space inside your ear, but if you were to unroll it, it would
stretch to about 33 to 35 mm in length (1.3 inches).
Now examine the picture of the cross-section of the cochlea, shown in Figure 10.18. You
will see that the cochlea has three liquid-filled chambers, called the tympanic canal, the mid-
dle canal (also called the cochlear duct), and the vestibular canal. In the apex (the end of
the cochlea) is an opening called the helicotrema that allows fluid to flow between the tym-
panic canal and the vestibular canal. The apex is the part of the cochlea farthest from the oval
window if the cochlea were uncoiled. Seated just underneath the oval window is the round
window. The round window is a soft tissue substance at the base of the tympanic canal. Its
function is as an “escape” valve for pressure from sounds that arrive in the cochlea, because liq-
uids do not behave the way that gasses do. Remember that in sound waves, the molecules com-
press, but in liquids, such as those that fill the cochlea, the molecules compress much less, so
when the oval window presses in, there needs to be a place that pushes out, namely, the round
window. We will return to function shortly, but we need to cover just a bit more anatomy first.
The Basilar Membrane of the Cochlea
Two membranes separate the canals of the cochlea. One is Reissner’s membrane, which
separates the vestibular canal and the middle canal. The other membrane is the basilar
2000 Hz
1000 Hz
800 Hz
400 Hz
600 Hz
3000 Hz
5000 Hz
4000 Hz
10000 Hz
20000 Hz
FIGURE 10.18
Cross-Section of the
Cochlea
The cochlea is the snail-
shaped structure. The base
is the starting point and
then it coils around to the
apex. The basilar membrane
separates the middle canal
from the tympanic canal.
The organ of Corti rests
along the basilar membrane.
Reissner’s membrane
separates the vestibular
canal from the middle canal.
Tympanic canal: one of the
three chambers in the cochlea;
separated from the middle
canal by the basilar membrane
Middle canal (cochlear duct):
one of the three chambers in
the cochlea; separated from
the tympanic canal by the
basilar membrane; contains
the organ of Corti
Vestibular canal: one of the
three chambers in the cochlea;
separated from the middle
canal by Reissner’s membrane
Round window: a soft tissue
substance at the base of the
tympanic canal whose function
is as an “escape” valve for
excess pressure from loud
sounds that arrive in the cochlea
ISLE 10.12
The Basilar Membrane
and Sound Stimuli
303 Chapter 10: The Auditory System
membrane, which separates the tympanic canal
and the middle canal. Lying along the basilar
membrane within the middle canal is the organ
of Corti, which contains the hair cells. The basi-
lar membrane is not really a membrane. Rather,
it is composed of harder and thicker material,
which allows it to vibrate in response to incom-
ing sound. At the base (nearest to the oval
and round windows), the basilar membrane is
thicker and stiffer and therefore more respon-
sive to high-frequency sounds. At the apex (the
uncoiled opposite end), the basilar membrane
is less thick and less stiff and therefore more
responsive to low-frequency sounds.
Take a look at Figure 10.19. Notice that
the stapes of the middle ear asserts pressure
on the oval window. This pressure from the
stapes causes a wave in the fluid (perilymph)
of the middle canal in the inner ear. This pres-
sure wave in the perilymph causes a traveling wave to move down the length of the
basilar membrane. Traveling wave here means that the wave moves from the base to
the apex of the basilar membrane (ISLE 10.13). If the sound being presented is high
frequency, the traveling wave will show greater motion toward the base of the basilar
membrane. Lower frequency sound will cause more movement farther down the basilar
membrane. The lowest frequency sounds we can hear move the basilar membrane near
the apex. The movement of this wave is critical to understanding how frequency is
coded in the cochlea.
To understand why the thick end of the basilar membrane is conducive to high-fre-
quency sounds and the thinner or “floppy” end to lower frequency sounds, think of
stringed instruments. On a violin, for example, lower pitches are produced by the G
string, located farthest to the left on the fingerboard. Pull on the G string, and it will
feel relatively loose. The highest pitches on a violin are produced by the tightly wound
E string, which is farthest to the right on the fingerboard. Pull on this string, and it
feels tight. If the E string is out of tune and too flat (too low in pitch), the violinist gets
it into tune by tightening the string. Because the E string is so tightly wound to begin
with, many novice violinists may snap the string altogether. If the E string is out of
tune and too sharp (too high in pitch), the violinist gets it into tune by loosening the
string. The basilar membrane is equivalent to this. The base is tightly wound and thus
more responsive to high frequencies, whereas the apex is loose and responsive to lower
frequencies. For an illustration of how the basilar membrane moves in response to dif-
ferent frequencies, go to ISLE 10.14.
Incoming vibrations will cause the basilar membrane to vibrate. The base of the bas-
ilar membrane is tightly wound and thus more responsive to high frequencies, whereas
the apex of the basilar membrane is loose and responsive to lower frequencies.
Indeed, the displacement of the basilar membrane in response to frequency is
quite specific. Each location along the basilar membrane responds to a characteristic
frequency. Any sound will move the basilar membrane at every location, but a par-
ticular location will respond the most, in terms of movement, to its characteristic
frequency. In the most common case, in which we hear a complex sound, complete
with harmonics, the basilar membrane will reflect these frequencies by moving at
various places along its length. In effect, the basilar membrane does a Fourier analysis,
breaking down complex sounds into their component frequencies (von Békésy, 1960).
To see this visually, look at Figure 10.20. You can also see a demonstration of this
on ISLE 10.15.
Reissner’s membrane: the
membrane that separates the
vestibular and middle canals
Basilar membrane: the
membrane that separates the
tympanic canal from the middle
canal; the organ of Corti lies on
the basilar membrane
Organ of Corti: a structure
on the basilar membrane that
houses the hair cells that
transduce sound into a neural
signal
Perilymph: the fluid that fills
the tympanic canal and the
vestibular canal
Characteristic frequency:
the frequency to which any
particular location along the
basilar membrane responds best
Perilymph
Basilar
membrane
At thicker, narrower, stiffer
base of basilar membrane,
high-frequency pressure
waves cause greatest
displacement.
In middle portion of basilar
membrane, mid-frequency
pressure waves cause
greatest displacement.
At thinner, wider, more
flexible apex of basilar
membrane, low-frequency
pressure waves cause
greatest displacement.
Vibration of stapes against oval window
causes pressure wave in perilymph.
Pressure wave in perilymph
causes traveling
wave in basilar
membrane.
FIGURE 10.19
Sound Waves and Changes to the Basilar Membrane
ISLE 10.13
The Travelling Wave
ISLE 10.14
Place Code Theory
ISLE 10.15
The Basilar Membrane
and Fourier Analysis
304 Sensation and Perception
FIGURE 10.20
Frequency and
Displacement Along the
Basilar Membrane
(a) The basilar membrane is
shown as if it were uncoiled
and spread in a line. Each
location along the basilar
membrane vibrates to the
greatest extent in response
to one frequency. That is,
a sound of a particular
frequency will maximally
displace the basilar membrane
at that location. (b) We can
see characteristic frequencies
and their displacement along a
schematic basilar membrane.
Sounds of high frequency
excite locations toward the
base of the basilar membrane,
whereas sounds of low
frequency excite locations
toward the apex of the basilar
membrane.
Apex
t
0
t
1
t
2
t
3 t4
t
0
t
1
t
2
t
3 t4
Base
Time
Wave responses to sound dominated by high frequencies
Traveling waves in basilar membrane
(displacement of basilar membrane from base to apex over time, from t
0
to t
4
)
20,000 Hz 1,000 Hz 20 Hz
10,000 Hz 100 Hz
Base
Characteristic frequencies
in basilar membrane
Apex
Time
Wave responses to sound dominated by low frequencies
(a)
(b)
Hair cells: cells that have
stereocilia for transducing
the movement of the basilar
membrane into a neural signal
Stereocilia: the hairlike parts
of the hair cells on the top of
the inner and outer hair cells
Outer hair cells: cells that
sharpen and amplify the
responses of the inner hair
cells
Inner hair cells: cells that are
responsible for transducing
the neural signal
Tectorial membrane: a
membrane that rests above the
hair cells within the organ of Corti
In essence, the basilar membrane converts the sound energy that beats against the
oval window into mechanical movement along its length with any particular location
along its length responding to particular frequencies of sound. We are now, finally,
ready to begin to discuss how this physical signal gets changed into a neural one.
The Organ of Corti
The organ of Corti is the structure along the basilar membrane that contains the hair
cells that transduce sound into a neural signal. The name Corti honors the Italian sci-
entist Alfonso Corti (1822–1876), who experimented on the function of the cochlea in
the 1850s. In addition to the hair cells, the organ of Corti also contains the dendrites
of the auditory nerve that brings the neural signal to the brain. The critical hair cells
in the organ of Corti are specialized cells for transducing the motion of the basilar
membrane into a neural signal. The hair cells have hairlike filaments called stereocilia
for transducing the movement of the basilar membrane into a neural signal. These ste-
reocilia bend in response to the movement of the basilar membrane, and the bending
changes the voltage within the hair cells. There are four layers of hair cells that follow
the basilar membrane. The first row is called the outer hair cells, and the row that lies
inside that is called the inner hair cells (Figure 10.21). There are about 3,500 inner hair
cells and about 3 times that many outer hair cells. Each hair cell has anywhere from 50
to 150 stereocilia sticking off its top in order to detect the motion of the basilar mem-
brane. Inner hair cells are responsible for transducing the neural signal, whereas outer
hair cells refine and amplify the neural responses of the inner hair cells. The tectorial
membrane sits above the hair cells within the organ of Corti, helping hold them in
place (ISLE 10.16).
ISLE 10.16
Transduction and Hair Cells
305 Chapter 10: The Auditory System
When a vibration of the basilar membrane causes the basilar membrane to move
upward, the stereocilia brush against the tectorial membrane. When stereocilia are
pushed in this manner, there is a change in the cell’s voltage potential. This voltage
change causes the release of neu-
rotransmitters, which cause the
auditory nerve to send a signal.
This process can be seen visually in
Figure 10.22. And with the induc-
tion of a signal in the auditory
nerve, the sound has been trans-
duced and sound information gets
conveyed to the brain.
One of the most impor-
tant scientists in this area was
Hungarian-born Georg von Békésy
(1899–1972) (Figure 10.23). He
did most of his important work
while on the faculty of Harvard
University. For his work on the
basilar membrane and how it codes
for frequency, von Békésy won the
1961 Nobel Prize in Medicine and
Physiology. Von Békésy was the
first to show that the basilar membrane vibrates more at certain locations along its
length in response to different frequencies, thus allowing the auditory system to discrim-
inate among frequencies. Although many of you may find this bizarre, von Békésy did
his most famous work by playing really loud sounds into the ears of human cadavers.
Much of the discussion of basilar membrane function in the previous paragraphs is
knowledge we learned from von Békésy’s work. His view of frequency representation
in the cochlea is known as the place code theory. The alternative view is known as the
temporal code theory (Wever & Bray, 1937), which states that frequency represen-
tation occurs because of a match between sound frequency and the firing rates of the
auditory nerve.
The evidence for place code theory rests largely on the observation that the bas-
ilar membrane’s thickness changes along the cochlea, and this thickness allows it to
FIGURE 10.21
The Organ of Corti
The organ of Corti contains both
inner hair cells and outer hair
cells, as well as the tectorial
membrane. The outer hair cells
connect to the auditory nerve.
Auditory
nerve
Type I
nerve
fiber
Endolymph
Tectorial membrane
Inner hair
cell
Type II
nerve
fiber
Movements of basilar and tectorial membranes,
resulting in shearing force on stereocilia
Stereocilia
Basilar membrane
Outer
hair
cell
Place code theory: the view
that different locations along the
basilar membrane respond to
different frequencies
Temporal code theory:
the view that frequency
representation occurs
because of a match between
sound frequency and the firing
rates of the auditory nerve
Outer hair cellsInner hair cells
Tectorial membrane
Basilar membrane
Upward phase
Shear
force
Downward phase
Shear
force
Sound-induced vibration
Resting position
FIGURE 10.22 Actions of Hair Cells
Vibration causes the tectorial membrane to shear against the hair cells, that is, to move in opposite
directions. This movement causes the stereocilia of the hair cells to transduce sound into a neural signal.
306 Sensation and Perception
respond differently to different frequencies along its length. Von Békésy also observed
the movement of the basilar membrane in response to loud sounds. In this way, the
basilar membrane separates out different frequencies, and the hair cells that lie along
the length of the basilar membrane can code for these different frequencies. Thus,
when hair cells at a specific position are activated, the auditory system can interpret
this as a sound at a particular frequency. This is illustrated in Figure 10.20 as well as
in ISLE 10.17.
As we get older, the basilar membrane gets stiffer. This accounts for the observa-
tion that as we age, we lose the ability to hear higher frequencies. By the time people
reach the age of 50 or so, they cannot hear frequencies above approximately 12,000
Hz. This occurs even in the absence of exposure to loud sounds. Even people at 25,
by and large, have lost hearing above 16,000 Hz. This age-related hearing loss in the
higher frequency range has some amusing consequences. Teenagers can purchase ring
tones for their cell phones at very high frequencies that will alert them to incom-
ing messages, but to which their teachers will be deaf. Most adults are not simply
impaired when it comes to hearing a 20,000 Hz tone; they are deaf. Thus, a teenager
receiving a call or text message has little risk of being detected by anyone else than
another teenager. On the other hand, some store owners, in an effort to keep teenagers
from “hanging out” in front of their stores, will play very loud high-frequency tones.
The store owners and their paying customers are deaf to these sounds and will there-
fore come and go as they like. But the loud high-frequency sounds will be painful to
the loitering teens, who will therefore seek somewhere else to hang out. Tit for tat,
we suppose.
TEST YOUR KNOWLEDGE
1. Describe how hair cells transduce the sound signal in the cochlea.
2. What is place code theory? How does the displacement of the basilar
membrane in response to specific frequencies support this view?
10.3
Examine the nature of hearing loss and what can be done
to improve hearing in hearing-impaired individuals.
Sc
ie
nc
e
H
is
to
ry
Im
ag
es
/A
la
m
y
St
oc
k
Ph
ot
o
FIGURE 10.23
Georg von Békésy
ISLE 10.17
Temporal Code Theory
EXPLORATION: Hearing Loss
Those who have lost the ability to hear can learn language
through sign languages and may often be quite competent
at spoken languages by reading lips and inferring contexts
(Figure 10.24). Many deaf people have accomplished
great things even without this crucial sensory system. In
a beautiful book, Josh Swiller (2007), a profoundly hear-
ing-impaired man, describes his adventures as a Peace
Corps volunteer in southern Africa. In his tireless efforts
to help the people of his assigned village, Swiller does not
let his hearing impairment hold him back. Nonetheless,
when his digital hearing aids are stolen while he is thou-
sands of miles away from possible replacements, Swiller
begins to understand what it is like to be truly deaf in a
world in which hearing is necessary.
We have already mentioned a number of ways in which the
auditory system is vulnerable to damage. In particular, the
mechanisms of the ear, while finely tuned to an incredible
range of amplitudes and frequencies, are also vulnerable to
loud noises and high pressures. And even though each hair
cell has a great many stereocilia, there are only so many
hair cells, so that damage to hair cells can have grave con-
sequences for hearing also. Luckily, there are many options
to improve hearing in those with hearing loss.
In the United States, more than 30 million people have hear-
ing loss, according to the Centers for Disease Control and
Prevention (2017). Approximately three quarters of these
people are over the age of 60. Presbycusis refers to the loss
307 Chapter 10: The Auditory System
of hearing associated with aging (Yost, 2007), which is more
common in men than women. Presbycusis is also more com-
mon in societies such as our own, in which more people are
exposed to loud sounds than people are in more traditional
societies, where they may not be subjected to all the mechan-
ical sounds people in industrialized societies are. (Think of
how many mornings you have awoken to the sounds of lawn
care machines outside your window—and now think of the
landscapers’ hearing.) There are also a number of genetic and
acquired hearing loss problems in younger adults. Disease
and injury can also cause hearing loss in people of all ages.
Audiologists are doctoral-level specialists who evaluate, diag-
nose, and treat hearing impairments, provided they do not
require immediate medical attention. Audiologists are equiva-
lent to optometrists in the visual domain, in that their specialty
is assessing the problem and then helping the patient find the
right hearing aid, just as an optometrist evaluates visual prob-
lems and then prescribes corrective eyewear. During an audi-
ological exam, an audiologist administers a set of tests using
an audiometer. It may be that you have had an audiological
exam at some point. The audiometer presents pure tones at
set frequencies and known amplitudes to either the left or
right ear. It is used in the assessment of absolute threshold
at each frequency for a patient. The result of this procedure
is an audiogram. Figure 10.25 shows an audiological report
of a patient with a genetic sensorineural hearing impairment
(i.e., hearing loss due to congenital damage to hair cells). This
patient’s peak impairment is around 4,000 Hz in both ears.
The patient has mostly normal hearing at lower frequencies.
We now consider the various forms of hearing impairment.
Conductive Hearing Loss
Conductive hearing loss is characterized by damage to some
aspect of sound transmission in the outer or middle ear.
Thus, in conductive hearing loss, sound does not properly
get to the cochlea for transduction into a neural signal. This
can occur because of blockage of the auditory canal, a torn
tympanic membrane, or damage to the ossicles. In particu-
lar, conductive hearing loss may occur because of otoscle-
rosis. Otosclerosis is an inherited bone disease in which the
ossicles, particularly the stapes, may calcify and therefore be
less conductive of sound. In some cases, hearing loss due to
otosclerosis can be improved by replacing the stapes with an
artificial bone.
There are also conditions in which hearing loss may occur on
a temporary basis. Ruptured tympanic membranes may heal
properly, restoring full hearing. Hearing loss may also occur
on a temporary basis during an ear infection, if the auditory
canal becomes blocked with fluid. Treatment of the infection
may be sufficient to return hearing to normal, but in some
cases, the middle ear must be drained to allow hearing to
return to normal.
Sensorineural Hearing Loss
Sensorineural hearing loss occurs because of damage to the
cochlea, the auditory nerve, or the primary auditory cortex.
The term sensorineural hearing loss refers to acquired
©
iStockphoto.com
/D
ean M
itchell
FIGURE 10.24 Sign Language
Normal impairment Caused by noise exposure
Left ear Right ear
125
−10
10
20
30
40
50
60
70
80
0
250 500
FREQUENCY in Hz
H
e
a
ri
n
g
l
e
v
e
l
in
d
B
1000 2000 4000 8000
FIGURE 10.25 Audiological Report
This patient has moderate to severe hearing loss in both ears in the high
frequency range. But you can also see that some frequencies are more
affected than others.
Source: Reprinted with permission from the Handbook for Acoustic Ecology, B.
Truax, ed., Cambridge Street Publications, CD-ROM edition, 1999.
Otosclerosis: an inherited bone disease in which the
ossicles, particularly the stapes, may calcify and therefore
be less conductive of sound
308 Sensation and Perception
hearing problems and genetic problems, and the condition
can range from minor hearing loss to profound hearing
deficits. This form of hearing loss is most often precipi-
tated by damage to hair cells, which can occur because of
noise exposure or certain drugs. In addition, certain anti-
biotics and cancer treatments have the side effect of dam-
aging hair cells in the cochlea. Although these medicines
are given only when a patient’s life is at stake, they can
affect hearing. Inherited sensorineural hearing loss is rare
but may show up at infancy, in childhood, and sometimes
not until adulthood. Today, tests are immediately given to
a newborn’s ear to determine if there is congenital hearing
loss. If so, parents can make appropriate decisions for their
infant in order to make sure that the infant develops lan-
guage normally.
Tinnitus
Tinnitus is the condition in which people perceive sounds
even when none are present. The perceived sound usually
sounds like a pure tone at a particular frequency. Most peo-
ple experience tinnitus occasionally and for brief periods
of time, and for the vast majority of us, tinnitus is seldom
a problem. But when it occurs all the time or is subjectively
loud, it becomes a problem (Figure 10.26). It is thought that
most cases of tinnitus involve a neural signal being sent to
the brain in the absence of an actual sound. Thus, tinni-
tus can interfere with the perception of real sounds in the
environment, including speech. Tinnitus is associated with
noise-induced hearing loss, but there may be other causes as
well (Møller, 2006). A former student of Dr. Schwartz was
afflicted with a bad case of tinnitus after being awakened
by a loud fire alarm just above his head. The illusory sound
was so loud for this young man that it interfered with his
ability to study. After several months, the tinnitus decreased
and eventually disappeared. In other cases, tinnitus may be
the result of damage to the cochlea or damage or infection
to the auditory nerve. Treatment may include hearing aids,
which can amplify external sounds, such as the frequencies
of human voices, while at the same time playing white noise
at the same frequency as the tinnitus sound, in hopes of
canceling it out. Some attempts to find drugs that reduce
tinnitus have also been successful.
Tinnitus: a condition in which people perceive sounds even
when none are present
©
iS
to
ck
ph
ot
o.
co
m
/a
po
m
ar
es
FIGURE 10.26 Tinnitus
APPLICATION: The Science of
Hearing Aids and Cochlear Implants
Hearing Aids
Hearing aids are electronic devices that amplify sound so
that people with hearing deficits can hear sounds that oth-
erwise would be below their thresholds. Hearing aids can
be the “behind-the-ear” style (see Figure 10.27a) or the
“in-the-ear” style (Figure 10.27b). In-the-ear hearing aids
are smaller and less obtrusive than behind-the-ear aids,
but behind-the-ear devices can amplify sounds more and
thus are preferable for people with moderate, severe, or
profound hearing loss. In-the-ear aids work fine for people
with mild to moderate hearing loss. Younger people with
hearing loss may also prefer in-the-ear devices because
they are less visible.
In the past, hearing aids were analog devices. Analog
devices amplify the actual sound present, but because they
work with the actual sound, they are limited in what other
forms of sound processing they can do. In general, analog
hearing aids amplify all sounds the same amount (though
Hearing aids: electronic devices that amplify sound so that
people with hearing deficits can hear sounds that otherwise
would be below their thresholds
309 Chapter 10: The Auditory System
many have volume controls). This is potentially problem-
atic because, as we have just seen, the pattern of hear-
ing loss may be different at different frequencies. Thus, if
we amplify all sounds, we may amplify some to a level at
which they can be heard, but that may mean that other
sounds are too loud and others are still too soft.
In technologically advanced countries, most hearing aids
are now digital devices. Digital hearing aids first con-
vert the sound signal into a computer code, which is then
reconverted into an analog sound for the wearer. This
transformation into a digital signal allows additional
processing to the signal in addition to amplification.
Digital hearing aids have a number of important advan-
tages over earlier analog aids. First, digital hearing aids
can be fitted to a particular individual’s pattern of hear-
ing loss. This is important because hearing loss may vary
greatly from one patient to another, both in the loudness
of sounds required to allow hearing and in the frequency
range of the hearing loss. Digital hearing aids can be pro-
grammed to amplify some frequencies more than other
frequencies. If a patient has nearly normal hearing at 400
Hz, a digital hearing aid can be programmed to amplify
not at all or very little at that frequency. But if the same
patient has severe hearing loss at 1,000 Hz, the aid can
be programmed to amplify much more at that frequency.
In this way, the digital aid can restore a pattern of hear-
ing that approximates what a person with normal hear-
ing would experience.
Digital hearing aids can also be programmed to have
directionally sensitive microphones. With this feature, a
person with hearing loss can amplify sound in front of
herself, allowing better hearing of a conversation, and, at
the same time, block out irrelevant sounds coming from
other directions. This may be useful while trying to have
conversations in noisy environments such as in restau-
rants or cars. In another situation, in which a person does
not know the direction from which relevant sounds will be
coming, the directional microphone can be switched off.
Digital hearing aids can also be programmed to amplify
different frequencies at different times. People with digital
hearing aids can adjust the programs they are running to
suit their needs. For example, a first-grade teacher may
have a program in her hearing aid that amplifies the fre-
quencies likely to belong to first graders’ voices while she
is teaching. She may turn that program off during recess,
when the kids are running around on the playground.
Later, when she gets home, she can switch to a program
that allows her to amplify the deeper voices of adult male
relatives.
Hearing aids may also be obtained that have external
microphones that can be placed near the desired sound
source, and the sound will be electronically transmitted
wirelessly into the hearing aid. Consider a student with a
hearing deficit. He can request that his professor wear a
microphone while teaching the class. The professor need
only place the microphone around her neck and speak
normally. The sound will be wirelessly sent to the hear-
ing aid, and the student will hear the professor’s voice
directly from the aid rather than across the room. This
aspect of hearing aids can be beneficial in restaurants as
well, as the microphone can be placed around the neck of
the person being spoken to. Then, despite the noise of the
background, the voice will be transmitted directly into the
receiver of the hearing aid. Some hearing aids also come
equipped with similar systems for watching television.
The audio transmission of the television can be transmit-
ted directly into the hearing aid (e.g., Bluetooth systems).
Such equipment, however, is often expensive and may not
be covered by insurance. Thus, many people with insuffi-
cient insurance or ability to afford aids may have to settle
for less complete systems. In the United States, hearing
aids are covered by Medicare, so older adults should have
access to quality aids.
FIGURE 10.27
Hearing Aids
(a) Behind-the-ear aids. (b)
In-the-ear aids. Hearing aids
amplify sounds so that the
person can hear better. Modern
digital hearing aids can be
adjusted to amplify only those
frequencies at which a person
is impaired.
©
iS
to
ck
ph
ot
o.
co
m
/A
va
ila
bl
eL
ig
ht
©
iS
to
ck
ph
ot
o.
co
m
/a
er
og
on
do (a) (b)
310 Sensation and Perception
Hearing aids require the presence of a minimum of some
transmission of a sensorineural signal from the hair cells
to the auditory nerve. Hearing aids amplify sound, allow-
ing damaged ears to hear sounds, but they do not replace
the need for a functioning cochlea. However, there is
another tool that can be used to restore hearing in those
who have become clinically deaf because of damage to the
cochlea (sensorineural deafness). This is the domain of the
cochlear implant, in which a mechanical device essentially
replaces the hair cells along the basilar membrane. We
turn next to cochlear implants.
Cochlear Implants
Cochlear implants are designed to restore some hear-
ing, typically of spoken voices, to deaf individuals.
Cochlear implants stimulate the auditory nerve artifi-
cially with an electronic system, replacing the hair cells
of the cochlea in the patient receiving the implant. This
restores some hearing to patients who have become
deaf. Some parents of deaf children are also electing
to have cochlear implants placed in their deaf chil-
dren’s inner ears to allow them to develop the ability
to understand spoken language. To be eligible for the
procedure, one must have profound hearing loss or
deafness in both ears, the hearing loss must be due to
sensorineural problems, but the auditory nerve must be
intact. Until recently, the procedure was done in just one
ear, but having implants in both ears is now becoming
more common. As of 2016, it was estimated that there
were more than 300,000 people with cochlear implants
worldwide (National Institute on Deafness and Other
Communication Disorders, 2016).
To place a cochlear implant into someone’s ear requires
minor surgery to place components inside the ear. Then it
requires anywhere from a few weeks to several months of
training and therapy to allow the person to be able to inter-
pret the sounds he is now hearing again (or, in children,
for the first time). The cochlear implant works by having
both external (outside of the ear) components and internal
(inside the cochlea) components. The cochlear implant sys-
tem is illustrated in Figure 10.28.
The first external component is a miniature microphone.
The microphone picks up sounds from the environment. The
microphone is attached to a small processor, which is essen-
tially a minicomputer. The processor filters out noise and
sounds not in the speech range, so that the patient can focus
on hearing language-related input. It can be reprogrammed
for other purposes as well, such as a person who has gone
deaf but wants to experience music again. The processor
sends a signal along a small wire to a transmitter. The trans-
mitter sits directly on the surface of the skin, attached to the
bone just behind the ear. During surgery, a small magnet is
placed on the inside of the skull to keep the transmitter in
place. This magnet is barely noticeable but acts to keep the
transmitter firmly in place when the implant is being used.
The transmitter sends a signal to the internal components of
the cochlear implant wirelessly via radio waves.
Underneath the skin are two components that are per-
manently in place after surgery. First, there is a receiver/
stimulator that picks up the radio waves from the external
device. The receiver/stimulator converts the radio waves
into an electric signal, which then travels by wire into the
cochlea. Within the cochlea, set along the length of the
basilar membrane, are a series of electrodes, perhaps as
many as 30. (In the early days of cochlear implants, there
may have been only 4 electrodes, but now up to 30 can be
safely placed inside the cochlea.) These electrodes, when
stimulated by the receiver/stimulator, will induce a neural
signal in the auditory nerve fibers that normally would be
stimulated by hair cells. The electrodes are placed along
the length of the basilar membrane, so when an electrode
fires, the person will hear a particular frequency associ-
ated with that location on the basilar membrane. Thus,
the cochlear implant uses an electric system to induce a
normal neural signal in the auditory nerve.
Because thousands of hair cells are being replaced by only
a couple dozen electrodes, patients should not expect,
Cochlear implants: devices that are designed to restore
some hearing, typically of spoken voices, to deaf individuals;
they stimulate the auditory nerve artificially with an
electronic system, replacing the hair cells of the cochlea
FIGURE 10.28 Cochlear Implants
Cochlear implants allow deaf people to hear again by electrodes placed
inside the cochlea. These electrodes are connected to an external
microphone, which selectively stimulates electrodes depending on
what frequencies are present in the sound signal. The electrodes then
directly stimulate auditory nerve fibers.
Transmitter
(on the surface of skin)
Receiver/stimulator
(under skin)
Cochlea
EardrumWire to
electrode
in cochlea
Microphone
(with speech
processor
behind ear)
311 Chapter 10: The Auditory System
nor will they receive, their old hearing back. Sounds will
not be perceived as richly with an implant as they were
before the person went deaf. Moreover, most patients will
not immediately be able to understand speech again once
the system is online. Patients will require many hours of
training and therapy to basically relearn to hear with their
new implants. This may be frustrating at first, but eventu-
ally, almost all patients learn to interpret their new hear-
ing abilities. Once this training occurs, many patients can
regain their understanding of speech at rather high levels.
And some patients may find the sound quality sufficient to
enjoy listening to music again.
One of the more controversial issues with respect to
cochlear implants is whether or not cochlear implants
should be placed in infants who are born congenitally
deaf. Many in the sign language deaf community object
to this practice, as they argue that such children can
develop normally and use language appropriately if they
start with sign languages from an early age. They argue
that forcing these children into the hearing world will
actually be a handicap in and of itself, when they could
develop language normally through visual sign languages.
Nonetheless, many parents, particularly hearing parents,
elect to go with cochlear implants. If cochlear implants
are placed in an infant’s ears within the first year of life,
with proper commitment on the part of the parents and
involved professionals, that infant is likely to grow up
being able to understand speech and to develop normal
speech. In some cases, the child may even be able to partic-
ipate in music activities later on. As you can see in Figure
10.29, the external components of a cochlear implants are
not large and look similar to an in-the-ear hearing aid,
with the addition of the transmitter. They will not impede
a young person from doing other activities.
FIGURE 10.29 Cochlear Implants
A child born deaf but equipped with cochlear implants can learn to play
and appreciate music.
©
A
gencja Fotograficzna Caro/A
lam
y
CHAPTER SUMMARY
10.1
Discuss the physical nature of sound and how it
correlates with the perceptual nature of sound.
The sound stimulus consists of the periodic variations in
air pressure traveling out from the source of the variations.
Sound waves are the waves of pressure changes that occur
in the air as a function of the vibration of the source. A cycle
is the amount of time between one peak of high pressure
and the next. A pure tone is a sound wave in which changes
in air pressure follow a sine wave pattern. Complex tones,
however, have many different pure tones mixed together,
making their waveforms more complex. The amplitude of a
sound is expressed as the difference between its maximum
and minimum sound pressure. Amplitude is measured on the
decibel (dB) scale. Loudness is the perceptual experience
of amplitude or the intensity of a sound stimulus. Persistent
exposure to sounds over 85 dB can result in hearing loss, and
even a one-time exposure to sounds over 135 dB can result
in damage to hearing. The frequency of a sound stimulus is
the number of cycles that occur in 1 second. Frequency is
measured in hertz (Hz). Pitch is the subjective experience of
sound that is most closely associated with the frequency of
a sound stimulus, related to the experience of whether the
sound is high or low (such as the two ends of the keyboard
of a piano). Humans can hear frequencies as low as 20 Hz
and, depending on age, as high as 20,000 Hz. As we get older,
we lose hearing in the high-frequency range. Harmonics are
higher frequencies present in a complex sound that are inte-
ger multiples of the fundamental frequency. The fundamental
frequency is the lowest frequency in a complex sound and
the one that determines the perceived pitch of that sound.
Timbre is the musical term that refers to the perceived sound
differences between sounds with the same pitch but pos-
sessing different higher harmonics. Phase is the position in
one cycle of a wave. There are 360 degrees in a single cycle
of a wave.
Sensation and Perception312
10.2
Describe the basic anatomy of the ear and the dif-
ference between the outer, middle, and inner ear.
The outside portion of the ear is called the pinna, and it col-
lects sound and funnels it into the external auditory canal.
The external auditory canal conducts sound from the pinna
to the tympanic membrane. The tympanic membrane, com-
monly known as the eardrum, is a thin elastic sheet that
vibrates in response to sounds coming through the external
auditory canal. The tympanic membrane causes changes
in the middle ear. The sound is transmitted by three small
bones called ossicles (the malleus, incus, and stapes). The
malleus receives vibrations from the tympanic membrane
and transmits them to the incus. The incus receives vibra-
tions from the malleus and transmits them to the stapes.
The stapes receives vibrations from the incus and transmits
them to the oval window of the inner ear. The eustachian
tube is a thin tube that connects the middle ear with the
pharynx and serves to equalize air pressure on either side
of the eardrum. The stapes beats against the oval window
of the inner ear. The cochlea is the snail-shaped structure
of the inner ear that houses the hair cells that transduce
sound into a neural signal. The basilar membrane is the
band of fibers that separate the tympanic canal from the
middle canal. The organ of Corti lies on the basilar mem-
brane. The organ of Corti is a structure that houses the hair
cells that transduce sound into a neural signal. Inner hair
cells have stereocilia for transducing the movement of the
basilar membrane into a neural signal. Place code theory
is the view that different locations along the basilar mem-
brane respond to different frequencies.
10.3
Examine the nature of hearing loss and what can
be done to improve hearing in hearing-impaired
individuals.
Hearing loss affects millions of people. Presbycusis is the loss
of hearing associated with aging. An audiometer presents pure
tones at set frequencies and known amplitudes to either the
left or right ear. An audiogram is a graphical display of the audi-
tory sensitivity of a patient compared with a standard listener.
Conductive hearing loss occurs because of structural damage
to the outer or inner ear. Otosclerosis is an inherited bone dis-
ease in which the ossicles, particularly the stapes, may calcify
and therefore be less conductive. Sensorineural hearing loss
occurs because of damage to the cochlea, the auditory nerve,
or the primary auditory cortex. Tinnitus is the condition in which
people perceive sounds even when none are present. Hearing
aids are electronic devices that amplify sound so that people
with hearing deficits can hear sounds that otherwise would be
below their thresholds. Digital hearing aids provide a set of fea-
tures that can allow a person with hearing loss to function well
in the hearing world. Cochlear implants are designed to restore
some hearing, typically of spoken voices, to deaf individuals.
Cochlear implants stimulate the auditory nerve artificially with
an electronic system, replacing the hair cells of the cochlea.
REVIEW QUESTIONS
1. What is sound? How is it transmitted through the
environment? How is it measured?
2. What are the relations between amplitude and
loudness, frequency and pitch, and waveform and
timbre?
3. Why do loud sounds potentially cause damage to
hearing? How loud must sound be to cause dam-
age if heard repeatedly? How loud must sound be to
cause immediate damage?
4. What are harmonics? How do they relate to the fun-
damental frequency? What do we hear when the
fundamental frequency is deleted from a sound?
5. Describe the anatomy of the outer and middle ear.
How does sound get transmitted from the pinna to
the oval window?
6. What are the ossicles? How do they transmit sound,
and how do they amplify sound? Why is their amplifi-
cation needed for normal hearing?
7. Describe the anatomy of the inner ear. How does
sound get from the oval window to the hair cells of
the organ of Corti?
8. What is place code theory? How does it describe the
relation of place along the basilar membrane to our
perception of pitch?
9. What is the difference between conductive hearing
loss and sensorineural hearing loss? How does loud
noise cause hearing loss?
10. What is the difference between hearing aids and
cochlear implants? How does each improve hearing
in the hearing impaired?
Chapter 10: The Auditory System 313
PONDER FURTHER
1. How would our hearing be different if we could hear
lower frequencies, as do elephants, or higher fre-
quencies, as do dogs?
2. Describe the different ways in which sound travels
through the ear, from the outer ear to the auditory
nerve.
KEY TERMS
Acoustic reflex, 301
Amplitude, 292
Basilar membrane, 302
Characteristic frequency, 303
Cochlea, 302
Cochlear implants, 310
Complex sound, 296
Cycle, 291
Decibel (dB), 293
Eustachian tube, 300
External auditory canal (external au-
ditory meatus), 298
Fourier analysis, 296
Frequency (sound stimulus), 294
Fundamental frequency, 296
Hair cells, 304
Harmonics, 296
Hearing aids, 308
Hertz (Hz), 294
Incus, 299
Inner hair cells, 304
Loudness, 293
Malleus, 299
Middle canal (cochlear duct), 302
Organ of Corti, 303
Ossicles, 299
Otosclerosis, 307
Outer hair cells, 304
Perilymph, 303
Phase, 297
Pinna, 298
Pitch, 294
Place code theory, 305
Pure tone, 292
Reissner’s membrane, 302
Round window, 302
Sound stimulus, 290
Sound waves, 291
Stapedius, 301
Stapes, 299
Stereocilia, 304
Tectorial membrane, 304
Temporal code theory, 305
Tensor tympani, 300
Timbre, 296
Tinnitus, 308
Tympanic canal, 302
Tympanic membrane, 298
Vestibular canal, 302
Sensation and Perception314
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
10.1 Discuss the physical nature of sound and how it correlates with
the perceptual nature of sound.
Absolute Pitch May Not Be So Absolute
Sensitivity and Selectivity of Neurons in Auditory Cortex to
the Pitch, Timbre, and Location of Sounds
10.2 Describe the basic anatomy of the ear and the difference
between the outer, middle, and inner ear.
Cochlear Animation
2-Minute Neuroscience: The Cochlea
10.3 Examine the nature of hearing loss and what can be done to
improve hearing in hearing-impaired individuals.
Temporary Deafness Can Impair Multisensory Integration: A
Study of Cochlear-Implant Users
Hearing Loss in Older Adulthood: What It Is and How It
Interacts With Cognitive Performance
Neuro-Music Therapy for Recent-Onset Tinnitus
Seeing Less Helps the Brain Hear More
Tinnitus: Why Won’t My Ears Stop Ringing?
Cochlear Implants Redefine What It Means to Be Deaf
Helping Those With Hearing Loss Get in the Loop
Scientific American Frontiers Cybersenses (cochlear implant
3:45–13:56)
New Closed-Captioning Glasses Help Deaf Go Out to the
Movies
DNA Illustrations/Science Source
11The Auditory Brain and Sound Localization
Alberto Ruggieri/Illustration Works/Getty Images
LEARNING OBJECTIVES
11.1 Discuss the ascending neural pathways from the cochlea to the
auditory cortex.
11.2
Identify the processes our auditory system uses to
localize the sources of sounds in space.
11.3
Explain the concept of auditory scene analysis and
how it is achieved by the auditory system.
11.4
Interpret how biosonar allows animals to use active
hearing to negotiate their environment.
11.5 Discuss factors that go into designing a concert hall with
good acoustics.
INTRODUCTION
Some of you may know people, perhaps family members, who constantly misplace their
cell phones. The routine for finding a missing cell phone is a well-known script. You
get someone to call the number of the missing phone. Once you hear it start ringing,
it is easy to locate the lost phone, perhaps under a pile of magazines moved out of the
way earlier in the day. In this particular situation, we take a simple fact of our auditory
system for granted—that we can use sound to localize objects in space. But how do we
determine from the sound of the hidden phone exactly where it is located? Few of us
reflect on this ability when we dig the phone out from under those magazines. But the
localization of objects in space via the auditory system is a very complex process and
one that we discuss at length in this chapter (Figure 11.1).
At a perceptual level, we use an important cue to home in on the spatial location of
the sound, namely, its loudness. The louder the phone sounds, the closer you are to its
source. Thus, if the missing phone sounds louder in the kitchen than it did in the living
room, you are getting closer. If it is louder still in the pantry, perhaps you left it by the
rice when you were cooking and talking on the phone. Interestingly, however, we can
localize objects by sound even when we are standing still. In this case, our auditory
system does an amazing calculation of differences in loudness and timing between the
two ears. Yes, if the cell phone is to your left, the sound will be louder in your left ear
ISLE EXERCISES
11.1 Sound Localization
Experiment
11.2 Interaural Time
Differences
11.3 Interaural Level
Differences
11.4 Auditory Scene
Analysis
11.5 Doppler Shift
11.6 Architectural Space
and Echoes
11.7 Testing a Concert
Hall
318 Sensation and Perception
than your right ear, and we can use such cues to help us
localize sound. However, this requires rather interesting
neural machinery.
Our auditory system has developed a mechanism
that allows this rapid and precise calculation to be made
quickly enough to detect the minute lag between when
auditory information reaches one of our ears and the
moment it reaches the other, as well as the tiny differ-
ences in loudness. These involve incredible neuronal
connections called the calyx of Held, named after the
German scientist Hans Held, who first discovered these
synapses at the end of the 19th century. The calyx of
Held is a super-giant synapse that connects two neurons
in the auditory primary cortex and has been found to
be responsible for spatial localization across a number
of mammalian species (Yang & Xu-Friedman, 2013).
Because these synapses are so big, they allow the extremely rapid transfer of infor-
mation from one cell in the network to the next. This extremely rapid transmission of
information is necessary for the millisecond-precise timing that is necessary for using
the auditory system to detect spatial differences. Thus, you can thank your calyxes of
Held for your ability to track down that missing cell phone.
As with vision, the auditory system sends information from the receptor cells to
various locations in the brain for processing. As we discuss these brain regions and their
responsibilities within the auditory system, think about how these systems are similar
to and different from the systems within the visual system.
BRAIN ANATOMY AND
THE PATHWAY OF HEARING
11.1 Discuss the ascending neural pathways from the cochlea to the auditory cortex.
Auditory Nerve Fibers
Inner hair cells in the cochlea form synapses with auditory nerve fibers. These nerve
fibers are bundled together in the eighth cranial nerve to be sent to the brain. We
describe the properties of auditory nerve fibers in this section. Any particular audi-
tory nerve fiber has a characteristic frequency to which it is most sensitive, consistent
with place code theory, discussed in Chapter 10. If you examine Figure 11.2, you will
see that the nerve fibers have characteristic frequencies to which they respond
best, but they also respond to sets of frequencies both higher and lower than these
characteristic frequencies. This is referred to as their tuning curve, which consists
of the range of tones the cell responds to and its peak characteristic frequency. In
Figure 11.2, the graph depicts sensitivity, the lowest sound level that a particular
nerve fiber cell will respond to. The lower the curve goes, the more sensitive that nerve
fiber is to a particular frequency. Thus, we can see that the auditory system continues
to code for frequency in the auditory nerve, similar to the way the optic nerve codes
for spatial location.
Now we will describe the path auditory information takes to the auditory regions
of the cortex. Follow carefully along with Figure 11.3 as you read this section. The
FIGURE 11.1 Where Is the Cell Phone?
©
iS
to
ck
ph
ot
o.
co
m
/a
le
xy
tr
en
er
319 Chapter 11: The Auditory Brain and Sound Localization
FIGURE 11.2 Tuning Curve for Eighth Cranial Nerve Fibers
These curves show the maximum sensitivity to frequency for different eighth cranial nerve fibers.
80
Fiber 1
0
80
Fiber 4
0
80
Fiber 2
0
80
Fiber 3
0
80
80Fiber 5
Fiber 6
0 0
0.1 1.0
Frequency (kHz)Frequency (kHz)
10.00.1 1.0 10.0
0.1 1.0 10.00.1 1.0 10.0
0.1 1.0 10.00.1 1.0 10.0
auditory nerve fibers form part of the eighth cranial nerve, which then makes its way to
the brain. The auditory part of the eighth cranial nerve takes a complex journey to the
auditory cortex. The auditory tract goes through the cochlear nucleus first. Attached
to the cochlear nucleus is the trapezoid body, which is important in determining the
direction of sound. The cochlear nucleus also contains subnuclei with specific functions,
such as sensitivity to the onset and offset of tones at particular frequencies. Other cells
in the cochlear nucleus also serve a lateral inhibition function. These cells sharpen our
detection of a particular frequency of incoming sound by inhibiting the response to
nearby frequencies, either higher or lower. The tuning curve is made steeper on the
sides, if you will.
From the cochlear nucleus and the trapezoid body, the sound signal goes to the
superior olive in the brain stem. The superior olive receives input from both ears. This
early crossing over of information from each side of the auditory system is critical for
sound localization. From the superior olive, the next synapse in the ascending pathway
of auditory information is the inferior colliculus (plural colliculi). The inferior collicu-
lus then projects to the medial geniculate nucleus of the thalamus. The medial genicu-
late nucleus then projects to the auditory cortex. The medial geniculate nucleus projects
to the cortex but also receives input back from the cortex (He, 2003). Indeed, there
are more returning (or efferent) connections from the cortex to the medial geniculate
Cochlear nucleus: a structure
in the brain stem that receives
input from the inner hair cells
Trapezoid body: a structure
in the brain stem that plays
a role in determining the
direction of sounds
Superior olive: a structure in
the brain stem that receives
input from the inner hair cells
and from the cochlear nucleus
Inferior colliculus: a structure
in the midbrain that receives
input from the superior olive
Medial geniculate nucleus: a
structure in the thalamus that
receives auditory input from the
inferior colliculus and sends
output to the auditory cortex
320 Sensation and Perception
Right hemisphere
Auditory cortex
Auditory
cortex
Cochlea
Cochlea
Main pathways
Secondary pathways
Type I auditory
nerve fibers from
inner hair cells
Superior olivary
complex
Superior
olivary
complex
Trapezoid body
Trapezoid
body
Lateral lemniscus
La
te
ra
l
le
m
ni
sc
us
Medial geniculate
body (in thalamus)
Medial
geniculate
body
Inferior
colliculus
Inferior
colliculus
Contralateral Ipsilateral
Auditory
cortex
Superior
olivary
complex
Medial
geniculate
body
Inferior
colliculus
Cochlear
nucleus
Cochlear nucleus
Auditory nerve
Auditory nerve
M
id
br
ai
n
M
id
br
ai
n
B
ra
in
s
te
m
B
ra
in
s
te
m
Left
hemisphere
C
or
te
x
C
or
te
x
Th
al
am
us
FIGURE 11.3 The Auditory Pathway
Information goes from the cochleae of the ears up the ascending pathway to the auditory cortex in both the left and
right hemispheres.
nucleus than there are ascending (or afferent) connections from the medial geniculate
nucleus to the cortex. The area in the cortex projected to by the medial geniculate
nucleus is called the primary auditory cortex, located in the temporal lobe of the brain.
Auditory nerve fibers from each ear go to each side of the temporal lobe, but there are
more from the right ear that go to the left temporal lobe and more from the left ear
that go to the right temporal lobe (see Figure 11.3). Because both ears project to both
hemispheres, it is often difficult to assess hemispheric specialization in the brain.
Auditory Cortex
The auditory cortex is a large multifaceted area located in the temporal lobe. It is
located under the lateral sulcus along the top of the temporal cortex. Figure 11.4 shows
the complex organization of the auditory cortex. The first area that receives input from
the medial geniculate nucleus is known as the primary auditory cortex (also known as
A1 or area 41). Cells in the primary auditory cortex show a tonotopic organization.
That is, cells show a maximal response to specific frequencies, and these cells are orga-
nized in maplike patterns. The primary auditory cortex is one of three areas that make
up the auditory core region. The other two are the rostral core and the rostrotemporal
core. Another area within the auditory cortex surrounds the auditory core region. The
belt and parabelt regions essentially wrap around the primary auditory cortex, hence
the reference to belts, but are not part of the core region. All of these regions can be
seen in Figure 11.4.
Figure 11.4 also shows the tonotopic organization of the auditory cortex. From
the basilar membrane on, the auditory system is coded in terms of the frequencies
Auditory cortex: the areas
in the temporal cortex that
process auditory stimuli
Primary auditory cortex: the
first area in the auditory cortex,
which receives input from the
medial geniculate nucleus
Tonotopic organization: the
organization of neurons within
a region in the brain according
to the different frequencies to
which they respond
Auditory core region: an
area of the auditory cortex,
consisting of the primary
auditory cortex, the rostral core,
and the rostrotemporal core
Rostral core: an area in the
auditory core region of the
auditory cortex
Rostrotemporal core: an
area, in addition to the rostral
core, in the auditory core
region of the auditory cortex
321 Chapter 11: The Auditory Brain and Sound Localization
of sounds in the environment. Within the
auditory core regions, one can find a tono-
topic organization of the tissue within this
region, gradually moving from high to low
frequencies. Thus, just as the visual system
is organized by space, we see frequency cod-
ing throughout the auditory system. The core
region appears to serve the same function as
V1, allowing for the primary analysis of fre-
quencies. The belt and parabelt regions seem
analogous to the extrastriate cortex, doing
more complex analyses of the auditory sig-
nal. For example, neurons in these regions
are less responsive to pure tones at particular
frequencies than they are to complex stimuli
consisting of multiple frequencies.
“What” information and “where” infor-
mation are separated in the auditory system
in a manner analogous to the visual system
(Figure 11.5). With respect to audition, the
“what” system is involved in using audi-
tory information to identify the identity of a
sound. The “what” system forms the basis of
both speech perception and music perception,
which we consider in Chapters 12 and 13,
respectively. The “what” system starts in the
core region and then moves to more anterior parts of the tempo-
ral lobe. In contrast, the “where” system is responsible for local-
izing sound in space, a topic for this chapter. It is this system that
allows us to determine that the alto saxophone is coming from
one side of a jazz band, but the electric bass is coming from the
other. The “where” system also begins in the core region of the
auditory cortex and then moves to posterior regions of the tem-
poral lobe as well as in the posterior parietal cortex (Rauschecker
& Scott, 2009).
TEST YOUR KNOWLEDGE
1. Describe the pathway as information leaves the cochlea
and heads to the cortex.
2. What is meant by the concept of the “what” and “where”
systems in the auditory cortex? How does each contribute
to our understanding of the auditory cortex?
LOCALIZING SOUND
11.2
Identify the processes our auditory system uses to
localize the sources of sounds in space.
Thousands of people have learned to scuba dive, and they flock to places like Florida and
the Bahamas to swim underwater among tropical fish and corals. Scuba diving is a very
A1
Rostral
core
Auditory cortexLateral sulcus
Temporal lobe
Rostrotemporal
core
Belt
Parabelt Low High
Transverse temporal gyrus
(Heschl’s gyrus)
Right hemisphere
Left hemisphere
Auditory
core region
Auditory cortex
Characteristic
frequency
FIGURE 11.4 Auditory Cortex
The auditory cortex is located under the lateral sulcus along the top of the temporal
cortex. The auditory cortex is composed of the primary auditory cortex as well as the
rostral core, the rostrotemporal core, and the belt and parabelt regions.
Parietal lobe
Occipital
lobe
Frontal lobe
Temporal lobe
Auditory core
region
“W
hat
”
“W
he
re
”
FIGURE 11.5 The “What” and “Where”
Systems in the Auditory Cortex
The “what” system is responsible for identifying the sources
of sounds, whereas the “where” system is responsible
for determining where in space those sounds are coming
from. The “what” system runs along the dorsal areas in the
temporal lobe and then into the frontal lobe. The “where”
system heads from the auditory cortex to the parietal lobe.
Belt: a region of the auditory
cortex that wraps around the
auditory core regions
Parabelt: a region of the
auditory cortex, in addition
to the belt area, that wraps
around the auditory core
regions
322 Sensation and Perception
safe activity, if done correctly and at relatively shallow depths. Perhaps the biggest danger
for scuba divers is swimming too close to the surface when motorboats are about. For this
reason, scuba divers are taught to listen for the sounds of boats and to associate that sound
with danger. The difficulty in hearing while completely immersed is that sound travels
much faster in water than it does in air. This creates difficulty in localizing the direction
of sound underwater. When a scuba diver hears a boat, it is much harder for him to deter-
mine if the boat is coming from the
left or right relative to his position. It
is also more difficult to determine if
the boat is in front of or behind the
diver. This is all a direct function of
the speed of sound in water, which
throws off the mechanisms we use
for sound localization, which are
based on differences in timing and
loudness between the left and right
ears. Because underwater, those dif-
ferences are less, sound is harder to
localize in space. On land, however,
we can make very clear judgments as
to whether a sound is coming from
the left or right. To test yourself on
this dimension, go to ISLE 11.1. In
this section, we look at the percep-
tual and physiological mechanisms
necessary for sound localization.
In vision, spatial localization is
direct and the main feature of cod-
ing in the visual cortex. Spatial position is determined by the retinal position of an
image. In the auditory system, the cochlea is organized tonotopically, and spatial local-
ization is done by several indirect mechanisms. In the auditory system, sound local-
ization is based on the comparison of sound in the two ears and is thus analogous to
stereoscopic vision.
To localize an object in space, we must know if it is to the left or right of us, whether
it is in front of or behind us, and whether it is above or below us. That is, we must be
able to localize sound in three-dimensional space. The azimuth refers to the left-right
or side-to-side aspect of sound localization. Elevation refers to the up-down dimension
of sound localization, and distance refers to how far a sound is from us, and whether
it is in front of or behind us (Figure 11.6). We discuss how we determine each of these
dimensions in this section.
Interaural Time Difference
The interaural time difference is the time interval between when a sound enters one ear
and when it enters the other ear. In principle, this is a rather straightforward concept.
A sound coming to us from the left will enter our left ear a split second before it enters
our right ear. A sound coming to us from the right will enter our right ear a split second
before it enters our left ear. Because our auditory system can detect this millisecond
difference in timing, we can use the interaural time difference to determine if a sound is
coming from the left or right. Thus, the interaural time difference gives us the location
of the object along the azimuth.
ISLE 11.1
Sound Localization Experiment
Azimuth: the left-right or
side-to-side aspect of sound
localization
Elevation: the up-down
dimension of sound
localization
Distance: how far a sound is
from the listener and whether
it is in front of or behind the
listener
Interaural time difference: the
time interval between when
a sound enters one ear and
when it enters the other ear
FIGURE 11.6 Sound Localization
The azimuth refers to the left-right or side-to-side position along the horizontal plane. Elevation
refers to the up-down dimension along the median plane. Distance refers to how far a sound is from
us and whether it is in front of or behind us. The horizontal plane bisects the head along the left-
right dimension, whereas the median plane bisects the head along the vertical axis.
Median Plane
Distance
Horizontal Plane
Elevation
Azimuth
323 Chapter 11: The Auditory Brain and Sound Localization
To determine the actual interaural time difference
is relatively straightforward, although it involves a
bit of arithmetic. The speed of sound in air is 343
m/s, and the left ear and right ear are about 10 cm
apart. If a sound is coming from a source directly
to our right, the sound will reach the right ear 640
microseconds (0.00064 seconds) before it reaches
the left ear. That’s an amazing 640-millionths-of-a-
second difference our ears are detecting! However,
not all sounds will be coming directly from the left
or the right. Some may be slightly in front on one
side or slightly behind (Figure 11.7). We can think of
a big circle around the head and measure the angle
of the sound to our head in degrees. If the sound
is coming from 90 degrees, that is, directly to our
left or right, the time difference will be 640 micro-
seconds. However, if the angle is only 20 degrees
(i.e., coming from in front of us but slightly to the
right), the time difference will be only 200 micro-
seconds. Thus, the longer the time lag is between the
ears, the more toward 90 degrees (or immediately
right or left) the sound is coming from. Figure 11.7
shows this point graphically. Research from psycho-
physical experiments confirms that people do detect
such incredibly small time lags (Fedderson, Sandel,
Teas, & Jeffress, 1957).
For a region in the brain to compute the interaural time difference, it must have
access to information entering the auditory system from both ears. It is likely that for
this reason, early crossing over of information from one side of the brain to the other
evolved within the auditory system. Physiologically, interaural time differences appear
to be computed in the medial superior olives. Yin and Chan (1990) found neurons
within the medial superior olives of cats that were sensitive to differences in the inter-
aural time difference, providing support for this region of the brain as being critical for
sound localization (Figure 11.8). Go to ISLE 11.2, both parts, to experience and see
how interaural time differences influence the direction from which you hear a sound.
FIGURE 11.7 Interaural Time Differences
At different angles relative to the head, a sound will reach the left and right ears
with different interaural time differences. The auditory system can compute
these time differences and use them to determine the direction of a sound.
90°
ITD = 640 µs
60°
ITD = 480 µs
120°
ITD = 480 µs
-60°
ITD = 480 µs
-20°
ITD = 200 µs
-160°
ITD = 200 µs
160°
ITD = 200 µs
20°
ITD = 200 µs
180°
ITD = 0 µs
0°
ITD = 0 µs
-120°
ITD = 480 µs
-90°
ITD = 640 µs
FIGURE 11.8 Interaural Time Difference in the Medial Superior Olives
Information from the cochlea makes a synapse in the cochlear nucleus and then travels to the medial superior olives,
where information from the right and left cochleae is first combined.
Right
cochlea
Sound
source
Auditory
nerve
Brain
stem
Cochlear nucleus
To higher brain centers
From right
cochlea
From left
cochlea
LSOLSO
MSO
MNTB
ISLE 11.2
Interaural Time Differences
324 Sensation and Perception
Interaural Level Difference
The interaural level difference is the difference in
loudness and frequency distribution between the
two ears. As sound travels, its strength dissipates.
For example, if you are very close to a loud sound,
it will sound loud to you. But if you are some dis-
tance from the same loud sound, it will not be as
loud. Think of a dog barking. If it is right in front
of you, it will sound loud, but if the same dog barks
across a big grassy field, the sound will be much less
loud to you. Amazingly, our ears can detect loudness
differences between the left and right ears. However,
more important for sound localization is that the
head casts an acoustic shadow, which changes the
loudness and frequency distribution of sound going
to each ear. We can define the acoustic shadow
as the area on the side of the head opposite from
the source of a sound in which the loudness of a
sound is less because of blocked sound waves.
The acoustic shadow is much more prominent for
high-frequency sounds than it is for low-frequency
sounds (Figure 11.9 and ISLE 11.3).
Thus, sound coming from the left or right will
have a different loudness in each ear and a different
frequency composition in each ear. High-frequency
sounds will be louder in the closer ear, although
low-frequency sounds will be approximately the
same loudness in each ear. That is, the ear that is
closer to the sound will hear the sound as some-
what louder, and that ear will also detect more of
the higher frequency components of the sound. If it
is a pure tone, then only the loudness difference will
matter, but even with pure tones, the loudness dif-
ference will be greater the higher the frequency of
the sound. Psychophysical research shows that peo-
ple are sensitive to these interaural level differences.
Physiological studies suggest that interaural level dif-
ferences are computed in the lateral superior olive.
The Cone of Confusion
The cone of confusion is a region of positions in space in which sounds create the
same interaural time and interaural level differences. That is, imagine a sound that
is coming from 45 degrees from below you and to the left. This sound will create
the same differences as a sound that is coming from 135 degrees above you and to
the right. If your head remains still, you cannot tell the difference in spatial position
between sounds coming from these sources. This cone of confusion is depicted in
Figure 11.10. Although the cone of confusion is real—it is easily demonstrable in psy-
chophysical experiments—it is easily remedied. As soon as the head moves, the ears
change position relative to the sources of sound, and sounds from different locations
now may have different characteristics. So the cone of confusion seldom bothers a
person in motion.
FIGURE 11.9 Acoustic Shadow
High-frequency sounds have shorter wavelengths than low-frequency sounds.
This causes more reflecting or blocking of the high-frequency waves off the side
of the head than occurs with low-frequency waves. Consider how big waves on
the ocean roll right past objects such as buoys, but smaller waves break off when
encountering such objects. It is the same principle here. When a sound wave
encounters objects smaller than its wavelength, the sound wave bends around
it, like the low-frequency sound does here. When a sound wave encounters
an object bigger than its wavelength, the sound wave does not bend as much
around the object. In fact, it may be blocked or distorted, as in the drawing.
Low-frequency
sound
High-frequency
sound
Acoustic
shadow
ISLE 11.3
Interaural Level Differences
Interaural level difference:
the difference in loudness
and frequency distribution
between the two ears
Acoustic shadow: the area on
the side of the head opposite from
the source of a sound in which
the loudness of a sound is less
because of blocked sound waves
325 Chapter 11: The Auditory Brain and Sound Localization
Elevation Perception
Sounds may be coming from above us and below
us as well. For spatial localization, identifying
this aspect of a sound is as critical as know-
ing the angle of orientation of our head to that
sound. Interestingly, the way our auditory sys-
tem detects elevation is a function of changes in
sound frequency created by the folds in our outer
ears, the pinnae (Figure 11.11). The bumps and
folds in the pinnae cause slight reverberations
(i.e., echoes). These reverberations amplify some
frequencies and dampen others. The spectral
shape cue is the change in a sound’s frequency
envelope created by the pinnae. It can be used
to provide information about the elevation of a
sound source. Experiments demonstrate that the
shape of the pinna affects elevation perception.
When the shape of the pinna is artificially altered,
elevation perception is impaired. However, after
sufficient time with a newly shaped pinna, ele-
vation perception will be relearned and achieve
normal levels (Hoffman, Van Riswick, & Van
Opstal, 1998). Thus, one might expect some-
one with an extreme ear piercing to temporar-
ily lose some ability to localize sound, but that
ability should return. Indeed, in Hoffman et al.’s
(1998) study, participants with modified pinnae returned to normal localization
after approximately 20 days (Figure 11.12).
Detecting Distance
Detecting the distance of a sound relies on a different set of principles. One of the chief
methods for inferring the distance of sounds relies on our internal knowledge of the
loudness of familiar sounds. Thus, when you hear a dog bark, you have knowledge of
the approximate loudness of that specific dog’s barking, that breed of dog’s barking,
or dog barking in general. Then, on the basis of the actual loudness of the bark, you
can judge its distance as being close or far. Similarly, human voices can be judged as
Axis of cone
FIGURE 11.10 The Cone of Confusion
Sounds coming from any location on the surface of the cone result in nearly
identical interaural time and interaural level differences. Note that the cone is
imaginary but exists relative to the sounds present, so there are many possible
cones of confusion for different ranges of sounds at different distances and
angles to the person.
Cone of confusion: a region
of positions in space in which
sounds create the same
interaural time and interaural
level differences
Spectral shape cue: the change
in a sound’s frequency envelope
created by the pinnae; it can be
used to provide information about
the elevation of a sound source
FIGURE 11.11 The Human Pinnae
Pinnae vary greatly from one person to the next. Each individual learns from birth how his or her pinnae change sound as it enters the ears. The shape
of the pinna can provide information about the height of the source of a sound.
©
iS
to
ck
ph
ot
o.
co
m
/b
ik
ec
©
iS
to
ck
ph
ot
o.
co
m
/i
ta
lb
y
©
C
ha
d
Ba
ke
r/
Ja
so
n
Re
ed
/R
ya
n
M
cV
ay
/P
ho
to
di
sc
/T
hi
nk
st
oc
k
©
C
ha
ts
am
/C
C-
BY
-S
A
-3
.0
326 Sensation and Perception
being closer or farther on the basis of their loudness. This, of course, may lead to
errors. We may judge an unseen person’s voice to be near simply because he is speaking
loudly. Frequency also plays a role in distance perception. High-frequency sounds show
a greater decrease in loudness as a function of distance than do low-frequency sounds.
Remember that you can hear the bass line of the music from the party across the lake,
but not the voice of the singer. This is also apparent when we hear thunder during a
thunderstorm. Thunder nearby has a distinctive “crack” that causes people to look
up and cats and dogs to scurry for shelter. Distant thunder lacks the high-frequency
component, and we hear it as a less-jarring “boom.” So, a diminishment of the high-
frequency component of sound also tells us about distance.
Another cue for distance is the proportion of direct sound to reflected sound. When
the dog barks across the park from you, some of the sound you pick up travels directly
from the dog to your ears. But some of the sound from the dog bounces off objects, such
as the ground, the trees, and the wall by the tennis courts. This reverberant sound may
also reach your ears. Close-by objects will have larger ratios of direct to reflected sound
than faraway objects, under most circumstances. Reverberant sound will have slightly
altered frequencies and interaural time differences than direct sound. This allows our
auditory systems to compute the ratio, and this gives us information about the relative
distances of sound sources.
We return to the calculation of distance in our discussion of bat echolocation at
the end of the chapter. For bats, detecting distance is easier because they can compare
their own sound production with the return of echoes, allowing direct computation of
distance.
TEST YOUR KNOWLEDGE
1. What is the cone of confusion? Why is it not ordinarily a problem for listeners?
2. Why is the distance between the two ears important in localizing sound? How
does having two ears contribute to our perception of localized sound? Might any
of the cues to sound localization work in a person with only one functioning ear?
AUDITORY SCENE ANALYSIS
11.3
Explain the concept of auditory scene analysis and
how it is achieved by the auditory system.
FIGURE 11.12 Ear Piercing
Cu
ltu
ra
C
re
at
iv
e
(R
F)
/A
la
m
y
St
oc
k
Ph
ot
o
©
iS
to
ck
ph
ot
o.
co
m
/a
xe
lb
ue
ck
er
t
To
m
G
ilk
s/
A
la
m
y
St
oc
k
Ph
ot
o
327 Chapter 11: The Auditory Brain and Sound Localization
Stop for a moment right here and listen to all the sounds, however faint, that are cur-
rently around you. What do you hear? Even in a quiet room, there are probably half a
dozen different sounds you can distinguish. You might be able to hear the slight pulse
of the air conditioner, the whirr of the refrigerator, and a car motoring past somewhere
outside your window. You might hear the slight chatter from your sister’s iPod even
though she’s wearing headphones, your mother on the telephone in the other room,
and the distinct sound of your cat’s breathing while it sleeps nearby. Each of these
sounds is made up of several frequencies, and in some cases, these frequencies may
overlap (Figure 11.13). They are all hitting your cochlea simultaneously but seemingly
not straining your ability to distinguish the sounds and localize them in space. This
ability to distinguish the different sounds in the ambient environment is called auditory
scene analysis (Bregman, 2005).
There are only rare situations in which we cannot hear multiple sounds. Being in
an environment with multiple sounds is the rule, not the exception. Thus, our audi-
tory systems have evolved to separate and distinguish all these sounds despite the fact
that the auditory stream from each sound may have overlapping frequencies as well
as overlapping timing. Thus, the auditory system must group together those frequen-
cies coming from common objects rather than simply grouping similar frequencies
together. That is, even if the frequency of your whirring refrigerator is the same as
that of your gently breathing cat, what is important is that we attribute each sound
to its source.
This is a distinctly different problem from the one we face with the visual system.
When we look at objects, spatial information about them usually overlaps. Although
Auditory scene analysis: the
process of identifying specific
sound-producing objects from
a complex set of sounds from
different objects at varying
and overlapping frequencies
FIGURE 11.13 Auditory Scene Analysis
Complex sounds from five different objects enter a person’s cochlea at exactly the same time. The person’s ability to
separate out these inputs and attribute them to the unique objects is known as auditory scene analysis.
Refrigerator
Frequencies produced by
�ve different objects.
All the sounds enter the ear
simultaneously in a complex
waveform.
The auditory system breaks down the
complex waveform and extracts
individual sounds from it, known as
auditory scene analysis.
Music from an iPod
Air conditioner
Cat purring
Person speaking
328 Sensation and Perception
objects may be occluded, parts of objects tend to be near to one another. Because our
visual system is organized in terms of space, scenes have a more inherent organization.
However, given that our auditory system is organized tonotopically, the analysis of
scenes is more complex, because any sound-emitting object is probably emitting sounds
at multiple frequencies, some of which may overlap in terms of frequency with other
sound-emitting objects.
Bregman’s (1990, 2005) view of auditory scene analysis is very much akin to the
principles of gestalt psychology. That is, the auditory system uses a number of heuris-
tic rules to determine which frequencies go with which other frequencies and which
sounds are associated with which objects. These rules are not perfect—they sometimes
lead to errors in auditory scene analysis—but more often than not, they allow us to
correctly parse the auditory landscape. Like the gestalt rules, these processes center on
the ability to group different patterns of sounds together. Auditory scene analysis rules
fall into three basic types. We group by timing—that is, sounds that are produced at
the same time may be grouped together (temporal segregation). We group by space—
that is, those sounds that are
emanating from the same place
in space are grouped together
(spatial segregation). We also
group by frequency—that is,
sounds that are of the same fre-
quency or harmonic pattern are
grouped together (spectral seg-
regation). We consider each in
turn. You can also learn more
about auditory scene analysis in
ISLE 11.4.
Temporal
Segregation
Consider the sound of your
washing machine. There might
be a relatively loud, high-fre-
quency sound caused by the
motor of your machine. At the
same time, there might be a
lower amplitude and lower fre-
quency sound being produced
by the rotation of clothes inside
the machine. We group these
sounds together because they
are linked or correlated in time.
When one stops, the other stops, and when the washing machine cycles again, both
sounds start anew. In music, we group the violas together because they are all playing
the same rhythms at the same time. This is the concept of temporal segregation.
Sounds that are linked in time are grouped together, whereas sounds that are not cor-
related with one another are not grouped together. However, in some situations, rapid
alternation between two frequencies may be linked in time, but lead to the perception
ISLE 11.4
Auditory Scene Analysis
Short time (t) between occurrences of same tone
Long time (T) between occurrences of same tone
Perceived as a distinct
auditory stream
Perceived as a distinct
auditory stream
Time
(a)
B B B B
A A A
t t t
t t t
AF
re
q
u
e
n
cy
Perceived as a single
auditory stream
Time
(b)
A A A
T
A
B B B B
F
re
q
u
e
n
cy
TT
TTT
FIGURE 11.14 Temporal Segregation
(a) In this sequence, because the high- and low-frequency tones alternate rapidly, we hear two
separate sources of sound. (b) In this sequence, when the time between the successive tones gets
longer, we join the two tones into a common theme and tend to hear one sound bouncing between two
frequencies.
Temporal segregation: the
process whereby sounds that
are linked in time are grouped
together, whereas sounds
that are not correlated with
one another are not grouped
together
329 Chapter 11: The Auditory Brain and Sound Localization
of different streams rather than the same stream (Figure 11.14). Composers often use
this rapid alternation of pitch in time to create the illusion of two sound streams from
one musical instrument.
Spatial Segregation
In the section on sound localization, we discussed the mechanisms by which the
auditory system can localize sound in space. To review, this involves comparing the
loudness, timing, and frequency distribution of sounds reaching our left and right
ears. Thus, with spatial segregation, we can distinguish where in space sounds are
coming from. In auditory scene analysis, we can use this to group sounds together
or separate them into different sources. If you can localize one frequency as coming
from behind you and slightly to the right and another frequency as coming from
above you and to the left, your auditory system will know that these frequencies are
associated with different sound sources. However, if both a high frequency and a
low frequency are coming from the same spot in space, you can assume that those
frequencies are linked. Thus, when we hear the revving of the motor and the thump-
ing of the stereo coming from the same source to our right, we associate both sounds
with the Ford Mustang waiting to our right for the traffic light to turn. Moreover,
when the light turns green, we hear all of these sounds getting softer together as the
Mustang accelerates and drives away.
Spectral Segregation
Spectral segregation refers to a number of separate grouping rules concerning how
we use frequency distributions to group sounds together. Note here that a source of
sound, such as a person’s voice, has multiple frequencies present. You hear a person’s
voice at its fundamental frequency, but that voice has a number of higher frequency
harmonics. Indeed, any complex sound will be composed of multiple frequencies.
Consider a person listening to another’s voice. The auditory system is detecting mul-
tiple frequencies coming from the same location in space. Should the auditory sys-
tem determine that the multiple frequencies are all coming from the same source, or
should the auditory system determine that there are multiple objects in the same loca-
tion, each emitting a different frequency? Obviously, in most cases, the former will
be the case, not the latter. Similarly, consider a person listening to a musical perfor-
mance. Each musical instrument has a fundamental frequency and a number of higher
frequency harmonics. The listener must associate the fundamental frequency and the
harmonics coming from the saxophone and segregate them from the frequencies com-
ing from the piano in order to parse the musical phrases. Thus, a key aspect of spectral
segregation is grouping by harmonic coherence (Figure 11.15).
Harmonic coherence is a very strong predictor of what sounds our auditory system
will group together. Consider listening to a recording of music. Through headphones
or earbuds, you hear a large grouping of frequencies simultaneously. Even though there
are only two sound sources—the speakers for your left and right ears—you hear a
number of auditory streams, depending on what kind of music you are listening to. For
example, if you are listening to a Mozart symphony, you will hear separate auditory
streams for the violins, the cellos, the clarinets, the trumpets, and so on. If you are lis-
tening to the Beatles, you will hear separate auditory streams for John, Paul, George,
and Ringo. This grouping occurs even when some of the frequencies are coming from
Spatial segregation: the
process whereby sounds that
are coming from the same
location are grouped together,
whereas sounds that are
coming from different locations
are not grouped together
Spectral segregation: the
process whereby sounds that
overlap in harmonic structure
are grouped together, whereas
sounds that do not overlap in
harmonic structure are not
grouped together
Harmonic coherence:
when frequencies present
in the environment resemble
the possible pattern of a
fundamental frequency and
higher harmonics
330 Sensation and Perception
1,100
880
660
440
F
re
q
u
e
n
cy
(
H
z)
Time
1st harmonic (fundamental)
2nd harmonic
4th harmonic
3rd harmonic
Perceived as a
single auditory
stream
(a)
5th harmonic
220
1,100
880
660
440
F
re
q
u
e
n
cy
(
H
z)
Time
1st harmonic (fundamental)
2nd harmonic
4th harmonic
nonharmonic tone
Perceived as a
distinct auditory
stream
Perceived as a
single auditory
stream
(b)
5th harmonic
220
FIGURE 11.15
Spectral Segregation
(a) When the fundamental
frequency and higher
harmonics of a particular
sound, such as a voice,
are presented together, the
auditory system of the listener
groups these tones together
into a single stream from a
single source. (b) When there
is a tone present that is not
possibly a higher harmonic of
the fundamental frequency,
that tone is perceived as a
separate auditory stream
against the background of the
grouped frequencies.
different sources. That is, harmonic coherence takes precedence over spatial segregation
(Figure 11.16).
TEST YOUR KNOWLEDGE
1. What is meant by the term auditory scene analysis? Why is auditory scene
analysis important, and what processes help our auditory system carry it out?
2. What is harmonic coherence? What is the relation of harmonic coherence to
spatial segregation?
Auditory Development
As most parents now know, the auditory system develops early. Indeed, studies show that
shortly after birth, infants will respond differently to sounds they heard in utero and sounds
they did not (Partanen et al., 2013). This does not mean that playing Mozart to your
unborn child will make that child a genius, but it does suggest that the auditory system
develops early. Findings show that the auditory system is functional at about the 25th week
of gestation (i.e., the 25th week of pregnancy), long before the visual system is operational
(Graven & Browne, 2008). Two-day-old infants can recognize the voices of their own
mothers relative to the voices of other mothers (DeCasper & Fifer, 1980), which also sug-
gests early development. However, hair cells and the auditory nerve will continue to change
and develop throughout the first few years of a child’s life (Graven & Browne, 2008).
In addition, experiments have shown that infants have equivalent thresholds across
the frequency range as do young adults. They can detect soft sounds across the fre-
quency range, at least from the age of 3 months, when it becomes possible to test
thresholds. An important task for older children and adults is to separate concurrent
sounds. Moreover, the research suggests that auditory localization of the sources of
sounds occurs early. Young infants by the age of 3 months are already tuned to separate
the sources of sounds in any auditory input (Grimault, Bacon, & Micheyl, 2002). In
fact, this ability is often used to test visual abilities in young children.
331 Chapter 11: The Auditory Brain and Sound Localization
Sound source A
Fundamental
frequency = 220 Hz
F
re
q
u
e
n
cy
(
H
z) 4th harmonic
1,100
880
660
440
220
2nd harmonic
1st harmonic
Time
Fundamental
frequency = 220 Hz
F
re
q
u
e
n
cy
(
H
z)
5th harmonic
1,100
880
660
440
220
3rd harmonic
+
(a)
+
(b)
Time
F
re
q
u
e
n
cy
(
H
z)
5th harmonic
4th harmonic
1,100
880
660
440
220
3rd harmonic
Perceived as a
single auditory
stream
2nd harmonic
1st harmonic
Time
Sound source B
Sound source A
Fundamental
frequency = 220 Hz
F
re
q
u
e
n
cy
(
H
z) 4th harmonic
1,100
880
660
440
220
2nd harmonic
1st harmonic (fundamental)
Time
Fundamental
frequency = 200 Hz
F
re
q
u
e
n
cy
(
H
z)
5th harmonic
1,100
880
660
440
220
3rd harmonic
Time
Sound source B
Perceived as a distinct auditory stream Perceived as a distinct auditory stream
FIGURE 11.16
Harmonic Coherence Takes
Precedence Over Spatial
Segregation
(a) Harmonics of a common
fundamental frequency are
presented simultaneously but from
different spatial sources. In this
situation, the listener hears one
auditory stream despite the spatial
differences. (b) When the harmonic
structure from two different sources
is not coherent, we hear two
separate auditory streams.
EXPLORATION: Biosonar in Bats and Dolphins
11.4 Interpret how biosonar allows animals to use active hearing to negotiate their environment.
You might not think bats and dolphins have much in com-
mon. Bats are small, nocturnal flying mammals, whereas
dolphins are large marine mammals (Figure 11.17). But
they share one important aspect of their biology: Both use
an active biosonar system. Biosonar is a process whereby
animals emit sounds and then use comparisons of these
emitted sounds and their returning echoes to sense the
world around them. Biosonar has much in common with
the electronic sonar systems human technology has devel-
oped. The basis of both systems is the determination of the
relation of emitted sounds and returning echoes (Simmons,
2012). This contrasts with our own hearing, which involves
Biosonar: a process whereby animals emit sounds and
then use comparisons of the emitted sounds and their
returning echoes to sense the world around them
332 Sensation and Perception
FIGURE 11.17 Bats and Dolphins Use Biosonar
Bats and dolphins use their auditory system to navigate the world. But bats and dolphins have a biosonar sense. They emit loud, high-frequency
sounds and then listen for the echoes. Both species, despite the difference in environments, use this information for hunting. Bats hunt small insects,
and dolphins hunt fish.
listening for external sounds but does not involve creating
echoes with our own voices. For this reason, biosonar is
thought of as a different perceptual system than our audi-
tory system. But because it involves the basic processes of
hearing, we include it here. For those who find this section
intriguing, we recommend the book Sensory Exotica by
Howard Hughes (1999), who discusses biosonar and a host
of other nonhuman sensory systems.
Bats hear sounds at much higher frequencies than we do.
Most species of bats can hear sounds at over 100,000
Hz, whereas our highest frequency tops out at 20,000 Hz
or below. Bats can produce very high-frequency sounds
themselves. It is this combination that allows them to
use biosonar. Because there is such a short wavelength
(remember that frequency and wavelength are inverses),
high-frequency sounds will be influenced by small objects
that obstruct the wave pattern. For instance, a mosquito
flying by would likely not impact a low-frequency wave,
but it would deflect a high-frequency wave (Figure 11.18).
That is, the low-frequency wave may miss the insect alto-
gether, but a high-frequency wave will hit the insect and
cause an echo to return to the bat. Thus, high-frequency
sonar allows bats to detect small prey items, such as mos-
quitoes, that lower frequencies would not pick up.
The problem with high frequencies, though, is that they
lose energy rapidly. This puts an additional requirement on
animals using biosonar. Because high frequencies lose vol-
ume rapidly, the initial sound must be very loud. Indeed,
both bats and dolphins call very loudly. Bat calls are often
as loud as 140 dB, and dolphin calls may reach 200 dB.
Luckily, we humans are not disturbed by these super loud
calls at night. Because these loud calls are made at frequen-
cies we cannot hear, they can be going on all around us
and we will not hear them. In essence, bats and dolphins
must call very loudly to give their calls a little more range
to strike potential targets.
Biosonar systems work by integrating the processing of
the call with the processing of the echo. Bats make calls,
and then their super-sensitive auditory systems listen for
the echoes that bounce off the objects in front of them
and return to their ears (see Figure 11.20). This system
provides the bat with information about the distance, size,
and speed of the target it is tracking. This system allows
bats to zoom in on prey and, in some cases, avoid obsta-
cles and bigger predators. Figure 11.19 shows the two dif-
ferent ways bats make these calls. In Figure 11.20, you
©
iS
to
ck
ph
ot
o.
co
m
/D
on
hy
pe
©
iS
to
ck
ph
ot
o.
co
m
/G
lo
ba
lP
FIGURE 11.18 High-Frequency Waves Are Better
for Capturing Information
(a) The low-frequency wave passes right through the small object,
which, for a bat, might be a tasty insect. The low-frequency wave will
not detect the insect. (b) The high-frequency wave will be deflected by
the small object, causing an echo to return toward the source of the
sound. It is for this reason that animals equipped with biosonar use
high-frequency sounds.
333 Chapter 11: The Auditory Brain and Sound Localization
can see how a bat, once it detects an insect, uses its calls to
home in on the insect.
A bat needs to determine the distance from itself to an object.
This is important—if the insect is too far away, the bat may
not be able to catch up. If the object is close by, the bat may
need to begin its capture behaviors. Distance from an object
is determined by a calculation of the amount of time it takes
for an echo to return to the bat. If the echo returns after a
very short lag, the bat knows the object in front of it is very
close. If the echo takes longer to return to the bat, the object
is farther away. In bat (and military) circles, this aspect is
known as the target range, that is, how far away the target
is. This is a quite remarkable ability when you consider how
close bats are likely to be to their targets and when you con-
sider how fast sound moves. Given that sound travels at 343
m/s, it will take only 12 ms between a bat’s call and the echo’s
return from a target 2 m away. Yet bat auditory systems can
track such incredibly fast echoes. A target farther away than
2 m will take more than 12 ms, and a target closer will take
less time. Thus, by timing the echo, the bat receives a precise
estimate of the target range.
Bats also need to know how large an object is. If a bat is
following an owl, for example, it may wind up being the
meal rather than finding a meal for itself. Thus, bats must
be able to infer size information from their biosonar sys-
tem. This information is also determined by the returning
echoes. Larger objects produce bigger echoes. Thus, a bat
can infer size from the relative loudness of the echoes. This
determination is relative to the distance of the object, which
is determined by timing. Thus, closer objects will produce
bigger echoes too, but the bat’s auditory system can account
for distance when using echo loudness to determine the size
of the object.
A bat needs to know if it is gaining on its target or falling
behind in its pursuit. If the insect is flying faster than the
bat, the bat may need to speed up. If the bat is flying faster
than its prey, it may need to moderate its speed to be ready
to engage in capturing behaviors. And if the bat is traveling
at the same speed as the moth it is pursuing, it will not be
able to catch it. This is normally not a problem, as bats fly
much faster than most of the insects they prey on. But the
bat still must know how fast it is approaching so that it can
initiate its catching behaviors at just the right time. They
determine their rate of approach by measuring something
called the Doppler shift in their calls. Doppler shifts are
apparent changes in frequency that occur when there is rela-
tive motion between the source of a sound and a detector. In
this case, both the source of the sound (the bat’s call) and the
detector (the bat’s detection of echoes) come from the same
place. The Doppler shift is an interesting phenomenon in
and of itself, so we take a slight digression to explain it here.
If a stationary object is emitting a sound at a particu-
lar frequency, a stationary perceiver will hear it at that
frequency. However, if the sound-emitting object starts
FIGURE 11.19 Bat Biosonar Calls
Constant frequency–frequency modulated (CF-FM) calls involve
long calls at a single frequency. When an object is detected, the
bat sweeps down in frequency. This is the characteristic pattern of
forest bats. Frequency modulated (FM) calls involve just the sweep
from high frequency down to relatively lower frequencies. This is the
characteristic pattern of desert bats.
CF-FM Call
emiTemiT
FM Call
90
60
30
3rd Harmonic
2nd Harmonic
1st HarmonicF
re
qu
en
cy
(k
H
z)
Components
CF FM FM only
B.
Detect and pursue
D.
Resume search
Return to search mode
C.
Capture
No calls at moment
of capture
0.05 second
“Feeding buzz”
A.
Search
Call in search mode
FIGURE 11.20 How Bats Use Biosonar
Bat biosonar is used for the pursuit and capture of insect prey. The bat
uses its call and the returning echo to locate food sources.
Target range: the distance of a predator from its potential
target, determined by timing an echo’s return
Rate of approach: the measure of whether a predator is
approaching a target or receding from it
334 Sensation and Perception
moving away from the perceiver, the object will still be
emitting at the same frequency, but each sound wave will
be coming from slightly farther away from the perceiver.
This creates a perceived frequency somewhat lower than
that of the actual sound. Similarly, if the sound-emitting
object is moving closer to the perceiver, the sound waves
will essentially bunch up together, creating the experience
of a higher frequency sound to the perceiver. This is why
an approaching train seems to get higher in pitch, and a
receding train appears to get lower in pitch to the station-
ary observer, waiting for the train to pass. A person on
board the train will not hear this shift because she is mov-
ing with the train and therefore hearing it at the frequency
at which the train sounds are emitted.
Now think about one of these bats calling as it flies though
the sky. Its calls come at a constant frequency, say 90,000
Hz. First, consider the bat is moving faster than the object,
but the bat is moving in the same direction as its calls. Thus,
relative to an object in front of the bat, the frequency will
appear slightly higher than the frequency the bat is actually
calling at because each call comes slightly closer to the pre-
vious call. If the object is moving faster than the bat is, it will
take longer for the waves to catch up with that object, and
the frequency will be perceived as lower than the actual call
(Figure 11.21 and ISLE 11.5).
In the case of the bat, its auditory system knows exactly
what frequency it is emitting. If the returning echo appears
to be slightly higher than
the frequency of the call,
the bat knows that it is
gaining on its target. Thus,
if it hears the echo at 90,050 Hz, the bat knows that it is
approaching the target. If the returning echo appears to be
slightly lower in frequency than the frequency of the call,
then the bat knows it is losing ground on its target. Thus,
if hears the echo at 89,950 Hz, the bat knows that it is
falling back from its target.
Finally, a bat needs to know if its target is moving to the
left or right and up or down relative to the bat’s position.
Left-right determination is done by a comparison of the
returning echo to the two ears, similar to the discussion
of sound localization earlier in this chapter. If the echo
is of equal amplitude in each ear, the bat knows the tar-
get is straight ahead. However, a difference in amplitude
between the left and right ears indicates that the target is
to the left or to the right. If the object is to the left of the
bat, the echo will be slightly stronger in the left ear than
the right ear, and if the object is to the right, the echo will
be slightly stronger in the right ear than the left ear. A bat
also needs to know if its target is rising or falling relative
to its flight pattern, that is, whether the target is flying
higher or lower than the bat. This turns out to be the most
complex computation by the bat’s auditory system, and
it involves comparing sound inputs distributed across its
complexly shaped pinnae. Bats have large movable pin-
nae, so they are much better at elevation determinations
than humans are. Studies have shown that blocking a bat’s
pinnae interferes with its determination of the elevation
of its target.
Using this information, a bat uses its auditory system
to “see” objects in the external environment (Simmons,
2012). Because it is using its auditory system, a bat can
use this system to guide its flight in complete darkness.
Biosonar also allows bats to be highly social. It has been
shown that they use their sonar systems to avoid bumping
into one another in the tight confines of caves, and some
bats also use sonar to identify their own offspring (Bohn,
Smarsh, & Smotherman, 2013).
What about dolphins? Dolphin sonar is also a call-and-
echo system (Hughes, 1999). Dolphins also use loud,
high-frequency pulses. Indeed, dolphin calls have registered
at over 200 dB and nearly 200,000 Hz! Dolphins com-
pute distance to target, approach to target, size of target,
and left-right and up-down differences in the same way as
bats. What makes the dolphin’s system remarkable is that
sound travels 4 times faster through water than it does
through air. Thus, the dolphin’s brain must be even more
sensitive to minute millisecond time differences than that
of the bat.
LL
1
1 • • • 5
2
3
4
5
λ
Listener
Sound Source
FIGURE 11.21 Doppler Shifts
If a sound source is approaching you, it will sound slightly higher
in frequency to you than it would to an object moving along with it.
Similarly, if a sound source is receding from you, it will sound slightly
lower in frequency to you than it would to an object moving along with it.
Because bats know the frequencies at which they are calling, they can
use these Doppler shifts in the echoes to calculate rate of approach.
ISLE 11.5
Doppler Shift
335 Chapter 11: The Auditory Brain and Sound Localization
APPLICATION: Concert Hall
Acoustics and Hearing
11.5 Discuss factors that go into designing a concert hall with good acoustics.
Many people enjoy live music. People gather in large num-
bers to hear concerts of varying types. In many forms of
popular music, a concert may be played in a large stadium.
Such stadiums are usually not designed for live music, and
typically music is amplified through a variety of electronic
means. This means that the sound that the audience hears
is not necessarily coming from the direction of the stage.
It is coming from wherever there are speakers projecting
that amplified sound. In very large stadiums, such as the
half-time show at a football game, such amplification is
necessary because no single human voice could carry across
such a stadium. Moreover, with the relatively slow speed of
sound, a fan in the upper part of the stadium might detect
a difference between the visual movements of the singer’s
mouth and the music that is reaching him. However, in
“classical” orchestral music, the music is not usually elec-
tronically amplified. In these concerts, the audience hears
the music emanating from the instruments on the stage, at
the sound level of the actual playing of the instruments or
the voices of the choir. For this reason, the design of the
concert hall is important (Figure 11.22). The concert hall
must be designed to deliver that music to the audience in a
conducive way without unnecessary echoing or distorting
the sound. This is especially important in the larger concert
halls, where sound must reach people in the back at suffi-
cient loudness.
Architectural acoustics is the study of how physical spaces
such as concert halls affect how sounds are reflected in a
room. Listen to ISLE 11.6 for an illustration of how the
physical space alters a sound. A concert hall wants the
sound to come directly to audience members without much
echoing or reverberation. Direct sound has advantages. For
example, because lower pitches have lower frequency, they
will tend to move around objects, such as chairs, that can
cause echoing, more so than higher pitches. Thus, direct
sound carries more of the intended musical pitches than
does indirect sound. Because it is impossible to eliminate
all indirect sound, it is also important to design the concert
hall such that the indirect sound is as muffled as possible.
Typically, architects try to create a 60-decibel drop from
the direct sound to the first reverberation of indirect sound
(Lokki & Patynen, 2015; Sabine, 1922). Indeed, Sabine
introduced the concept of reverberation time to represent
the difference between the onset of direct sound and the first
onset of indirect sound. In some cases, it is defined differ-
ently, but we go with Sabine’s original definition. Therefore,
room acoustics tells us how sound travels from instruments
to the listeners in the audience. The auditory system of the
listener depends on the direction of the sound and the fre-
quencies of the sound. Because higher frequencies are more
influenced by room dynamics, architects must design spaces
to especially reduce the reverberation of those higher fre-
quencies (Patynen & Lokki, 2016). It is also important
to design a concert hall in which the reverberation time
is least intrusive. Most concert halls look for a reverber-
ation time of about 2 sec-
onds because this allows
the music to be heard as
intended and not distorted
ISLE 11.6
Architectural Space and Echoes
Architectural acoustics: the study of how physical spaces
such as concert halls affect how sounds are reflected in a
room
Reverberation time: the difference between the onset of
direct sound and the first onset of indirect sound
FIGURE 11.22 Concert Hall
People gather in such halls to hear musical performances. Acoustical
engineers design these halls to channel the sound in order to make the
music enjoyable and without unnecessary echoing or distorting the sound.
Shutterstock.com
/m
ichaeljung
336 Sensation and Perception
or essentially blurred by the presence of echoes. Recording
studios will often use an even shorter reverberation time to
allow for very precise recording (Beranek, 2003).
An important factor in architectural acoustics is the
expected loudness of the concert hall. As the loudness
of the music increases, the importance of good acous-
tics increases. At softer volumes, there is less reverbera-
tion off the walls and ceiling of the concert hall, but this
increases as the loudness increases (Meyer, 2009). Indeed,
Meyer suggests that one way to test a concert hall is
to examine the pattern of reverberation when loud music
is presented. Most concert halls allow for softer sounds
to sound pure, but as the music gets louder, the acous-
tics become more critical. For this reason, it is import-
ant to test each concert
hall while it is under
construction to ensure
a high-quality sound
(Beranek, 2003). ISLE 11.7 illustrates this process for an
actual renovated concert hall.
The next time you have the pleasure of hearing music live
in a concert hall, look at the walls and the ceiling. They
are designed to muffle the indirect sound as much as pos-
sible. Absorbing materials such as fiber boards make
up the odd-looking material on the walls and ceiling. Take note
of the loudness level before the concert starts. Even though
there might be more than 1,000 people there, you can prob-
ably talk with your friends or family in a normal voice and be
heard. Contrast that with a busy restaurant with typical walls
without soundproofing. Even with only a dozen or so people
in a restaurant without soundproofing, the loudness level may
interfere with the ability to hear each other. You might think
that some restaurants would add soundproofing so that their
customers could converse better. But restaurants find that at
noisier levels, customers order more and leave earlier, so unlike
a concert hall, in which good acoustics is critical, restaurants
might actually prefer the extra sound.
ISLE 11.7
Testing a Concert Hall
CHAPTER SUMMARY
11.1
Discuss the ascending neural pathways from the
cochlea to the auditory cortex.
Hair cells send signals into the auditory nerve, which then
leave the ear and head toward the brain. The cochlear
nucleus is a structure in the brain stem that receives input
from the inner hair cells. The signal is then sent to the
superior olive and from there to the inferior colliculus. The
inferior colliculus sends the auditory signal to the medial
geniculate nucleus, which then sends its output to the
auditory cortex. The primary auditory cortex (and rostral
core) is the first area in the auditory cortex that receives
input from the medial geniculate nucleus. It is surrounded
by the belt and parabelt regions. Tonotopic organization
means that the auditory cortex is organized by frequency.
The auditory cortex develops early in the fetus’s neural
development.
11.2
Identify the processes our auditory system uses
to localize the sources of sounds in space.
To localize an object in space, we must know if it is to
the left or right of us, whether it is in front of or behind
us, and whether it is above or below us. Sound localiza-
tion is a very important aspect of the auditory system, as
it is often important to pinpoint a sound’s source. That is,
we must be able to localize sound in three-dimensional
space. The interaural time difference is the time interval
between when a sound enters one ear and when it enters
the other ear. The interaural level difference is the differ-
ence in loudness and frequency distribution between the
two ears. The acoustic shadow is the area on the side of
the head opposite from the source of a sound in which
the loudness of a sound is less because of blocked sound
waves. The cone of confusion is a region of positions in
space in which sounds create the same interaural time
and interaural level differences. The shape of the pinna
affects elevation perception, which has been demon-
strated in experiments. When the shape of the pinna is
artificially altered, elevation perception is impaired. This
is known as the spectral shape cue.
11.3 Explain the concept of auditory scene analysis
and how it is achieved by the auditory system.
Auditory scene analysis is the process of identifying
specific sound-producing objects from a complex set of
sounds from different objects at varying and overlapping
frequencies. The rules of auditory scene analysis fall into
three basic types: temporal segregation, spatial segrega-
tion, and spectral segregation. The auditory system devel-
ops early. Indeed, studies show that shortly after birth,
Chapter 11: The Auditory Brain and Sound Localization 337
infants will respond differently to sounds they heard
in utero and sounds they did not.
11.4 Interpret how biosonar allows animals to use
active hearing to negotiate their environment.
Bats and dolphins use a complex system known as
biosonar to negotiate their environments. Biosonar is
a system of active hearing. Animals produce high-fre-
quency sounds at very loud volumes and then listen for
the echoes of those sounds. By comparing the sound
produced to the echo received, these animals can
extract useful information such as the distance to an
object and whether they are gaining on or losing that
object. Both bats and dolphins use biosonar to avoid
obstacles and hunt prey.
11.5 Discuss factors that go into designing a concert
hall with good acoustics.
A concert hall is a place where people gather to listen to
music. For this reason, it is important to design concert
halls with the best acoustics to allow people to enjoy the
music. Architects design concert halls to reduce indirect
sound, that is, the sound bouncing off walls and ceilings
rather than coming directly from the musicians. The more
such indirect sound can be reduced, the better the con-
cert will be.
REVIEW QUESTIONS
1. List all of the brain regions that make up the ascend-
ing auditory pathway. Describe at least one dif-
ference of this auditory pathway from the visual
pathways to the brain.
2. What are the “what” and “where” systems in audi-
tory perception? What brain regions are involved in
each system?
3. What is meant by the term tonotopic organization of
the auditory cortex?
4. How can the interaural time difference be used to
compute the spatial coordinates of a sound in the
external world?
5. Why are interaural level differences more useful
in localizing high-frequency sounds than low-fre-
quency sounds?
6. What is the cone of confusion? How does it affect
sound localization for an unmoving perceiver?
7. What are the mechanisms human auditory systems
use to detect the distance of a sound? Why are we
better at judging distance for a familiar sound? Why
are bats and dolphins better at detecting distance?
8. What is meant by the term auditory scene analysis?
What mechanisms do we use to group frequencies
together from common sources?
9. What is the difference between a call and an echo
in bat echolocation? Why does a bat need both to be
able to detect objects?
10. How does a bat compute its rate of approach to
an object? How might a bat be fooled by an insect
equipped with the ability to produce high-frequency
sounds but not the ability to fly faster than the bat?
PONDER FURTHER
1. Can you relate specific gestalt principles to spe-
cific ideas of auditory scene analysis? For example,
how would the “law of simplicity” map onto spatial
segregation?
2. Consider a difference in the visual and auditory sys-
tem. The crossing over from the left and right sides
of the world takes place much earlier and much
more often for the neural processing of audition than
vision. What advantages does this crossover provide
for audition?
Sensation and Perception338
KEY TERMS
Acoustic shadow, 324
Architectural acoustics, 335
Auditory core region, 320
Auditory cortex, 320
Auditory scene analysis, 327
Azimuth, 322
Belt, 320
Biosonar, 331
Cochlear nucleus, 319
Cone of confusion, 324
Distance, 322
Elevation, 322
Harmonic coherence, 329
Inferior colliculus, 319
Interaural level difference, 324
Interaural time difference, 322
Medial geniculate nucleus, 319
Parabelt, 320
Primary auditory cortex, 320
Rate of approach, 333
Reverberation time, 335
Rostral core, 320
Rostrotemporal core, 320
Spatial segregation, 329
Spectral segregation, 329
Spectral shape cue, 325
Superior olive, 319
Target range, 333
Temporal segregation, 328
Tonotopic organization, 320
Trapezoid body, 319
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
11.1 Discuss the ascending neural pathways from the cochlea to the
auditory cortex.
11.2 Identify the processes our auditory system uses to localize the
sources of sounds in space.
Auditory Spatial Processing in the Human Cortex
Auditory Azimuthal Localization Performance in Water as a
Function of Prior Exposure
11.3 Explain the concept of auditory scene analysis and how it is
achieved by the auditory system.
Audio Demonstrations Of Auditory Scene Analysis
Tuning In to the Brain’s “Cocktail Party Effect”
11.4 Interpret how biosonar allows animals to use active hearing to
negotiate their environment.
Daniel Kish: How I Use Sonar To Navigate The World
11.5 Discuss factors that go into designing a concert hall with good
acoustics.
10+ Tips for Designing Classrooms, Hospitals and Offices
That Are Kind on Ears, From Julian Treasure
One Man’s Quest to Find the “Sonic Wonders of the World”
(start at 6:40)
Alberto Ruggieri/Illustration Works/Getty Images
12Speech Perception
Gusto/Science Source
LEARNING OBJECTIVES
12.1
Discuss the complex process of speech perception and
speech production with regard to the speech stimulus.
12.2
Sketch the mechanisms our speech perception system uses
to extract coherent speech from the speech signal.
12.3
Contrast the different types of theories of speech perception,
noting their similarities and differences.
12.4
Diagram the areas of the brain involved in speech perception
and what happens when they are damaged.
INTRODUCTION
There is no function of our auditory system more vital to human beings than speech
perception. Speech perception is critical in interacting and socializing with the people
around us. Unless you spend most of your time in your study writing textbooks, you
are likely to spend most of your waking hours talking to and listening to other people.
Other people constantly surround us, and they communicate with us using speech.
You hear “What’s your name?” and this sound informs you that the person speaking
is asking to interact with you. You hear somebody say, “What’s the best restaurant
near here?” and you know that she wants your opinion. Speech is everywhere and vital
for our everyday life (Figure 12.1). Moreover, from the auditory signal of a person’s
voice, we extract not just the information the speaker is conveying but also information
about the speaker, including gender, age, mood, native language, national background,
regional background, educational level, and so on. And all of this information comes
from the auditory speech signal.
We need to be able to understand speech rapidly. The average speaker may talk at a
rate of roughly four words per second. That is one word every 250 ms. This means our
auditory system must convert the sound signal into meaningful language information at
very rapid rates to allow us to gather all the information that we need from speech. Our
auditory system uses every bit of available information to do this, including using cross-
modal information from vision to help us understand speech. It also turns out that the
speech signal is very complex, which further taxes our speech perception system. This
chapter examines some of the processes that allow our auditory systems to quickly
interpret very complex speech signals.
ISLE EXERCISES
12.1 Coarticulation
12.2 Voicing-Onset Time
12.3 McGurk Effect
12.4 Familiar vs.
Unfamiliar Languages
12.5 Phonemic
Restoration Effect
12.6 Genie
12.7 Broca’s and
Wernicke’s Aphasia
342 Sensation and Perception
A situation many people find themselves in from time
to time is a crowded room filled with many conversations
taking place at once. This situation might occur in a busy
restaurant, while watching a sporting event, while at a fra-
ternity party, or at an old-fashioned cocktail party. Indeed,
in the technical literature, this phenomenon is known as the
“cocktail party effect.” In the cocktail party effect, you are
listening to the speech of one person, but your attention is
then distracted by the mention of your name by someone
across the room. You may not have even been aware of
this conversation, but the mention of your name can drag
your attention from the conversation you are a part of to
one across the room (Cherry, 1953). To researchers in the
1950s and 1960s, this observation suggested that our atten-
tional mechanism does not screen out all perceptual input
even when we are focused on one conversation. We covered
attention in an earlier chapter, but we mention it here to note
that our speech perception systems are capable of monitor-
ing multiple speech inputs at the same time. This requires enormously complex processing
in our auditory system to separate out the different voices coming from different directions.
From the point of view of your auditory system, all of the voices you hear in different
conversations are causing movements along your basilar membrane at the same time.
Think of this: Every sound has one entry point into our auditory system, via the stapes
pressing on the oval window. Thus, the auditory system must first be able to separate out
the various voices as well as all other sounds that are all occurring at the same time. This
problem of segmenting the auditory signal into its component parts is called auditory
scene analysis (discussed in Chapter 11), and it is necessary to determine which particular
sounds are coming from which source (Bregman, 1990). Even if no person is speaking to
you as you read these words, think of the different sounds you can pick up. You can sep-
arate out the sound of the radio playing music in the other room easily from the barking
of the dog across the street. Similarly, even when multiple voices are talking at the same
time, we can separate out which voice goes with which person and place those voices
appropriately in terms of their locations. Recent research shows that an important com-
ponent of scene analysis for speech is the familiarity of a voice. A familiar voice, such as
that of a spouse, a child, or a parent, can be used to mark a particular signal to either be
attended to or not. We are better at both with familiar voices relative to unfamiliar voices
when listening amid a chatter of conversations (Johnsrude et al., 2013).
Like many perceptual processes, speech perception seems effortless and fluent to
adults, in this case, listening to fluent speakers of their native language. However, as
with many perceptual processes, what our auditory system must do to achieve this fluent
perception is remarkably complex. Indeed, computer speech-processing systems are only
now becoming truly workable, and even so, they require enormous computing power.
THE HUMAN VOICE AS STIMULUS
12.1
Discuss the complex process of speech perception and
speech production with regard to the speech stimulus.
Perceptual processes begin with a stimulus in the environment. In the case of human
speech perception, that stimulus is a voice. Other people produce speech, which our
©
iS
to
ck
ph
ot
o.
co
m
/J
oh
nn
yG
re
ig
FIGURE 12.1 Listening to Language Is Critical
People must listen to and understand others’ speech in most aspects of
their lives.
343 Chapter 12: Speech Perception
perceptual apparatus must hear and understand.
Therefore, it is necessary to understand just a bit
about the acoustics of human voices in order to
begin our discussion of speech perception. We
are sure you will not be surprised to learn that
the human speech organs are quite complex, and
many different parts of our anatomy play a role
in producing the myriad speech sounds we make.
Speech sounds are produced by movements
of the vocal apparatus (Figure 12.2). Speech
sounds are acoustic signals, which start as air
pressure changes in the lungs that are then mod-
ified by a number of structures in the neck and
mouth that create the sounds we use as speech.
First, air that produces the sound passes through
the trachea (or windpipe) and into the larynx
(also known as the voice box). The larynx is an
important part in the vocal tract but not the only
one necessary for speech. Vocal folds within the
larynx open and close to change the pitch of the
sound. However, parts of the vocal tract higher
up from the trachea are necessary for the array of
consonant sounds our voices must make. From
the larynx, the air passes through the pharynx
into the mouth and nose, where teeth, tongue,
lips, and the uvula can affect the sound signal.
The pharynx is the top portion of the throat. The uvula is tissue in the back of the mouth
attached to the soft palate. Closing the uvula prevents sounds from going up through
the nasal cavity, affecting the quality of the sound. The sound signal then exits the vocal
apparatus through the mouth and the nose. These articulators are depicted in Figure 12.2.
Vowels and Consonants
Human vocal tracts have to be able to make two categories of speech sounds: vowels
and consonants. These terms are equivalent to the categories one learns when learning
to read. Vowels are represented in English by the letters a, e, i, o, u, and sometimes y.
Consonants are the letters that surround these vowel sounds, such as the sounds rep-
resented by the letters b, v, and p. Vowels and consonants have different origins within
the vocal tract. Vowels are produced by unrestricted airflow through the pharynx and
mouth. Changing the shape of the mouth creates different vowel sounds. Restricting the
airflow in one place or another along the way up from the larynx produces consonants.
For example, movements of the tongue restrict the sound and change the nature of a
consonant. Perceptually, as well, vowels and consonants are two distinct categories.
Vowels are produced by vibrations of the vocal cords, and specific vowel sounds
(“oo,” “ah,” “ee,” etc.) are made by changes in the position of the oral cavity, particu-
larly the shape of the mouth. If you speak aloud the standard vowel sounds in English,
you will feel the shape of your mouth move. As we change the shape of our mouth and
vocal tract, we change the resonances in the sound. That is, each vowel sound has a
characteristic pattern of harmonics. The harmonics that are of highest amplitude are
known as formants. Formants are the frequency bands with higher amplitudes among
the harmonics of a vowel sound. Each individual vowel sound has a specific pattern
of formants. Figure 12.3 shows the shapes of the mouth and the frequency spectra for
two different vowel sounds. Note that the fundamental frequency is the same for each
Hard
palate
Soft palate
(velum)
Uvula
Pharynx
Larynx
Air from lungs
Open
Closed
Alveolar
ridge
Teeth
Nasal
cavity
Lips
Oral cavity
Vocal folds
Vocal folds
Tongue
FIGURE 12.2 The Vocal Tract
Human beings have a sophisticated anatomical system for producing language
sounds. Speech is initiated with air being pushed out of the lungs into the larynx.
Vocal folds in the larynx vibrate at different frequencies, producing the different
pitches human voices are capable of. Changes in the position of the pharynx, oral
cavity, tongue, lips, and teeth can then shape that sound into the particular speech
sound the person is saying.
Trachea (windpipe): the tube
bringing air to and from the
mouth
Larynx (voice box): a
structure that affects the
pitches of sounds being made
by the human vocal tract
Pharynx: the top portion of
the throat
Uvula: a flap of tissue at the
top of the throat that can close
off the nasal cavity
Vowels: speech sounds made
with unrestricted airflow
Consonants: speech sounds
made with restricted airflow
Formants: frequency bands
with higher amplitudes among
the harmonics of a vowel
sound; each individual vowel
sound has a specific pattern of
formants
344 Sensation and Perception
vowel. Vowels are distinguished from one
another by their formant frequencies.
Consonants are produced by restricting
or closing the flow of air along the vocal
tract. In English, the letters b, d, and f all rep-
resent consonant sounds. Some sounds, such
as “b” and “v” and “d” and “f,” are very
similar and are therefore sometimes difficult
to distinguish. Other consonant sounds used
in English include “m” as in mom and “k”
as in kick. In English, we use the consonant
sound “sh,” though other languages, such as
Spanish, do not. In contrast, Spanish uses
sounds, such as the “ñ” in niño, which we
do not typically use in English.
Three physical features are important
in determining the sound of a consonant.
The place of articulation refers to the point
along the vocal tract at which the airflow
is constricted. The place of articulation
may include the tongue, the lips, the teeth,
and structures at the back of the mouth,
such as the soft or hard palate. Try saying
“b” versus “d.” The manner of articula-
tion refers to how that restriction occurs.
This involves whether the lips are pushed
together, whether the tongue is at the front
or back of the mouth, and other variants
of the mouth’s position. Try saying a few
simple words (e.g., “Bring the plate of choc-
olates, but do not drop it on the floor”) or
simple nonsense syllables (e.g., “b,” “f,” and
“m”), and attend to the positions of your tongue, teeth, and lips as you say each sound,
and you will see how each sound is accompanied by different positioning of the vocal
tract. Finally, voicing refers to whether the vocal cords are vibrating or not. Think of the
difference between the way we say the sound in the letter p and the sound in the letter
b. When you say the letter b, you can feel your vocal cords vibrating immediately as you
produce the sound. “P” is not accompanied by vocal cord vibration until after the “p” has
been pronounced. We say that “b” is a voiced consonant and that “p” is an unvoiced
consonant. “S” and “z” are also complementary unvoiced and voiced sounds. Figure 12.4
shows what our vocal tract is doing when we speak various sounds.
Speech
The purpose of speech is to convey information. When you tell your friend “I am hun-
gry,” you are telling that person how you are feeling and likely implying what you want
to do—have lunch. In order for your friend to understand what you are saying and
your intentions behind it, he must be able to correctly perceive your utterance. Thus,
speech perception involves the process of how we go from the sound signal coming
from a speaker to understanding in a listener. This involves complex motor tasks in the
speaker, as we just discussed, and complex auditory and cognitive tasks in the listener,
which we turn to now. We start with phonemes.
/i/ as in “bead”
/æ/ as in “bad”
Oral cavity
(a)
(b)
Tongue
Pharynx
Oral cavity
Tongue
Pharynx
F
2
F
2
F
1
F
1
F
3
F
3
Frequency (Hz)
A
m
pl
itu
de
(d
b
S
P
L)
0
0 5,000
20
40
60
Frequency (Hz)
A
m
pl
itu
de
(d
b
S
P
L)
0
0 5,000
20
40
60
FIGURE 12.3 Vowel Sound Production
(a) The mouth producing two different sounds. (b) The frequency spectra for those sounds.
Place of articulation: the
point along the vocal tract
at which the airflow is
constricted
Manner of articulation: how
airflow restriction in the vocal
tract occurs
Voicing: whether the vocal
cords are vibrating or not
Voiced consonant:
a consonant that is produced
using the vocal chords
Unvoiced consonant:
a consonant that is produced
without using the vocal chords
345 Chapter 12: Speech Perception
Phonemes are the basic units of sound in human language.
When a phoneme is changed, the meaning of the utterance is
changed. Consider the word mop, which consists of three pho-
nemes: “m,” “ɒ” (the international symbol for the vowel sound
in mop), and “p.” If we change the first phoneme from “m”
to “h,” we get a new word, hop, with a different meaning. If
we change the vowel sound in the middle from “ɒ” to the “æ”
sound in map, we also get a different word. Finally, we can
change the “p” sound at the end of the word to a “b” sound and
get mob. Thus, in this case, each of the three letters in the word
mop represents a separate phoneme. It is important to note
that phonemes refer to sounds, not letters. We must represent
some phonemes with letters in this book, but any particular
letter may stand in for multiple phonemes. Think of the letter
combination ch, which may represent the first sound in chil-
dren and the first sound in choir, despite the fact that the two
sounds are quite different and it is two letters being used for
one phoneme in each case. Figure 12.5 shows a classic diagram
of how we use the mouth to make many different phonemes.
In English, as in many languages, convention in spell-
ing does not match phonemes in a straightforward and
direct manner. Users of English must learn by rote what
vowel sound to use when pronouncing such words as
mood and blood, rough and through, and heard and
beard. In other cases, we may have two separate symbols
that represent the same phoneme, such as in the “f” sound
“pit,” “bit”
/p/, /b/
“fine,” “vine”
/f/, /v/
“tip,” “dip”
/t/, /d/
“kit,” “get”
/k/, /g/
FIGURE 12.4 Articulation of Consonants
Consonant sounds depend on the place of articulation, manner of
articulation, and voicing. Several consonant sounds are depicted here.
FIGURE 12.5
Production of Vocal Sounds
Seventeenth-century diagrams of the
anatomy of the human throat, showing
how vocal sounds are produced. Each
of the smaller 34 diagrams shows the
vocalization of a particular letter or sound.
The larger diagram (lower right) is labeled
with the epiglottis, the larynx, the trachea
(aspera arteria), and the esophagus. These
diagrams are from An Essay towards a Real
Character and a Philosophical Language
(1668) by English clergyman and natural
philosopher John Wilkins (1614–1672). In
this book, Wilkins attempted to establish a
universal language.
Phonemes: the basic units of
sound in human language
346 Sensation and Perception
TABLE 12.1 Phonemes
of American English Using the
International Phonetic
Alphabet
Vowel
International
Phonetic
Alphabet
Example
Words
a ace, stay
a hat, cat
a art, father
ay/ei play, eight
e pet, red
e he, key
ear/ere fear, here
ere/air there, pair
i sit, mit
i pipe, life
ow, ou how, pout
o go, home
o spot, lock
ou/a thought, ball
tour, pure
oi/oy join, toy
oul/u could, put
oo/ue food, blue
our/ure
ur/ear burn, earn
Consonant
International
Phonetic
Alphabet
Example
Words
b bat, jab
c cab, block
ch
choke,
church
d do, bad
f fan, if
g game, log
h hot, help
j jump, large
l let, liftel
m map, lime
n note, pen
n sting, fi nger
p pool, tap
r rest, train
s soap, kiss
s
treasure,
vision
sh shirt, trash
t tip, setting
th
thought,
bath
th this, brother
v vote, hive
w win, willow
y yell, yet
z zoom, crazy
International Phonetic
Alphabet: an alphabetic
convention that provides a
unique symbol for each and
every phoneme in use in
human languages
in father and phoneme. Thus, spelling and written letters only partially capture the
richness of phonemes.
Linguists, in studying phonemes, require a system in which a single symbol rep-
resents each sound that people make in a particular language. This alphabet is known
as the International Phonetic Alphabet, which provides a unique symbol for each
and every phoneme in use in human languages. The International Phonetic Alphabet
includes symbols for the hundreds of unique sounds that are used across the thousands
of languages in use today (MacMahon, 1996). Table 12.1 shows the phonemes used in
English and the symbols used to represent them in the International Phonetic Alphabet.
Inspect Table 12.1 carefully. You will see that first, in contrast to what you were taught
in elementary school, the English language has 15 vowel sounds and 24 consonant
sounds in what is considered standard American English, though there is a lively debate
on whether there is a standard American English. Because we use only 26 symbols in
347 Chapter 12: Speech Perception
English to represent 39 sounds, many individual letters and letter combinations (e.g.,
sh, oo) must be used to represent multiple sounds. For example, using the International
Phonetic Alphabet, the word mop is spelled “mɒp,” while the word through is spelled
“θru,” and cash would be spelled “kæ∫.” It takes a while to get comfortable using the
International Phonetic Alphabet.
You might well wonder why we do not switch to the International Phonetic
Alphabet, as each word’s spelling uniquely describes how that word is pronounced,
and this might make spelling easier. This is true, except that it would mean that all
homophones (e.g., bear and bare) would be spelled the same, and the meaning would
depend on context. As it is, our writing system is made more difficult by the complex
correspondence between symbol and sound, but also less difficult by this disambigua-
tion of words that have multiple meanings. Using the International Phonetic Alphabet
would also mean that regional differences in pronunciation would require different
spellings. For example, the word schedule would need to be spelled differently in
the United States and the United Kingdom, as Americans and Britons use different
pronunciations for this word. It would also require that spellings vary as a function
of region within any particular English-speaking country. As Harvard linguist Steven
Pinker (1994) noted, for native Bostonians, the words orphan and often would be
spelled identically using the International Phonetic Alphabet. Thus, although it may be
appealing to come up with a completely phonetic spelling system, it is also not without
its problems.
TEST YOUR KNOWLEDGE
1. Describe the pathway of air as it moves from the lungs
and out of the mouth in making speech sounds.
2. Compare and contrast phonemes and the role they play
in speech with letters and the role they play in writing.
VARIABILITY IN THE
ACOUSTICS OF PHONEMES
12.2 Sketch the mechanisms our speech perception system
uses to extract coherent speech from the speech signal.
When we hear a speaker utter the expression “The boy was resist-
ing arrest,” we must engage in some complex auditory processing
to go from the sound signal to perceiving phonemes to under-
standing the sentence. For example, could this sentence really be
“The boy was resisting a rest,” with far less serious implications?
In this case, listeners must use top-down processing using con-
textual information to parse the words in a sentence, that is, to
break the ongoing stream of language into separate words. If the
sentence is said at a day care center for 5-year-olds, we might
gravitate toward the latter interpretation. If it is said by a police
officer during a trial, we would opt for the first interpretation.
Note that for this sentence, the manner in which most speakers of
English would say it aloud gives us no clues. In this case, only the
context can disambiguate the speech (Figure 12.6). We will see in
©
iStockphoto.com
/boggy22
FIGURE 12.6 Parsing Word Boundaries
The difference between “resisting arrest” and “resisting a rest.”
©
iStockphoto.com
/Cylonphoto
348 Sensation and Perception
this section that speech perception requires a number of “tricks” that help the auditory
system make fast and accurate interpretations of the speech signal.
Coarticulation
Speech perception must take place at very fast rates, as the average speaker can talk at
the rate of four words per second. Or, to phrase it another way, the average speaker can
produce about 15 phonemes per second. To produce this rapid speech, our articulators
(e.g., the parts of our mouth, vocal tract) must do things simultaneously. Indeed, when
we speak, we also anticipate what sounds are coming next. In this way, we will say the
phoneme “b” in the word bat in a slightly different way than we say the phoneme “b”
in bet, because a different vowel sound follows the “b.” Think about the position of
your mouth when you say bat—it is more rounded right at the start than when you
say bet. Similarly, the “a” sound in bat is said slightly differently than the “a” sound in
back. This phenomenon is referred to as coarticulation. We can define coarticulation
as the phenomenon in which one phoneme affects the acoustic properties of subsequent
phonemes (ISLE 12.1).
What this means is that the consonant and vowel sounds in “ba” overlap when they
are spoken. It also means that the “a” sound is influencing how the “b” is being said.
This is a reciprocal process, with the vowel influencing the consonant and the conso-
nant influencing the vowel. We can see this pattern of coarticulation in sound spec-
trograms of people speaking different consonant–vowel pairs. A sound spectrogram
is a way of plotting sounds to help understand complex acoustic stimuli. Time is on
the x-axis and the different frequencies in the sound are plotted on the y-axis. Finally,
the darker the portion of the graph is, the more intense the frequency is. Thus, you can see
how the frequencies change in intensity and which frequencies are present over time.
The physical acoustics of “ba” are different from those of “be.” This is illustrated graph-
ically in Figure 12.7. In Figure 12.7, you can see that the spectrogram looks different
right at the beginning for the two different sounds, which both start with the letter b.
Coarticulation is an acoustic reality. The acoustic stimuli of “bah,” “bee,” and “boo”
are different, as you can see in Figure 12.7. However, as perceivers of speech, we do not
hear the differences in the “b” sounds among “bah,” “bee,” and “boo.” All we hear is the
phoneme “b.” Thus, even though the signal varies, what we hear is a constant.
We encountered the concept of perceptual constancy in our discussion of visual
perception. We discussed how we see the same color regardless of the wavelength of
ISLE 12.1
Coarticulation
6000
0
0 Time (s)
F
re
q
u
e
n
cy
(
H
z)
0.4944
6000
0
0 Time (s)
F
re
q
u
e
n
cy
(
H
z)
0.542
6000
0
0 Time (s)
F
re
q
u
e
n
cy
(
H
z)
0.6443
FIGURE 12.7 Coarticulation in the Pronunciation of Consonants
These spectrograms show the formants for the sounds “bah,” “bee,” and “boo.” You can see that the highest frequency formant is highest for “boo”
relative to “bah” and “bee.” This is a consequence of coarticulation.
Coarticulation: the
phenomenon in which one
phoneme affects the acoustic
properties of subsequent
phonemes
349 Chapter 12: Speech Perception
illumination in color constancy, and that objects appeared the same size regardless
of retinal size. Our perception of coarticulation is an example of an auditory con-
stancy, similar to the concepts of constancy with respect to vision. Because the various
“b” sounds refer to the same phoneme, we perceive them as being identical. To reiterate,
perception of coarticulation is that two or more different physical sounds are heard as
identical phonemes.
What this means for our speech perception systems is that several different sounds
must be grouped together to represent a particular phoneme, depending on context.
This happens early in auditory processing, such that we do not perceive a difference
between the “b” in bet and the “b” in bat. This can sometimes be a problem when learn-
ing a new language. For example, Japanese speakers group together what we English
speakers hear as “l” and “r” into a single phoneme. Thus, when learning English, words
such as rail and lair are difficult to distinguish because the two words sound identical to
a native Japanese speaker. It is not simply a matter of not being able to pronounce them.
Essentially, native Japanese speakers must redefine their phoneme groupings in order
to perceive ours. Similarly, there are sounds in other languages that English perceivers
do not hear. Nonetheless, our speech perception system groups sounds together, such as
the “b” in bet and bat, and the difference between these sounds implicitly allows us to
anticipate the sounds that follow each use of the phoneme.
Categorical Perception
As we have seen, being able to distinguish phonemes is critical to speech perception.
Thus, our auditory system uses a number of processes to help us hear the right phoneme.
Of course, phonemes represent categories but are made from a range of different physi-
cal sounds. To help us with phoneme perception, perceptual variation is clumped using
categorical perception. Categorical perception refers to our perception of different
acoustic stimuli as being identical phonemes up to a point at which our perception
suddenly shifts to perceive another phoneme. That is, we do not hear the variation
in the signal—we hear only the phoneme. And then, at a certain point, the variation
crosses a boundary, and we hear a different phoneme altogether. Categorical perception
exists in other sensory modalities as well. We see blue across a wide range of the visual
spectrum, but then blue abruptly becomes green at about 480 nm. Recall the Bornstein
et al. (1976) study examining color perception in infants in Chapter 6. It was taking
advantage of categorical perception. In speech, we may hear the “r” sound across a
wide range of acoustics, but it then abruptly becomes “l” at a certain point. In the case
of “l” and “r,” it is the tongue’s position that determines which sound we are making.
Sounds with intermediate tongue positions will be heard as either “l” or “r,” and we
seldom find these sounds strange.
With respect to phonemes, we hear a particular sound, such as “t,” across a range of
acoustic stimuli. Then, at a particular point along an acoustic dimension, our perception
shifts, and we hear the sound as a different phoneme (e.g., “d”). This is illustrated nicely with
a phenomenon called voicing-onset time. Voicing-onset time refers to the time difference
between the first sound of the phoneme and the movement of the vocal cords. Variation in
voicing-onset time allows us to tell the difference between voiced and unvoiced consonants.
The movement of the vocal cords is called voicing. Consider the difference between the pho-
nemes “s” and “z.” The phonemes “s” and “z” are similar with respect to the position of the
mouth, but “s” is unvoiced, and “z” is voiced. Try saying each consonant while placing your
hand on your Adam’s apple. You can feel the vibration for the “z” but not for the “s.” That
is, the vocal cords do not vibrate when we say “s,” but they do when we say “z.” The conso-
nants “t” and “d” are also a pair of consonants formed the same way but the “t” is unvoiced
and the “d” is voiced. In the sound “ta,” our vocal cords vibrate 74 ms after the burst of
Categorical perception:
the perception of different
acoustic stimuli as being
identical phonemes up to a
point at which perception flips
to perceive another phoneme
Voicing-onset time:
the production of certain
consonants (called stop
consonants) in which there is
a difference between the first
sound of the phoneme and the
movement of the vocal cords
(called voicing)
350 Sensation and Perception
sound for the “t,” corresponding to
the “a” part of the sound. However,
when we say the voiced “da,” there
is vocal cord vibration within 5 ms
of the start of sound. This is illus-
trated in Figure 12.8. You can see an
example on ISLE 12.2. In these sound
spectrograms, you can see voicing
by vertical striations (light and dark
areas) going horizontally through
the figure.
In normal speech, in words such
as “ta-ta” or “da-da,” for example,
the voicing will be different, with
“ta” not showing voicing until
much later than “da.” But what happens when we change the natural voicing? This can
be done easily in the lab with sound-processing software. In essence, in the lab, we can
create a hybrid sound—something intermediate between the “t” and the “d.” Thus, the
question becomes, what do we hear when we hear a “t/d”-like sound with voicing half-
way in between “ta” and “da”?
This is exactly what Eimas and Corbit (1973) did in a now classic experiment on
categorical perception. They presented listeners with sounds in which the voicing varied
6000
Beginning of sound
(a)
Beginning of voicing
0
0 Time (s)
F
re
q
u
e
n
cy
(
H
z)
0.6443
6000
Beginning of sound
(b)
Beginning of voicing
0
0 Time (s)
F
re
q
u
e
n
cy
(
H
z)
0.5584
FIGURE 12.8 Voicing-Onset Times in Voiceless and Voiced Consonants
(a) The sound spectrogram for “ta.” (b) The sound spectrogram for “da.”
ISLE 12.2
Voicing-Onset Time
100
(a)
“Same” “Different”
80
/da/
/ta/
60
40
P
e
rc
e
n
ta
g
e
/
d
a
/
re
sp
o
n
se
s
20
0
0 20 40
Voicing-onset time (msec)
60 80 0 5 10 15 20 25 30
Voicing-onset time (msec)
/p
a
/ re
sp
o
n
se
s (%
) /b
a
/
re
sp
o
n
se
s
(%
)
35 40 45 50 60
0
10
20
30
40
50
60
70
80
90
1000
90
80
70
60
50
40
30
20
10
100
Phonemic
boundary
55
(b)
FIGURE 12.9 Categorical Perception
In an experiment, Eimas and Corbit (1973) asked participants to classify sounds as either “ta” or “da.” They then presented participants with sounds
with varying onsets of voicing. They found (a) that almost all sounds with voicing onset lower than 35 ms were classified as “da,” but almost all sounds
with voicing onset over 35 ms were classified as “ta.” (b) The 30-ms phonemic boundary for “p” and “b.”
351 Chapter 12: Speech Perception
from 0 ms up to 80 ms for “ta” and “da.” At 0 ms, listeners heard the sound as “da,”
and at 80 ms, listeners heard the sound as “ta.” Eimas and Corbit were interested in
what listeners would hear when intermediate voicings were presented (e.g., 20-, 40-,
and 60-ms voicing-onset times). What they found was categorical perception. People
heard seemingly normal “ta” and “da” sounds, which abruptly switched from one to
the other at a voicing-onset time in between the two. That is, we hear the syllable “da”
up to about 35 ms, and then our perception abruptly changes, so that at 40 ms, we hear
“ta.” In only a small zone is the stimulus ambiguous, and once the change of perception
is made, we do not hear anything odd about these nonnatural sounds. This transition
at 35 ms is the phonemic boundary between “t” and “d.” A similar phonemic boundary
exists for other voiced–unvoiced pairs, such as “p” and “b,” which transition when the
voicing occurs at around 30 ms. Figure 12.9 illustrates these results graphically.
Functionally, categorical perception simplifies the determination of what phoneme is
being produced and allows us to extract relevant linguistic information from individual
and contextual differences in speech. Thus, for example, we could imagine a speaker
whose native language is not English, who may voice the vowel after “p” slightly earlier
than we do in English. When this speaker says a word such as principal or poet, we
hear the “p” sound as a “p” because of categorical perception, which translates a wide
range of voicing into one phoneme.
The Effect of Vision on Speech
Perception and the McGurk Effect
Until the advent of telephones in 1876, almost all speech was done within the range
of one speaker seeing the other speaker. Yes, people shouted at a distance back then,
but speech without vision was rare, to say the least.
Even today, outside of telephone conversations, in most
cases, we see the people we are speaking to. And with the
increased usage of video calling in Skype and FaceTime,
we are returning to the time when almost all of our con-
versations occur when we can see each other, near and
far (see Figure 12.10). We watch as our friends talk to us,
we look up toward our teachers when they are address-
ing the class (and if we are not looking at them, chances
are we are not attending to them), and we watch actors
move and talk in movies and television shows. Some of
us may spend a great bit of time talking to friends and
family on the telephone, particularly if we live some dis-
tance from those friends and family. But here is a phe-
nomenon you may notice when speaking to a person you
do not know via telephone. It is often difficult to distin-
guish unfamiliar words over the telephone. A customer
representative tells you his name, but you cannot tell if it is Denny or Benny. This is less
likely to happen in person because of the presence of visual cues we lack when convers-
ing on the phone. In some instances, visual cues can greatly influence our perception
of speech. For example, “dubbing” movies requires great skill. If the movements of the
mouth do not match up with the sound signal, it can greatly decrease the realism of the
movie. Nonetheless, as experimental psychologists, we can ask the question, How much
does vision influence speech perception?
A very compelling demonstration of the influence of vision on speech perception was
developed by McGurk and MacDonald (1976) and has come to be known as the McGurk
effect. To demonstrate the McGurk effect, participants are shown a video of a person’s
mouth saying monosyllabic sounds, such as “ba,” “da,” and “tha.” However, the audio
©
iStockphoto.com
/Raw
pixel
FIGURE 12.10 Video Call Chatting Communication
McGurk effect: a
phenomenon in which vision
influences the sounds people
report hearing
352 Sensation and Perception
component does not always match what the speaker’s mouth was saying when the syl-
lables were recorded. That is, the video has been dubbed, and the sound track is simply
“ba” over and over again. To be clear, the sound is “ba,” but the movement of the mouth
may signal “ga.” The question McGurk and MacDonald posed was what would the par-
ticipants hear? Would they hear what they heard or what they saw? Thus, the question
McGurk and MacDonald were interested in was whether people would hear the sound
track or what the mouth was doing. Strangely, but compellingly, when participants watch
the video, they perceive the sounds as being differ-
ent both from what they actually hear and what
phoneme the mouth makes that they are watching.
In Figure 12.11, the observer is watching a mouth
say “ga,” but the sound track is “ba.” However, the
observer’s perceptual experience is that of hearing
“da,” a perception different from the actual sound.
To really understand the McGurk effect, though,
you have to hear it and see it for yourself. You can
see an example on ISLE 12.3. Watch the video once
and think about what you hear. Then play the video
again and keep your eyes closed. You will be sur-
prised to find out that initially, you heard what you
saw. The McGurk effect is a very compelling illusion
that affects virtually all people.
The McGurk effect is surprisingly robust, given
that it is fundamentally an error in perception. It
works when participants can see only the mouth
and when they can see the entire face saying the
syllables. It works with people of all ages and lan-
guage backgrounds, and it works on faces so degraded
that they are scarcely recognizable as faces. Indeed,
one study found that there was a McGurk effect for
touch (Fowler & Dekle, 1991). In this study, partic-
ipants felt a mouth saying one set of syllables, while
a sound track played another set. Fowler and Dekle
found that the participants heard what they felt. Szycik, Stadler, Tempelmann, and Münte
(2012) examined the McGurk effect while participants were undergoing functional mag-
netic resonance imaging (fMRI). They found an area of the brain that was active during
McGurk effect illusions, that is, when there was a mismatch between audition and vision.
This area was not active when participants only heard the sounds or when the sounds and
visuals were compatible. This integrative area that drives the McGurk effect seems to rest
along the superior temporal sulcus at the top of the temporal lobe.
Top-Down Processing and Speech Perception
Think about listening to someone speaking in English (presumably a language you are
fluent in, if you are reading this text) and about listening to someone speak in a language
with which you are not familiar (e.g., Telugu, Yalunka, or Sorani). When listening to
English, we hear distinct words, pauses in between words, and then more words again
(ISLE 12.4). When listening to an unfamiliar language, it often sounds like a continuous
cascade of sound. In a language you are learning, there may be a flip between hearing
a continuous stream of speech and hearing breaks between words as your experience
increases. In some cases, you may be able to parse the speech correctly into words, but
in other cases, you may not. Why does this perception occur? It turns out that speech
ISLE 12.3
McGurk Effect
Sound from monitor:
“ba-ba”
Speaker’s lips:
“ga-ga”
Observer hears:
“da-da”
FIGURE 12.11 The McGurk Effect
An observer is watching a mouth. The mouth is saying “ga,” but the sound track
plays the syllable “ba.” The observer does not hear what the actual sound is.
Rather, the observer hears a “da” sound.
353 Chapter 12: Speech Perception
perception is dependent on a number of top-down processes. That is, knowledge about
language influences how we perceive speech. For example, because we know where the
boundaries between English words are, we are likely to hear pauses between individual
English words. Earlier we pointed out the difference between “The boy was resisting
arrest,” and “The boy was resisting a rest.” To hear the difference between these two
sentences, we must use top-down processes to determine
where the word boundary goes between a and rest. Because
we may not be familiar with Telugu (a language spoken in
India), we do not hear these word boundaries when we are
listening to a person speaking Telugu. To be more specific,
evidence for top-down processing in speech perception
comes from knowledge of specific combinations of pho-
nemes within a language and knowledge of the context of
speech. For example, we know in English that “s” sounds
may be followed by “p” sounds, but not by “f” sounds.
Thus, if we hear someone say “sfecial,” we may assume that
what he meant to say was “special.” Or, if the context is
different and we know that the person is talking informally
about a man or “fellow,” the person may have said “this
fella,” but we heard the “s” in “this” run into the “f” in
“fella” (see Figure 12.12).
Word segmentation is the ability of speakers of a lan-
guage to correctly perceive boundaries between words.
This means that we use knowledge of our language to draw boundaries as to where one
word ends and the next word begins. Consider the following sentences:
How to wreck a nice peach.
How to recognize speech.
In these sentences, we must determine, depending on context, whether the speaker is
intending to say three words, wreck a nice, or simply one, recognize. Examining a sound
spectrogram will reveal no differences in the pauses between the syllables of the three words
and the one word. As a fluent speaker of English, one immediately uses context to determine
which of these two utterances is intended. If you are in sensation and perception class at 8
a.m., you are likely to opt for the second sentence, but if you are at a juice bar, and the person
making your smoothie accidentally drops a piece of fruit on the floor, you might think the
word boundaries correspond to the first sentence. If you are not a fluent speaker of English,
you will probably not be able to distinguish these utterances, and therefore not even know
how many words the speaker intended to say. Context, which is provided by existing knowl-
edge, is therefore an important aspect of speech perception.
The Phonemic Restoration Effect
We have seen with the McGurk effect that it is possible to induce an illusion of one
speech sound even though the actual sound in the environment is another speech sound.
In this case, processing of the visual information overrides the input from the cochlea.
In the phonemic restoration effect, top-down processing of what one expects to hear
overrides input from the cochlea. Like the McGurk effect, phonemic restoration is a
very strong subjective effect, and we encourage all readers to go to ISLE 12.5 and listen
to it. The phonemic restoration effect refers to an illusion that illustrates the importance
of top-down processing for speech perception.
ISLE 12.4
Familiar vs. Unfamiliar Languages
Wherearethe s i l e n c e s be t w een wo rd s
FIGURE 12.12 Parsing Word Boundaries
The physical boundaries in sound among syllables do not always
correspond to the boundaries between one word and the next.
Word segmentation: the
ability of speakers of a
language to correctly perceive
boundaries between words
Phonemic restoration
effect: an illusion in which
participants hear sounds that
are masked by white noise,
but context makes the missing
sound apparent
354 Sensation and Perception
In the phonemic restoration effect, an experimenter uses a computer to delete or
mask a particular sound in a sentence in which the context clearly indicates what the
missing sound should be (Warren, 1970). The experimenter then asks the participant
what she just heard. For example, the sentence might be
British viewers flocked to the opening **ight performance of Doctor Who.
In this sentence, the “n” sound in night has been replaced by white noise, represented here
by the double asterisk. Thus, the “n” sound is not actually present, but listeners are asked what
they heard. Indeed, listeners report hearing the word night, complete with the “n” sound that
is not physically present. It is not merely that they infer that the word must be night; partici-
pants actually hear the missing sound. To sample the phonemic restoration effect for yourself,
go to ISLE 12.5.
What is particularly striking about the phonemic restoration effect is that it works
even when the context of the missing sound occurs after the missing sound. Consider
the following sentence:
It was found that the **eel was on the axle.
In this sentence, the context clearly suggests that the missing sound is “wh,” as in wheel.
However, at the time the participant hears “**eel,” he has not yet heard the context. We do not
learn about the axle until after the missing sound. Nonetheless, when participants heard this
sentence (actually used in Warren’s research), they reported hearing the missing “wh” sound.
This was not a fluke of this particular sentence. Warren found the same thing when partici-
pants listened to this sentence:
It was found that the **eel was on the orange.
Note that here, the sentence is identical to the previous sentence with the exception of
the last word. As in the “wheel” sentence, the context occurs about a third of a second after
the missing sound. Nonetheless, here too, participants reported hearing the correct word, in
this case peel. For this reason, the phonemic restoration effect has intrigued philosophers as
well as psychologists, because speech perception essentially goes back in time and supplies a
perceptual experience after the stimulus has been past for almost half a second. It speaks to the
strong power of expectations, or what we call here top-down processing, to influence percep-
tual experience, even when that experience occurred a split second earlier.
Some recent research suggests strongly that the phonemic restoration effect occurs
early in information processing, certainly before conscious control, despite the nature
of the top-down processing. Mattys, Barden, and Samuel (2014) showed that the per-
ception of the missing sound became more pronounced as a secondary task became
more difficult. That is, when participants had to devote more attention to a secondary
visual task they were doing in addition to the phonemic listening task, the illusion of
hearing the missing sound grew stronger. Thus, the phonemic restoration effect must
occur at a preattention stage in speech perception processing. This emphasizes how
critical the understanding of context is to understanding fluent speech.
We can ask what neural mechanisms allow us to unconsciously infer the missing
sound even when it occurs before the context is supplied. Sunami et al. (2013) used
magnetoencephalography to examine the neurological correlates of the phonemic res-
toration effect. They found that areas within the auditory cortex in the temporal lobe
were involved with the phonemic restoration effect, presumably the areas responsible
for the “hearing” of the missing sound. But just prior to that activation, they found
areas in the left prefrontal lobe that responded more strongly to context for missing
ISLE 12.5
Phonemic Restoration Effect
355 Chapter 12: Speech Perception
sounds than for sounds that were actually present. It is likely that this area of the
brain houses the processes that make the top-down inference about context and then
what the sound must be. It then transmits this information to the temporal lobe, which
“hears” the missing sound.
TEST YOUR KNOWLEDGE
1. How does our speech production system create different consonant sounds?
2. Create a diagram to illustrate how categorical perception works, and explain its
role in speech perception.
THEORIES OF SPEECH PERCEPTION
12.3
Contrast the different types of theories of speech perception,
noting their similarities and differences.
What should be clear from the discussion so far is that our sensory systems engage in
complex processing to transform a complex speech signal into meaning, and they do
so amazingly quickly. We have introduced a number of features the human speech per-
ception system uses to allow this rapid processing. We attend to coarticulation, that is,
that the sound being heard in the present informs us as to what to expect in the future.
Our perceptual systems also benefit from categorical perception, which allows us to
quickly distinguish among similar phonemes. Furthermore, we use the visual signal
of the movements of the mouth to help us understand speech. And we fill in missing
sounds when the context suggests what they should be. But are there overall rules that
guide speech perception? That is, are there theories that can explain the overall process
of speech perception?
Such theories can be divided into two general classes. First, some theorists argue that
speech is no different than any other sound and that we use the same mechanism with
speech that we do with other sounds. These theories are called general-mechanism
theories. By contrast, other theorists argue that because of the importance of language
to humans, special mechanisms have evolved that are specific to speech and are not used
in the processing of other kinds of sound. Not surprisingly, these theories are called
special-mechanism theories (Diehl, Lotto, & Holt, 2004).
Special-mechanism theories start with the premise that there is a unique neuro-
cognitive system for speech perception that is distinct from other kinds of auditory
perception. One influential version of the special mechanism is the motor theory of
speech perception (Liberman & Mattingly, 1985). This view contends that we have a
special mechanism that allows us to detect speech as unique and then relate the sounds
to the presumed speech movements (i.e., talking) of the speaker (Galantucci, Fowler, &
Turvey, 2006). The goal of speech perception is to infer the movements of the speaker’s
mouth. This may sound crazy, but it was developed with the observation in mind that
there is seemingly nothing constant about the auditory signal—remember that “b” is
a different sound depending on whether it is followed by an “ah” sound or an “eh”
sound. In the motor theory view, what is constant across individual phonemes is the
speech articulations that produce that sound. Evidence for this view certainly comes
from the McGurk effect, in which the speech sound we perceive is what we are seeing,
not what is coming in on the sound track. We will see another way to look at special
mechanisms later when we discuss how different areas of brain damage influence dif-
ferent aspects of speech processing, including speech perception.
General-mechanism
theories: theories of speech
perception that claim that
the mechanisms for speech
perception are the same as
the mechanisms for auditory
perception in general
Special-mechanism
theories: theories of speech
perception that claim that
the mechanisms for speech
perception are distinct
and unique relative to the
mechanisms for auditory
perception in general
Motor theory of speech
perception: the theory that
the core of speech perception
is that the system infers the
sound from the movements of
the vocal tract
356 Sensation and Perception
In contrast, the general-mechanism approach argues
that speech perception occurs through the same neuro-
cognitive processes as other forms of auditory perception.
In this view, what makes speech perception unique is its
importance, which is learned rather than based on an
innate neural mechanism. In terms of theories, scientists
tend to prefer a simpler theory unless there is compelling
evidence to support a more complex theory. In this case,
the general-mechanism theory is less complex than the
special-mechanism theory because the general-mechanism
theory requires only one neurocognitive system. Thus,
this theory should be considered the default until pro-
ponents of the special-mechanism theory can definitively
demonstrate that speech perception requires its own
unique mechanism.
One general-mechanism approach includes the view
that speech perception involves top-down mechanisms of
categorization. Thus, any sound is analyzed by processes
that categorize sound in general. When we hear speech,
we immediately classify it as such. If we hear the creaking of a door, we do not invest
any meaning into that sound other than that someone or something is pushing on that
door. If the sound is something like “meow,” we classify it as a nonspeech sound, although,
in this case, one that might contain information (Figure 12.13). Any cat owner knows the
difference between her cat’s meow that means “feed me” and the one that means “open
the door.” However, when we hear a stimulus that sounds like “Open the door, please”
(I’m not a cat, so of course I say “please”), we immediately classify many features of the
utterance, such as the speaker’s gender, regional dialect, age, emotional state, and identity.
It is this act of classification that represents what makes speech perception unique (Holt &
Lotto, 2010).
Holt and Lotto (2010) pointed out that in many cases, nonspeech sounds
can influence our perception of speech sounds, consistent with the gener-
al-mechanism approach. For example, in one study (Holt, 2005), a speech
sound such as “ga” or “da” was preceded by a series of 21 nonspeech
sounds. Each series created a different history of sound perception intended
to influence the perception of the speech sounds presented at the end. If
speech perception occurs by a unique and special mechanism, the pattern
of preceding nonspeech sounds should have no effect on the perception of
speech. However, if the general-mechanism approach is correct, then there is
the possibility that nonspeech sounds influence speech perception. And this
is what Holt found. The pattern of the 21 nonspeech sounds influenced the
likelihood of hearing the speech sound as “ga” or “da,” consistent with the
general-mechanism view (Figure 12.14).
Because of studies such as Holt’s (2005) and others, most researchers today
think of speech perception as a form of auditory perception in general. The
tricky part, however, is still how we extract speech signals, such as phonemes,
from complex and variable stimuli. Thus, many speech perception researchers
have moved away from the special-mechanism model but still think the goal of
speech perception is to connect sound to the source of that sound, namely, the
movements of the vocal tract (Fowler & Thompson, 2010). Fowler’s view is a
direct perception view (e.g., Gibson, 1979). She argues that the goal of percep-
tion is to guide us through the environment. In the case of speech perception,
Fowler argues that it is the movement of the vocal tract that is the invariant
©
iS
to
ck
ph
ot
o.
co
m
/N
ev
en
a1
98
7
FIGURE 12.13 Do We Know What Cats Are Saying?
Cat owners know the messages their cats are sending when they listen to
their meows. Cats use a different meow to indicate “feed me” than they
do for “scratch my ears.”
100
80
60
40
20
0
1 2 3 4 5
Consonant–vowel stimulus
P
e
rc
e
n
ta
g
e
o
f
“g
a
”
re
sp
o
n
se
s
6 7 8 9
High Mean
Mid Mean/
Low Variance
Low Mean
Mid Mean/
High Variance
FIGURE 12.14 Perception of
Speech Is Influenced by Nonspeech
Sounds (Holt, 2005)
The more repetitions of the nonword stimulus,
the less likely the test stimulus was heard as a
speech sound.
357 Chapter 12: Speech Perception
in the word, and that the perceptual apparatus is tuned to that invariant. In other words,
our speech perception is really about figuring out what the vocal tracts of others are doing.
Thus, it is no wonder that our speech perception is sometimes fooled by sounds, if our goal
is to infer how somebody’s vocal tract works rather than to perceive sounds per se.
The Development of Phoneme Perception
Infants are born into the world with a remarkable aptitude for acquiring language
but no genetic penchant for learning one language or another. The language learned
is, of course, determined by the linguistic environment the infant finds himself in. An
infant raised by an English-speaking mother will learn English, and an infant raised by
a Sorani-speaking mother will learn Sorani (Kurdish). However, languages vary in the
phonemes they use, and even when they use the same phonemes, there may be subtle
differences among them. For example, the English “p” sound is more explosive than
the Spanish “p” sound. During the first year of life, infants are engaged in an intensive
learning of the rules of speech perception in the language or languages that surround
them. In the United States, monolingualism is the norm, but in many other countries,
children are bilingual or multilingual from a very early age.
During the first 6 months of life, an infant can distinguish among all of the pho-
nemes used in a language and can discern subtle differences in sound among equivalent
phonemes across languages (Harley, 2014). We may think of infants at this age as not
being linguistic in nature, as they cannot speak yet and do not understand meaning, but
these infants are paying very close attention to sound. Indeed, they are paying closer
attention to sound than are the adults around them. Consider the difference between
the English “p” and the Spanish “p.” When we hear a person who is a native speaker
of Spanish speak in English, we may note that she has an accent, but when we listen to
her speech, we are attending to meaning, not subtle differences in sound. The difference
between saying “Harry Potter” with an explosive English “p” or “Harry Potter” with
a soft Spanish “p” is irrelevant. Either way, we are talking about a fictional wizard.
However, young infants are attending to just these differences (Harley, 2014). And, just
in case you do not know, Harry Potter should not go back to Hogwarts.
Consider a study done by Janet Werker and her colleagues (e.g., Maurer & Werker,
2014). They compared infants and adults in their perceptions of the two ways of saying
the “t” sound in Hindi, a language widely spoken in India and throughout the Indian
diaspora. In Hindi, there is a “t” sound spoken with the tongue at the back of the
mouth, and a “t” spoken with the tongue at the front of the mouth, as it is in English.
Because the sounds may be associated with different meanings in Hindi, Hindi adults
recognize the difference between these two sounds. To English-speaking adults, how-
ever, they both sound like “t,” and we do not hear the difference.
In one of her seminal studies, Werker looked at whether infants being raised in
English-speaking homes would hear the sound difference between the two Hindi “t”
sounds (see Werker, 2012). Werker found that at 6 months of age, these infants were
able to distinguish the two sounds with nearly 100% accuracy. However, by the time
these infants were 10 months old, their accuracy had dropped to about 20%. In con-
trast, Indian babies (being raised in a Hindi-speaking environment) maintained this
100% accuracy at 10 months and beyond. Thus, because the sound difference is rel-
evant in Hindi, Hindi babies maintain the distinction, but because it is irrelevant in
English, English babies no longer perceive the difference.
These results illustrate something that Werker calls perceptual narrowing (Werker &
Gervain, 2013). Perceptual narrowing refers to the developmental process whereby
regularly experienced phonemes are homed in on, as well as the simultaneous diminish-
ing of the ability to discriminate unfamiliar phonemes. That is, as infants get older, they
Perceptual narrowing:
the developmental process
whereby regularly experienced
phonemes are homed in on,
with simultaneous diminishing
of the ability to discriminate
unfamiliar phonemes
358 Sensation and Perception
focus their attention on stimuli that are relevant to them, rather than attending to all
stimuli out there. This is advantageous in learning one’s first language, though it makes
it more difficult to acquire a native-sounding accent in a second language later on. We
have focused here on the experiments comparing Hindi-language infants and English-
language infants, but one can see these perceptual narrowing differences across many
language pairs (Harley, 2014). Because speech signals are so complex, it benefits young
children (and, later, adults) to ignore irrelevant differences in sound and focus only on
those sound differences that are meaningful in the language that they speak.
Normal speech development, as mentioned earlier, takes place in an environment
rich in language. But what happens if the child grows up without that stimulation?
Tragically, there have been a few cases of children that were raised in extreme social
isolation that removed the child from this essential linguistic environment. One famous
case is that of a child who is called Genie (Curtiss, 2014). After having suffered tre-
mendous abuse under horrific circumstances, she was discovered at the age of 13 and
was taken from her home. She had grown up socially isolated and had minimal con-
tact with her mother and none with her father or other family members. The degree
and duration of isolation were extreme even relative to most other cases (Fromkin,
Krashen, Curtiss, Rigler, & Rigler, 1974). Without going into details, the circumstances
were unspeakable. However, she survived. She was unable to speak when discovered,
though there is some evidence that she might have begun normal language develop-
ment within her first 20 months. Perhaps some of the perceptual narrowing mentioned
by Werker above might have taken place. Still, she could not speak or understand
language at first. Her communications at first can be described as whispered grunts.
Still, over time, Genie has shown a remarkable ability to learn to speak and, particu-
larly, to understand speech. She learned to understand the difference between singular
and plural nouns, negatives, possessives, and a number of prepositions, particularly in
regard to perception and comprehension (Fromkin et al., 1974). Although she never
likely developed adult language, her development is remarkable, nonetheless (Curtiss,
2014). Early development is extremely important for language, but it appears that
some speech learning abilities can persist into later life. You can see some video of
Genie in ISLE 12.6.
TEST YOUR KNOWLEDGE
1. What are the general-mechanism and the special-mechanism theories of
speech perception? What differences do they anticipate?
2. What is perceptual narrowing? What does it do for a developing child? Can
you think of a phenomenon later in life in which perceptual narrowing leads to
difficulties?
SPEECH PERCEPTION AND THE BRAIN
12.4
Diagram the areas of the brain involved in speech perception
and what happens when they are damaged.
Understanding language is an extremely important aspect of being a human being.
Therefore, we should expect to see complex neural systems involved in the processing of
the human speech signal. And this is exactly what we find in the human brain. Although
we focus on perceptual aspects of language, equally important to language is producing
ISLE 12.6
Genie
Broca’s area: an important
area in the production of
speech, located in the left
frontal lobe
Wernicke’s area: an
important area in speech
comprehension, located in the
left temporal lobe
Aphasia: an impairment
in language production or
comprehension brought about
by neurological damage
Broca’s aphasia: a form of
aphasia resulting from damage
to Broca’s area, causing a
deficit in language production
359 Chapter 12: Speech Perception
speech. Indeed, there is close integration of the
perception and comprehension networks for lan-
guage and the brain regions responsible for pro-
ducing speech.
Two 19th-century neurologists, Pierre Broca
and Carl Wernicke, were instrumental in begin-
ning our understanding of the neuroanatomy
of speech and language (Figure 12.15). For
their work, each has an area in the brain named
after him: Broca’s area and Wernicke’s area.
Interestingly, the patient Broca studied had dam-
age in an area different from the one now named
after him, but Broca is given credit for being one
of the first to associate specific areas of the brain
with unique language functions. Wernicke cor-
rectly identified the areas for the production of
language and for the comprehension of language.
For this reason, some anatomists call Broca’s area
Broca–Wernicke’s area to honor the bet-
ter scientist but still distinguish it from
Wernicke’s area proper. We use the term
Broca’s area, despite Broca’s own mis-
identification of the area. It is also impor-
tant to note that Broca’s and Wernicke’s
areas are not the only areas in the brain
associated with language, and there is
even some debate as to the role of these
two areas in language function. Broca’s
area and Wernicke’s area are depicted in
Figure 12.16.
Broca’s area is in the left frontal lobe
directly in front of the primary motor cor-
tex and is an important area in the pro-
duction of speech. Wernicke’s area is in the
left temporal lobe and is critical in under-
standing language. In the vast majority of
people, Broca’s and Wernicke’s areas are
localized in the left hemisphere, although
a very small minority, most of them left-
handers, may have these areas localized in
the right hemisphere.
Aphasia is an impairment in language production or comprehension brought about
by neurological damage. In Broca’s aphasia, the damage is to Broca’s area of the brain.
Broca’s aphasia is characterized by nonfluent speech. However, by and large, speech
perception is not affected, and language comprehension is normal. Broca’s aphasics
have a halted speech pattern and have difficulty speaking sentences. Their frustration
at their inability to speak can sometimes be palpable, as they have an understand-
ing of meaning, but cannot translate it into speech. There is also some evidence that
Broca’s aphasics have deficits in understanding complex grammar relative to controls,
even though their word comprehension shows no such deficit. A video of patients with
Broca’s aphasia is available in ISLE 12.7.
ISLE 12.7
Broca’s and Wernicke’s Aphasia
Paul Fearn/A
lam
y Stock Photo
Sc
ie
nc
e
&
S
oc
ie
ty
P
ic
tu
re
L
ib
ra
ry
/S
SP
L/
G
et
ty
Im
ag
es
FIGURE 12.15 Two Early Scientists on Language and the Brain:
Pierre Broca (left) and Carl Wernicke (right)
FIGURE 12.16 Broca’s and Wernicke’s Areas
Broca’s area is in the frontal lobe, and Wernicke’s area is in the temporal lobe.
Broca’s area
Motor cortex
Angular gyrus
Primary
visual
cortex
Wernicke’s area
Lateral
�ssure
360 Sensation and Perception
Wernicke’s area is located in
areas of the brain associated with
the auditory system in the tempo-
ral lobe. Anatomically, it is located
in the posterior section of the supe-
rior temporal gyrus. This area is
also known as Brodmann area 22.
Damage to Wernicke’s area results in
deficits in the comprehension of lan-
guage, a condition called Wernicke’s
aphasia. Severe Wern icke’s aphasia
may result in a complete absence
of understanding language. Speech
is, by and large, fluent, but it may
appear to not make sense to listen-
ers, as the patients themselves cannot
understand what they are saying.
This meaningless speech is some-
times called jargon aphasia. Unlike a
person with Broca’s aphasia, individ-
uals with Wernicke’s aphasia often
show a blithe indifference to their
disorder and seem unaware of their
problems. Videos of patients with
Wernicke’s aphasia can be found in
ISLE 12.7.
Interestingly, although Wernicke’s
area clearly emerges from auditory
processing parts of the brain, its
role in language is comprehension.
There are cases in which sign lan-
guage speakers have developed brain damage in Wernicke’s area. These sign language
speakers have a deficit in understanding sign language equivalent to the deficit in
comprehension seen in Wernicke’s aphasia for spoken language (Bellugi, Klima, &
Hickok, 2010). Thus, in people whose language is visual–manual instead of auditory,
it is areas of the brain associated with the auditory cortex that are involved in inter-
preting language.
As with any neurological damage, the extent of the brain damage may vary from
patient to patient. Thus, a patient with a relatively small lesion in Wernicke’s area may
be able to produce sensible speech and understand some elements of others’ speech.
However, a patient with a large lesion may not understand speech at all.
As you have probably guessed by now, nothing having to do with perception is
simple. This is true for the neurological basis for speech perception as well. Although
Wernicke’s area is critical for speech perception, there are many other areas of the
cortex also involved in this process. This includes auditory perception areas in the
temporal lobes as well as monitoring areas in the left prefrontal cortex. Studies with
neuroimaging techniques have delineated some of the connections and links between
these areas. In particular, many neuroscientists now think that the distinction between
“what” and “where” is applicable to speech perception. That is, our auditory cortex
has pathways for identifying the “what” of the signal, namely, recognizing meaning
Via higher order frontal networks
Articulatory network
pIFG, PM, anterior insula
(left dominant)
Spectrotemporal analysis
Dorsal STG
(bilateral)
Phonological network
Mid-post STS
(bilateral)
Conceptual network
Widely distributed
Combinatorial network
aMTG, aITS
(left dominant?)
Lexical interface
pMTG, pITS
(weak left-hemisphere bias)
Ventral stream
Dorsal stream
Input from
other sensory
modalities
Sensorimotor interface
Parietal–temporal Spt
(left dominant)
(b)
(a)
FIGURE 12.17
The Dual-Stream Model of Speech Perception (Hickok & Poeppel, 2007)
The dual-stream model of speech perception involves a ventral pathway that recognizes speech
as speech and a dorsal stream that links that speech to the movements of individual speakers.
Abbreviations refer to regions of the brain. The regions are color coded so that the color of the
box matches the brain region. For the intensely curious: aITS, anterior inferior temporal sulcus;
aMTG, anterior middle temporal gyrus; pIFG, posterior inferior frontal gyrus; PM, premotor cortex;
pMTG, posterior middle temporal gyrus; Spt, parietal lobe temporal lobe boundary; STG, superior
temporal gyrus; STS, superior temporal sulcus.
Wernicke’s aphasia: a form
of aphasia resulting from
damage to Wernicke’s area,
causing a deficit in language
comprehension
361 Chapter 12: Speech Perception
in speech, and a “where” system, which
processes where the speech signal is com-
ing from (Hickok & Poeppel, 2007).
Figure 12.17 shows these areas associ-
ated with the two streams.
Some other neuroscience evidence is
relevant to the topic of whether speech
perception constitutes a special mecha-
nism or is best thought of as a function of
a general auditory perception mechanism.
This research concerns the discovery of a
voice area in the superior temporal sulcus.
Research shows that this area becomes
more active in response to human voices
than it does to nonspeech sounds (Belin,
Bestelmeyer, Latinus, & Watson, 2011).
Indeed, fMRI studies show that an area
Belin et al. (2011) called the temporal voice area, located in the superior temporal sulcus,
shows greater responses to voices than to natural nonvoice sounds or to unidentifiable
noise (Figure 12.18).
One of the questions that has always fascinated neuroscientists and laypersons alike
is whether we can tell what a person is thinking on the basis of the observable activity
of his brain. Many science fiction movies and novels involve fancy electronic equipment
that can determine exactly what someone is thinking. With the advent of neuroimaging,
perhaps we can ask whether a neuroscientist watching the activity of your brain in real
time with fMRI might be able to know that you are thinking about the time you were
looking over the rim at the Grand Canyon, or about how much Descartes’s religious
beliefs informed his philosophy. Or perhaps you were thinking about something you
would prefer the neuroscientist not know about and that we will not mention here.
This kind of research is still in its infancy, but some fascinating research has been able
to infer what words a person is listening to based on the activity in her auditory cortex
(Pasley et al., 2012).
In this unique and fascinating study, Pasley et al. (2012) recruited patients who were
soon to undergo surgery on their temporal lobes as a treatment for epilepsy or brain
tumors. All of the participants had normal language abilities. Because of the impending
neurosurgery, the patients had been fitted with intracranial electrodes, that is, sensitive
electrodes fitted on the temporal lobe underneath the skull, thus allowing fine spatial
and temporal resolution of ongoing human brain activity. While these electrodes were
actively recording brain activity, the patients heard recordings of words and sentences
from a variety of speakers. This is interesting enough as it is, but what Pasley et al. did
then was feed the pattern of brain activity into a computer programmed to decode
what those words and sentences were. This program did not originally know what the
stimuli were, so it allowed Pasley et al. to determine if it was possible to infer what the
speech areas of the brain were listening to by observing activity in the auditory cortex
alone. In essence, their program serves as a speech decoder, taking the brain’s output to
re-create the input.
So here is the goal of the algorithm built into the computer program: Based only
on the pattern of activity seen in the temporal lobe, can the program extract the orig-
inal auditory signal? In this way, an experimenter will know what word was spoken
to the patient without actually having heard the word, but only seeing the output
FIGURE 12.18 The Temporal Voice Area (Belin et al., 2011)
The temporal voice area is located in the superior temporal sulcus, shown here. It responds
more to voice than to nonvoice sounds.
Voice area: an area located in
the superior temporal sulcus
that responds to the sound of
the human voice, but less so to
other stimuli
362 Sensation and Perception
of the computer program. Although not perfect—in the
best case, it was still less than 60% accurate—the algo-
rithm in the computer program was able to re-create the
auditory signal on the basis of the pattern of activity
in the auditory cortex, and it did so particularly well
for words, though less well for sentences. You can see
both the process and the results in Figure 12.19. In
the words of Pasley et al. (2012), “The results provide
insights into higher order neural speech processing and
suggest it may be possible to read out intended speech
directly from brain activity” (p. 2). We think this is an
important and bold step not just in the understanding of
speech perception but in the way in which neuroscience
is heading.
TEST YOUR KNOWLEDGE
1. What is aphasia? Develop a classification system
for Broca’s and Wernicke’s aphasia.
2. Describe what we learn about how the brain
processes speech from aphasia.
Acoustic waveform
Time (s)
Reconstructed
spectrogram
Reconstruction
model
Cortical surface
�eld potentials
Time
e
le
ctro
d
e
s
X
tim
e
la
g
s
Fr
e
q
u
e
n
cy
(
kH
z)
0
0.2
1
7
2
= x
FIGURE 12.19
Reinterpreting Brain Signals (Pasley et al., 2012)
This figure shows how the original signal is recorded in the brain and
then re-created via the algorithm that interprets the electrical activity in
the temporal lobe.
EXPLORATION: Hearing Loss
and Speech Perception
Taylor Monroe is a fictional 45-year-old woman. She has
a graduate degree in education and has been teaching high
school social studies for 20 years, and she is one of the more
popular teachers among the students. Ms. Monroe has been
wearing hearing aids to compensate for sensorineural hearing
loss since she was in college. Ms. Monroe’s hairstyles tend to
cover her ears, so most of her students do not know that she
has a hearing impairment. Ms. Monroe uses the latest tech-
nology in hearing aids, but she still complains that it is often
difficult for her to understand her students’ questions when
there is more than one person talking or if there is construc-
tion noise outside. Ms. Monroe’s complaint is typical of many
hearing-impaired people. Even with amplification, speech
comprehension may still be difficult, especially when other
sounds are present. Although Ms. Monroe has had her whole
life to adjust to her hearing loss, this problem is even more per-
vasive in older adults who experience hearing loss late in life.
As we discussed in the previous chapter, today’s digital
hearing aids are amazing apparatuses that use complex
engineering to help people hear (Figure 12.20). As recently
as 20 years ago, hearing aids merely amplified sound. But
now they have complex programs to help individuals with
hearing loss, especially with the problem of speech percep-
tion. Nonetheless, the major goal of hearing aids still is the
selective amplification of frequencies to compensate for
higher thresholds at those frequencies (Kochkin, 2005).
FIGURE 12.20 Hearing Aids
Hearing aids are small and easily concealable, but they help people
with hearing disabilities in tremendous ways.
©
iS
to
ck
ph
ot
o.
co
m
/s
na
pp
ho
to
363 Chapter 12: Speech Perception
Amplification of speech brings sounds for which an indi-
vidual is hearing impaired above threshold, so that he can
hear them, but the same amplification may also amplify
sounds the person can hear normally, resulting in their
being too loud. As we know, any voice has multiple har-
monics (formants), some of which may not be amplified
and some of which may be amplified too much. These
frequency components that are too loud introduce a new
kind of distortion. Many of the latest tricks in hearing aids
are designed to compensate for this aspect of hearing. But
because one can never be certain of what a new person’s
voice will sound like, in practice, this is very difficult. To
summarize the problem, when hearing aids compensate
for loss of sensitivity, they may introduce distortion by
amplifying irrelevant aspects of the signal.
Imagine a speaker saying an unexpected sentence, such as
“The Jade Rabbit landed on the moon.” Unless you have
been following the Chinese space agency’s moon explo-
ration program, this sentence might not make sense to
you at first. In the case of our hypothetical teacher, con-
text may not lend much of a hand to help Ms. Monroe
figure out what her student just said about a jade rab-
bit. As we have emphasized in this chapter, speech takes
place over time. It takes a small amount of time to say
the word rabbit, and coarticulation helps listeners decode
sounds. However, if there is noise, either natural or dis-
tortion produced by hearing aids, comprehension of the
words and sentence may be slowed to a point at which the
person cannot make intelligible sense of the words. Amid
noise, hearing-impaired individuals have more difficulty
following the stream of speech, because they are missing
cues that are present when there is less noise or that are
always available to those with normal hearing. The noise
may interfere with the signal such that syllables within
words are less clearly separated in time. Thus, people
with hearing loss have difficulty understanding speech in
noise (Henry, Turner, & Behrens, 2005). That is, because
speech perception is so complex, and the processes must
be achieved so quickly, those with hearing loss may not
have sufficient time to process speech stimuli, even when
they are hearing sounds amplified with their hearing aids.
This problem may be even more profound in older adults
who develop hearing loss later in life (Anderson, White-
Schwoch, Parbery-Clark, & Kraus, 2013).
The situation for setting up hearing aids becomes even
more complicated when different languages are con-
sidered. Different languages have different phoneme
structures, leading to the differences in development of
phoneme perception that we have already discussed earlier
in the chapter. Current methods of programming hearing
aids can allow the aids to be adjusted to be sensitive to
some of these differences in phonemes. For example,
Slavic language speakers need hearing aids programmed
to boost frequencies in the 3,000 to 3,500 Hz range when
compared with hearing aids for English speakers, whereas
Chinese speakers need their hearing aids to boost the
amplitude of frequencies more in the range of 2,700 to
3,000 Hz (Chasin, 2011).
However, capturing phonemes does not reveal all of the
differences between languages that occur at the word and
sentence levels. For example, English has a subject-verb-
object basic word order for sentences. Other languages,
such as French, Spanish, and Tamil, have a subject-object-verb
word order. We often reduce the intensity of the speech
sounds at the end of our sentences, but if that end word
is a verb, and you have hearing loss, then a subject-object-
verb word order would cause you to have more trouble
understanding what is being said than for languages with
word orders like English does. In one study, Chasin (2012)
found that for these subject-object-verb word order lan-
guages you need to change the programming so that the
ends of sentences are selectively amplified relative to lan-
guages with other word orders.
Hearing aids should also be sensitive to other differences
as well, such as “tone,” seen in languages such as Mandarin
Chinese, other Chinese languages, and Vietnamese (and
also some West African languages). English is a language
that forms its phonemes by the structure, not the pitch,
of the sound (see Chapter 13 for more on what pitch is).
Chinese and Vietnamese use pitch to denote differences
in phonemes and therefore differences in meaning. Let
us look at vowels. As mentioned earlier, it is the ratio
of the formants that plays a key role in determining the
phoneme, whether an “a” or an “e,” in English, not the
pitch at which the sound is spoken. In Chinese, different
pitches can indicate different phonemes. Current hearing
aid technology and even cochlear implants do not repro-
duce pitch as well as they do consonants. For example,
Wong and Wong (2004) found that Cantonese children
with cochlear implants had difficulty discriminating the
tones they needed to understand their language.
Given that hearing aids are of limited help in many lan-
guages, there are some general recommendations given to
help communicating with hearing-impaired individuals.
For example, the speaker can stand close and face-to-face
to the hearing-impaired listener. In addition, the speaker
should speak slowly and distinctly. It also helps to use
gestures and posture to help convey what is being said.
Eliminating distracting sounds can also be very important
364 Sensation and Perception
to communicating to a hearing-impaired person (Huang &
Tang, 2010).
To summarize, individuals with hearing impairments
choose to wear hearing aids to help them understand
speech. However, evidence suggests that some difficul-
ties in speech perception are actually introduced by the
pattern of amplification and suppression from the hear-
ing aids themselves. In essence, the combination of the
hearing aid and the impaired cochlea results in a num-
ber of ways in which speech perception can be affected
adversely. Because the signal going into the auditory
nerve is impaired, it requires the auditory cortex to work
harder to decode the signal, leading to impaired percep-
tion amid noise or if the individual is distracted (Leek &
Molis, 2009).
The solution is to design hearing aids with faster and
more efficient processing with greater sensitivity to dif-
ferent languages, words, and sentences. But the exact
nature of that processing will require research to deter-
mine what features of the human auditory system need
tweaking in each individual patient. Although appropriate
amplification may address the problem of impaired hear-
ing in general, it may not be enough to compensate for the
slowed temporal processing and distortion prevalent in
people with moderate sensorineural hearing loss (Leek &
Molis, 2009). As the science of hearing aids continues to
improve, patients can expect to find hearing aids with a
greater range of internal programs that adjust the acous-
tics of the situation automatically depending on ambient
conditions. Thus, in a noisy environment, hearing aids will
focus on amplifying sounds in the frequencies commonly
heard in speech. In addition, loud sounds will generate
a quick attenuation of the amplification of those sounds,
such that coughs or squeaking chairs lead to less inter-
ference with speech perception. When the person moves
to another environment, say a quiet room at home, the
hearing aid will adjust to that room and inhibit only some
high-frequency sounds, such as the hum of an air con-
ditioner or the buzz of a refrigerator, leaving the person
maximally able to converse with his or her family. Even
with hearing aids, Ms. Monroe may never be able to pick
up speech in a noisy classroom as well as her nonimpaired
colleagues, but hearing aids are evolving quickly to maxi-
mize speech perception.
APPLICATION: Hey Siri, or Are You Cortana?
Computer Speech Recognition
“Hey Cortana, tell me a joke.”
“I wondered why the baseball was getting bigger.
Then it hit me.”
“Alexa, who’s your favorite Beatle?”
“John, Paul, George, or Ringo.”
Who are Cortana and Alexa? Cortana is the name giv-
en to the search function on Windows machines, and Cor-
tana has the ability to both respond to verbal commands
and “speak” its responses. Alexa is the name used to talk to
the Amazon Echo, a home device that can play music, set
times, control lights, and perform an increasing number of
other home functions, all by speaking to it (Figure 12.21
shows one such device). So the conversations above are
possible short conversations one can have with a computer.
In recent years, there has been an explosion of devices
that allow you to talk to them. In addition to these devices,
there is “Siri” for Apple devices, and you can say “OK,
Google” to activate speech recognition on Android phones.
Originally you had to press a button to start the device
listening, but now you can use a wake-up word such as
“Hey Siri” to activate the application. In other domains,
speech recognition is also being developed. Many cars
now have speech recognition systems that allow you to
tell your car’s computer where you want to go without
taking your eyes off the road. Thus, now, you can talk to
your phone, tablet, laptop, or car. Speech recognition can
also be found in military applications.
We are not far at all from the old Star Trek “Computer,
tell me whatever I need to know to further the plot.” Even
back then, the creators of Star Trek recognized the need for
a wake-up word so that the device knows when you are
talking to it, and addressing the computer as “Computer”
was their way, though as you see, the actual trend is to
give our computers women’s names. As with so much of
365 Chapter 12: Speech Perception
perception, the current speech recognition abilities of these
devices seem easy, and we will soon take for granted these
abilities, but years of research understanding speech per-
ception processes lay behind these remarkable new tech-
nologies. In fact, research on speech recognition goes back
to the 1930s at the remarkable Bell Laboratories (Juang &
Rabiner, 2005). Thus, there is a lot of work behind these
neat little devices that must solve many of the same issues
that our perceptual system does to understand speech. Let
us look at a bit of it.
As discussed earlier, there is a lot of ambiguity in the
speech stimulus. Coarticulation and other features make
for a lot of variations. Whatever device is listening to
you must be able to decode those ambiguities to cor-
rectly interpret what you are saying. The problem is the
same for the device as it is for our brain. It is clear that
a great deal of progress has been made in understanding
our speech, but these devices are certainly not perfect.
Words that are not commonly used and those that have
multiple pronunciations are often more confusable. This
is true for us, but to a much greater degree for speech
recognition systems. Try asking your device, “Do I have
a dactylion?” You might not know what the word means
(it’s an anatomical marker at the tip of the middle finger),
but you could repeat the word back. One speech recog-
nition system responded with “Do I have a deck tillian?”
The last part is not even a word. There are also features
of speech that can confuse these systems. For example, if
you are speaking along and use some sort of nonspeech
sounds, like the ever present “uh,” your speech recognition
system might struggle to get what was said correct. Yet,
these sorts of nonspeech sounds rarely impede our own
understanding; just listen to your professor (Goldwater,
Jurafsky, & Manning, 2010).
If you watch your voice recognition system as you talk,
some of them show their current estimate of what you say
as you go along. You can see several guesses for a partic-
ular word before it finalizes on what it thinks you said.
These systems try to consider linguistic context, just as we
do, to disambiguate what is being said by you. One of the
ways that these systems work is to use an expectation of
word order to figure out your sentence. As was mentioned
in the Exploration section of the chapter, English uses a
subject-verb-object word order, and speech recognition sys-
tems for English expect that word order. So, mixing syntax
can confuse these systems much more than us. For example,
say to your device, as the Star Wars character Yoda might,
“Red the apple is” and see what you get. Cortana recently
replied, “Where did the apolis?” Cortana was confused and
did not make sense. Our ability to respond to context is
much more fluid than these systems that work best with
simple, expected grammatical constructions.
Another issue for these systems is accents. Although we may
struggle with determining what people with second-language
accents or regional accents say, mostly we can figure them out,
even if we occasionally have to ask for clarification. However,
speech recognition systems still struggle with accents despite
efforts to improve them (Hansen & Arslen, 1995). So, despite
the great advances in trying to figure out the words we are say-
ing, there is progress to be made in computer voice recognition
when words are pronounced in unusual ways (Abdelaziz &
Kolossa, 2016; Schädler, Warzybok, Hochmuth, & Kollmeier,
2015). Again, the issues speech recognition systems face are
the same ones we face in understanding language.
Think of the phonemic restoration effect. Recall that the
phonemic restoration effect occurs when expected words are
removed from the speech signal. Our own speech recogni-
tion is so efficient that we can remove a significant amount of
the speech stimulus and still understand what is being said to
us. This ability is vital as we are rarely in a completely quiet
environment. Other sounds occur and can cover or mask
another person’s speech. Think of a party with loud music and
lots of conversations or the situation created in the cocktail
FIGURE 12.21 The Amazon Echo Speech Interface
Boston G
lobe/G
etty Im
ages
366 Sensation and Perception
party effect. We still can follow along with what is being said
in our conversation, despite the noise around us. A computer
speech recognition system must be able to ultimately perform
at the same level in noisy environments, but they are not there
yet. Dai and Soon (2013) developed an algorithm that tries
to simulate human abilities to extract speech sounds out of
other noise. The algorithm tries to examine the temporal and
other characteristics of the sound to determine what is speech
and what is not speech. However, this aspect of speech recog-
nition cannot yet match what any person can do.
Speech recognition has advanced greatly in recent years,
but there is still progress to be made. Although these
systems use computers and complicated mathematics to
solve their problems, they are the same problems that
our auditory systems have to solve with tissue and nerve
fibers—that is, to understand what is being said every
day. Knowledge of human speech perception aids these
researchers in their work, and it is not too much to expect
that the solutions for computer speech recognition will
resemble how our brains accomplish the same task.
CHAPTER SUMMARY
12.1
Discuss the complex process of speech percep-
tion and speech production with regard to the
speech stimulus.
Speech perception is the most critical aspect of auditory
perception for human beings. Perceptual processes begin
with a stimulus in the environment. In the case of human
speech perception, that stimulus is a voice. The human
vocal tract produces both consonant and vowel sounds,
which are the bases of the sounds used in human language.
Formants are the frequency bands with higher amplitudes
among the harmonics of a vowel sound. Each individual
vowel sound has a specific pattern of formants. The place
of articulation is the point along the vocal tract at which the
airflow is constricted. The manner of articulation is how that
restriction occurs. Voicing refers to whether the vocal cords
are vibrating or not. Phonemes are the basic units of sound
in human language. The International Phonetic Alphabet is
an alphabetic convention that provides a unique symbol for
each and every phoneme in use in human languages.
12.2
Sketch the mechanisms our speech perception
system uses to extract coherent speech from the
speech signal.
A problem for our speech perception systems is to iden-
tify what is constant in the speech signal. Our auditory
system uses a number of mechanisms to identify pho-
nemes and understand speech. Coarticulation is the
phenomenon in which one phoneme affects the acoustic
properties of subsequent phonemes. Our auditory sys-
tems pick up on coarticulation and use it to understand
speech. Categorical perception is our perception of dif-
ferent acoustic stimuli as being identical phonemes, up to
a point at which our perception flips to perceive another
phoneme. Voicing-onset time is the production of certain
consonants (called stop consonants) in which there is a
difference between the first sound of the phoneme and
the movement of the vocal cords. The movement of the
vocal cords is called voicing. In the McGurk effect, par-
ticipants are shown a video of a person’s mouth saying
monosyllabic sounds, such as “ba,” “da,” and “tha.”
However, the audio component does not always match
what the speaker’s mouth was saying when the syllables
were recorded. The results show that the visual input
affects what people report hearing. Word segmentation is
the ability of speakers of a language to correctly perceive
boundaries between words. The phonemic restoration
effect is an illusion in which participants hear sounds that
are masked by white noise, but context makes the missing
sounds apparent.
12.3
Contrast the different types of theories of
speech perception, noting their similarities and
differences.
General-mechanism theories of speech perception claim
that the mechanisms for speech perception are the same
as the mechanisms for auditory perception in general.
Special-mechanism theories claim that the mechanisms
for speech perception are distinct and unique relative to
the mechanisms for auditory perception in general. The
motor theory of speech perception argues for a special
mechanism that makes attributes about sound from the
movements of the vocal tract.
12.4
Diagram the areas of the brain involved in
speech perception and what happens when they
are damaged.
Perceptual narrowing is the developmental process
whereby regularly experienced phonemes are homed
Chapter 12: Speech Perception 367
in on, with the simultaneous diminishing of the ability to
discriminate unfamiliar phonemes. Broca’s area is in the
left frontal lobe and is an important area in the produc-
tion of speech. Wernicke’s area is located in areas of the
brain associated with the auditory system in the tempo-
ral lobe. Aphasia is an impairment in language produc-
tion or comprehension brought about by neurological
damage. Broca’s aphasia is a form of aphasia resulting
from damage to Broca’s area. In Broca’s aphasia, the
deficit is in language production. Wernicke’s aphasia is
a form of aphasia resulting from damage to Wernicke’s
area. In Wernicke’s aphasia, the deficit is in language
comprehension. The voice area is located in the superior
temporal sulcus and responds to the sound of the human
voice. In a fascinating study by Pasley et al. (2012), a com-
puter program was able to determine what a speaker was
saying based only on the activity of the speaker’s auditory
cortex. Speech perception in hearing-impaired individu-
als may be a particularly difficult problem for hearing aids
to address. Amplification of higher harmonics may distort
the speech signal, requiring the auditory systems of hear-
ing-impaired people to slow down in their interpretation
of human speech signals. Future hearing aids need to be
designed with this problem in mind.
REVIEW QUESTIONS
1. What are the important parts of the vocal tract? How
are consonants and vowels produced in our vocal
tract?
2. What is meant by the terms place of articulation,
manner of articulation, and voicing?
3. What is coarticulation? How does its perception
affect our understanding of speech?
4. What is categorical perception? How does it affect
our perception of speech? What is its likely function?
5. What is the McGurk effect? How does it show the
relation between vision and audition with respect to
speech perception?
6. What is phonemic restoration? How does it demon-
strate top-down processing in speech perception?
7. What is the difference between general-mechanism
theories of speech perception and special-mecha-
nism theories of speech perception? Which theory
offers a better explanation of speech perception?
What is the motor theory of speech perception?
8. What is perceptual narrowing? How does it help
infants improve their speech perception? What
problems can develop from it?
9. What areas of the brain are associated with speech
production and language comprehension? What
other areas of the brain may be involved in speech
perception?
10. Why is speech perception difficult for those who
wear hearing aids? What aspect of hearing-aid tech-
nology needs to be improved to help those with mild
to medium hearing impairments?
PONDER FURTHER
1. Outline the several ways that the speech stimulus is
ambiguous. Given that the speech stimulus is ambig-
uous, discuss how perceptual mechanisms work to
make speech perception work so well.
2. Examine how speech perception takes advantage of
other features of auditory perception and what fea-
tures of speech perception might be unique.
KEY TERMS
Aphasia, 359
Broca’s aphasia, 359
Broca’s area, 359
Categorical perception, 349
Coarticulation, 348
Consonants, 343
Formants, 343
General-mechanism theories, 355
International Phonetic Alphabet, 346
Larynx (voice box), 343
Manner of articulation, 344
McGurk effect, 351
Sensation and Perception368
Motor theory of speech
perception, 355
Perceptual narrowing, 357
Pharynx, 343
Phonemes, 345
Phonemic restoration effect, 353
Place of articulation, 344
Special-mechanism theories, 355
Trachea (windpipe), 343
Unvoiced consonant, 344
Uvula, 343
Voice area, 361
Voiced consonant, 344
Voicing, 344
Voicing-onset time, 349
Vowels, 343
Wernicke’s aphasia, 360
Wernicke’s area, 359
Word segmentation, 353
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
12.1 Discuss the complex process of speech perception and speech
production with regard to the speech stimulus.
Speech Perception: Cognitive Foundations and Cortical
Implementation
Auditory Demonstrations
Study Illuminates How Babies Learn to Speak
12.2 Sketch the mechanisms our speech perception system uses to
extract coherent speech from the speech signal.
Speech Perception as a Multimodal Phenomenon
The Time Course of Interpretation in Speech
Comprehension
Sense of Touch Can Help Hearing, Study Says
What’s He Saying? “Bahh” or “Fahh”? A Brain Mystery
12.3 Contrast the different types of theories of speech perception,
noting their similarities and differences.
How Does the Brain Decode Speech?
12.4 Diagram the areas of the brain involved in speech perception
and what happens when they are damaged.
Wernicke’s Aphasia
Broca’s Aphasia
Gusto/Science Source
13Music Perception
florin1961 (Florin Cnejevici)/Alamy Stock Photo
LEARNING OBJECTIVES
13.1 Explain how frequency is related to pitch, chroma, and the octave.
13.2
Summarize the basic neuroscience of music, including how training
and experience can affect the representation of music in the brain.
13.3 Discuss how learning and culture affect music perception.
INTRODUCTION
Wherever you travel, you will find music. It may sound very different from the music you
are accustomed to hearing, but you will recognize it instantly as music. In Kurdistan, we
find a unique culture of music featuring such instruments as the tanbur (a fretted string
instrument), the qernête (a double-reed wind instrument), and the şimşal (a flutelike
instrument) (Figure 13.1). Although most of you may never have heard of these instru-
ments and may never have heard Kurdish music before, you would instantly recognize
them as musical instruments, and you might even like Kurdish music (see ISLE 13.1 for
an example of Kurdish music).
ISLE EXERCISES
13.1 Kurdish Music Example
13.2 Javanese Gamelan
Music Example
13.3 Ancient Greek Music
13.4 35,000-Year-Old Flute
13.5 Is This Music?
13.6 The Octave and
Tone Similarity
13.7 Pentatonic Music
13.8 Meter and Beat
13.9 Bolero Clip
13.10 Attack and Decay
13.11 Examples of Melody
13.12 Types of Scales
13.13 Gestalt Principles
Review
13.14 Gestalt Principle:
Proximity: Bach’s Partita
No. 3 in E major
13.15 A Shave and a Haircut
13.16 Cross-Modal
Matchings as a
Simulation of Synesthesia
13.17. Indian Raga Music
Example
13.18 Bach’s Violin
Partita No. 2 in D minor
13.19 Shepard Tones
13.20 Octave Illusion
13.21 Scale Illusion
13.22 Tritone Paradox
FIGURE 13.1 A Tanbur
Man playing a tanbur, a traditional Kurdish instrument.
©
A
urora Photos/A
lam
y
372 Sensation and Perception
Better known in the United States, though further from our
own musical tradition, is Javanese gamelan. Gamelan music uses
a different scale system from our own, so it sounds very different.
The slendro scale is a pentatonic (five-note) scale using intervals
not used in Western music. Despite this difference, we certainly
recognize gamelan as music (listen to ISLE 13.2 for examples of
Javanese gamelan music). Figure 13.2 shows the xylophone-like
instruments that are used in gamelan music.
Within our own culture, we make the most of differences in
musical tradition. Many of you may debate the relative merits of
East Coast hip-hop and snap music, or funk metal versus nu metal
(Figure 13.3). There is, however, continuity in our Western music
tradition. All of these varieties of music, from classical to jazz to
country to gangsta rap, use the basic Western music system, even
if the performers violate Western norms of dress and body art. In
this manner, most variants of rock music have more in common
with the orchestral music tradition than fans of either style might
care to admit. For example, both Mozart and gangsta rap use the
same basic Western scale system, playing the same notes, and in mostly the
same keys. One can contrast either style of music with the aforementioned
gamelan music, which uses a completely different scale system.
Music also has a long history. Wherever we find written records of past
civilizations, we find descriptions of musical events. For example, the ancient
Greeks left numerous written descriptions of music, as well as many illustra-
tions of musical instruments. The story of Orpheus is as poignant today as
it was then, because we can relate to the longing power of music, just as the
Greeks did when the story was new. In the story, Orpheus uses music to win
his love back from the dead, only to lose her again. Greeks also used a form of
written music. It consisted of using certain letters to represent pitch. Although
precious few examples of ancient Greek music in written form remain today,
there are a few preserved parchments that allow us to re-create music from
almost 2,000 years ago. The longest single written musical piece from this
time period is the Seikilos song, written in approximately 200 CE. It was prob-
ably not a “hit” at the time, but it is the longest segment of ancient Greek
music that can be played now, thanks to its preservation in written form. (See
Cartwright, 2013, or ISLE 13.3.)
Traveling millennia further back in time, there are no written records of
music notation. But there is a fine archaeological record that demonstrates
musical instruments being made far back into the Stone Age. Wind, percussion,
and string instruments all date back this far into antiquity. The oldest known
instruments are flutes made from the bones of birds, some of which date back
as far as 35,000 years (Conard, Malina, & Münzel, 2009). Figure 13.4 shows such flutes.
We can wonder what a prehistoric man or woman might have played on one of these flutes,
looking across a primordial forest landscape from the mouth of a cave, but we will never
know. However, reconstructions of these flutes show that notes representing octave equiva-
lence were present. You can hear a reconstruction of such a flute played in ISLE 13.4. This
suggests that music has been a part of human culture for as long as humans have had culture.
We can also ask this question: What is music? A dictionary might define music as an
art form based on sound. But how do we know what sounds are art and what sounds are,
well, just sounds? On one hand, when we hear Rihanna singing “Love on the Brain” or the
Cleveland Orchestra playing Schubert’s Symphony No. 2, there is no disagreement—we
are hearing music. And when we hear the sound of a washing machine whirring or the
sound of landscapers mowing lawns, we know that such sounds are not music. However,
ISLE 13.1
Kurdish Music Example
ISLE 13.2
Javanese Gamelan
Music Example
©
iS
to
ck
ph
ot
o.
co
m
/M
ith
ril
FIGURE 13.2 Different Musical Cultures
Gamelan musical instruments.
©
iS
to
ck
ph
ot
o.
co
m
/c
re
o7
7
FIGURE 13.3 Popular Music
Rock music is popular throughout the world.
ISLE 13.3
Ancient Greek Music
373 Chapter 13: Music Perception
some artists stretch the limits of music. For example, in John Cage’s famous
piece 4'33″, audiences “listen” to a performer doing absolutely nothing for
4 minutes and 33 seconds. The music is the rustle of people in their seats and the
occasional embarrassed cough. Is this music? That depends on your perspective.
Certainly, Cage wanted us to think of music in a whole new way. And what
about the following? The Melbourne Symphony Orchestra played a piece of
music in which every member of the orchestra was playing beer bottles instead
of his or her normal musical instrument. Many of you may have also heard the
typewriter symphony, which went viral on YouTube in 2012. You can see both
of these pieces performed in ISLE 13.5. Are these pieces satire, or are they actu-
ally music? Finally, we can also consider whether natural sounds are music. We
may find many natural sounds beautiful, from birds singing to waves lapping to
the wind whistling. But is birdsong music? What about the sounds of waves lap-
ping on the sand on a peaceful beach? Most of us would hesitate to classify this
as music, even though the sounds may be decidedly pleasing to listen to. Thus,
it may actually be difficult to come up with a definition of music that satisfies
all of its boundary conditions. But we will try to define music as follows: Music
is ordered sound made and perceived by human beings, created in meaningful
patterns (Tan, Pfordresher, & Harre, 2010).
The last introductory question concerns the function of music. Why do we do
it? Many scholars from many different disciplines have sought to determine the
function of music for human beings, given the universality of music to the human
species. Some have argued that this implies that music evolved, in the biological
sense of the word, and therefore must have a function. What function might music
serve in evolution? Some have argued that it served a sexual selection function. A
highly musical person was likely fit, with musical ability signaling both good health and intel-
ligence. In this view, music is something of a peacock’s tail: Only a fit bird can afford such an
extravagant tail. By analogy, only a fit person has the time to develop musical talent. Another
evolutionary view is that music serves to bind people together in coherent groups. Singing
and dancing brought people together and helped them find common purpose. Of course, it
is also possible that music served no evolutionary function and is just a happy by-product of
the evolution of auditory processing in humans in general. The answers to these questions are
beyond the scope of this book. We now turn to issues in sensation and perception.
THE ACOUSTICS OF MUSIC
13.1 Explain how frequency is related to pitch, chroma, and the octave.
Pitch, Chroma, and the Octave
In Chapter 10, we described the relation between pitch and frequency. As frequency
increases, we hear sounds at higher and higher pitches. As frequency decreases, we hear
sounds at lower and lower pitches. Human beings can hear sounds between 20 and 20,000
Hz, but the range that is used in music is more restricted. Indeed, music is generally played
in the range of only up to a maximum of about 5,000 Hz. A piano, for example, has its low-
est note tuned at 27.5 Hz and its highest note tuned at 4,186 Hz (Figure 13.5). No Western
instruments play lower than 27.5 Hz, and only a few Western instruments play higher than
the piano does (e.g., the piccolo). In terms of the range at which humans can sing, the range
is even more restricted. A human bass voice may get as low as 75 Hz, and a human soprano
may get as high as 1,300 Hz. Thus, the notes used in music fall within a subrange of the full
range of human hearing.
ISLE 13.4
35,000-Year-Old Flute
FIGURE 13.4 Paleolithic Musical
Instruments (Conard et al., 2009)
Bone flutes dating to at least 30,000 years ago.
ISLE 13.5
Is This Music?
Music: ordered sound made
and perceived by human
beings, created in meaningful
patterns
374 Sensation and Perception
Although the fundamental
frequency of musical notes seldom
exceeds 5,000 Hz, harmonics
typically range higher than this.
Therefore, higher frequencies are
important for music perception.
Remember that natural sounds,
including those of all voices and
musical instruments, have higher
harmonics. That means that in
addition to the pitch we hear,
there are other sounds present
at higher frequencies. These higher harmonics contribute to the experience of timbre. Thus,
having recording equipment that records at higher frequencies will preserve the timbre (to be
reviewed shortly) of voices and instruments. Even then, we seldom use the very high frequen-
cies for music—a good thing, as most of us lose our hearing above 10,000 Hz anyway by the
time we are in our 30s or 40s.
The Western orchestra uses a range of instruments, some of which are designed to play
lower notes and others designed to play higher notes. Among the string instruments, double
basses play at the lower end of the musical range of pitches, whereas violins reach to some
of the highest pitches used in music. Thus, in a string orchestra, without wind or brass
instruments, the violins will play the higher notes, the violas and cellos will play intermedi-
ate pitches, and the double basses will play the lower notes. Among the brass instruments,
tubas and trombones play at lower pitches, whereas trumpets play at higher pitches. Among
woodwinds, bassoons play at the lower end of the pitch range, whereas the piccolo has the
highest notes of any instrument used in Western music. Figure 13.6 shows the frequency
ranges of many common Western musical instruments.
36
9.
99
41
5.
30
34
.6
48
38
.8
91
46
.2
69
51
.9
13
58
.2
70
69
.2
69
77
.7
82
92
.4
99
10
3.
83
11
6.
54
13
8.
59
15
5.
56
18
5.
00
20
7.
65
23
3.
08
27
7.
18
31
1.
13
46
6.
16
55
4.
37
62
2.
25
73
9.
99
83
0.
61
93
2.
33
11
08
.7
12
44
.5
14
80
.1
16
61
.2
18
64
.7
22
17
.5
24
89
.0
29
60
.0
33
22
.4
37
29
.3
29
.1
35
27
.5
00
A
0
Fr
eq
ue
nc
y
(H
z)
N
ot
e
B
0
30
.8
63
C1
32
.7
03
D
1
36
.7
08
E1
41
.2
03
F1
43
.6
54
G
1
48
.9
99
A
1
55
.0
00
B
1
61
.7
35
C2
65
.4
06
D
2
73
.4
16
E2
82
.4
07
F2
87
.3
07
G
2
97
.9
99
A
2
11
0.
00
B
2
12
3.
47
C3
13
0.
81
D
3
14
6.
83
E3
16
4.
81
F3
17
4.
61
G
3
19
6.
00
A
3
22
0.
00
B
3
24
6.
94
C4
26
1.
63
D
4
29
3.
67
E4
32
9.
63
F4
34
9.
23
G
4
39
2.
00
A
4
44
0.
00
B
4
49
3.
88
C5
52
3.
25
D
5
58
7.
33
E5
65
9.
26
F5
69
8.
46
G
5
78
3.
99
A
5
88
0.
00
B
5
98
7.
77
C6
10
46
.5
D
6
11
74
.7
E6
13
18
.5
F6
13
96
.9
G
6
15
68
.0
A
6
17
60
.0
B
6
19
75
.5
C7
20
93
.0
D
7
23
49
.3
E7
26
37
.0
F7
27
93
.0
G
7
31
36
.0
A
7
35
20
.0
B
7
39
51
.1
C8
41
86
.0
FIGURE 13.5 Piano Keyboard
A piano’s notes start at 27.5 Hz at the far left and go up to 4,186 Hz at the far right. Most music is played
within this range.
A
27
.5
00
B
30
.8
63
C
32
.7
03
D
36
.7
08
E
41
.2
03
F
43
.6
54
G
48
.9
99
A
55
.0
00
B
61
.7
35
C
65
.4
06
D
73
.4
16
E
82
.4
07
F
87
.3
07
G
97
.9
99
A
11
0.
00
B
12
3.
47
C
13
0.
81
D
14
6.
83
E
16
4.
81
F
17
4.
61
G
19
6.
00
A
22
0.
00
B
24
6.
94
C
26
1.
63
M
id
dl
e
C
D
29
3.
66
E
32
9.
63
F
34
9.
23
G
39
2.
00
A
44
0.
00
A
–4
40
B
49
3.
88
C
52
3.
25
D
58
7.
33
E
65
9.
26
F
69
8.
46
G
78
3.
99
A
88
0.
00
B
98
7.
77
C
10
46
.5
D
11
74
.7
E
13
18
.5
F
13
96
.9
G
15
68
.0
A
17
60
.0
B
19
75
.5
C
20
93
.0
D
23
49
.3
E
26
37
.0
F
27
93
.0
G
31
36
.0
A
35
20
.0
B
39
51
.1
C
41
86
.0
29
.1
35
34
.6
48
38
.8
91
69
.2
69
77
.7
82
13
8.
59
15
5.
56
27
7.
18
31
1.
13
55
4.
37
62
2.
25
11
08
.7
12
44
.5
22
17
.5
24
89
.0
46
.2
49
51
.9
13
58
.2
70
92
.4
99
10
3.
83
11
6.
54
18
5.
00
20
7.
65
23
3.
08
36
9.
99
41
5.
30
46
6.
16
73
9.
99
83
0.
61
93
2.
33
14
80
.0
16
61
.2
18
64
.7
29
60
.0
33
22
.4
37
29
.3
Timpani
Trumpet
Flute
Chimes
Guitar
Bass
FIGURE 13.6 The
Symphony Orchestra:
Frequency and Pitch
This diagram shows several
instruments and their
frequency ranges.
375 Chapter 13: Music Perception
The Octave
Pitches get higher as frequencies go up, but there is another important dimension of
pitch that is highly relevant to music: the octave. The octave is the interval between
one note and a note with either double the frequency or half the frequency of that note.
This is a physical definition: A frequency of 200 Hz has octaves of 100 Hz below it and
400 Hz above it. Psychologically, we hear similarities between these doubled or halved
frequencies. In musical terms, we refer to them by the same note name, but at different
octaves. Thus, even though notes at 200 and 220 Hz are more similar in pitch, we hear
notes at 200 and 400 Hz as being alike in a way that notes at 200 and 220 Hz are not
(to hear this for yourself, go to ISLE 13.6).
We hear notes that are an octave apart as similar in a fundamental
way. That is, there are perceived similarities between sounds that are
an octave apart from one another. Notes that are one octave apart are
said to be of the same chroma. This concept of an octave is present
in all Western and non-Western musical traditions, including, as we
mentioned earlier, in the functioning of prehistoric musical instru-
ments. When we hear two notes that are an octave apart, they sound
similar to us, despite their difference in pitch. On a piano keyboard,
we label notes an octave apart with the same name. Thus, middle C
has a frequency of 261.6 Hz, and the C one octave above it has a
frequency of 523.3 Hz, or approximately double that frequency. The
next C is at 1,046.5 Hz. Any musician recognizes that a scale begins
at one note and continues to the same note at the next octave.
Think now about a piano keyboard and examine the illustra-
tion in Figure 13.5. We see a pattern of white and black keys. You
will see the white keys labeled as being one of seven chromas of
notes, C, D, E, F, G, A, and B, and then the pattern repeats back to
C. This pattern repeats across the piano keyboard. Each C shares
a feature of sound in common with other C’s, but not with other
notes. Similarly, each G shares a feature of sound in common with
other G’s, but not with other notes. This feature that these notes
share in common is that they sound similar to us, and we call this
feature chroma. For example, middle C (262 Hz) is closer in fre-
quency to the D just above it (294 Hz), but it sounds more similar
to the C in the next octave (523 Hz). This similarity of chroma
from one octave to the next is represented by the pitch helix shown in Figure 13.7. As
one goes up the helix, pitches get progressively higher, but the twists in the helix indi-
cate the octave equivalence across similar notes.
Returning to the piano keyboard, we also have the black keys, which represent
“sharps” and “flats” in musical terms. These keys are at frequencies between the white
keys to either side. Thus, the black key between middle C and the D next to it plays at
a frequency of 277 Hz, approximately halfway between the frequencies of the C and
the D. In musical notation, this black key can be called either C-sharp or D-flat. The
black key between the D and the E can be called either D-sharp or E-flat. Whether the
note is called by its sharp name or its flat name depends on the musical context, but
the sound is the same. When we add the sharps and flats to our musical hierarchy, we
have 12 notes in an octave, as we ascend from one note to the same note an octave
higher. Each adjacent note is sometimes called a semitone. There are 12 semitones in
an octave in Western music. In music, when every note, including the sharps and flats,
is played between one octave and the next (i.e., every semitone), this is called the chro-
matic scale. This would mean playing a 13-note scale, starting, for example, with C and
including and ending with the C one octave above it. Almost all Western instruments
ISLE 13.6
The Octave and Tone Similarity
Octave: the interval between
one note and a note with
either double the frequency or
half the frequency of that note
Chroma: the subjective
quality of a pitch; we judge
sounds an octave apart to be
of the same chroma
Semitones: the 12 equivalent
intervals or notes within each
octave
increasin
g fre
que
nc
y
E4F4
G4
G3
G2
G1
F3
F2
F1
A1
Aligned notes have
same chroma
Color
indicates
tone chroma
A2
A3
A4
A5
E3
E2
E1
B1
C1
D1
C2
Tone
heightD2
C3
D3
C4
C5
D4
B2
B3
B4
B5
FIGURE 13.7 Pitch Helix (Shepard, 1982)
The pitch helix shows the relation of both pitch and
frequency and of pitch similarity across octaves.
376 Sensation and Perception
allow musicians to play all 12 notes of the octave. Exceptions include some
kinds of harps and recorders.
The other feature of the Western musical tradition is the use of an
equal-temperament scale. This means that every adjacent note has an
identical frequency ratio. The absolute difference between adjacent notes
increases as one gets higher in frequency, but the ratio matters for per-
ception. In this way, we perceive the difference between each successive
semitone as equivalent in terms of difference in pitch to the one before it.
This demonstrates Weber’s law. What matters in perception is the ratio, not
the absolute difference. One advantage of the equal-temperament system is
that any melody can be played starting on any particular note.
In most Western music, the differences in frequency between each note
are well established and do not vary (this may change in some music, such
as a cappella choirs). When musicians tune their instruments, they tune them
so that their C’s (or, usually, A above middle C) all match at the same pitch
or frequency. A piano or tuning whistle often provides this frequency. This
organization has become standardized across Western music. Thus, a violinist
in California and a cello player in Zurich, Switzerland, will usually agree that
the A above middle C is tuned to 440 Hz (as long as they are not specifically
tuning to standards from centuries past, as some orchestras do).
Traditional Chinese music uses a different scale system. Instead of the
diatonic (eight-note) scale used in Western music (C, D, E, F, G, A, B, and C),
Chinese music uses only a five-note (pentatonic) scale. In addition, the
notes are not tuned according to an equal-temperament system, so that one
cannot play the same melody starting on a different note, because the ratios
between successive notes are not the same. Some early 20th-century clas-
sical music, in trying to defy convention, essentially used pentatonic scales
as well. Figure 13.8 shows a woman playing a guqin, a traditional Chinese
instrument. The guqin is a seven-string instrument similar to a zither. Traditionally, it
was tuned to the Chinese scale known as zheng diao, a pentatonic scale, although most
instrumentalists use Western-based notes today.
Westerners typically find traditional Chinese music a bit odd because the notes do
not map directly onto the notes in our scale, which we have become so accustomed to
hearing. Some Western forms of music use pentatonic scales, but these versions use the
notes or pitches used in the equal-temperament scale system. These pentatonic tradi-
tions include Celtic folk music, some forms of West African music, and the American
blues tradition. The five-note tradition makes improvisation, a hallmark of both Celtic
music and American blues, easier. ISLE 13.7 gives examples of both Celtic music and
improvisation in the American blues tradition.
To summarize, pitch is the psychological experience of frequency. As frequency gets
higher, we hear the sound at a higher pitch. Musical notes are set at particular frequencies,
and the relations between notes in Western music follow an equal-temperament system.
TEST YOUR KNOWLEDGE
1. What is meant by the term chroma? How is chroma related to the pitch helix?
2. What is meant by the term semitone? What is an equal-temperament scale?
Consonance and Dissonance
In most music, more than one note is played at the same time. This is true in any musical
style. Even a lonely folk singer and his or her guitar is playing at least two notes (one
in voice, one on guitar) at the same time. A piano player has 10 fingers and thus can
Equal-temperament scale:
a tuning system in which the
difference between each
successive semitone is
constant both in pitch and
in frequency
FIGURE 13.8 A Guqin
A woman playing a guqin, a traditional Chinese
instrument.
©
B
lu
e
Je
an
Im
ag
es
/A
la
m
y
ISLE 13.7
Pentatonic Music
377 Chapter 13: Music Perception
play 10 notes at the same time, though this is very rare. A symphony orchestra may
have many instruments playing several different notes at the same time. Jazz bands may
have a number of different musical instruments playing at once. Rock bands tend to
have singing, guitar playing, and percussion simultaneously. How do composers know
which notes will sound good to listeners when played at the same time as other notes?
The concept of harmony in music refers to which pitches sound pleasing when
played together. In technical terms, consonance refers the perception of pleasantness or
harmony when two or more notes are played; that is, the notes fit with each other. In con-
trast, dissonance refers to the perception of unpleasantness or disharmony when two
or more notes do not fit together. Why some notes are consonant when played together
whereas others are dissonant has been the subject of much debate within Western cul-
ture, with theories going back all the way to the time of the ancient Greeks. The Greeks
were impressed that two tones that could be expressed as a simple ratio of each other
tended to sound consonant, whereas those that were more complex tended to sound
dissonant. They did not know about frequency, but they measured these ratios in terms
of the lengths of vibrating strings. Thus, the Greeks knew that a vibrating string twice
the length of another would produce a consonant octave sound. We now know that two
notes separated by an octave have approximately a 2:1 ratio of frequency. For example,
concert A is 440 Hz, and the A above it is 880 Hz. Similarly, intervals of a major third
(e.g., C and E) and a perfect fourth (e.g., C and F) sound consonant, but adjacent notes
(e.g., C and D, a major second) sound dissonant. Major thirds and perfect fourths are
easy to express as ratios, whereas adjacent notes are not.
When more than two notes are played at the same time, the result is called a chord.
Chords are often played on the piano with the left hand, while the right hand plays a
melody. Fundamental training in music allows musicians to learn which chords are con-
sonant and which are dissonant. In many pieces of music, chords are selected to be har-
monious or consonant with the melody line. We will discuss melody later in this section.
Musical context also plays a role in our perception of consonance and dissonance.
There may be some musical situations in which adjacent notes go together and would
sound consonant, so consonance goes beyond simple ratios. In addition, culture plays
a role in our perception of consonance and dissonance. What we find consonant in
Western culture might be dissonant in traditional Chinese music, and what traditional
Chinese music deems consonant we might find dissonant. In addition, norms within
a culture change over time. This is true of the major third in Western music. Prior to
Bach’s time, the major third was avoided, as it was considered dissonant. It is now con-
sidered the most consonant interval in Western music after the octave itself.
Dynamics and Rhythm
Music is not just a series of pitches. Equally important in the production and appre-
ciation of music are dynamics and rhythm. Indeed, drum music may not vary at all
in pitch—the differences are in the complex rhythms. We start by defining the rele-
vant terms in this section. Dynamics refers to the relative loudness and how loudness
changes across a composition. That is, a piece may start off very loud, then grow softer,
and then finish loud again. Changing from loud to soft may be important in trans-
mitting the meaning and emotion in any piece of music. In musical notation, soft is
indicated by a p for piano, and loud is indicated by an f for forte (these are the Italian
terms for “soft” and “loud”). In physics terms, dynamics refers to amplitude, measured
in decibels. Forte means more decibels, whereas piano means fewer decibels.
Rhythm refers to the temporal patterning of the music, including the tempo, the meter,
and the beat. Tempo refers to how fast or slow a piece of music is played, that is, the
speed of the music. For example, a beginning musician may elect to play a piece at a
Harmony: the pleasant sound
that results when two or more
notes are played together
Consonance: the perception
of pleasantness or harmony
when two or more notes are
played; that is, the notes fit
with each other
Dissonance: the perception of
unpleasantness or disharmony
when two or more notes do
not fit together
Dynamics: relative loudness
and how loudness changes
across a composition
Rhythm: the temporal
patterning of music, including
the tempo, the beat, and the
meter
Tempo: the pace at which a
piece of music is played
378 Sensation and Perception
slower tempo so as not to make mistakes, whereas a more experienced musician may play
the piece faster. Tempo can also change within a piece. Usually brisk or fast tempos are
used to express joy, whereas slower tempos render a sadder feeling. Think of Christmas
music. “Rudolf, the Red-Nosed Reindeer” is played quickly to express joy, whereas
“Silent Night” is a slow piece that reflects a more thoughtful or religious approach to the
holiday. Meter refers to the temporal pattern of sound across time, which usually repeats
itself across the piece. Meter is completely intertwined with beat. Beat refers to spaced
pulses that indicate if a piece is fast or slow. Thus, meter tells you how many beats occur
per musical measure (the repeating temporal pattern), and beat tells you which notes to
emphasize. In rock music, drums usually “keep the beat” by pulsing throughout each
measure. In traditional classical music, instruments such as the double bass are respon-
sible for keeping the beat. In most popular music, as well as in marches and many other
styles of music, the meter is called 4/4, meaning that there are four beats per measure.
In this meter, there is usually an emphasis, often indicated by relative loudness, on the
first beat out of every four and a secondary emphasis on the third beat in each measure.
Waltzes are played in 3/4 time, with the emphasis placed on the first beat out of every
three in a measure. The characteristic feature of Jamaican reggae music is that instead of
the first beat getting the emphasis in a 4/4 measure, the second and the fourth beats out
of every four get the emphasis in each measure. If you hum the melody to such nearly uni-
versally known tunes as Bob Marley’s “Jammin,” you can feel the pulses on those second
and fourth beats (see ISLE 13.8 for some examples of meter and beat).
Rhythm is therefore a complicated feature of music. It refers to tempo, meter, and
beat. In any given piece of music, each note or pitch may also be maintained for either
a short period of time or a long period of time. That is, a note, such as B-flat, may be
played for just one beat, or it may be sustained across four or more beats. The pattern
of notes across these beats also contributes to rhythm. In jazz, for example, a common
motif is a tendency to have a slightly longer note followed by a slightly shorter note,
typically eighth notes. These eighth notes are indicated by the same musical notation,
but a jazz musician automatically plays the first note for a bit longer and shortens the
second note. This pattern gives jazz its characteristic rhythm (Figure 13.9). Waltzes usu-
ally contrast a note played on the first beat with notes played on the other two beats, to
give waltzes their particular 3-count rhythm, which also makes them easy to dance to.
Timbre
Timbre refers to the complex sound created by harmonics (see Chapter 10 if this defi-
nition does not make sense). For example, a violin and a flute may be playing a note
with the same pitch, but it sounds different on each instrument. The harmonics, as well
as attack and decay characteristics, give each voice and each instrument its own dis-
tinct sound. Composers will select specific musical instruments because of their timbres.
Depending on context, specific timbres of different instruments will convey particular
meanings or emotions. The oboe, for example, is often used to express sadness, bitter-
sweet emotion, and perhaps puzzlement, whereas a flute is more likely to express joy.
In his famous piece Bolero (1928), Maurice Ravel has different instruments play the
same theme repeatedly. Each instrument gives the theme a different feel, as Ravel builds
up to finally having all the strings play the theme together and then the entire orchestra
(you can hear this piece on ISLE 13.9). Ravel’s Bolero also neatly illustrates a number
of other principles. It is written in 3/4 meter, and you can hear the emphasis on the first
beat of every measure. Moreover, as the piece progresses, the dynamics change, and the
piece gradually builds from very soft to very loud.
Meter: the temporal pattern of
sound across time
Beat: spaced pulses that
indicate if a piece is fast
or slow
ISLE 13.8
Meter and Beat
FIGURE 13.9
Louis Armstrong
Louis Armstrong (1901–1971) was a
famous trumpet player and singer in
the jazz tradition. Jazz has roots in
Western art music, popular music,
and West African musical traditions.
©
H
an
k
M
or
ga
n/
Sc
ie
nc
e
So
ur
ce
.
ISLE 13.9
Bolero Clip
379 Chapter 13: Music Perception
As stated earlier, the fundamen-
tal frequencies of music predomi-
nantly fall below 5,000 Hz. Only
the piccolo and piano even come
close to that frequency. However,
the harmonics of musical notes often
exceed 5,000 Hz, and these har-
monics contribute to the timbre of a
voice or instrument. For this reason,
recording equipment should be able
to record frequencies well in excess
of 5,000 Hz in order to capture the full complexity and musicality of any musical
piece, even though we do not perceive these high-frequency harmonics as actual
pitches (Figure 13.10).
Timbre is also important in distinguishing between well-made and poorly made
instruments. The materials and craftsmanship that go into a well-made instrument
allow harmonics to be created, each at the right level of loudness. Thus, well-made
instruments sound better than poorly made ones, assuming the musician playing each
one is of equal ability. That is, the same good musician playing on a fine violin relative
to a cheap violin will sound much better on the fine violin. The well-made violin has
a rich and deep timbre, even when high notes are being played, whereas the cheap
violin will sound shrill on higher notes, even when played by an expert. It is for this
reason that violinists favor well-made violins, including such famous antique violins as
the legendary Stradivarius violins. Because of differences in timbre from instrument to
instrument, the price differences between well-made and poorly made instruments can
be shocking. A beginner’s violin might cost as little as U.S. $80, whereas violins made
for professionals usually run higher than U.S. $30,000 (and even higher; some violins
cost millions). Similarly, a student’s saxophone may cost as little as U.S. $200, whereas
a professional one may cost more than U.S. $8,000.
It is also clear that harmonics are not the only factor that affects timbre. Two other
important features of timbre are attack and decay. Attack refers to the beginning
buildup of a note. This means how quickly the instrument expresses all of its frequen-
cies and if there are any differences in the onset of harmonics. Decay refers to how long
the fundamental frequency and harmonics remain at their peak loudness until they start
to disappear. For example, a trumpet has a very fast attack, leading to the sharp sound
we associate with trumpets. In electronic instruments, attack and decay can be altered
to mimic the sounds of other instruments or to create timbres that are not possible
using string or wind instruments. You can hear differences in attack and decay by going
to ISLE 13.10.
That gives us the basic building blocks of music—pitch, loudness, rhythm, and tim-
bre. Musicians combine these building blocks in infinite ways to create music of all
kinds. But to understand the perception of music requires more than a description of
the building blocks—it also requires a more gestalt approach, as music transpires over
time. For this reason, melody is of the utmost importance. We turn to melody in the
next section.
TEST YOUR KNOWLEDGE
1. What is the difference between rhythm, tempo, and beat?
2. What is timbre? What physical differences produce differences in timbre?
FIGURE 13.10 Sound spectrograms of two different instruments, an oboe (a) and a flute
(b), playing the same note.
A
m
p
li
tu
d
e
(
d
B
)
Frequency (Hz)
100
30
20
10
0
1000 10,000
a. Note with frequency of 1046 Hz,
played on the oboe
A
m
p
li
tu
d
e
(
d
B
)
Frequency (Hz)
100
30
20
10
0
1000 10,000
b. Note with frequency of 1046 Hz,
played on the �ute
Attack: the beginning buildup
of a note
Decay: how long the
fundamental frequency and
harmonics remain at their
peak loudness until they start
to disappear
ISLE 13.10
Attack and Decay
380 Sensation and Perception
Melody
Most people can hum a variety of melodies, from tunes
learned in childhood, such as “Mary Had a Little Lamb,”
to Christmas songs to famous classical melodies, such as
Beethoven’s Ode to Joy, to the melody of the current hot
songs on the Top 40. If you think about these tunes, you
may realize that melody is essentially a series of pitches
joined together with rhythm created by different lengths
of each note (Figure 13.11). Thus, we can define melody
as a rhythmically organized sequence of notes, which we
perceive as a single musical unit or idea. What carries
melody beyond pitch and rhythm is that the sequence
forms a unit with properties that transcend the individ-
ual pitches and lengths of notes. A melody coheres in
time to create an experience in its listeners. Thus, the
two melodies in Figure 13.11 are very similar in terms
of the notes used and the rhythms used, but anyone
brought up in Western culture would never confuse
these two melodies (also see ISLE 13.11). Most music, in any tradition, starts with a
melody, usually sung by a voice, played on the piano or with other instruments, which
is then augmented by various musical accompaniments. Untrained listeners focus first
on the melody.
Scales and Keys and Their Relation to Melody
Consider the piano keyboard again (see Figure 13.5). If we start on middle C and play every
white note to the next C, we have played a C major scale. A scale is a set of ordered notes start-
ing at one note and ending at the same note one octave higher. In this way, a scale is a very simple
melody. In Western music, major scales refer to sequences of notes with the following pattern
of semitones: 2, 2, 1, 2, 2, 2, 1. The numeral 2 means that we go up two semitones, whereas the
numeral 1 means that we go up one semitone. Thus, a G major scale starting on G will include
one black note (F-sharp). One can start a major scale on any note on the piano and follow this
sequence. For example, the C-sharp major scale will have the following notes: C-sharp, D-sharp,
F (E-sharp), F-sharp, G-sharp, A-sharp, C (B-sharp), and C-sharp. In essence, you can start a
major scale on any note if you follow the pattern of 2, 2, 1, 2, 2, 2, 1 on your piano keyboard
or any other instrument. Major scales are among the first melodies any instrumentalist learns
when first starting to learn to play an instrument, and the major scale is the most common kind
of scale in Western music. (You can hear an assortment of scales in ISLE 13.12.)
Major scales can be contrasted with the chromatic scale, in which every step is one
semitone. Thus, the chromatic scale cannot be divided into keys, because it does not
matter where you start or stop—the sequence is always the same. Each note is one
semitone higher or lower than the previous one. On a piano, a chromatic scale means
playing every key, including all of the black keys (again, see ISLE 13.12).
There are also a number of different types of minor scales, which have different
sequences of semitones as one moves from one octave to the next. For example, the nat-
ural minor scale has the following sequence: 2, 1, 2, 2, 1, 2, 2. The natural minor scale is
relatively simple in both its sequence and its relation to the major scale. However, more
commonly used in music is the harmonic minor scale, with the following sequence: 2, 1,
2, 2, 1, 3, 1. The harmonic minor scale is often used in Western music to express sad-
ness. It is also commonly used in Middle Eastern music. Other minor scales exist, but
they are seldom used in music today. If you have taken a course in music theory, how-
ever, you are familiar with the whole family of minor scales.
(a)
(b)
FIGURE 13.11 Musical Notation
(a) The musical notation for “Mary Had a Little Lamb.” (b) The musical
notation for Beethoven’s Ode to Joy. These pieces are seldom grouped
together because of their different histories, but they are quite similar in
terms of their melodies.
ISLE 13.11
Examples of Melody
ISLE 13.12
Types of Scales
Melody: a rhythmically
organized sequence of notes,
which we perceive as a single
musical unit or idea
Scale: a set of ordered notes
starting at one note and
ending at the same note one
octave higher
381 Chapter 13: Music Perception
Any particular melody can be expressed in terms of its key signature, which relates
the melody to the pattern of scales described in the previous paragraphs. That is, every
melody is played in a particular key, which refers to the main scale pattern. If we are
playing “Mary Had a Little Lamb” in the key of C major, this means that the tonic is C,
and we are not likely to have any sharps or flats (i.e., no black keys on the piano). Thus,
key refers to the tonic note (e.g., C in a C major or minor scale) that gives a subjective
sense of arrival and rest in a musical piece. Because melodies are defined in terms of
the pattern of notes relative to other notes, any melody can be played in any key. Thus,
“Mary Had a Little Lamb” can be played in the key of C, the key of G, or any other
key. If you hum the piece, its last note is the tonic of that key. If you are singing it in the
key of C major, the tonic will be C. If you switch to another key, the name of that key
will be the tonic. Composers will make deviations from the key. Thus, when a G-sharp
is called for in a melody played in the key of C, the G-sharp is called an “accidental”
by musicians. Thus, for musicians, the term accidental refers to a note that requires a
special mark to remind the musician to play the sharp or flat not present in that key.
In most cases, what defines a melody is the relation of pitches within a piece rather
than the absolute pitches. For example, it really does not matter what note we start
“Mary Had a Little Lamb” on, as long as the remaining notes show the same relation
to that note as in the original version. For example, “Mary Had a Little Lamb” is shown
in the key of G in Figure 13.11. In this key, the first note is B, the second is A, and the
third is G. Each of these notes is one step (or interval or two semitones) higher than the
next note in the sequence. If we switch the key to F, the first three notes will be A, G,
and F. Although there is no overlap in actual notes, we hear these sequences as being
the same, and both can create the melody of “Mary Had a Little Lamb.” That there
can be two or more versions of a melody, each starting on a different note, is known as
a transposition in music. Trained musicians may be able to detect what key a simple
melody is being played in, but most listeners hear the melody as such but do not register
the key or starting note.
Our perception of melody across transpositions starts very early in life. Plantinga
and Trainor (2005) examined melody perception in 6-month-old infants. In the study,
Plantinga and Trainor played particular melodies to infants numerous times over a
7-day period. On the next day, the infants either heard the same melody, but transposed
into another key, or a novel melody. If the transposed melody was heard as the same
melody as the original, the infant would not consider it novel and would look toward
the source of the novel melody. If, however, the infant heard the transposed melody
as novel, the infant would show no difference in looking time toward the source of
the transposed melody or the new melody. The results showed that the infants looked
more often toward the source of the novel melody, rather than the transposed melody,
indicating that they perceived the transposed melody as being similar to something
heard earlier. In this way, we can assert that even young infants hear melodies across
transpositions of key.
Gestalt Principles of Melody
Because of the importance to melody of the relation among notes rather than absolute
pitch, and because the perception of melody is qualitatively different than the percep-
tion of a string of pitches, melody perception lends itself to the use of gestalt principles.
If you remember from Chapter 5, gestalt psychology approaches perception by exam-
ining emergent properties that can be seen across a perceptual array but may not be
obvious in any particular single element of that stimulus. That is, the motto of gestalt
psychology is that the “whole is bigger than the sum of the parts.” The gestalt principles
described in Chapter 5 are certainly applicable to melody perception (Tan et al., 2010).
We review these principles and then apply them to music (also see ISLE 13.13).
Key: the tonic note (e.g., C in
a C major or minor scale) that
gives a subjective sense of
arrival and rest in a musical
piece
Transposition: the process
through which one can create
multiple versions of a melody
that start on different notes
but contain the same intervals
or sequence of changes
in notes
382 Sensation and Perception
The four principles are as follows:
1. Proximity: Elements near each other are seen as a group.
2. Similarity: Elements that are similar are seen as a group.
3. Closure: An incomplete pattern is seen as whole when the completion occurs.
4. Good continuation: Smooth continuity is preferred over changes in direction.
These principles are applied in melody processing over time rather than space (e.g., visual
processing). Indeed, music transpires over time—a melody is a sequence of notes in time. For
example, we tend to hear notes that are close in chroma as grouped together, even when they
come from different instruments or different locations, a source of the music illusions described
at the end of the chapter. Of course, other aspects of music involve space—the source of a voice
or instrumental sound is often critical—but the time dimension comes first. Space does play a
role in music perception, as anyone who has heard an old monophonic record can attest. The old
monophonic recordings lack the depth provided by modern recordings, which allow listeners
to imagine where different instruments’ sounds are coming from. But returning to the gestalt
principles, we start with proximity. We then consider similarity and closure.
Proximity. In music, proximity may refer to elements’ being close together in pitch, time,
or space (Tan et al., 2010). For example, notes that are similar in pitch may be grouped
together. Notes are also grouped together if they are played together in time or if they
come from the same instrument or section of a larger musical group. To get a sense for the
idea of proximity, imagine a person playing a piano. Typically, the right hand plays notes
that are higher in pitch than the left hand. Also, most often, it is the right hand that plays
the melody, whereas the left hand plays the bass line or accompaniment. Even though all
of the notes are played in close spatial proximity and at approximately the same time, we
hear the notes from the right hand emerging as melody because they are grouped together
with respect to pitch (Figure 13.12). Similarly, in some of Bach’s famous solo music for
violin, the violinist essentially creates two streams of music by simultaneously playing
both high and lower notes. Perceptually, we group the high notes together and group the
low notes together, so we hear it as polyphonic or as two lines of music (for an example,
go to ISLE 13.14 to hear Bach’s Partita No. 3 in E major).
Similarity. Think of listening to your favorite music. Chances are your favorite music is
created by a group of musicians, playing different parts. From hometown garage bands to
the Vienna Philharmonic, most music consists of mul-
tiple parts. A rock band may have a drummer, a guitar
player, a bass player, and one or more singers (Figure
13.13). An orchestra may consist of more than 100
musicians playing 16 different instruments. Composers
will use our perception of similarity to create seamless
perceptions of melody even when the melody crosses
from one voice or one instrument to another. Similarity
plays out at several levels. We may hear similar timbres
grouped together. A modern orchestra may have 16 vio-
linists all playing the same part. Because these musicians
are playing the same notes with the same approximate
timbre, we hear them as grouped together. Moreover,
once a melody has been established, we may follow
the melody because of its similarity across changes in
instruments. In Ravel’s Bolero, the instruments playing
the melody constantly change, but we have no difficulty
distinguishing the melody from the bass line, drum
rhythms, and harmony (hear this in ISLE 13.9).
ISLE 13.13
Gestalt Principles Review
C D C B
FIGURE 13.12
Notes Grouped Together
by Proximity
Because C and D are close in pitch,
they are grouped together. Because
C and B in a higher octave are not
close in pitch, we think of them as
separate.
ISLE 13.14
Gestalt Principle: Proximity:
Bach’s Partita No. 3 in E major
©
iS
to
ck
ph
ot
o.
co
m
/o
ne
in
ch
pu
nc
h
FIGURE 13.13 A Rock Band
A rock band may have a drummer, a guitar player, a bass player, and one or
more singers. We infer notes that are similar in pitch as coming from the
same musician.
383 Chapter 13: Music Perception
Closure. In music, closure means that a melody
should end on the tonic note of any particular scale or
another note implied by the progression of the melody.
Typically, if the melody is played in the key of C,
the last note will be C. Occasionally, the note might
be G, but seldom any other note in the key of C. To
illustrate this point, think of the very short melody of
the song “Shave and a Haircut.” If you do not know
the melody, but can read music, see Figure 13.14
(you can hear it in ISLE 13.15). If you simply play the notes or sing the words “shave and a
haircut,” most people experience a strong longing to hear or sing the last two notes (“two
bits”). Try it yourself: Most people cannot stop themselves from singing the last two notes
of the sequence. In the 1988 movie Who Framed Roger Rabbit? the character of Roger
Rabbit is lured out of hiding because he cannot stop himself from completing this melody.
The importance of closure in melody perception was demonstrated in an experiment
by DeWitt and Samuel (1990). Their experiment was a musical demonstration of the
phonemic restoration effect we discussed in the last chapter, except instead of hearing
a missing phoneme, participants heard an implied but missing note. In this perceptual
restoration effect, participants heard a major scale plus the next two notes, for a total
of 10 notes, each predictable from the note played before it. One note of the 10 was
replaced by white noise. Under these conditions, many participants reported hearing
the missing note. This effect was greater when the note was later in the scale, allowing
more time for expectations to build up. The effect did not occur if the notes were ran-
domly arranged rather than in a melody-like scale. Thus, our expectation of what to
hear in a particular sequence can actually create the perception of that note.
Good continuation. Most composers will tend to have one note be relatively close to
the previous note in pitch. That is, a C is more likely to be followed by a D than by an
F. This allows the listener to hear those notes as connected. Some composers (e.g., Bach)
will often create two lines within a musical piece by alternating between a high note and
a low note successively. Because of continuation, we hear the lower notes as one line
and the higher notes as another.
TEST YOUR KNOWLEDGE
1. Why are melodies easy to transpose in the Western system of music-making?
2. How do each of the gestalt principles apply to the concept of melody?
THE NEUROSCIENCE OF MUSIC
13.2
Summarize the basic neuroscience of music, including how training
and experience can affect the representation of music in the brain.
One of the central tenets of modern psychology is that perceptual and cognitive pro-
cesses arise in the brain. Even if these processes are about objects in the world and per-
ceived through sensory organs, the brain’s role is still considered central. Implicit in this
view is that all human brains are organized in similar ways. This turns out to be sup-
ported over and over again. For example, regardless of gender, age, ethnic background,
racial identification, native language, and any other feature that distinguishes one
human from another, brain regions serve the same functions across these distinctions.
For example, the occipital lobe processes visual information for all sighted persons
Shave and a hair-cut two bits
FIGURE 13.14 Principle of Closure
It is hard not to want closure of this famous, albeit very short, piece of music.
ISLE 13.15
A Shave and a Haircut
384 Sensation and Perception
(indeed, all sighted mammals). Wernicke’s area and Broca’s area are language areas in
all human brains. The primary auditory cortex processes input from the cochlea in all
human brains. Neurosurgeons may need to be aware of slight deviations in individual
human brains—one region may be shifted a few millimeters forward or backward rel-
ative to other individuals—but by and large, this rule of brain universalism has been
upheld in modern science.
The Neuroanatomy of Music
The neuroanatomy of music is a bit different because music is in some ways an optional
feature of human cognition. Although all cultures have music (including those that for-
bid it), people vary greatly in their interest in music, the time spent listening to music,
their individual training in music, and the musical traditions they are exposed to. As a
result, there are greater individual differences in the regions responsible for music per-
ception and in the way these regions function than there are for many other functions of
the brain. Nonetheless, we can make some generalizations about how music perception
occurs in the brain.
First, we start with a quick review of information covered in Chapters 10 and 11.
Recall that from the cochlea to the auditory cortex, the auditory signal has a tonotopic
organization. This means that the auditory nerve preserves a representation of the fre-
quency of sound, which we perceive in music as the pitch of a particular note. Loudness
is represented by the strength of the signal at any particular frequency.
We also see tonotopic organization throughout the primary auditory
cortex. Music perception is certainly a variant of sound perception,
but not all sounds are music. Thus, we can ask if there are common
areas of the brain that process musical stimuli, independent of other
sounds, in all human beings. We find these areas starting in the sec-
ondary auditory cortex in the temporal lobe (Overy, Peretz, Zatorre,
Lopez, & Majno, 2012).
One of the clear findings is that music perception usually causes
greater activation in the right temporal lobe than the left tempo-
ral lobe (Overy et al., 2012). It seems that the right hemisphere is
more sensitive to small changes in pitch, which are likely relevant
to music but less relevant to speech. For example, Hyde, Peretz, and
Zatorre (2008) used functional magnetic resonance imaging (fMRI)
to examine the function of the right and left auditory cortical regions
in frequency processing of melodic sequences. They found that better
behavioral pitch resolution was associated with activity in the right
secondary auditory cortex. More specifically, these areas included the
planum temporale as well as some areas within the primary auditory
cortex (Figures 13.15 and 13.16). Indeed, many neuroimaging studies
have now shown the importance of the right secondary auditory cortex in pitch per-
ception in music (Janata et al., 2002; Overy et al., 2012). However, the more musical
training an individual has, the more the left hemisphere is involved in music perception
(Habibi, Wirantana, & Starr, 2013). This is true in children as well as adults (Habibi,
Cahn, Damasio, & Damasio, 2016). That is, musical training forces the brain to devote
more networks to music and perhaps requires the brain to involve meaning and lan-
guage circuits to help with music perception and cognition. Indeed, many argue that
musical training affects the way we hear music as well.
Other neuroimaging studies have focused on harmonic expectations. For exam-
ple, Seger et al. (2013) played small samples of Western classical music to participants
while they were being monitored by fMRI. Compared with when participants were not
FIGURE 13.15 Secondary Auditory Cortex
Secondary auditory cortex areas with specialization in
fine pitch perception are important in music perception.
Secondary
auditory
cortex
Primary
auditory
cortex
385 Chapter 13: Music Perception
listening to music, Seger et al. found activity in the bilateral superior
temporal gyrus and the right inferior frontal gyrus. These areas also
became even more active when the experimenters changed the music
to violate expected patterns.
Another important component of music, as previously discussed,
is rhythm. Rhythm appears to be processed in areas of the primary
auditory cortex and, more noticeably, in the right hemisphere as well.
In particular, the belt and parabelt areas are important in the process-
ing of rhythm (Snyder & Large, 2005; Tramo, 2001). Moreover, when
people are producing rhythm, we also see some more prominent activ-
ity in the left hemisphere, including areas of both the left prefrontal
cortex and the left parietal cortex. Because people producing rhythm
are also engaged in action, we also see activity in the cerebellum
(Tramo, 2001). Varieties of musical training, ranging from learning to
play the violin to learning to play the drums, may also impact neural
development (Slater, Azem, Nicol, Swedenborg, & Kraus, 2017).
Most of the studies reviewed in this section were conducted with
participants who were college students without specific musical train-
ing. Most college students have spent many hours over the course of
their lives listening and attending to music. But we can also ask how
musical training affects the networks in the brain for music perception. Although there are
a great many similarities between the brains of nonmusicians and musicians, we can find
some important differences as a function of musical training. For example, the organization
of the motor cortex changes in response to the demands of the complex motor movements
needed to play many instruments. In particular, Krings et al. (2000) examined the brain
areas used by professional piano players and a control group. Piano players must use com-
plex movements of both hands, and in many cases, the movements of each hand may follow
very different patterns simultaneously. Using fMRI, they found that the professional piano
players required lower levels of cortical activation in motor areas of the brain relative to
controls while doing the same task. That is, musical training allowed greater control of the
hands in piano players, meaning that they needed to recruit fewer neurons to do an easy
manual task relative to controls. In essence, musical training also recruits motor networks
to allow musicians to engage in the complex motor movements necessary to play music.
Recent neuroimaging studies show that visual areas of the brain are activated when
people are listening to music, consistent with a number of studies linking auditory and
visual cortices (Liang, Mouraux, Hu, & Iannetti, 2013). It may be that listening to
music invokes thoughts that invoke visual images, which we know are produced in the
visual areas of the brain. Certainly, this is often the goal of some composers, that is, to
cause us to bring to mind a particular image. If this is the case, then we may find more
interactions between vision and music that might be intuitive. To test this view, Landry,
Shiller, and Champoux (2013) compared listeners under normal conditions with those
who had been deprived of visual stimulation for 90 minutes. The listeners who had
been kept in the dark showed a temporary improvement in their perception of harmo-
nicity, that is, whether a chord was in tune or slightly out of tune. The participants who
had been visually deprived performed better at this task for up to 5 minutes after the
visual deprivation ended. Landry et al. interpreted this to mean that the visual system
may play a role in music perception, as there was an observed interaction.
Synesthesia
The interaction between music and the visual system is even more pronounced in people
with color–music synesthesia. Synesthesia is defined as a condition in which a stimulus in
FIGURE 13.16 fMRI While Listening to Music
The subject (lying in the MRI scanner) listens to
instrumental music. Image shows brain areas (mostly
the auditory cortex) responding to a meaningful auditory
stimulus (beyond the sounds of the MRI apparatus).
Synesthesia: a condition
in which a stimulus in one
modality consistently triggers
a response in another modality
386 Sensation and Perception
one modality consistently triggers a response in another modality.
Estimates of the incidence of synesthesia suggest that it occurs in
approximately 1% to 4% of the population (Simner et al., 2006).
Synesthesia includes a number of different kinds of cross-modality
experiences. For some people with synesthesia, particular words
or letters may elicit particular colors, whereas for others, visual
stimuli may trigger a taste experience. Color–music synesthesia
occurs when particular pitches, notes, or chords elicit experiences
of particular visual colors (Figure 13.17) (Farina, Mitchell, &
Roche, 2017). Whereas most of us do not have synesthesia, we can
do cross-modality matching with some degree of consistency and
accuracy. That is, most people will use similar principles to match
pitch to color or loudness to temperature (you can try this for
vision–audition comparisons in ISLE 13.16). Although normal
people may make similar judgments, we seldom experience color
while listening to music. The interesting aspect of synesthesia is
that these people do experience a sensation in another modal-
ity. Note that people with synesthesia are not hallucinating—
they are well aware that the secondary experience is illusory.
Nonetheless, the experience in the second modality may be
vivid and strong. Color–music synesthesia has been described
by many musicians and composers, including classical compos-
ers Leonard Bernstein and Nikolai Rimsky-Korsakov and jazz
pianist Marian McPartland.
Recent neuroimaging studies confirm that people with
synesthesia have different brain organization than those who do not have synesthe-
sia (Farina et al., 2017; Hubbard, Brang, & Ramachandran, 2011; Loui, Zamm, &
Schlaug, 2012). These studies show that people with synesthesia tend to have stronger
connections between one sensory area and another sensory area than do people without
synesthesia. To be more specific, this means that the white matter (axons) between one
perceptual area and another is stronger in those with synesthesia. Zamm, Schlaug, and
Eagleman (2013) examined the brains of people with color–music synesthesia. They
found that relative to controls, people with color–music synesthesia had stronger con-
nections between the visual and auditory cortices and areas in the frontal lobe. They
found that a tract from the sensory areas to the frontal lobe called the inferior fron-
to-occipital fasciculus was enlarged in people with synesthesia (Figure 13.18). Zamm
et al. showed that connections between visual areas in the occipital lobe and auditory
association regions in the temporal lobe may be differently structured in people with
color–music synesthesia.
The Neuropsychology of Music
Amusia is a condition in which brain damage interferes with the perception of music, but
does not otherwise interfere with other aspects of auditory processing. Amusia usually is
acquired after brain damage, but there is also a form called congenital amusia, in which
individuals are seemingly born with an impairment in music perception. The critical deficit
in most forms of amusia, including congenital amusia, is that people with this condition
have an impaired ability to discriminate pitches, which affects their music perception but,
in most cases, leaves speech perception intact. This is likely the case because pitch is less
critical in phoneme perception, but the condition interferes with their ability to perceive
and therefore appreciate music (Peretz & Hyde, 2003). Amusia garnered public attention
because of the publication of Oliver Sacks’s bestselling 2007 book Musicophilia, which
describes a number of fascinating cases of amusia and also describes its opposite, that is,
A
nd
y
Zi
to
/I
llu
st
ra
tio
n
W
or
ks
/G
et
ty
Im
ag
es
FIGURE 13.17 Color–Music Synesthesia
Color–music synesthesia:
a form of synesthesia that
occurs when particular
pitches, notes, or chords elicit
experiences of particular
visual colors
Congenital amusia: a
condition in which people
are inherently poor at music
perception
ISLE 13.16
Cross-Modal Matchings as a
Simulation of Synesthesia
387 Chapter 13: Music Perception
cases of people who have become intensely musical
after brain damage.
Isabelle Peretz and her colleagues at the
University of Montreal have been conducting
extensive studies on congenital amusia (e.g.,
Moreau, Jolicoeur, & Peretz, 2013; Wilbiks,
Vuvan, Girard, Peretz, & Russo, 2016). People
with congenital amusia show deficits in music per-
ception as well as production (e.g., they cannot
sing in tune and have difficulty learning to play
musical instruments). Although it is extremely rare,
Peretz estimates that as many as 4% of the popu-
lation may suffer from some form of amusia. You
may know some of these people as the people who
cannot sing even a simple tune and who have no
interest in going to concerts with you. Congenital
amusia seems to be related to impaired pitch dis-
crimination, so people with congenital amusia will
not show deficits in speech perception or in most
other aspects of auditory perception.
As indicated earlier, it is likely that poor
pitch perception lies at the heart of congen-
ital amusia. However, Peretz (2013) was
concerned that an initial deficit in pitch per-
ception may spiral in people with amusia.
Because they cannot appreciate melodies
like normal individuals, they may avoid
listening to music. Because of this lack of
exposure, their musical impairment will
grow with lack of exposure. To remedy this
potential in the real world, Peretz conducted
experiments in which people diagnosed
with amusia agreed to listen to music for an
hour per day over a series of weeks. Peretz
showed that patients with congenital amu-
sia who are exposed to music over a long
period of time do not show any improve-
ment in pitch perception or in musical
understanding (Mignault-Goulet, Moreau,
Robitaille, & Peretz, 2012). Thus, mere
exposure to music does not “treat” amusia.
However, Wilbiks et al. (2016) showed some
improvement in music production with an
amusic after intensive training.
Because of this, Peretz (2013) is con-
vinced that congenital amusia is a genet-
ically linked syndrome that occurs in some people. Indeed, Peretz (2008) described
research that shows that congenital amusia occurs within families more than chance
would predict, thus pointing to a genetic component. She argues for a neuroanatomical
pathway that might be suppressed or impaired in people with congenital amusia. For
example, she argued that research shows that there may be deficits in the transmission
of information from the auditory associative cortex, that is, those areas that surround
FIGURE 13.18 The Brain in Synesthesia (Zamm et al., 2013)
People with color–music synesthesia have stronger connections between the
visual and auditory cortices and areas in the frontal lobe. This is demonstrated in
these functional magnetic resonance images.
Gene
1
Tonal encoding
of pitch
Failure to detect
anomalous pitches
in melodies
Indifference
to
dissonance
Failure to
recognize
tunes
Singing
out of tune
Acoustical encoding
of pitch
Gene
2
Gene
3
Env.
1
Env.
2
Env.
3ETIOLOGY
BRAIN
COGNITION
BEHAVIOR
FIGURE 13.19 Causation of Congenital Amusia
This diagram illustrates the potential causes and manifestations of amusia.
388 Sensation and Perception
the primary auditory cortex, to areas in the frontal lobe, such as the inferior frontal
gyrus (Figure 13.19).
We will cover one last interesting aspect of congenital amusia. We have seen that one
of the primary deficits is an inability to distinguish close pitches. Because of this pitch
confusion, it may be hard for individuals to distinguish music that is in tune from music
that is out of tune, and music that is consonant from music that is dissonant. Thus, most
individuals with congenital amusia tend to shy away from music. However, what hap-
pens to individuals with congenital amusia when they attempt to learn a language such
as Mandarin (Chinese) or Vietnamese, in which the pitch with which a word is said
is important to meaning? Early studies suggest these are extremely difficult languages
for congenital amusia individuals to learn as second languages, but we do not know
if native Mandarin speakers with congenital amusia have a deficit in understanding
semantics conveyed by pitch (see Peretz, 2008). Future research will hopefully tease
these issues out.
TEST YOUR KNOWLEDGE
1. What neural differences does one see in professional musicians compared with
appropriate control populations?
2. What is congenital amusia? Why might its incidence in the population be
underestimated?
LEARNING, CULTURE,
AND MUSIC PERCEPTION
13.3 Discuss how learning and culture affect music perception.
Music and Language
One of the ongoing debates in the field of music perception is the extent of the meta-
phor between language and music. Is music a form of language in which the ideas trans-
mitted are not words and semantic meaning but notes and emotions? Are there special
parallels in the processes that allow us to understand language and appreciate music?
Some researchers argue that language and music are very similar processes, whereas
other researchers argue for little overlap between the two. We briefly address some of
the arguments for both views here.
One of the most passionate spokespeople for the idea that language and music share
similar neurocognitive systems is noted music neuroscientist Aniruddh Patel (Patel,
2008, 2013). Patel asserts that language and music have much in common at the behav-
ioral level. First, music and language are both perceptive (listening) and productive
(singing, talking) systems in which perceiving and producing are equally important (if
only to sing in the shower). Moreover, both involve the perception of novel and com-
plex sounds that unfold rapidly over time. Subjectively, hearing a melody is different
from hearing a sentence, but both are sound stimuli that transmit meaning, so it is not
unrealistic to expect some overlap. Patel (2013) also argues that both music and lan-
guage have structure that must be followed for the sounds to make sense to listeners.
For example, language has syntax that governs which words can be joined together to
make a coherent sentence. Patel argues that music theory describes a syntax that serves
389 Chapter 13: Music Perception
a similar function in music, namely, limiting those notes that can be joined together to
form consonant music. Similarly, words have specific meanings, but that meaning can
depend on context. For example, the word bugger may be a term of affection in one
situation but a vile insult in another. Meaning can also vary in music as a function of
context. In many situations, minor keys denote sadness, but there are also a great many
wedding celebration songs written in minor keys.
On a neural level, there are also some striking parallels between music and lan-
guage. First, both use the same basic auditory machinery. Whereas language uses more
neural space in the left hemisphere, music perception and production appear to be
housed in the analogous regions of the right hemisphere. Moreover, the better someone
becomes at language, the more right hemisphere involvement we see. Similarly, many
studies have shown the acquisition of musical expertise is accompanied by greater
left-hemisphere involvement in music (Patel, 2013).
Nonetheless, there are also important differences between music perception and lan-
guage perception that must be acknowledged, which cloud the analogy between music
and language. First, speech perception is based on the inference of subtle differences in
the patterns that produce different vowels and consonants, whereas music focuses on
pitch and pitch contrasts. We can say a sentence without varying the pitch; the move-
ments of the mouth create different sounds that carry phoneme information. Similarly,
music can be sung using different phonemes, but as long as the pitch remains, we rec-
ognize the music as such. For example, think of the conventional way of singing Henry
Mancini’s “Pink Panther” (1963)—“dead ant, dead ant, dead ant, dead ant, dead ant,
dead ant, dead ant. . . .” We could certainly change the semantic content from dearly
departed insects to anything we like and still represent the melody of this song. Indeed,
when humming the melody, we may think of the Pink Panther’s bumbling French detec-
tives or cool jazz, but seldom do we think of it as a dirge for the Formicidae. Thus, the
meaning in music extends beyond what is sung. Finally, it is also possible to interpret
the neural evidence as suggesting differences between language and music. That is, lan-
guage predominates in the left hemisphere, whereas music predominates in the right
hemisphere. What could be a more basic difference than that?
Culture and Music Perception
An obvious truism about music is that it varies so much—from culture to culture, from
generation to generation, from “pop” traditions to “highbrow” traditions. Given this
incredible diversity of music, are we justified in making the generalizations about music
perception that we have been making throughout this chapter? Our assertion here is
that despite the differences in music across cultures, there are some universalities that
allow us to talk about music and not just “varieties of music.” We have already dis-
cussed, for example, the universality of the octave, which all music traditions respect.
All cultures use pitch and rhythm to express emotion in their music, either with or
without singing. Therefore, we now briefly consider some rules that may be universal
and some that may be specific to our own Western traditions.
A brief reminder of the context of the term Western music: Our use of the term
refers to a huge gamut of music, including what most of us would commonly call
“classical” music and “pop” music, as well as jazz, hip-hop, rap, reggae, southern rock,
rock ’n’ roll, country, grunge, and so on. All of these styles follow the Western music
tradition. However passionately you may love one form (e.g., reggae) and hate another
(e.g., country), they all share the Western music tradition and therefore have more in
common with one another than they do with non-Western forms of music. Western
musical styles use the same scale structure, the same relations among notes within the
octave, a common means of notating written music, and a common set of assumptions
390 Sensation and Perception
about what is consonant and what is dissonant.
Indeed, they use many of the same musical instru-
ments (Figure 13.20). Although from where most of
us sit, the tattooed and nose-ringed fans of a heavy
metal group may have little to do with the tuxedoed
and gowned attendees of an opera, they are both
engaging with music that derives clearly and directly
from Western music traditions.
But outside the Western music tradition, we find
music that is organized by radically different principles.
For example, the Indian rag (or raga) scales that gov-
ern much traditional Indian music are very different
from Western scales. First, in much Indian music,
there are 22 notes within each octave, far more than
the traditional Western 12 (ISLE 13.17). In addition,
few of these notes fall exactly at the same frequen-
cies as Western notes (Figure 13.21). Thus, at a basic
level, Indian music is using notes that would fall
between the notes of the Western music scale. It would be impossible to play raga music
on a Western instrument, such as a piano or any woodwind instrument. Moreover, in
traditional Indian music, different scales are associated with different times of year,
different moods, and even different times of day (Tan et al., 2010). Research shows
that the networks in the brain react differently to daily
exposure to Indian music as opposed to Western music
(Ambady & Bharucha, 2009).
Similarly, Javanese gamelan music uses different scale
systems, called slendro, which is a five-tone scale, and pelog,
which is a seven-tone scale. These scales bear a rough cor-
respondence to Western scales, but the notes are distributed
at different intervals relative to the octave of each scale.
Perlman and Krumhansl (1996) found that Western listeners
were impaired in their ability to detect aspects of Javanese
music relative to those who were more familiar with it.
Performance may also vary across musical traditions. In
the Western tradition—from art and classical music on one
hand to garage rock bands on the other—we have perform-
ers, and we have listeners. Listeners may dance and shout
in less formal venues (but do not try that in a symphony
concert hall), but they are not part of the musical perfor-
mance. This history of performers and listeners goes back
centuries in our musical traditions. In many non-Western music traditions, it is expected
that all present will be part of the act of making music as well as listening to it.
Musical traditions differ in their approaches to rhythm as well. In particular, research
has focused on differences between Western musical approaches to rhythm and those of
traditional West African drumming (Temperley, 2000). Temperley argues that syncopa-
tion (varying the emphasized beat in a musical piece) is usually more pronounced in West
African traditions (Figure 13.22). However, syncopation became a part of the Western
tradition in jazz and in classical music in the 20th century, perhaps borrowing from
African traditions. Thus, differences in rhythm may be quantitative changes among simi-
lar traditions rather than markers of completely different musical traditions, as we see in
the case of different notes within a scale.
©
iS
to
ck
ph
ot
o.
co
m
/N
ad
ez
da
st
oy
an
ov
a
FIGURE 13.20 Havana, Cuba, May 10, 2013
The conductor performs with a brass band in the streets of Havana, Cuba, in
Central Park Square near Hotel Inglaterra.
ISLE 13.17
Indian Raga Music Example
Bilawal scale
Charukesi scale
Poorvi scale
FIGURE 13.21 Indian Raga Scales
The Bilawal scale is identical to our major scale, but the other ragas are
quite different from the scales used in Western music.
391 Chapter 13: Music Perception
An interesting pattern that may be universal
across musical traditions is the relation between
music and the experience of emotion. Seemingly,
in all cultures, music is used to convey emotion
ranging from sadness and anger to joy and ecstasy.
Most of us know this experience firsthand. A song
comes on the radio and reminds us of a partic-
ularly romantic night with our significant other;
another song reminds us of a particularly unpleas-
ant breakup. The composer Johann Sebastian
Bach wrote the sarabande of his Violin Partita
No. 2 in D minor (Opus 1004) in the weeks
after the death of his wife. Even today, more than
300 years later, we can hear the inconsolable sad-
ness in the piece (you can hear a sample of this
piece on ISLE 13.18). Even if you have never
listened to classical music, you should be able
to determine the sadness conveyed by the minor
chords and the haunting melody.
However, moving across cultures, it may be
difficult to detect the intended emotion in a musical composition. In the Western music
tradition, minor scales often convey sadness, as certainly Bach’s Violin Partita No. 2 in
D minor does. However, in Middle Eastern music, those same minor scales may be used
to express joy. The research, however, suggests that listeners can detect the intended
emotion across musical traditions, supporting the idea of the universality of emotion in
music. For example, Balkwill and Thompson (1999) found that Western listeners could
accurately identify the intended emotion in Indian raga music. Listeners attended to
pitch (lower is sadder, higher is happier) and tempo (slower is sadder, faster is happier)
to find the intended emotion, and these features appear to be universal. Meyer, Palmer,
and Mazo (1998) showed that Western listeners could identify the emotional content of
traditional Russian laments by listening for timbre cues in the singers’ voices. Thus, it
may be that the expression of emotion in music transcends musical traditions.
TEST YOUR KNOWLEDGE
1. What are the features in common between language and music? Do you think
they evolved for similar purposes or different ones?
2. What are minor scales? What do they represent in different cultures?
ISLE 13.18
Bach’s Violin Partita
No. 2 in D minor
©
iStockphoto.com
/arrow
sg
FIGURE 13.22 Santa Maria, Cape Verde, Sal, March 27, 2016
EXPLORATION: Musical Illusions
Our perceptual systems are designed not only to detect
stimuli in the environment but also to extract meaning
from those sensory stimuli. In a sense, this is what music
is—the extraction of patterns and emotional meaning out
of a stream of patterned auditory stimuli. As we have seen
throughout this chapter, what creates music is a pattern in
melody, in harmony, or in rhythm. And as you have seen
throughout this book, when our perceptual systems attend
to patterns, they can be tricked into perceiving patterns
even when elements of those patterns are missing. Music is
no exception. Music perception researchers have identified
and created a number of engaging musical illusions. These
illusions are fun to listen to, but they also tell us about the
underlying structures and functions of musical perception.
392 Sensation and Perception
We will start with one of the more compelling and frus-
trating musical illusions, called Shepard tones after the
researcher who first designed this illusion (Shepard, 1964).
Shepard Tones
In Shepard tones, one hears a scale that sounds as if it
increases in pitch continually. (The illusion can also be
designed so that one hears a scale that sounds as if it
is decreasing in pitch.) Each sound in the scale seems
a bit higher than the one preceding it, but the listener
eventually realizes that the tone one is hearing is back
at the pitch at which the scale started, although all one
hears is increasing pitches (the example on ISLE 13.19
is a must-hear). That is, the pitches sound as if they are
getting continually higher, but in fact, the sound fre-
quencies return back to lower frequencies without our
noticing it in any change from one note to the next.
The illusion can also be run in reverse, with the per-
ception being that the notes get lower and lower, when
actually they do not.
Again, please listen to
t h e d e m o n s t r a t i o n —
in this case, hearing
is believing. How did
Shepard do this?
The illusion is created by simultaneously sweeping dif-
ferent pure tones that are an octave apart. By sweeping,
we mean starting at one note and sliding through all the
intermediate frequencies to another note. Thus, the scale
may start with an A at 220 Hz, and the tone slowly slides
up to an A at 440 Hz. At the same time, there is another
A starting at 880 Hz
and sliding down to
440 Hz. This creates
the illusion of a rising
pitch, even though there is no dif-
ference in the frequencies being
presented (Figure 13.23). In
essence, this is an auditory ver-
sion of the barber pole illusion,
in which the color pattern looks
as if it is continually going up or
going down, despite the obvious
fact that this cannot be occurring
(Figure 13.24).
The Octave Illusion
Deutsch (1974) described the
octave illusion, a phenomenon
she had been studying in her
laboratory. You can listen to the
octave illusion in ISLE 13.20.
It is a stereo illusion, so please
make sure that you listen to it
with headphones on. If you do
not, the illusion will not work
properly. In the octave illusion,
one tone is presented to one ear
while another tone, exactly one
octave higher or lower, is pre-
sented simultaneously to the
other ear. However, the next note
combination is of the same two
notes, but to the opposite ears.
That is, if a middle G is presented to the left ear, and
the G an octave lower is presented to the right ear, the
next notes will be a middle G presented to the right ear
and the G an octave lower presented to the left ear (see
Figure 13.25).
This is an illusion, so think first about what you should hear:
the same note, alternating between ears, and another note
also alternating between ears. It should sound the same, as
the stimuli are the same for both notes, just presented to
different ears. But listen to it on ISLE again. What do you
actually hear? What most people report hearing is the fol-
lowing: You hear a single note (the middle G) in your right
ear followed by a single note an octave lower in your left ear.
And then a continuous alternation between the two occurs,
regardless of which ear the higher G is actually being pre-
sented to. So what you hear differs from what is actually
being presented—hence the term illusion. If you reverse your
ISLE 13.19
Shepard Tones
FIGURE 13.23 Spectrogram of Shepard Tones
The spectrogram shows that the interlacing of rising tones along
with an octave shift down (indicated by yellow arrows) causes the
perception of a gradually increasing sequence in pitch, even though the
actual sequence does not rise in pitch.
ISLE 13.20
Octave Illusion
FIGURE 13.24
The Barber Pole
Illusion
When this barber pole is
set in motion, it looks as if it
continually rises (or falls),
when it actually just circles
back to the same place.
393 Chapter 13: Music Perception
headphones, you get the feeling not that the sounds are com-
ing from different ears, but that the order of notes reverses
(Deutsch, 1975a). Some left-handers may hear the pattern
in reverse, that is, the higher note in the left ear. This illu-
sion is likely due to differences in pitch processing between
the left and right auditory cortices (see Deutsch, 2013). You
can also go to Dr. Deutsch’s website (http://deutsch.ucsd.edu/
psychology/pages.php?i=201) to hear a number of variants
of this illusion.
The Scale Illusion
Deutsch also discovered the scale illusion that shares
several features with the octave illusion (Deutsch,
1975b). Like the octave illusion, the scale illusion has
a different pattern presented to each ear (Figure 13.26).
You should go to ISLE 13.21 to try what you would
hear in each ear separately following the directions
on the ISLE. Each pattern sounds rather random
and violates many of the gestalt principles of hearing mel-
odies that were discussed earlier. Next, try listening with
headphones on both ears and play the sequence. Most peo-
ple hear the patterns shown at the bottom of Figure 13.26.
A descending and ascending scale is heard in one
ear and an ascending and descending scale is heard
in the other ear. In other words, each ear hears
a scale with the direction of the scale in the opposite
direction for each ear. You can figure out how the scales
can be assembled from what is played in each ear if
you start with the first note for the right ear. With this
note you are at the top of a scale. The next note for this
descending scale is found in the second note played but
in the left ear. The third note is back in the right ear, and
so forth.
Refer back to the role of the gestalt principles in the
perception of melody discussed earlier. For example,
proximity and good continuation are important prin-
ciples in hearing a melody amid a whole constellation
of notes. The tunes played in each ear violate both
of these gestalt principles, but our perception follows
both of them very nicely. Compare the two parts of
Figure 13.26 and see how the perception follows the
gestalt laws much better than what is played in each
ear. It seems our need for coherent perception overrides
what ear the sound
arrives in, even when
the sound is limited to
one ear as when head-
phones are used.
ISLE 13.21
Scale Illusion
Sound pattern
Sound perception
= right ear= left ear
FIGURE 13.25 The Octave Illusion
Deutsch (1974) presented one tone to one ear and another tone,
exactly one octave higher or lower, simultaneously to the other ear.
However, the next note combination was of the same two notes, but to
the opposite ears. You hear a single note (middle G) in your right ear,
followed by a single note an octave lower in your left ear.
Fr
om
h
tt
p:
//
de
ut
sc
h.
uc
sd
.e
du
/p
sy
ch
ol
og
y/
pa
ge
s.
ph
p?
i=
20
3
FIGURE 13.26 Scale Illusion
= left = right = 240
(a)
Sound Pattern
(b)
(c)
Perception
From
http://deutsch.ucsd.edu/psychology/pages.php?i=203
394 Sensation and Perception
C
C#
A#
G#
F#
F
E
G
A D#
B
D
FIGURE 13.27 The Pitch Class Circle (Deutsch, 1986)
As you move to the left on the circle, notes sound higher in pitch. As
you move to the right, notes sound lower in pitch.
ISLE 13.22
Tritone Paradox
The Tritone Paradox
This illusion was also discovered by Deutsch (1986). In music,
tritone refers to the half octave, or the interval spanning six
semitones. Thus, in the key of C major, there is one tritone:
If you start on F, you can go up six semitones to B. Similarly,
E and A-sharp are tri-
tones (Figure 13.27).
In the tritone paradox,
Deutsch presents stimuli
generated similar to the way Shepard generated his paradox-
ical scale; that is, each note is an envelope of sound sweeping
from one octave to the next, but with a heard pitch equiva-
lent to the lower note. Thus, in the tritone paradox, Deutsch
played a note with a perceived pitch of C and one with a
perceived pitch of F-sharp, a tritone away (you can hear
this illusion in ISLE 13.22). Here’s the paradox: Some peo-
ple hear the notes as ascending, as in a lower C to a higher
F-sharp, whereas other people hear the notes descending, as
in a higher C to a lower F-sharp. Deutsch even tested musi-
cians and found the same result. Thus, it is good to do this
demonstration in a group, because people will disagree on
what they just heard.
What is the explanation of the individual differences in the
perception of these tritones? Deutsch and her colleagues have
studied it extensively (Deutsch, 2013). It turns out that there
are regional differences in the perception of the tritone par-
adox. One sees a different distribution of hearing the tritone
paradox as ascending or descending whether one is examining
Americans in California or the English in England. Vietnamese
who emigrated to the United States at an early age show
a different distribution of perceptions of the tritone
paradox than do Vietnamese who emigrated later. Deutsch
thinks these differences have to do with the pitches typically
heard in speech for different communities. Vietnamese and
the English show greater variance in their pitch patterns in
speech than do Americans. Thus, this illusion potentially
shows a relation between music perception and speech per-
ception. For more on Deutsch’s work, you can visit her website
or listen to a number of other of her illusions at http://www
.radiolab.org/story/292109-musical-illusions (also linked to
on ISLE 13.22).
APPLICATION: Music Perception
in Hearing-Impaired Listeners
Most everyone knows the story of the great composer,
Ludwig van Beethoven (1770–1827) (Figure 13.28).
Beethoven was a composer, conductor, and piano virtu-
oso. He defined the transition from the Classical era to the
Romantic era in music. However, Beethoven started suffer-
ing from hearing loss in his late 20s. By the age of 40, he was
sufficiently hearing-impaired that he was forced to stop per-
forming and conducting. His knowledge of music, his work
ethic, and his ability to create musical imagery allowed him
to continue composing music even after he could no longer
hear what he was writing. The story of Beethoven is usually
considered uniquely tragic, given the man’s dedication to
music and his subsequent deafness. However, his story is
not unique. Many music lovers experience hearing loss, and
many musicians experience hearing loss, sometimes as a
consequence of their careers as musicians. Indeed, profes-
sional musicians have almost 4 times the risk of hearing loss
compared with people in the general population (Schink
et al. 2014). Many popular musicians today experience
hearing loss, including Peter Townshend, Ozzy Osbourne,
Neil Young, Sting, Phil Collins, Grimes (Claire Boucher),
and will.i.am (of the Black Eyed Peas). These musicians are
395 Chapter 13: Music Perception
all “rockers,” but hearing loss also occurs among classi-
cal musicians (Toppila, Koskinen, & Pykkö, 2011). Other
famous composers such as Bedřich Smetana, Gabriel Fauré,
and Ralph Vaughan Williams all suffered from hearing loss.
In many musicians, the hearing loss may result from pro-
longed exposure to loud music over a long time. The high
decibel level of the sound can cause hearing loss, particu-
larly in the high-frequency range. This may seem obvious in
the case of the rockers, as this form of music is often played
very loudly and with electronic amplification. Classical and
jazz musicians may also be exposed to loud music, both from
their proximity to their own instrument and their proxim-
ity to instruments close by. For example, violinists tend to
show selective hearing loss in their left ears, which is close
to the source of sound in their violin (Royster, Royster, &
Killion, 1991; Schmidt, 2011).
In Beethoven’s time, there was very little that could be done
about hearing loss. Although Beethoven had some residual
hearing, he used a variety of “horns” as hearing aids. The
problem with these horns is that they amplified all sounds
equally, much as early hearing aids did in the past. For a
musician, this only makes the problem worse because being a
musician is as much about hearing differences among sounds
as it is hearing them at sufficient amplitude. A collection of
Beethoven’s hearing aid horns can be found at the Beethoven
museum in Bonn, Germany, if your travels ever take you
there (Ealy, 1994). Today, however, musicians can continue
to perform with the help of digital hearing aids, and some
profoundly deaf individuals can have cochlear implants
adjusted to allow a returned sense of musical enjoyment.
Sensorineural hearing loss is likely to affect the hearing of
some frequencies more than other frequencies. For musicians
exposed to loud music, it is often the high frequencies that
are most impaired. Digital hearing aids can selectively amplify
the impaired range of frequency. Moreover, hearing aids can
be selectively programmed to increase the amplitude of musi-
cally relevant stimuli (Chasin & Hockley, 2014). But increased
amplitude is only the first part of the equation. Music is
played louder than speech and at a greater range of frequency
than most speech, so ideally a hearing aid wearer will have
the flexibility in his or her hearing aid’s programming to have
separate programs for conversation and for music listening.
The listener will want to hear both the low-frequency sounds
of the bass and the high-frequency sounds of the lead singer’s
voice, hence the need for amplification at a greater range of
frequencies than for speech. In addition to the amplification,
the fidelity or sound quality is also crucial to the enjoyment
of music but less relevant for speech perception. Timbre per-
ception is also affected by hearing loss, as high-frequency
components contribute to timbre. If those frequencies cannot
be heard, it interferes with the completeness of the music. As
such, improving the timbre of sound heard through hearing
aids is an issue that needs improvement.
One problem with the sound quality achieved while using
hearing aids is that the processing of the sound signal by the
aids can slow down the transmission of information to the
cochlea. For example, one problem any hearing aid wearer
struggles with is the feedback problem that often occurs espe-
cially when loud sounds are in the environment or when there
is physical contact with the aid. When the hearing aid receiver
picks up the sound the transmitter is projecting, a characteris-
tic whistle occurs, which interferes with all sound perception.
Digital hearing aids have cancelation systems to counteract
feedback, but these may slow down processing, leading the
listener to a smeared or blurred sound rather than a high-clar-
ity fidelity (Chasin & Hockley, 2014). Although many listen-
ers of music might not notice the difference in sound quality,
musicians often do because their training leads them to be
more sensitive to this factor (Zakis, Fulton, & Steele, 2012).
As complex as hearing aids can be, they only amplify sound
and cannot change the frequency tuning of the individual.
With hearing aids, it is still the hair cells of the cochlea that are
actually doing the hearing. When hearing loss affects the outer
hair cells, the frequency tuning of the inner hair cells becomes
greater, meaning the same inner hair cell is responding to a
FIGURE 13.28 Ludwig van Beethoven
Joseph Karl Stieler [Public dom
ain], via W
ikim
edia Com
m
ons
396 Sensation and Perception
range of frequencies (Moore, 2012). This means that no mat-
ter how good the amplification or the tuning from the hearing
aid is, there is going to be a loss of sound quality because
people with sensorineural hearing loss cannot discriminate
among close pitches (or chroma, in musical terms), thus lead-
ing to a less clear sound (Chasin & Hockley, 2014).
An issue for musicians is that most hearing aids automati-
cally dampen sound at loud volumes. This is problematic for
musicians who must be able to hear the correct dynamics,
as played by themselves and musicians in their group. The
dampening of the sound in this way may cause the quality of
the sound to be affected as well. This leads to an odd prob-
lem for musicians with hearing loss because it is their hearing
aid’s design to protect them from loud sounds (which may
have caused their hearing loss in the first place) that is inter-
fering with their ability to play the music correctly. Chasin
and Hockley (2014) review a number of solutions that musi-
cians may use to help them with this problem, including
simply putting tape over the hearing aid so a louder level of
ambient sound is necessary to trigger the dampening. Older
musicians may also switch the instrument they are playing
to one whose range of sound is less in their impaired range.
Because high-frequency sounds are often the first ones lost,
violin players may find they can continue to play music if
they switch to the viola. Clarinet players can focus on their
skill as bass-clarinet players. Chasin and Hockley also review
recent technological advances that will allow musicians to
safely hear these loud sounds without distortion.
Next consider individuals with cochlear implants who wish
to enjoy music again (or for the first time) (Figure 13.29).
Many of the problems that confront hearing aid users
are compounded in cochlear implant users. As with hear-
ing aids, the main function of cochlear implants is speech
perception (Limb & Roy, 2014). If “location, location,
location” is the mantra of real estate agents, then “speech
perception, speech perception, speech perception” is the
mantra of audiologists (we’ve been waiting all book to use
that line). Speech perception involves a much more limited
band of frequencies and a much narrower range of loud-
ness. So programs that work well for speech perception do
not necessarily work well for music listening. The biggest
single difficulty for cochlear implant users is that pitch per-
ception is very poor. Because of the tuning characteristics
of the implanted electrodes, there is just insufficient ability
to distinguish between notes. Because the notes are hard
to distinguish, cochlear implant users have a very difficult
time determining basic musical features such as melody and
harmony (Limb & Roy, 2014). This leads to even further
difficulties in perceiving musical features such as the per-
ceptual integration needed for auditory stream segregation.
However, Limb and Roy claim that with improving technol-
ogies and much training, it is possible for cochlear implant
users to regain some ability to perceive and therefore enjoy
music. In sum, even people with profound hearing impair-
ment can still find enjoyment in the art of music.
FIGURE 13.29 Music and Cochlear Implants
Ja
m
es
K
in
g-
H
ol
m
es
/S
ci
en
ce
S
ou
rc
e
CHAPTER SUMMARY
13.1
Explain how frequency is related to pitch,
chroma, and the octave.
Music is ordered sound made and perceived by human beings
created in meaningful patterns. Humans have been making
music since at least the Stone Age. Pitch is the subjective
experience of sound that is most closely associated with the
frequency of a sound stimulus. Pitch is related to the experi-
ence of whether a sound is high or low, such as the notes at
the far right and far left of a piano. The octave is the interval
between one note and a note with either double the frequency
or half the frequency of that note. Chroma is the subjective
quality of a pitch. We judge sounds an octave apart to be of
the same chroma. In Western music, there are 12 semitones or
12 equivalent intervals or notes within each octave. Western
music also uses an equal-temperament scale in which the
difference between each successive semitone is constant in
pitch and a constant ratio in frequency. Harmony occurs when
two or more notes sound pleasant when played together. In
musical terms, consonance is the perception of pleasantness
Chapter 13: Music Perception 397
or harmony when two or more notes are played; that is, the
notes fit with each other. In contrast, dissonance is the per-
ception of unpleasantness or disharmony when two or more
notes do not fit together.
Pitch is not the only critical aspect of music. Dynamics refers
to the relative loudness and how loudness changes across a
composition. Rhythm is the temporal patterning of the music,
including the tempo, the meter, and the beat. Tempo is the
speed at which a piece of music is played. Meter is the tempo-
ral pattern of sound across time. Beat refers to spaced pulses
that indicate if a piece is fast or slow. Timbre is the complex
sound created by harmonics. Attack is the beginning buildup
of a note. Decay refers to how long the fundamental frequency
and harmonics remain at their peak loudness until they start to
disappear. All of these factors are critical to music.
Melody is the rhythmically organized sequence of notes,
which we perceive as a single musical unit or idea. A scale is
a set of ordered notes starting at one note and ending at the
same note one octave higher. Key refers to the tonic note (e.g.,
C in a C major or minor scale) that gives a subjective sense
of arrival and rest in a musical piece. Transposition allows
more than one version of the same melody, beginning on dif-
ferent notes but containing the same intervals or sequences
of changes in notes. Gestalt principles predict many of the
patterns that determine melody in musical compositions.
13.2
Summarize the basic neuroscience of music,
including how training and experience can affect
the representation of music in the brain.
The neuroanatomy of music is a bit different than the neuro-
anatomy of many other cognitive abilities because music is
in some ways an optional feature of human cognition. Most
prominent are areas in the right temporal cortex, adjacent to
the right auditory regions. One clear finding is that music per-
ception usually causes greater activation in the right tempo-
ral lobe than the left temporal lobe, but we also see activity in
the left temporal lobes and the frontal lobes when perceiving
music. In trained musicians, it has been found that the level
of activation of the left hemisphere increases when listen-
ing to music. Synesthesia is a condition in which a stimulus
in one modality consistently triggers a response in another
modality. Color–music synesthesia occurs when particular
pitches, notes, or chords elicit experiences of particular
visual colors. People with color–music synesthesia show a
greater activation of the tract that connects the frontal lobes
to the auditory cortex. Amusia is a condition in which brain
damage interferes with the perception of music but does not
otherwise interfere with other aspects of auditory process-
ing. Congenital amusia is a condition in which people are
inherently poor at music perception. There is some research
that suggests connections between music and language.
13.3
Discuss how learning and culture affect music
perception.
Music is seen in all cultures, but the music of other cul-
tures differs in systematic ways from Western music. For
example, ragas from India use a 22-note scale instead
of the Western 12-note scale. Moreover, the notes of
the raga scale fall at different frequencies than Western
notes. Shepard tones, the octave illusion, and the tri-
tone paradox are all illusions that illustrate how listeners
extract musical meaning from stimuli, even when it is not
an accurate description of the physical stimuli.
REVIEW QUESTIONS
1. Provide a definition of music. How is musical per-
ception different from other forms of perception, and
how is it similar?
2. What is the relation of pitch to chroma? What is the
octave? And what evidence is there that the octave
is a musical universal?
3. What is meant by consonance and dissonance? How
do they relate to chroma and octaves?
4. What are the differences between tempo, meter, and
beat? How does each contribute to musical perception?
5. What is timbre? What defines the physical differ-
ences that make up timbre? How is timbre used by
musicians to convey meaning or mood?
6. What is a scale? How does it differ from culture
to culture? What starts and ends a scale? What is
meant by transposition?
7. What areas of the brain are critical to perceiving
music? What other areas are needed for musicians?
How does the brain change with musical training?
8. What is synesthesia? What is color–music synesthesia?
What is amusia?
9. How does music differ from culture to culture? In
particular, how does the scale system differ between
Western music and ragas from India?
10. Describe two musical illusions. What are the physi-
cal stimuli? How are those stimuli perceived?
Sensation and Perception398
PONDER FURTHER
1. Music perception necessarily involves experience.
How can researchers distinguish between auditory
processes that are learned versus those that may be
“built” into the brain by studying music?
2. Much of what we have been discussing in this chapter
is the perception of music rather than the production of
music. Performing musicians are engaged in physical
movements. How might such movement affect the per-
ception of music and why?
KEY TERMS
Attack, 379
Beat, 378
Chroma, 375
Color–music synesthesia, 386
Congenital amusia, 386
Consonance, 377
Decay, 379
Dissonance, 377
Dynamics, 377
Equal-temperament scale, 376
Harmony, 377
Key, 381
Melody, 380
Meter, 378
Music, 373
Octave, 375
Rhythm, 377
Scale, 380
Semitones, 375
Synesthesia, 385
Tempo, 377
Transposition, 381
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
13.1 Explain how frequency is related to pitch, chroma, and the
octave.
13.2 Summarize the basic neuroscience of music, including how
training and experience can affect the representation of music
in the brain.
Musical Disorders: From Behavior to Genes
This Is Your Brain. This Is Your Brain on Music
Born to Be Tone Deaf?
Ani Patel Talks About Musical Training and the Brain
Charles Limb: Your Brain On Improv
Daniel Levitin: Music and the Brain
What Color Is Tuesday? Exploring Synesthesia
13.3 Discuss how learning and culture affect music perception. What Can Experiments Reveal About the Origins of Music?
The Development Of The Aesthetic Experience Of Music:
Preference, Emotions, And Beauty
Think Before You Clap: You Could Be Beat Deaf
florin1961 (Florin Cnejevici)/Alamy Stock Photo
14Touch and Pain
Kai Tirkkonen/The Image Bank/Getty Images
LEARNING OBJECTIVES
14.1 Classify how touch perception is actually a number of
senses served by a number of receptor systems.
14.2
Sketch the two main pathways from receptors in the
skin to the somatosensory cortex in the brain.
14.3 Examine the role of endogenous opioids in controlling pain perception.
14.4 Contrast the difference between pain and itch and how they interact.
14.5
Assess the role movement plays in enhancing the perception
of touch, allowing us to perceive objects.
14.6
Illustrate how the vestibular system operates to perceive head rotation and
movement and interact with other senses to help us maintain balance.
INTRODUCTION
Think of many of the things that bring us the most pleasure and the most discomfort.
Think of the relaxation brought by stroking the fur of a sleepy cat. Think of the feeling
of the joy of life when the cool water of a pool rushes around your face as you dive in.
Think of the thrill and the excitement as your lips meet those of your romantic partner.
You will note that all of these desirable experiences occur through our senses that arise
from the skin. Similarly, think of unpleasant sensations, the throbbing pain of a tooth-
ache, the quick pain when you cut yourself while shaving, or the maddening itchiness
of a mosquito bite. You will note here that many of the experiences we deem to be most
negative also occur through the skin senses, mainly the skin sense we know as pain. We
often take our senses related to touch for granted, but in reality, they are essential in
many ways. Take a look at Figure 14.1 and see if you can imagine how these various
surfaces would feel to your skin. Luckily, we have very poor imagery for pain, so it is
hard to conjure up the experience of a toothache without actually having one.
The touch senses are different in an important way from the already discussed vision
and audition. Vision, audition, and olfaction can work at a distance and are sometimes
called distal senses. For example, I can see the boat on the lake even though it is a half
mile away, I can hear the barking of the dogs even though they are across the street, and
ISLE EXERCISES
14.1 Action of
Mechanoreceptors
14.2 Mechanoreceptors
and Aristotle’s Illusion
14.3 Heat Grille
14.4 Somatosensory
Pathways
14.5 Melzack and Wall’s
Gate Control Theory
14.6 Professor
Ramachandran and
Phantom Limb Syndrome
14.7 Treatment of
Phantom Limb Pain
402 Sensation and Perception
FIGURE 14.1 Somatosensory Experiences
Imagine what each of these would feel like on your skin. Some of these may be touch experiences we long
for, whereas others may be perceptions we would prefer to avoid.
I can smell the cookies baking in the other room. Touch is more intimate; it requires direct
bodily contact and preferably contact and bodily motion. Sometimes touch and its related
sensations are called proximal senses. As such, touch is interactive. It is often quite diffi-
cult to detect whether a surface is smooth or rough using a nonmoving finger. We move
our fingers and the rest of our skin to sense surfaces. Thus, from the very beginning of our
discussion of the touch senses, we will need to consider movement of the body as well.
Here is another thought about the importance of our touch systems. Think about
waking up in the middle of the night and feeling very hungry. You do not want to wake
anyone else up, so you decide not to turn the lights on. Without visual or auditory cues,
you can feel your way from your bedroom into the kitchen, find the cutlery drawer and
remove a fork, feel the piece of cake that was left on the counter from dessert earlier
in the evening, and enjoy your midnight snack alone in the dark. You do all these tasks
that you might normally do with visual guidance by using your touch senses alone. You
may move about the house a bit more slowly as you feel your way along the wall, but
you can probably do this without stumbling. If you have midnight snacks too often,
you may need to go on a diet, but the point is, we can feel our way around familiar
environments without the use of sight.
Before we begin our discussion of the details of our touch senses, we will note we are
using the plural to describe these senses. Properly speaking, there is not a single sense
of touch, but several somatosensory senses, that is, those sensations that arise from the
skin, muscles, and other interior senses. Just as an aside, soma in the word somatosen-
sory means “body,” so these senses are intimately connected to our body and inform
our brain about events in and on our body. There are different kinds of receptors in
our skin to detect light pressure, deep pressure, pain, coldness, and heat. There are also
receptors within our muscles that help us regulate the position of our body, which we
also consider in this chapter. This chapter also considers the vestibular system, which
is not a somatosensory system, per se, but we examine it here to ensure that we cover
©
iS
to
ck
ph
ot
o.
co
m
/W
1z
za
rd
©
iS
to
ck
ph
ot
o.
co
m
/h
av
es
ee
n
©
iS
to
ck
ph
ot
o.
co
m
/e
so
lla
©
iS
to
ck
ph
ot
o.
co
m
/C
Pa
ul
us
se
n
403 Chapter 14: Touch and Pain
all the sensory systems in this book. In addition, stimulation for this sense results from
the motion of our body, in particular, our head, so it fits in a broad way. The vestibular
system is rather unique in that, unlike the other senses we consider here, we are not usu-
ally aware of its functioning. We also include a diversion into the realm of nonhuman
animal senses in this chapter. The Exploration section is about electroreception in fish.
THE SKIN AND ITS RECEPTORS
14.1
Classify how touch perception is actually a number of
senses served by a number of receptor systems.
If you are ever on a game show, and you
are asked the following question, you
will now get it right and win thousands
of dollars: What is the heaviest organ
of the body? The answer is the skin,
which weighs in at more than 4 kg (9
lb). The skin can be considered the sense
organ of touch, much as the eyes house
the visual system receptors and the ears
house the auditory receptors. Touch
receptors exist everywhere on the sur-
face of the skin, though not necessarily
in a uniform fashion. Touch receptors
are closely grouped on your fingers and
lips and less closely grouped on your
upper back, legs, and arms. There are
also touch receptors inside your mouth
and on your tongue.
The skin is a complex organ com-
posed of differing layers, despite its
familiar surface features. Many touch
receptors are located just below the
outer layer of skin, called the epidermis.
The epidermis is interestingly avascu-
lar, as it draws oxygen directly from
the air rather than from the blood-
stream. The epidermis is thickest on
our palms and the soles of our feet,
and it is thinnest on our eyelids. In
addition to its sensory functions, the
epidermis functions to keep out pathogens and keep in fluids. Indeed, it is composed
mainly of dead cells that protect the dermis below. Below the epidermis is the dermis,
which houses most of our touch receptors. To help you keep track of terms, epi means
“above” or “on top of,” so the epidermis is above the dermis. The dermis also holds the
connective tissue and has a blood supply. Skin can also be divided into hairy skin, that
is, skin with hair growing on it, and glabrous skin, which is hairless skin. Glabrous skin
can be found on the palms and fingertips and the soles of our feet and bottoms of our
toes. The anatomy of the skin is depicted in Figure 14.2.
Meissner’s
corpuscle
Free nerve
ending
Merkel’s discs
Pacinian corpuscle
Ruf ni ending
Hairs
FIGURE 14.2 Touch Receptors in a Cross-Section of Skin
This illustration shows the dermis, the epidermis, and the different types of nerve endings found
in the skin.
Epidermis: the outer layer of
the skin
Dermis: the inner layer of the
skin, which also houses touch
receptors
404 Sensation and Perception
Mechanoreception
Touch perception occurs when the skin is moved or touched. This includes indentation,
such as when a finger presses against your skin; vibration, such as when you touch an
active electric toothbrush; and stretching, such as when someone scratches your back
or pulls on your skin. Such mechanical stimulation of the skin activates one or more
of the four types of mechanoreceptors in your skin. Mechanoreceptors are sensory
receptors in the skin that transduce physical movement on the skin into neural signals,
which are sent to the brain. Now, take a deep breath, as we need to get a bit technical
and introduce some jargon. There is no avoiding it—touch perception is complex, with
multiple kinds of receptors, each with a multisyllabic name. Take your time and repeat
the material until you feel comfortable with the terms.
The four types of mechanoreceptors are called SAI mechanoreceptors, SAII mech-
anoreceptors, FAI mechanoreceptors, and FAII mechanoreceptors. Each mechanore-
ceptor differs on a number of relevant dimensions, which are important to producing
a complex touch response. The mechanoreceptors are distinguishable anatomically and
also in terms of their functional capacities. SA stands for “slow-adapting,” whereas
FA stands for “fast-adapting.” The mechanoreceptors labeled with a Roman numeral I
have small receptive fields, whereas the II receptors have larger receptive fields. As you
read through these distinctions, think about how they map onto other sensory distinc-
tions, such as the differences between the magnocellular tract and the parvocellular
tract in vision.
The slow-adapting mechanoreceptors (SAI and SAII) produce a steady stream of
neural response when the skin is deformed, that is, a sustained response that continues
for as long as the skin is stimulated. This is important because we want to know if there
is continued pressure on our skin, such as when someone is holding your arm. The
fast-adapting mechanoreceptors (FAI and FAII) respond vigorously when the skin is
first touched and then again when the stimulus ends. This is important because it gives
us information about changes on our skin—when something contacts us and when it is
no longer in contact with us. However, if the pressure continues, FA mechanoreceptor
responses lessen and do not increase until the stimulus is over. Thus, the SA mecha-
noreceptors tell us about continued pressure on the skin, such as the constant contact
between our skin and our shirts. The FA receptors give us information about the begin-
ning and ending of touches and about temporary stimulation of the skin, such as when
that annoying mosquito lands on our arm.
The SAI and FAI receptors have relatively small receptive fields with densely packed
receptors. This gives them high spatial resolution, allowing us to detect exactly where on
the skin a stimulation occurs. That is, SAI and FAI fibers help us detect small objects and
pinpoint objects on our skin. Again, this is useful for detecting the location of the mos-
quito on the skin and for fine manipulation of objects, such as when we thread a needle.
Both SAI and FAI mechanoreceptors are close to the skin’s surface.
In contrast, the SAII and FAII mechanoreceptors are deeper in the skin. The SAII and
FAII receptors have larger receptive fields with more dispersed mechanoreceptors. This
means that their spatial resolution is not as good as the SAI and FAI mechanoreceptors,
but they have a lower threshold or higher sensitivity to light touch. Thus, they help us
feel very light touches, as they sum across space, but they are not as precise at determin-
ing where on the skin these touches occur. Thus, when an entire hand brushes against
our arm, the SAII and FAII mechanoreceptors let us know that our arm is being moved.
These differences are summarized in Table 14.1. You can see a video of the actions of
the mechanoreceptors on ISLE 14.1. We now review each mechanoreceptor’s structure
and function.
Mechanoreceptors: the
sensory receptors in the
skin that transduce physical
movement on the skin into
neural signals, which are sent
to the brain
SAI mechanoreceptors:
slow-adapting receptors
using Merkel cells, with small
receptive fields, densely
packed near the surface of
the skin
SAII mechanoreceptors:
slow-adapting receptors using
Ruffini endings, with large
receptive fields, more widely
distributed, deeper in the skin
FAI mechanoreceptors:
fast-adapting receptors, with
Meissner corpuscle endings
and small receptive fields,
densely packed near the
surface of the skin
FAII mechanoreceptors:
fast-adapting receptors with
Pacinian corpuscle endings
and large receptive fields,
more widely distributed,
deeper in the skin
Meissner corpuscles:
specialized transduction cells
in FAI mechanoreceptors
Pacinian corpuscles:
specialized transduction cells
in FAII mechanoreceptors
Merkel cells: specialized
transduction cells in SAI
mechanoreceptors
ISLE 14.1
Action of Mechanoreceptors
405 Chapter 14: Touch and Pain
SAI Mechanoreceptors
SAI mechanoreceptors, using Merkel cells, have a
sustained response to continued pressure, giving
them maximum response to steady pressure. They
have small receptive fields and thus have high
spatial sensitivity. They respond best to vibrations
at low frequencies. They are important for the
touch perceptions of pattern and texture. Because
of their high spatial sensitivity, SAI mechanore-
ceptors are responsible for two-point thresholds,
that is, the minimum distance at which a person
can detect two touches instead of just one (Figure
14.3). Thus, these cells are important when we
need fine manual control, especially without
visual feedback. SAI mechanoreceptors are also
critical for blind individuals reading Braille. Two-
point threshold responses vary across the skin’s
surface. Where it is most sensitive, such as on the fingertips and lips, we find the highest den-
sity of SAI mechanoreceptors. Where it is least sensitive, such as on the back and legs, we find
the lowest density of SAI mechanoreceptors. For a discussion and illustration of the relation
of SAI mechanoreceptors and the Aristotle
illusion, see ISLE 14.2.
SAII Mechanoreceptors
SAII mechanoreceptors, using Ruffini end-
ings, have a sustained response to contin-
ued pressure, also giving them maximum
response to steady pressure. However, they
are also good at stretching from side to
side, making them crucial for object grasp-
ing. Thus, when you pick up your spoon to
eat your soup, your SAII mechanoreceptors
will be critical. SAII mechanoreceptors have
much larger receptive fields than SAI mech-
anoreceptors, and so they are more vital for
detecting the presence of a light touch than
for pinpointing where it occurs.
FAI Mechanoreceptors
FAI mechanoreceptors respond to the
onset and offset of a stimulus, that is, when
a stimulus starts and ends. These mecha-
noreceptors with Meissner corpuscle end-
ings also have small receptive fields for
good spatial accuracy. They also respond
well to low-frequency vibrations. They are
especially good at detecting “slip,” that is,
when an object is sliding across the surface
of the skin. As such, they are useful in avoiding dropping objects, as they detect an
object as it begins to slip away from your hands. These mechanoreceptors are also
FIGURE 14.3 A Model of the Body’s Two-Point Threshold Response
In this diagram, a person is touched at two points on the skin or one point on the skin. The
person must determine if there is one point or two points of touch. Sensitivity to two-point
touch is better in parts of the body with higher densities of SAI mechanoreceptors. Two-
point thresholds are better on the fingers than on the back.
TABLE 14.1 Mechanoreceptors: Types and Response Properties
Fast Adapting Slow Adapting
Small receptive
field
Larger receptive
field
Small receptive
field
Larger receptive
field
FAI FAII SAI SAI
Meissner
corpuscles
Pacinian
corpuscles
Merkel cells Ruffini endings
High spatial
resolution
Low spatial
resolution
High spatial
resolution
Low spatial
resolution
Upper dermis Lower dermis Upper dermis Dermis
Medium
sensitivity to
temperature
variation
High Low Low
Perceiving
change
Fine texture Patterns Stretch/feedback
ISLE 14.2
Mechanoreceptors and
Aristotle’s Illusion
406 Sensation and Perception
critical in maintaining grip for sports. For example, when a baseball hits a bat, the force
causes slippage of the grip on the bat by the batter. FAI mechanoreceptors detect this
slip and cause us to tighten our grip on the bat.
FAII Mechanoreceptors
FAII mechanoreceptors also respond to the onset and offset of a stimulus. They have
Pacinian corpuscle endings and larger receptive fields, as they are less densely packed in
the skin. They are also more sensitive to higher frequency vibrations. Experientially, when
FAII mechanoreceptors are firing, what we feel is more of a buzz than for the other mech-
anoreceptors. Because of their high sensitivity to touch, they are helpful in feeling small
pressure on the skin, such as when an insect lands on our skin. These mechanoreceptors
are also used when we use fine motor control, such as when writing with a pen or tighten-
ing a screw with a small screwdriver.
The names of the receptive cells in each of these types of mechanoreceptors are given in
Table 14.1. In all four types of mechanoreceptors, the mechanical movement of the ending
of the receptor induces a neural signal, which is sent first to the spinal column and then to
the brain. The nerve fibers from the mechanoreceptors are myelinated, which allows fast
transmission of these signals. Interestingly, a new kind of unmyelinated mechanoreceptor
has been discovered (Olausson, Wessberg, Morrison, McGlone, & Valbo, 2010). This new
fifth mechanoreceptor is known as the C-tactile mechanoreceptor. C-tactile mechanorecep-
tors are present only in hairy skin and respond to slow gentle movements on the skin. When
stimulated, C-tactile mechanoreceptors induce a pleasant feeling. C-tactile fibers project to
the insular cortex, which also receives input from pleasant tastes and odors.
TEST YOUR KNOWLEDGE
1. Why is it said that the skin senses are a set of multiple senses rather than a
single sense?
2. Describe the difference between slow-adapting and fast-adapting
mechanoreceptors. How is each important for perceiving different aspects of
the perceptual world?
Proprioception: Perceiving Limb Position
Proprioception is perhaps our most unique sense, as it is designed to monitor not the
external world but the internal world. The mechanoreceptors, the rods and cones of our
retinae, and the hair cells of our cochleae in our auditory system are all designed to pick
up features external to us, whereas proprioception gives us our awareness of how our
own bodies are positioned. Thus, you do not have to see your arms to know that they
are in front of your torso, extended outward (doing what you normally do—playing with
your phone). You also do not need to see or even feel your feet touching the floor to know
that your legs are below you and that you are in a sitting position. We define proprio-
ception as the perception of the movements and position of our limbs. You may also see
the term kinesthesis, which refers to our awareness or perception of bodily movements.
There are three different kinds of sensory receptors in our bodies that provide us with
information about limb movement and position. They are the muscle spindles, joint recep-
tors, and Golgi tendon organs. We consider each in turn. Muscle spindles are a type of mus-
cle cells that have receptors connected to them that sense information about muscle length
and therefore muscle action. As muscles contract and lengthen, different neural signals are
transduced in the spindles, giving the brain information on muscle length and stretch. Joint
receptors are receptors found in each joint that sense information about the angle of the
joint. This provides the brain with information about how far the limb is stretched and
Ruffini endings: specialized
transduction cells in SAII
mechanoreceptors
Proprioception: the
perception of the movements
and position of our limbs
Muscle spindles: receptors
embedded in the muscles
that sense information about
muscle length and therefore
muscle action
Joint receptors: receptors
found in each joint that sense
information about the angle of
the joint
407 Chapter 14: Touch and Pain
whether it can be stretched any farther before it must
be contracted. Golgi tendon organs are receptors
in the tendons that measure the force of a muscle’s
contraction. Because force will be a function of how
many muscle fibers are used, Golgi tendon organs
can provide feedback as to how much more force
has been applied by that muscle (see Figure 14.4). In
Figure 14.4, the afferent fibers are the sensory fibers
carrying information to the brain.
Because proprioception is directed inward, we
seldom consciously focus on it. Rather, we take it
for granted that we are aware of the position of our
body, how much force we are asserting, and what
muscles are moving. However, if we did not have
Golgi tendon organs, we might not be able to gauge
whether we are applying enough muscle strength
to lift weights at the gym or if we are applying too
much muscle strength when we intend to be gently
patting a friend on the back. We can be thankful for
these receptors when we do not break any bones in
the fingers of our friends as we shake their hands.
When a limb is under physical pressure and blood is
temporarily cut off, we may have the experience of
an arm or leg “going to sleep” and we cannot feel the
location of the limb. If one arm has fallen to sleep,
you might need to move your other arm to find it.
This feeling is caused by a temporary inability of the
proprioception system to detect limb position.
Alcohol consumption affects our proprioception
system, making it harder for our sensory receptors to
give feedback on limb position. It is for this reason that
one of the main tests police administer for sobriety is
a proprioception test. When a driver is suspected of
driving under the influence of alcohol, a field sobriety
test is given. One of these tests is to ask the driver
to touch her nose with eyes closed (Figure 14.5).
Inaccuracy in this test suggests that alcohol con-
sumption has compromised the functioning of the
proprioception system.
TEST YOUR KNOWLEDGE
1. What is meant by proprioception? What deficits would a person have if that
person lost his proprioception systems?
2. What are the differences between muscle spindles, joint receptors, and Golgi
tendon organs?
Thermoreception
We are warm-blooded animals, which means that, to survive, we must keep our internal
temperature fairly constant. But internal temperature is influenced by the temperature
of our environment. If you live in a part of the world that has cold winters, think about
Muscle fibers
Afferent
nerve fiber
Tendon
Muscle
spindle
Muscle
fiber
Afferent
nerve fiber
Efferent
nerve fiber
Capsule
Capsule
Joint
Joint receptors
Tendon
Muscle
FIGURE 14.4 Sensory Receptors for Proprioception
This anatomical drawing shows where one can find muscle spindles, joint
receptors, and Golgi tendon organs.
Yellow
D
og Productions/The Im
age Bank/G
etty Im
ages
FIGURE 14.5 Testing for Sobriety
The touching the nose test assesses if the proprioception system has been
impaired by alcohol consumption.
Golgi tendon organs:
receptors in the tendons
that measure the force of a
muscle’s contraction
Afferent fibers: neural fibers
that carry sensory information
to the central nervous system
408 Sensation and Perception
stepping outside when you leave your home for school or work. The wind and cold
seem to bind to your face, you shiver, and you pull your coat a little tighter around your
body. Compare this with the feeling of leaving your air-conditioned hotel on a summer
visit to Phoenix, Las Vegas, or some other very hot and very dry climate. Here, it is the
heat that stings you. Few people would mistake one experience for the other.
Thermoreception is the ability to sense changes in temperature on the skin. This can be
passive, as when cold air blows against your face on a winter’s morning, or it can be active, as
when we touch another’s forehead to determine if that person has a fever. Obviously, thermo-
reception has an important function: Being able to sense temperature is critical for survival.
Imagine not being able to sense cold and going out into an Arctic blizzard in a swimsuit.
Or imagine not being able to sense how hot it
is in the Nevada desert in July and wearing a
winter coat. In each case, the lack of thermo-
reception could have deadly consequences. We
must maintain our internal body temperature,
and this is why having a fever is an illness.
Thermoreceptors are the sensory recep-
tors in the skin that signal information
about the temperature as measured on the
skin. Thermoreceptors respond to a range
of skin temperatures, from 17 °C (63 °F) to
43 °C (109 °F). This is the range of tempera-
tures experienced by our skin, not the actual
ambient temperature. Thus, the weather may
be colder than 17 °C or hotter than 43 °C, but
our bodies are designed to regulate the condi-
tions in and on our bodies. Skin temperatures
above 43 °C and below 17 °C are experienced as pain. In general, our skin maintains a
surface temperature between 30 °C and 36 °C (86 °F and 97 °F). This temperature range is
sometimes called physiological zero, as you feel neither hot nor cold. At these temperatures,
our thermoreceptors are mostly inactive. However, when the temperature goes below 30 °C,
our cold fibers become active, and when the temperature rises above 36 °C, our warm fibers
become active. If you are inside wearing a thick sweater and sitting by a warm open fire,
your skin temperature will increase, and your warm fibers will start firing. If you take off
your sweater and go out into the blizzard, your skin will rapidly decrease in temperature, and
your cold fibers will start increasing their firing rate. Cold fibers are thermoreceptors that
fire in response to colder (30 °C and below) temperatures as measured on the skin. Warm
fibers are different thermoreceptors that fire in response to warmer temperatures (above 36
°C) as measured on the skin. At intermediate temperatures, both fibers show a steady firing
rate. They differ when the temperature rises above 36 °C or falls below 30 °C (Figure 14.6).
Cold and warm fibers also respond when you touch objects that are either colder
or warmer than the temperature of your skin. For example, when you remove the ice
cream container from the freezer, the surface of the ice cream container will feel cold
because the temperature of the container is lower than that of your fingers, causing your
cold fibers to fire. When you pick up your hot mug of coffee, the mug feels hot because
it is causing warm fibers to fire. Both cold and warm fibers also adapt, somewhat, to
new temperatures. Thus, when you first jump into a pool, the water, which is colder
than your skin, triggers responses in the cold fibers. But after a couple of minutes, your
cold fibers adapt, and the pool no longer feels quite so cold.
Interestingly, your warm fibers have a secondary peak in sensitivity when they are
exposed to very low temperatures. This is also known as a paradoxical heat experience
because it is brought about by contact with extremely cold temperatures. The temperatures
Cold
�bers
10
0
2
4
6
8
10
20 30 40 50 60
Warm
�bers
Nerve fiber temperature (°C)
Im
p
u
ls
e
s
p
e
r
se
co
n
d
FIGURE 14.6 Rate of Firing in Response to Skin Temperature
(Guyton, 1991)
Graph of firing rates of cold and warm nerve fibers.
Thermoreception: the
ability to sense changes in
temperature on the skin
Thermoreceptors: the
sensory receptors in the skin
that signal information about
the temperature as measured
on the skin
Cold fibers: thermoreceptors
that fire in response to
colder (30 °C and below)
temperatures as measured on
the skin
Warm fibers:
thermoreceptors that fire
in response to warmer
temperatures (above 36 °C) as
measured on the skin
Pain: the perception and
unpleasant experience of
actual or threatened tissue
damage
409 Chapter 14: Touch and Pain
are so low that they also induce pain responses. Nonetheless, some of you may have expe-
rienced this during minor medical treatment. If you have ever had a skin abnormality, such
as a wart, treated with liquid nitrogen, you know the experience of paradoxical heat. Liquid
nitrogen is kept at about –200 °C (–328 °F). When it is applied to our skin, however, we
feel pain and heat, not coldness, because of this secondary peak for the warm fibers. Some
Antarctic explorers have also described feeling paradoxical heat when being buffeted by
160 km/h winds in –60 °C cold. See ISLE 14.3 for instructions on a safe way to demonstrate
this phenomenon to yourself.
TEST YOUR KNOWLEDGE
1. What is thermoreception?
2. Why is it likely that animals, such as ourselves, evolved to have two separate
systems, one for detecting cold and one for detecting heat? What advantages
does this have over a single-receptor system that simply detects temperature,
much as a thermometer might?
Nociception and the
Perception of Pain
Pain is the perception and the unpleasant experience of
actual or threatened tissue damage (Figure 14.7). Thus,
pain is the result of activation of receptors in our skin and
elsewhere, as well as the unpleasant subjective feeling asso-
ciated with it. As we will see in this chapter, pain can arise
from several different causes and may be accompanied by
emotional distress that may act to increase the experience
of pain. In this section, we focus on the sensory receptors in
the skin that transduce a neural signal, causing an experi-
ence of pain in the affected area. This type of pain is called
nociceptive pain. Nociceptive pain is the pain that devel-
ops from tissue damage that causes nociceptors in the skin
to fire. This type of pain occurs from direct trauma to the
skin, such as from cutting, puncturing, pinching, heating, freezing, or coming in con-
tact with toxic chemicals (ouch!). These types of events cause nociceptors in the skin
to fire, leading to a signal to the brain. Nociceptors are sensory receptors in the skin
that, when activated, cause us to feel pain. They are found in both the epidermis and
dermis. Although we focus on the nociceptors in the skin, there are nociceptors in many
other areas of the body, including muscle, bone, and the digestive system. There are also
other forms of pain, such as inflammatory pain, in which an inflamed or swollen region
causes changes in nearby nociceptors. Neuropathic pain occurs when the nervous system
itself is damaged. Nociceptors are anatomically distinguishable from other skin recep-
tors. Nociceptors are often referred to as free nerve endings because of their anatomical
appearance (Figure 14.8).
Nociceptors are divided into two main types: A-delta fibers and C-fibers. A-delta
fibers are myelinated, so they conduct signals rapidly and respond to both heat and
pressure, both of which can induce pain. C-fibers are nonmyelinated and hence much
slower; they respond to pressure, extreme degrees of either heat or cold, and toxic
chemicals. The signals from both of these free nerve endings are experienced as pain.
A-delta fibers are associated with the stinging feeling of pain. This stinging pain is often
what we experience first when we are injured. C-fibers are associated with the more
chronic experience of throbbing pain (Williams & Purves, 2001). This pain may be a
ISLE 14.3
Heat Grille
FIGURE 14.7 Pain Is Unpleasant
We experience pain as a result of threatened or actual tissue damage.
Corey Rich/A
urora/G
etty Im
ages
Nociceptive pain: pain that
develops from tissue damage
that causes nociceptors in the
skin to fire
Nociceptors: sensory
receptors in the skin that,
when activated, cause us to
feel pain; they are found in
both the epidermis and the
dermis
A-delta fibers: myelinated
nociceptors that conduct
signals rapidly and respond to
both heat and pressure
C-fibers: nonmyelinated
nociceptors that are slower
and respond to pressure,
extreme degrees of either heat
or cold, and toxic chemicals
410 Sensation and Perception
bit delayed from the actual accident. Think
about touching a hot stove top. You first get
a searing pain, and you quickly move your
hand away from the hot surface. This sear-
ing pain is the result of the fast action of the
A-delta fibers. After you start treating your
injury, you start to feel continued dull throb-
bing in your finger, which is the result of the
C-fiber response (see Figure 14.8 for a figure
showing the nociceptors).
It probably has crossed every human
being’s mind at one time or another how
much better life would be if we did not expe-
rience pain at all. Certainly, anyone who has
experienced serious pain can identify with
the wish not to have pain at all. Something
as seemingly simple as an infected tooth can
cause excruciating and debilitating pain, as
anyone who has ever gone through a root
canal can tell you. We certainly pay a great
deal of money as a society to reduce and
control pain. However, the argument can be
made that pain serves an important evolu-
tionary function, by alerting an organism
to tissue damage, allowing it to take steps
to minimize or repair the tissue damage or
move away from the source of that damage. Through evolution, pain evolved pre-
sumably because organisms that moved away from sources of pain were more likely
to survive than those that did not. When we do not experience pain, we might not act
to avoid these consequences. Indeed, Melzack and Wall (1988) described a case of a
human patient lacking in nociceptors. This woman experienced numerous avoidable
injuries because she lacked pain perception. These injuries included burns from not
removing her hand from a stove top, biting her own tongue, early joint problems, and,
ultimately, death from curable infections.
TEST YOUR KNOWLEDGE
1. Describe the differences between A-delta fibers and C-fibers. How does each
contribute to the perception of pain?
2. Develop a diagram that relates different receptors to different sensations
arising from the skin.
NEURAL PATHWAYS
14.2
Sketch the two main pathways from receptors in the
skin to the somatosensory cortex in the brain.
In May, off the coast of the Dominican Republic, boats can take you out to go free div-
ing with the humpback whales that migrate close to the shores of that country. Diving
with some magnificent creatures is an amazing experience, as humans are dwarfed by
Pacinian corpusclePacPacPacPacPacPacPacPacPacPacacPacPacPacPacaPacPacPacPacPacPacPacPacacPacPacccPacPPacPaPacPacPacPacacPacPPPacPacPPacPaPPacPPaccPPacPPaPaPacaaPacPacPaPacccacccciniiniiniinnnniiniiniiniiniiniiniiniiniiniinininininiiininininnnniniiniinnninnnninniii iiiniiniinnnnniniinnninnnniinnnnnnianaan ananananannanannananananaaaaaanan anaaaaaaaanananananaaananaaaannnan an anananaaannnnananananaan nnnnannanaanann ananannanan aanaan annnannnaaaaannannnaaannnan aaaaaaanaaannannn anaaannnnaaannannaan aannannaaan nnnnn anannnnnannnnaaa corcorcorcorcorcorcorcorcorcccorcococorcorcococorcoroocorcorrorcororcorcocorccccocoococorcororcorcorcorcorcorcorcorccorccoccooocorcorrcorcorcorcorcorcorccorcocccoorrcorcocorccorcocccorcororrcocorccocorrrcoccccccocorrorcococcocccocorcoooorrcorcoccccooroorccccc rcccccocoorcccccocororccccoooorcccccccoooorcccoroooooorcccoooccocooooo puspuspuspupppuspuspupuspuspuspupuspuspuspuuuupuspuspuspuspuspuspuspuspuspuspuspuspuupuspuspupupupuuupuuuspuupuspuspuppususpuupuspuspusppupupuspuspuspuspuspuupusppupuppuupuupuspppppupuuupussusppppppppuuuupupuuuuppuuuupppp cleclecleeclecleclecleclecleclecleclecleclecleclelecleclecleclcleclecleclecleecleclecleclecleleeecleleeeeecleclleleeecleleeelcleclecleclllclleccleeecleleecc
Nociceptors
FIGURE 14.8 Nociceptors in the Skin
Nociceptors are located just below the epidermis, in the dermis. Nociceptors are
activated when tissue is damaged, leading to the experience of pain.
Dorsal root ganglion: a node
on the spine where one finds
nerve cells carrying signals
from sensory organs toward
the somatosensory areas of
the brain
Dorsal root: the end of the
spinal nerve where sensory
information enters the spinal
cord
Ventral root: the end of the
spinal cord where motor
information leaves the
spinal cord
411 Chapter 14: Touch and Pain
the incredible size of these whales, which can exceed 16 m
(52 ft). You can swim right up to these creatures, which do
not see divers as a threat and are sometimes curious about
their presence. You are not supposed to touch the animals at
all, but what would happen if you brushed against the tail
of a whale (Figure 14.9)? Given the distance between the
whale’s tail and the whale’s brain, it would take upward of
a second for the whale to feel your touch. That is, if instead
of a gentle brush, you pricked the tail with a pin, it would
be nearly a second before the whale experienced pain (Hof
& van der Gucht, 2007). Of course, reflex circuits would
cause the whale to swish its tail away from you much ear-
lier, hopefully filling your mouth and mask with seawater
(after all, you pricked the whale’s tail).
In humans, the distance nerve fibers must travel is much
less than in whales, but it is still much farther for touch and
pain than it is for sensory systems already arranged in the
head (vision, audition). For a tall person,
it may still be 2 m (6 ft 6 in.) from toes to
somatosensory cortex. Thus, when you stub
your toe, the neural message has a greater
distance to travel than when someone yanks
your ear or when light hits your retinae. As
a function of this distributed feature of the
somatosensory system, we see some major
differences, too, in the pathways for these
senses arising from the skin and body. All
right, now, get your attention in gear, as we
start with the complex anatomy involved
in transmitting the neural signals for touch,
temperature, and pain from the skin to the
brain. We will also consider the areas of the
brain responsible for the touch senses and
pain.
Starting with the neural pathways,
consider a nerve ending in the skin of
the palm of your hand. This nerve end-
ing sends its axon into a nerve bundle,
where it is joined by many other axons
from adjacent nerve fibers. These neurons
are oddly constructed. The part of the cell
that has the nucleus is not at the beginning
of the neuron but just before it enters the
spinal cord, in what is called the dorsal
root ganglion. The cells enter the spinal
cord in what is called the dorsal root (the
ventral root transmits information to the
muscles). The dorsal root forms one of the
two branches of nerves that enter and leave the spinal cord (Figure 14.10). The axons
of the sensory cells that pass through the dorsal root enter the dorsal (i.e., back) part
of the spinal column. (You can see an interactive model of how our touch and pain
senses enter the spinal cord in ISLE 14.4.) Just to help you keep track of directions,
FIGURE 14.9 A Whale’s Tail
A humpback whale’s tail may be as far as 16 m from its brain. Thus,
the neural signal that occurs when the diver touches the tail may take
nearly a second to reach the somatosensory cortex of the whale.
©
iStockphoto.com
/ShaneG
ross
ISLE 14.4
Somatosensory Pathways
FIGURE 14.10 The Dorsal Root Ganglion
Nerve fibers from nociceptors enter the dorsal root ganglion. In this illustration, you can
see the anatomy of the ganglion and its exit route into the spinal column.
Sensory neuron
to brain
Dorsal root
Dorsal root
ganglion
Sensory neuron
from hand
Spinal
neuron
Biceps muscle
Ventral
root
Motor
neuron
Interneuron
Ventral
horn
Motor neuron
from brain
412 Sensation and Perception
dorsal refers to back and ventral refers to
front, when we are talking about our body
as a whole.
Once in the spinal column, this somato-
sensory information is divided into two
distinct tracts or pathways, which travel
up the spinal column to the brain. It is
important to keep these two tracts distinct,
as they serve different functions, and carry
different sensations. Both the anatomy and
the terminology are tricky. So, stay with the
text and review the text and figures often.
You can also follow along on ISLE 14.4
to help you learn about these different
pathways. One tract is called the dorsal
column–medial lemniscal pathway; this
pathway carries information from the
mechanoreceptors (i.e., tactile perception)
and from the proprioceptors (i.e., muscle
position perception). The other track is
called the spinothalamic pathway, and it
carries information from the nociceptors
(pain) and the thermoreceptors (tempera-
ture). The names are a mouthful, but the
anatomy is tricky too. The dorsal column–
medial lemniscal pathway travels on the
dorsal (remember, the back) side of the spi-
nal column and on the ipsilateral side of
input from the skin (the same side as the
input from the body). The dorsal column–
medial lemniscal pathway makes a synapse
in the medulla of the brain, where it crosses
over to the contralateral side (the opposite
side of the input from the body). It then ascends into the brain as the medial lemnis-
cus. From the medulla, it travels to the ventral posterior nucleus of the thalamus and
from there to the somatosensory cortex (see Figure 14.11 for a graphical display of
this tract).
The spinothalamic pathway’s fibers first synapse in the spinal cord and then cross
over to the contralateral side within the spinal column and then ascend toward the
brain. That is, information from the left side of the body travels up the right side of
the spinal cord in the right spinothalamic pathway, and information from the right side
of the body travels up the left spinothalamic pathway. Then, without any additional
synapses, the spinothalamic pathway goes directly to the ventral posterior nucleus of
the thalamus and from there to the somatosensory cortex. This anatomy is depicted in
Figure 14.11 and ISLE 14.4.
The goal of these pathways is to get information to the brain for processing. There
are also reflex channels in the spinal cord that take the information and send it right
back to the muscles to allow fast reactions to dangerous situations. To experience the
feeling, though, the information must be sent to the somatosensory cortex. You may
have experienced this at one time or another. If you ever accidentally (or on purpose)
placed your hand on a hot stove top, you may have noticed that you jerked your hand
away before you actually felt the acute pain. Like the whale’s tail, it takes a bit longer
Anterior cingulate cortex
Signals to anterior
cingulate cortex
Signals to
insular cortex
Somatosensory
cortex
Spinothalamic
tract
Medulla
Spinal cord
Ventral posterior
nucleus of thalamus
Medial lemniscus
First synapse
(dorsal)
First synapse
(spinothalamic)
Dorsal root
ganglion
Dorsal horn
Thalamus
Medulla
Spinal cord
Somatosensory cortex
Nerve fibers carrying neural
signals for tactile perception
and proprioception
Nerve fibers carrying neural
signals for nociception and
thermoreception
Spinothalamic pathway
Dorsal column–medial
lemniscal pathway
FIGURE 14.11 The Two Pathways to the Brain
This anatomical diagram shows the dorsal column–medial lemniscal pathway and the
spinothalamic pathway.
Dorsal: in or toward the back of
the body; in the head, it means
at the top or toward the top
Ventral: in or toward the front of
the body; in the head, it means at
the bottom or toward the bottom
Dorsal column–medial
lemniscal pathway: a pathway
for the mechanoreceptors
(tactile perception) and
proprioceptors (muscle position)
that travels up the spinal column
on the ipsilateral side and
crosses to the contralateral side
in the medulla
Ipsilateral: literally, same (ipsi)
side (lateral), meaning, in this
context, that sensory information
is on the same side of the
nervous system as it entered
413 Chapter 14: Touch and Pain
for the information to get to your brain for you to experience
pain than it does for the reflex arc to allow you to remove your
hand quickly.
Somatosensory Cortex
The somatosensory cortex is an area in the parietal lobe of the
cerebral cortex devoted to processing the information coming
from the skin senses. The somatosensory cortex is in the very
anterior (front) of the parietal lobe, just behind the central sulcus,
which divides the parietal lobe from the frontal lobe. The most
anterior area is called the primary somatosensory cortex (S1), and
just posterior to it is the secondary somatosensory cortex (S2)
(Figure 14.12). The primary somatosensory cortex receives input
from the ventral posterior nucleus of the thalamus and thus
receives input from both the dorsal column–medial lemniscal
pathway and the spinothalamic pathway. As we will discuss in
more detail, different parts of the somatosensory cortex process
information from different parts of the body. Directly across the
central sulcus lies an area in the frontal lobe devoted to the con-
trol of movement. The movement area in the frontal lobe maps
mostly onto the primary somatosensory cortex. This means that
if the primary somatosensory cortex receives input
from the left thumb, the area adjacent to it in the
frontal lobe motor cortex will be involved in move-
ment of this same thumb.
A brief historical interlude is called for here.
Much of what we know of the function of the
somatosensory cortex comes from pioneering
studies by North American neurosurgeon Wilder
Penfield (1891–1976). Penfield was interested in
surgical ways to relieve the agony of epilepsy. He
reasoned that if damaged brain tissue was surgi-
cally removed, patients with severe epilepsy might
improve. However, it was important to know the
function of the brain areas in question before they
were surgically removed. Therefore, Penfield pio-
neered a technique of directly stimulating areas
of the brain with an electrical probe and observ-
ing the behavior of the patient. This required only
local anesthetic to the skull and skin, as the brain
itself has no nociceptors. The brain feels no pain
when it is stimulated, just the pain from the body
traveling into the head to be experienced. When
probing along the primary somatosensory cor-
tex, Penfield found that if he stimulated one area,
the patient felt a tingling in a specific area of the
body. Moving to an adjacent area of the somato-
sensory cortex, the tingling would occur in an
adjacent area of skin. In this way, Penfield was able to map out the relation between
the primary somatosensory cortex and the skin’s surface (Penfield & Rasmussen,
1950). You can see this map in Figure 14.13.
S1
S1
S2
Postcentral
sulcus
Postcentral sulcus
1
2
3b
3a
Posterior
parietal
cortex
Central sulcus
Central sulcus
Lateral sulcus
FIGURE 14.12 Somatosensory Cortex
Regions S1 and S2 are important in somatosensory perception,
from touch to pain.
Shoulder
Hip
Knee
Toes
Trunk
Neck
Arm
Elbow
Wrist
Hand
Fingers
Thumb
Eye
Brow
Face
Lips
Swallowing
Jaw
Tongue
Hip
nee
es
b
row
Face
LipL s
Swallowing
Jaw
FIGURE 14.13 Somatosensory Cortex
A homunculus drawing of the somatosensory cortex as conceived by Penfield
and Rasmussen (1950). Note the larger areas in the somatosensory cortex
devoted to the fingers and mouth and the relatively smaller areas devoted to the
back and the legs.
414 Sensation and Perception
The primary somatosensory cortex maintains a somato-
topic map of the body. Recall that soma means “body,” and
therefore a somatotopic map is a map of the body. In the
somatotopic map, the skin of the body maps onto the sur-
face of the primary somatosensory cortex in a systematic
way, just as we saw with the mapping of the retina in the
retinotopic map and the mapping of the basilar membrane
in the tonotopic map. When you scratch your chin, this
stimulates an area in the primary somatosensory cortex
responsible for perceiving sensations on your chin. Scratch
the tip of your nose, and an area slightly higher in the
somatotopic map will be stimulated. Rub your forehead,
and an adjacent area to that in the somatosensory cortex
becomes active. In fact, as Figure 14.14 demonstrates, the
somatosensory cortex actually holds multiple maps of the
skin surface. But throughout these maps, you can see the
feature Penfield originally noted. The maps are distorted.
Areas of the body for which we need greater sensitivity
(e.g., hands, mouth) have a greater representation in the
somatosensory cortex maps (i.e., they take more area on the
map) than do areas of the body for which we do not need as
high sensitivity (e.g., back, legs). It is for this reason that the
homunculus drawing (Figure 14.13) looks so odd. Penfield
and Rasmussen drew an image of a human enlarging those
areas that receive greater space in the somatosensory cor-
tex and shrinking those areas that receive less space in the
somatosensory cortex. This figure is drawn over the top of
the somatosensory cortex in Figure 14.13.
Suborganization of the Somatosensory Cortex
The primary somatosensory cortex (S1) is divided into three distinct neuroanatomical
regions. One of these regions is then divided again into two regions. These regions are
called Area 1, Area 2, Area 3A, and Area 3B. The terminology is a bit confusing as
these areas—1, 2, 3A, and 3B—are all part of S1, the primary somatosensory cortex.
Each area has a distinct map of the body’s surface. In addition, each area receives input
from a particular tract in the somatosensory system. Area 1 receives input from mech-
anoreceptors and is therefore the primary area for tactile perception. Area 2 receives
input from proprioceptors in the muscles and tendons (as does Area 3A). Area 3A
receives input from nociceptors. Area 3B also receives input from nociceptors, along
with input from the mechanoreceptors. Thus, each subarea of the primary somatosen-
sory cortex processes different fundamental sensations that arise from the skin and
body. These areas then send information to S2 (the secondary somatosensory cortex),
which is the somatosensory system’s “what” channel for identifying the nature of the
touched object (Hsiao, 2008). That is, this channel, sometimes called the ventral sys-
tem, is critical for using touch information to identify both the shape of an object and
the identity of that object. Thus, this area allows us to discriminate softballs from
grapefruits (Figure 14.15).
There is also a “where” channel or dorsal system in the somatosensory system. The
dorsal system allows us to control guided movements based on input from the somato-
sensory system. For example, we use feedback from this system to adjust our grip on
Leg
Foot
Toes
Genitalia
Throat
Tongue
Teeth, jaw, gums
Trunk
S1
S2
Neck
Head
Shoulder
Primary
somatosensory
cortex (S1)
Area 1
Area 2
Area 3
Secondary
somatosensory
cortex (S2)
Arm
Elbow
Forearm
Hand
Digit 5
Digit 4
Digit 3
Digit 2
Thumb
Eyes
Nose
Face
Upper lip
Lower lip
Chin
FIGURE 14.14 The Somatotopic Map
A more modern view of the somatotopic map, showing multiple regions
of the somatosensory cortex and both S1 and S2.
Contralateral: literally, opposite
(contra) side (lateral), meaning,
in this context, that sensory
information is on the side of the
nervous system opposite the
one from which it entered
Somatosensory cortex: an
area in the parietal lobe of
the cerebral cortex devoted
to processing the information
coming from the skin senses
Ventral posterior nucleus of
the thalamus: an area in the
thalamus that receives input
from both the dorsal column–
medial lemniscal pathway and
the spinothalamic pathway
Spinothalamic pathway: a
pathway for the nociceptors
(pain) and thermoreceptors
(temperature) that travels up the
contralateral side of the spinal
column; does not synapse in the
brain until the ventral posterior
nucleus of the thalamus
415 Chapter 14: Touch and Pain
a large textbook when it starts slipping away
from our hands. When we feel that the barbell
we are about to lift is heavy, feedback from the
somatosensory system tightens our grip. The
“where” channel continues from areas in S1 to
the posterior, or back part of, the parietal cor-
tex, an area involved in the control of action,
and then back forward to the premotor cortex
in the frontal lobe (Hsiao, 2008).
Left out of the previous description is
the pathway for temperature information. It
turns out that temperature information takes
a slightly different pathway when it makes
its way to the cortex. Thermoreceptors send
axons up the spinothalamic pathway that
travel to the ventral posterior nucleus of the thalamus and from there to S1. In con-
trast to other somatosensory systems, temperature information then goes to areas of
the frontal lobe, including the insular cortex and the anterior cingulate cortex (Hua,
Strigo, Baxter, Johnson, & Craig, 2005). The insular cortex and anterior cingulate
cortex have complex roles in cognition and are not typically associated with sensory
perception. Thus, their roles in perceiving temperature remain to be determined. But
given that both areas are also associated with emotion, it may explain why some peo-
ple feel so passionate about the weather.
Pathways for Pain
When we touch a hot stove, or prick a finger with a sewing needle, or feel the injection of
Novocain into our gums at the dentist’s office, we feel pain. Much to our regret, nothing
could be more real than the uncomfortable, distracting, and unpleasant experience of pain.
We may try to avoid it, we may dread it, we may develop ways of coping with it, but from
time to time, human beings experience pain, almost invariably unpleasant. However, it
turns out that the experience of pain arises from interactions among multiple systems, not
just the nociceptors. Pain can also be modified by emotion and cognition, which act to
change the pain experience in very real ways. For example, we describe in the next chap-
ter how the experience of pain can enhance the perception of flavor in spicy foods, a rare
situation in which pain is perceived as a positive. The neuroscience of pain is therefore a
fascinating story of the complex interactions of bottom-up (nociceptive) and top-down
(cognitive and emotional) processes.
As we discussed earlier, nociceptors in the skin detect damage or trauma at the skin
and transmit that information up the spinothalamic pathway. However, there is also a
downward pathway, leading from higher centers in the brain and heading down into
the spinal column. The information coming from the brain can inhibit the flow of infor-
mation upward toward the brain from the nociceptors. When it does so, the experience
of pain is reduced or even inhibited. When the downward signals are excitatory, the
transmission of pain information is blocked or inhibited. This view of pain perception
has been called the gate control theory (Melzack & Wall, 1988). It is depicted in Figure
14.16 and can be seen in ISLE 14.5. We also know where gate control occurs. The
nociceptors first synapse in the spinal cord in an area called the substantia gelatinosa
of the dorsal horn. It is here that neural signals from the brain can inhibit the upward
flow of pain information.
Somatotopic map: a feature
whereby the skin of the body
maps onto the surface of the
primary somatosensory cortex
in a systematic way
Homunculus: a drawing of a
human in which the proportions
of the body parts match the
relative sizes each body part
has on the somatotopic map.
Gate control theory: a model
that allows for top-down
control of the pain signal
coming up the spinal cord
Substantia gelatinosa:
the region in the dorsal horn
where neurons meet
Dorsal horn: an area of the
spinal cord that receives
input from nociceptors and
feedback from the brain
FIGURE 14.15 Shape and Texture
The “what” channel allows us to discriminate and identify objects that have similar
shapes and sizes, such as this softball and this grapefruit.
©
iStockphoto.com
/JoeG
ough
©
iS
to
ck
ph
ot
o.
co
m
/m
ic
ha
kl
oo
tw
ijk
ISLE 14.5
Melzack and Wall’s
Gate Control Theory
416 Sensation and Perception
Think of the implications of the gate
control model. Think, if you will for just a
moment, of a prisoner being tortured. The
fear a prisoner may experience in this cir-
cumstance may ensure that the gate control
is wide open, and all pain signals are head-
ing upstream unchecked. Indeed, a small pin-
prick may cause enormous pain under these
circumstances. Contrast that with a visit to
the dentist. The dentist is not your enemy
but your doctor. You know your dentist is
not out to maim you but rather to make sure
your teeth are healthy. The comfort of that
knowledge may be enough to activate the
gate control mechanism and effectively lower
the experience of pain. Visits to the dentist
may still involve pain, but because we know
the reasons behind this pain, our gate control
mechanism may mute the pain.
This leads us to the role of the anterior
cingulate cortex in emotional responses
to pain (Davis, Taylor, Crawley, Wood, &
Mikulis, 1997). The anterior cingulate cor-
tex receives input from the primary and
secondary somatosensory cortices (S1 and
S2) and responds to pain caused by pinches,
pricks, and extreme heat and cold. Indeed,
in one study, patients undergoing neurosur-
gery showed strong activity in their ante-
rior cingulate cortices when experiencing
pain (Hutchinson, Davis, Lozano, Tasker, & Dostrovsky, 1999). In another study
(Rainville, Duncan, Price, Carrier, & Bushnell, 1997), participants were hypnotized
and then had their hands placed in either painfully hot water or tepid water. S1 and
S2 were activated regardless of hypnotic suggestions given to participants, but the
activity in the anterior cingulate cortex varied as a function of hypnosis condition.
When participants were led to believe that more pain was coming, more activity was
seen in the anterior cingulate cortex than when people were led to believe that pain
was diminishing. Another study has shown that people show activity in the anterior
cingulate cortex when other people are experiencing pain (Singer et al., 2004). In
this way, the anterior cingulate cortex is seen as an area important to the emotional
component of pain perception. It can regulate pain and likely can initiate the gate
control mechanism to inhibit pain.
TEST YOUR KNOWLEDGE
1. Diagram the dorsal column–medial lemniscal pathway and the spinothalamic
pathways. Where is each located, and what somatosensory systems is each
responsible for?
2. Explain to your roommate the significance of the somatosensory homunculus in
terms of what it tells us about sensitivity to different parts of the body.
The brain’s response to painful stimuli
releases endorphins in the periaqueductal
gray area, which sends an inhibitory message
to the spinal cord
Midbrain
Periaqueductal
gray area
Pons
Medulla
Spinal cord
Enkephalin
Message from
pain
receptors
Substance P
Reduced pain message
to brain
FIGURE 14.16 Gate Control Theory
This model shows both how pain arises in the nociceptors and how it is transmitted
to the brain. It also depicts top-down control of the pain signal coming down from the
brain through the spinal column.
Anterior cingulate cortex:
a region in the prefrontal lobe
of the brain associated with
the emotional experience of
unpleasantness during pain
perception
417 Chapter 14: Touch and Pain
THE NEUROCHEMISTRY OF
PAIN: ENDOGENOUS OPIOIDS
14.3
Examine the role of endogenous opioids
in controlling pain perception.
As we have described, pain is useful because it alerts an organ-
ism to the potential of trauma to the body. This is useful because
it allows the organism to move away from or reduce the poten-
tial for further injury. We learn from pain. However, there may
be some situations in which an organism must continue to put
itself in harm’s way. For example, think of the pain an ante-
lope may feel from a thorn in its foot as it runs away from
a cheetah. In other circumstances, this pain might be a signal
to slow down and see if the antelope can shake out the thorn,
but with the cheetah in pursuit, the pain must be ignored because a greater danger needs
to be confronted. Similarly, think of a human mountain climber battling the steep slope
she must descend to return from the mountain and the pain she is experiencing from a
twisted ankle. Giving in to the pain of the ankle means death, so the climber must ignore
the pain to continue her descent (Figure 14.17). Humans may also mimic some of these
situations in athletic contests. Consider the marathon runner, whose muscles are exhausted
and overheated and whose nociceptors are firing at high rates by the middle of a race, even
in the best of conditioned athletes. To complete the 26.2 miles, the marathon runner must
continue to run despite considerable pain. By now it should not surprise you to learn that
the nervous system has mechanisms to reduce pain perception in these circumstances. The
brain can release chemicals known as endogenous opioids at various sites in the nervous
system, which act as analgesics to reduce pain. Endogenous opioids are neurotransmitters
produced by the body that reduce pain, via analgesia, throughout the body. They are called
endogenous opioids because opiate drugs such as morphine and heroin have their effects
by mimicking or acting like these substances in the body (Froehlich, 1997; Terenius, 2000).
Thus, the marathon runner will begin to feel the “runner’s high” when these opioids kick in.
The pain associated with muscle fatigue seems to lessen, and the runner can even speed up at
the finish. Stories abound of lost hikers who overcame pain and injury to make it to safety.
Endogenous opioids may have contributed to many of these self-rescues.
Looking closer at the opiate drugs can give us some insight into the operation of these
endogenous opioids. Opiates include many drugs, both legal and illegal, that people take
externally to reduce pain. Opiates include medically used painkillers, such as codeine, and
illegal drugs, such as heroin. Endorphins are a class of endogenous opioids produced by
the body, which inhibit pain responses in the central nervous system and thus reduce pain
perception. Because artificial opiates mimic the effects of these natural painkillers, they
can be effective at reducing pain, although in many cases, the risk for addiction is high as
well. For this reason, the use of opiates as painkillers is by prescription only. Even with
this precaution, there is a severe epidemic of prescription opiate abuse in this country
(Compton, Jones, & Baldwin, 2016).
TEST YOUR KNOWLEDGE
1. Explain endogenous opiates. How do they work to control pain?
2. Compare and contrast endogenous opiates and opiates on their control of pain.
A
scent Xm
edia/Photographer’s Choice/G
etty Im
ages
FIGURE 14.17 Control of Pain Perception
The climber might feel pain at this point, but the climber must ignore
the pain. Letting go at this point could mean death.
Endogenous opioids:
chemicals produced by
the body that reduce pain
throughout the body
Analgesia: processes that act
to reduce pain perception
418 Sensation and Perception
THE PERCEPTION OF ITCH
14.4
Contrast the difference between pain
and itch and how they interact.
Itchiness is usually a minor inconvenience. Dry skin feels itchy, and
you give it a quick scratch and move on. A single mosquito bite
annoys you with its itchiness, but it is easily ignored. But itchiness
can also be tremendously debilitating. Jellyfish stings can itch all
over one’s skin with an incredible intensity. This itchiness can lead
to self-induced wounds that may get infected. Itchiness can also
disrupt sleep patterns and distract attention from necessary tasks.
There is a disease called river blindness (technically, onchocercia-
sis), which is a major problem in tropical regions of Africa. The
disease may affect tissue in the eye, causing partial or complete blindness, but it also causes
a terrible itching sensation all over the body. People with river blindness have been known
to throw themselves into water, even when crocodiles may be swimming about in that
water, just to relieve the itching.
If you think about it subjectively, itch is different from pain, even though both may
be considered negative sensory experiences. Itchiness causes us to want to scratch the
affected skin, a response not usually caused by pain (Figure 14.18). Pain induces a with-
drawal response—we move away from pain. Thus, behaviorally, they have different
consequences as well. Other animals use itch perception in other ways. Think of your
cat and her notorious itchy ears. Cats’ faces and ears are loaded with itch receptors to
induce them to rub against landmarks and leave their scents for other cats to detect.
Other animals may feel itchy for similar reasons.
Recent research shows that itch perception is caused by a different class of recep-
tors in our skin. These receptors have been labeled pruriceptors (pruri is a Latin root
meaning “itch”). Pruriceptors respond mostly to chemical irritants on the skin rather
than tissue damage (LaMotte, Shimada, Green, & Zelterman, 2009). Like nociceptors,
pruriceptors also send their axons up the spinothalamic tract, where they eventually
synapse in the somatosensory cortex. Pruriceptors have been less well studied than
other forms of skin perception, but there is now strong evidence that pruriceptors are
anatomically different than nociceptors.
The function of the relation of itching and scratching has undergone some scrutiny.
One hypothesis is that we scratch to remove the possible irritant that may be bothering us.
Thus, a landing mosquito causes our skin to itch, and our scratch removes the insect from
our skin. Another hypothesis is that itching causes us to scratch, which then induces actual,
albeit minor, tissue damage. That is, the goal of the itchy sensation is to induce us to cause
minor tissue damage. This tissue damage initiates an autoimmune response, which acts to
reduce the risk caused by the original irritant (LaMotte et al., 2009). Consistent with this
view is the finding that pain inhibits itch. That is, when you scratch an irritant on your skin,
it may induce mild pain, which causes the itch to decrease as well as possibly an immune
response (Ward, Wright, & McMahon, 1996). Thus, for most people, having one’s back
scratched feels good at first, but if the scratching is too hard, pain perception takes over. So,
the next time you get a mosquito bite, you can feel a bit more comfortable scratching your
itch, knowing that in small doses, it may help your body react to the irritant.
TEST YOUR KNOWLEDGE
1. Describe the anatomical and functional differences between pain and itch.
2. Evaluate the evolutionary purpose of itch.
FIGURE 14.18 The Perception of Itch
Skin irritations cause itching, and itching induces us to scratch.
Sh
ut
te
rs
to
ck
.c
om
/n
am
tip
St
ud
io
Pruriceptors: receptors in
our skin that respond to mild
irritants by producing itch
sensations
419 Chapter 14: Touch and Pain
HAPTIC PERCEPTION
14.5
Assess the role movement plays in
enhancing the perception of touch,
allowing us to perceive objects.
The retina is a fixed shape, and the basilar membrane waits
for sounds to enter the ear to respond and move. But our
skin is different. It moves as we move and changes shape
as we interact with our environment. Think about find-
ing your way around in a dark room. You reach out and
touch objects to determine what they are, but you do not
just touch them—you pick them up and put your hands
around them. Indeed, the determination of shape and
identity from touch involves a dynamic process of percep-
tion, motor control, and feedback. We cannot do this on
ISLE, but try having a friend blindfold you and then give
you common objects to identify by touch. When given a
small rectangular wafer-shaped metallic object, you feel it,
you move it around, and you see if it has moving parts
before you confidently declare that it is a flash drive. This
dynamic process of object identification by touch is called
haptic perception. Haptic perception refers to the active
use of touch to identify objects. Haptic perception includes
integrating information from mechanoreceptors, proprio-
ceptors, thermoreceptors, and perhaps nociceptors as well.
Normally, we are not blindfolded, but haptic percep-
tion is important in many real-world situations as well. For
example, you may need to find a quarter (25-cent piece)
in your pocket. You do not need to take out every coin
and examine them visually to determine the right coin. Rather, you feel the shapes of
the coins in your pocket and use your haptic perception to determine the correct coin.
People who work with tools all the time can pick up the desired tool by feel alone.
Cooks know when their batter is ready to go in the oven not because it looks right but
because they feel it with their hands and know when the texture is correct. And perhaps
most important, surgeons may often be required to perform operations by touch, as
that information is more readily available than visual information. Thus, haptic percep-
tion is relevant in many different situations.
Think again about identifying objects while blindfolded. Experiments have examined
exactly that ability in people. For example, Klatzky (see Lederman & Klatzky, 2009)
gave participants 100 common objects to touch and identify. These objects included
eyeglasses, keys, spoons, and coffee cups. Not only were the participants highly accu-
rate (nearly 100%), but they made their accurate identifications very quickly. Klatzky,
Loomis, Lederman, Wake, and Fujita (1993) showed that wearing a glove while attempt-
ing to identify objects interfered with the haptic perception and lowered accuracy. They
hypothesized that the glove prevented the receptors from picking up vital information
from the objects, thus reducing the accuracy of the judgments. Thus, we can identify
objects via touch, and factors that interfere with efficient touch can interfere with object
identification.
To identify objects, participants make a number of discrete movements, such as
lateral motion, applying pressure, following the edges, supporting the object to deter-
mine approximate weight, and several others (Figure 14.19). These motions are called
Lateral Motion
(Texture)
Unsupported Holding
(Weight)
Pressure
(Hardness)
Enclosure
(Global Shape)
(Volume)
Static Contact
(Temperature)
Contour Following
(Global Shape)
(Exact Shape)
FIGURE 14.19
Exploratory Procedures (Lederman & Klatzky, 2009)
We use our hands to explore objects and determine their shapes and
identities.
Haptic perception: the active
use of touch to identify objects
420 Sensation and Perception
exploratory procedures. Exploratory procedures are hand movements
we make to identify an object. Thus, for example, we can determine the
texture of an object by lateral motion, or moving our hands along its
surface. A smooth object will result in a very different pattern on our
mechanoreceptors than will a bumpy object. You can tell the difference
between your cat and your dog without looking at them by feeling the
differences in the shape of their heads.
Think about moving your fingers across a rough surface, perhaps
sandpaper. As you move your fingers across the sandpaper, the pattern
registers in unique ways on the mechanoreceptors of your fingers. And
depending on the grain of the sandpaper, different patterns of high and
low activity will occur in the FA and SA receptors. This pattern allows
the somatosensory cortex to develop a spatial map of what the surface is.
This conjecture was put to the experimental test in a clever experiment
conducted by Hollins, Bensmaia, and Washburn (2001), who compared the responses
of mechanoreceptor fibers across different surfaces.
Hollins et al. (2001) did this by inducing a tactile illusion. They started with the
assumption that FAII (fast-adapting, large receptive fields) mechanoreceptors would be
important in determining the identities of objects with fine texture (e.g., the least scratchy
sandpaper). They fatigued these receptors by presenting to participants a high-frequency
vibration. The idea here was that the high-frequency vibration would tire or cause adap-
tation in the FAII receptors. After exposure to these vibrations, participants found the sur-
faces of objects less “rough” than when they were not preadapted to these vibrations. A
low-frequency vibration did not have these effects. Thus, this experiment supports the idea
that our different mechanoreceptors contribute to different aspects of haptic perception
(Pei, Hsiao, Craig, & Bensmaia, 2011).
Reading Braille
One skill in which haptic perception is vital is reading
Braille. Braille is an alphabet system using easy-to-feel
tactile letters instead of visual letters. It was developed
by Louis Braille (1809–1852). Braille was a young boy
in France when an accident robbed him of his sight. He
struggled to use raised letters to read, which are diffi-
cult to tell apart. Finding that this was the case for most
blind individuals, Braille set out to develop a writing
system that would be easier to read via touch. The sys-
tem he developed nearly 200 years ago is still a criti-
cal system for the blind today (see Figure 14.20 for an
illustration of the Braille system). Interestingly, Braille
was based on a night-writing system developed so that
military orders could be given by the French army at
night without having to alert enemies to their position. Braille is usually read using the
index finger, which feels the dots raised above the surface of the page. Blind readers
can now read Braille off the surface of a computer (Figure 14.21). It should be noted
that in recent years, there has been a slight decline in the use of Braille, as computer
technology allows text-to-voice translation, allowing blind individuals to hear instead
of feel what they need to read.
To read Braille, one must feel the dots raised above the page and perceive the number
and pattern of the dots. As you can see in Figure 14.20, small differences in the number
a b c d e f g h i j k
l m n o p q r s t u v
w x y z
FIGURE 14.20 The Braille Alphabet
These letters are raised off the page, so that blind
readers can feel them. A fluent Braille reader can
read almost half as fast as a sighted individual can
read text.
FIGURE 14.21 Person Reading Braille
©
iS
to
ck
ph
ot
o.
co
m
/p
or
to
ka
lis
Exploratory procedures:
hand movements made in
order to identify an object
421 Chapter 14: Touch and Pain
and pattern of dots indicate different letters. Thus, Braille is dependent on fine touch
and the “what” system in the somatosensory cortex. Fluent visual readers may perceive
many letters at the same time, but research shows that Braille readers feel fewer letters
per unit of time than do visual readers seeing letters. On average, a competent Braille
reader can read about 100 words per minute, somewhat less than the 250 words per
minute sighted people can read (Mountcastle, 2005). As such, Braille reading tends to
be slower than visual reading. In general, because our index fingers have the greatest
number of mechanoreceptors, even compared with other fingers, Braille readers are able
to read fastest by using their two index fingers together. Fluent Braille readers will also
move the left hand down to the next line of text, even as the right hand continues to
finish the line above (Lowenfield & Able, 1977). This research also suggests that natural
left-handers can read Braille faster.
Neuroimaging studies have revealed interesting reorganization of the brain in con-
genitally blind individuals compared with individuals who became blind later in life
(Voss & Zatorre, 2012). First, we see more white-matter fibers in the area of the somato-
sensory cortex for congenitally blind individuals than for individuals who become
blind later in life. Moreover, the occipital lobe reorganizes and receives input from the
somatosensory cortex (and from the auditory cortex) in congenitally blind individuals.
It is thought that this reorganization allows blind people greater area to devote to
spatial processing deriving from nonvisual spatial modalities. Moreover, Braille readers
show activity in the occipital lobe when reading (Voss & Zatorre, 2012). Although peo-
ple who become blind later in life will show activity in the occipital lobe when touching
objects, the earlier a person becomes blind, the more the occipital lobe is co-opted by
other senses (Collignon et al., 2013).
This research speaks to the relation of behavioral adaptation and neural reorgani-
zation in the face of disruption of normal sensory systems. Thus, the brain does not
waste the visual cortex when a person loses sight (due to damage to the eyes). Rather,
the visual cortex is co-opted for spatial perception through other modalities. Reading
by touch allows blind individuals the same opportunities in reading as does sight in
normal individuals. It also gives blind people a distinct advantage: They can read in
total darkness, without making a sound.
Tactile Agnosia
Tactile agnosia is a neurological condition caused by damage to the somatosensory
areas of the parietal lobe. Tactile agnosia is defined as an inability to identify objects
by touch, a seeming loss of haptic perception. For a patient to be diagnosed with tactile
agnosia, he must show normal perception of texture, temperature, and pain and must
show no deficits in motion. For example, a patient should be able to tell you that a
surface is smooth and cold but not be able to identify it as an icepack. That is, the neu-
rological problem must be one of identification rather than perception (Reed, Caselli,
& Farah, 1996).
An important characteristic of most patients with tactile agnosia is that only one
hand is affected while the other hand is spared. This interesting observation is because
the left hemisphere receives input from the right hand, and the right hemisphere receives
input from the left hand. Thus, tactile agnosia is typically seen in only one hand. If the
damage is to the left somatosensory cortex, tactile agnosia will be seen with the right
hand, but not the left hand. If both hands show agnosia, a different neural cause is
suspected (Gerstmann, 2001).
Reed et al. (1996) studied a patient with tactile agnosia. E.C. was a 65-year-old
woman who had tactile agnosia only in her right hand because of a left hemisphere
Tactile agnosia: an inability to
identify objects by touch
422 Sensation and Perception
lesion caused by a stroke in that area. The patient had no difficulty identifying objects
visually or with her left hand. However, when identifying objects by using only her
right hand, she showed a massive deficit in object identification, though she could still
identify textures, shapes, and characteristics such as smoothness. The patient also had
cognitive knowledge of the shapes of objects. That is, she could describe the differences
in textures among objects. However, when she felt objects with only her right hand
(and could not see what they were), she was unable to identify most objects. The tactile
agnosia, however, was not the only problem she had with her somatosensory system.
She reported general numbness in her right hand, though thresholds and temperature
sensitivity appeared normal. Thus, although her perception of basic sensory charac-
teristics was not affected, her ability to identify objects was specifically impaired, thus
classifying the diagnosis as agnosia.
The Development of Haptic Perception
The pattern of development of our sensations arising from the skin has not been studied
extensively. There are studies that have determined the number of some of the different
types of receptors in the skin over the life span. Some types of receptors reach their peak
number before birth and actually start to decline in number before birth. Others reach
their peak early after birth and decline throughout life. It should not be any surprise
that various types of thresholds to skin sensations decline throughout the life span
(Bleyenheuft & Thonnard, 2009).
The more interesting studies of the development of touch have had to do with
haptic perception. If you recall, studying infant visual perception has been difficult,
and often we can only study visual perception starting at a few months. Streri, Lhote,
and Dutilleul (2000) were able to study haptic perception in newborns. The average
age of the infants in the study was 44.6 hours—that is less than 2 days old! Streri and
colleagues used a haptic version of the habituation and dishabituation paradigm we
discussed earlier (see Chapter 6 for an example). It appears that, because we use our
hands to explore, our hands prefer novel objects just as our eyes do.
An object was placed in the infant’s hand in a way that the infant could not see
the object. Eventually, the infant let go and the researchers measured how long the
infant held the object. On the first trial, the infant held the object for about 30 sec-
onds. When the same object was placed in the hand, the infant held the object for a
shorter time, under 10 seconds by the third trial. This finding could be due to habit-
uation or fatigue. In the critical trial, a new object was put into the infant’s hand.
The new object was carefully selected to differ only in the contours of the shape and
no other general touch feature. The researchers hoped to show that haptic percep-
tion was driving the results. With the new object, holding time increased to about
20 seconds, showing that habituation does explain the results. Given the careful
choice in the object, a cylinder and a prism, these results also suggest that newborns
have some haptic perception (Streri et al., 2000). Haptic perception continues to
develop and children get better at using this sensory ability over the first few years of
life (Bleyenheuft, & Thonnard, 2009).
TEST YOUR KNOWLEDGE
1. Appraise haptic perception and how it differs from simple touch perception.
2. Define exploratory procedures and explain how they contribute to haptic
perception.
423 Chapter 14: Touch and Pain
THE VESTIBULAR SYSTEM:
THE PERCEPTION OF BALANCE
14.6
Illustrate how the vestibular system operates to perceive head rotation and
movement and interact with other senses to help us maintain balance.
We are including the vestibular system in this chapter, although the vestibular system
is not directly related to the somatosensory system, because this system deals with the
movement of our bodies. The vestibular system may be most linked to the auditory sys-
tem, with which it shares a number of anatomical features, but it interacts with several
sensory systems, most particularly our proprioceptive system.
Movement is essential to any animal, including humans. We are constantly in motion.
As tempting as it is to remain in bed when your alarm clock goes off at 6 a.m., you must
stand up and leave your bedroom. Once in the kitchen, you may need to bend down to
pick up the coffee beans from the bottom shelf to brew yourself some coffee. After that,
you may have to reach up to get a coffee cup from the top shelf. All of these ordinary
daily activities require balance. Your weight shifts as you perform each of these tasks,
and your ability to counter gravity changes as well. Balance is even more important in
the sports we play. Consider a downhill skier who must keep herself upright on thin
strips of carbon fiber while hurtling down a steep and slippery mountain at 85 mph
(137 km/h). Balance here is the critical difference between winning a gold medal and
spending the next 6 months recovering from serious injuries in the hospital. Nothing is
worse for a skier than a compromised vestibular system!
The vestibular system is the sensory system responsible for the perception of bal-
ance and acceleration, particularly of the head, and it is housed in the semicircular
canals and otolith organs, both located adjacent to the inner ear. The semicircular
canals are three tubes located in the inner ear responsible for the signaling of head rota-
tion. The semicircular canals are filled with a fluid called endolymph. The otolith organs
are responsible for detecting acceleration of the head and identifying when the head is
being held at a tilted angle. Hair cells within the semicircular canals signal information
about rotations of the head, and hair cells within the otolith organs signal information
about acceleration in linear directions. The anatomy of the vestibular system is depicted
in Figure 14.22. Note the proximity of the vestibular system to the cochlea of the ear;
in fact, they are connected and share fluid. In addition, the same nerve that carries
auditory information to the brain carries the vestibular information. This is why a head
cold can sometimes affect both our hearing and our sense of balance, as both of these
areas may be clogged.
The semicircular canals are tubes aligned in a perpendicular way to one another.
Each semicircular canal is filled with a liquid called endolymph. At the bottom of each
canal is a chamber called the ampulla, which contains a structure called the crista.
Inside the crista are the hair cells, the receptors. Similarly, in the otolith organs is a
structure called the macula, which houses the hair cells that respond to changes in head
orientation.
When our head moves in any particular direction, the endolymph lags behind
because inertia and gravity cause a relative movement in the opposite direction. Think
of holding up a glass. If you hold it straight, the water level is aligned with the glass.
However, if you tilt the glass to the left, the water does not move with the glass but lags
behind and tries to stay aligned with gravity. The water stays aligned with the floor but
Vestibular system: the
sensory system responsible
for the perception of balance
and acceleration, housed in
the semicircular canals and
otolith organs, both located
adjacent to the inner ear
Semicircular canals: three
tubes located in the inner ear
responsible for the signaling of
head rotation
Otolith organs: organs
responsible for detecting
acceleration of the head and
identifying when the head is
being held at a tilted angle
Endolymph: fluid that fills the
semicircular canals
Ampulla: the structure at the
base of each semicircular
canal that contains the crista
Crista: the structure in the
ampulla of each semicircular
canal that contains the
receptors
Macula: the structure in the
otolith organs that contains
the receptors
424 Sensation and Perception
Saccule
Semicircular
canals
Cupula
displacement
Direction of
acceleration
Endolymph
flow
Otoliths
Vestibular nerve
Facial nerve
Cochlear nerve
Utricle
Cochlea
Gelatinous
material
(a)
(b)
(c)
Hair cells
Neurons
FIGURE 14.22
The Anatomy of the
Vestibular System
A diagram of the
semicircular canals and the
otolith organs. (a) A diagram
of the main structures of the
vestibular system showing
its location relative to the
cochlea of the auditory
system. (b) The receptors
of the semi-circular
canals. The receptors are
embedded in the cupula
and motion of the cupula is
transduced by the receptors.
(c) A detail of the otolith
organs showing the hair
cell receptors. Motion of
the gelatinous material is
transduced by the receptors.
not the glass. Similarly, if you move your head, the endolymph lags behind and tries
to stay aligned with gravity. If you move your head left, the endolymph lags behind,
creating a relative motion to the right against the hair cells, which do keep up with the
head. This relative motion bends the cilia on the hair cells in a manner very similar to
what we saw with hearing, triggering a neural response. When the endolymph shifts,
the hair cells bend, transducing a neural signal, which informs the brain about head
motion. Because the three semicircular canals are perpendicular to one another, each
transmits information about head rotation along a different axis. That is, by comparing
the movement in each canal, the brain can make inferences about rotations to the left
or right (yaw), in front or behind (roll), and up or down (pitch). Thus, the movement
of endolymph in each canal can provide information about relative head movement in
great detail.
Meanwhile, the otolith organs are responsible for detecting linear acceleration.
When you start sprinting down the track, hair cells in the otolith organs bend, trans-
ducing a neural signal, thus providing you with information about motion and acceler-
ation. Similarly, there are hair cells set to detect accelerations up and down and left and
right. Thus, when you stand up or slide to the right, your brain will have information
about these accelerations.
If you have ever spent extended time at sea—sometimes even a relatively short ferry
ride will do it—you may have experienced the following illusion created by the vestibu-
lar system. After you return to dry land after your 7-day cruise through the Caribbean,
you may continue to experience a sensation of rocking or swaying while on what you
know to be terra firma, such as in your own home. In the vast majority of people, these
symptoms disappear after a few hours, though in some very rare cases, they may persist
425 Chapter 14: Touch and Pain
for years. It is likely that these symptoms are caused by adaptation in the vestibular system.
After a day or two at sea, you adapt to the constant motion caused by the rocking boat,
but then when you return to land, it takes a while to readapt to land, leading to the
temporary disorientation.
The nerve fibers from the semicircular canals and the otolith come together in the
vestibular nerve that then synapses in a brain stem area called the vestibular complex.
The vestibular complex projects to several areas, including the parietal insular vestib-
ular cortex, located in the parietal lobe. This area of the brain is thought to maintain
a representation of head angle, critical for maintaining balance. Patients with damage
to this area of the cortex may experience distortions of orientation, including vertigo,
a sense of the world spinning when it is not, and illusory tilt; that is, they may feel that
their heads are tilted when they are not. Indeed, some patients with damage in the pari-
etal insular vestibular cortex may hold their heads at odd angles because it feels like the
proper orientation to them.
Thus, the vestibular system is an important sensory system in its own right and quite
different from the more widely known and studied systems. Damage to it can have
severe consequences, but we seldom attend to it unless there is something wrong, such
as in the case of seasickness. This system combines with information from many other
senses, including vision, proprioception, and even touch, to help us keep our balance
in the world.
TEST YOUR KNOWLEDGE
1. Explain and illustrate the function of the vestibular system.
2. Diagram the anatomy of the vestibular system, and explain how its anatomy is
related to its function.
EXPLORATION: Electroreception in Fish
The bodies of all animals generate electricity. Think about
the billions of neurons throughout our nervous systems
sending electrical signals among one another. In the terres-
trial environment, the electric fields generated by animals
are incredibly weak, because air is such a poor conductor of
electricity. This is why we need to put electrodes directly on
the scalp to record electroencephalograms. No known land
animal has a sensory system that picks up electrical output,
all claims of extrasensory perception notwithstanding.
However, as every worrying mother knows, water is much
better at conducting electricity than air. (At the first sign of
lightning, every parent considers it a sacred duty to get every
child out of the pool at once.) Thus, the electrical output of
the nervous systems of fish is detectable by other fish if they
are in relatively close proximity and if those fish have evolved
special electroreceptors. It turns out that many species of fish
have sensory organs that allow them to detect the electric
fields of other fish. Many sharks and rays, for example, are
able to detect prey in complete darkness by homing in on their
electric fields (Hughes, 1999). Think of Jaws closing in on you
as you swim at night simply because you are deep in thought.
Now you might not really want to go back to the beach.
Electroreception in fish can be considered either passive or
active. Passive electroreception means simply that an organ-
ism can detect the electric fields generated by other animals.
It is analogous to our hearing—we hear the sound gener-
ated by objects in our environment. Active electroreception
means that the fish generates its own electric field around
itself and then senses disturbances to that electric field. This
Electroreception: the ability to detect electric fields, seen
in many species of fish
Passive electroreception: the ability only to detect electric
fields
Active electroreception: the ability to generate electric
fields and then detect disturbances or changes to those
electric fields caused by external events
Vestibular complex: a brain
stem area that receives input
from the vestibular nerve and
sends the information to the
forebrain
Parietal insular vestibular
cortex: an area in the parietal
lobe that receives input from
the vestibular nerve and is
responsible for the perception
of balance and orientation
426 Sensation and Perception
is analogous to the biosonar systems of bats and dolphins,
animals that listen for echoes from their own calls.
Electroreception involves detecting electric fields, but a number
of electric fish have also evolved the ability to generate strong
electric fields for the purpose of hunting and predation avoid-
ance (Hughes, 1999). But our attention here focuses on electro-
reception. Electroreception has evolved multiple times among
many species of fish. Thus, our discussion includes much gener-
alization. Electroreception has also been discovered in at least
one species of aquatic mammals, the platypus (Pettigrew, 1999).
The electroreceptors are located inside the scales along the
surface of most fish, though variations exist. Electroreceptors
are also found in the lateral line—a long row of mechano-
receptors that stretch along the backs of many fish, which
allow them to coordinate their rapid swimming movements.
But the electroreceptors detect electric fields while the mech-
anoreceptors detect the movement of water. The electrore-
ceptors are known as ampullae of Lorenzini, after the Italian
anatomist who first identified them. The ampullae are used
for passive electroreception. A second class of receptors,
called the tuberous receptors, are used for active electro-
reception in those fish with this ability. These receptors are
shown in Figure 14.23. In Figure 14.24, we see the mouth
and teeth of a tiger shark (Galeocerdo cuvier). The pits or
dots along its snout are ampullae of Lorenzini.
The ampullae of Lorenzini and the tuberous receptors are
tuned to electric fields of different frequencies. In terms of
electricity, frequency means variations in voltage across time.
Batteries, for example, produce direct current (DC), in which
voltage does not vary across time. However, the electricity in
our houses and offices is alternating current (AC), in which
the voltage varies at a specific rate or frequency. Biological
organisms tend to produce AC. The ampullae of Lorenzini are
tuned to DC and to very low frequency AC, whereas tuberous
receptors are tuned to much higher AC frequencies (Fields,
2007; Hughes, 1999). As such, the two types of receptors are
tuned to very different kinds of electrical events in the water.
The ampullae of Lorenzini are tuned to detect the weak volt-
age produced by the movements and body functions of other
nearby fish. The tuberous receptors, however, are tuned by
evolution to detect the fields generated by specific electric
discharges by that fish. That is, just as bats listen for their
own echoes, the tuberous receptors sense the changes in the
AC produced by the fish itself. Fish equipped with tuberous
receptors can then detect the differences between smaller fish,
which might mean food, and bigger fish, which they want to
avoid. In general, these electric fields are not that powerful
and would give a human hand only a mild shock.
Until quite recently (the 1950s), scientists did not know
that fish had this electric sense and puzzled over the pur-
pose of these obvious sense receptors. Because electric
senses are not feasible in land animals such as ourselves, it
was hard to imagine that animals such as tiger sharks could
be so dependent on this completely alien sense. This is not
to say that humans were unaware of the electric abilities
of fish. Egyptian fishermen have feared the Nile catfish for
thousands of years, and Amazonian peoples have feared the
electric eel for presumably at least as long. But it really was
not until the 20th century that we determined the relation
between these sensory receptors and electricity.
FIGURE 14.23 Electroreception (Hughes, 1999)
The ampullae of Lorenzini and the tuberous receptors.
FIGURE 14.24 Tiger Shark
The mouth and teeth of a tiger shark (Galeocerdo cuvier). The pits or
dots along its snout are ampullae of Lorenzini. We probably do not
want to mess with this guy.
©
iS
to
ck
ph
ot
o.
co
m
/S
te
ve
nB
en
ja
m
in
Ampullae of Lorenzini: the organ that contains the
hair cells that detect electric fields, used in passive
electroreception
Tuberous receptor: the organs that contain the hair cells
that detect electric fields, used in active electroreception
427 Chapter 14: Touch and Pain
APPLICATION: Phantom Limbs
and Phantom Limb Pain
Consistently, as teachers, we find that one of the phenom-
ena our students are most interested in is phantom limb
syndrome. This condition occurs when people who have
lost a limb feel as if it is still there, either through pain
or proprioception. In people who have lost limbs through
warfare, accidents, or surgery, false proprioception can
occur, in a condition known as phantom limb syndrome.
Phantom pain occurs when a person feels pain in a part of
the body that is missing.
Phantom limb syndrome refers to the continued but
illusory sensory reception in a missing appendage. Some
amputees have the sense that they feel the position of a
missing limb. That is, an amputee may feel as if his arm
is resting at his side, in much the way we know our arm
is resting at our side even if our eyes are closed. They can
even control and move the missing limb as they would
their remaining limb and feel it move (Walsh, Long, &
Haggard, 2015). Phantom limb syndrome is likely the
result of continued activity in the regions of the brain that
would have responded to sensory input from the missing
limb. Of course, phantom limb feelings can be quite dis-
tressing at first for the patient. However, phantom limb
proprioception, confusing as it must be at times, has a
benefit. Phantom limb proprioception is useful in help-
ing an amputee adjust to life with a prosthetic (Weeks,
Anderson-Barnes, & Tsao, 2010). Patients with phantom
limb proprioception quickly associate the feeling they
have in the missing leg to the prosthetic. Amputees who
lack phantom limb proprioception take longer to use the
prosthetic (Weeks et al., 2010).
Refer all the way back to Figure 14.13. The somatotopic
map showed how the body is laid out across the somato-
sensory cortex. Examining this map closely, you will see
that the representation of the face is very close to the repre-
sentation of the hands, and the representation of the face is
not near the top of the neck. This organization turned out
to be important in determining some of the mysteries asso-
ciated with phantom limb syndrome. Patients with phan-
tom limb syndrome may experience sensation in a missing
hand when they are touched on the face. They may also
experience sensation in a missing hand when touched on
what remains of their arm. Ramachandran and Hirstein
(1998) hypothesized that this is because the hand and face
are next to each other on the somatosensory cortex, just as
the area for the remaining limb is next to the hand in the
somatotopic map. In their view, the area normally respon-
sible for feeling on the face starts to draw on areas that are
otherwise dormant because they are not receiving signals
from a hand no longer present. However, because the rest
of the brain is functioning on the assumption that the area
responsible for the hand is perceiving sensation from the
hand, the touching of the face causes the experience of
having one’s missing hand touched. Initially, this sensa-
tion may be disturbing to patients, but they get used to
it. In some cases, however, patients may continue to have
illusions of feeling in their missing hands. This explana-
tion is very similar to the explanation for Aristotle’s illu-
sion (review ISLE 14.2).
You can also see Professor
Ramachandran talking
about phantom limb pain
in ISLE 14.6.
Unlike proprioception in which the experience of a phan-
tom limb can help an amputee, real problems occur when
people experience pain in missing limbs. Phantom limb
pain refers to experiencing pain in the lost limb. Because
there is no limb, amputees may be very confused when
they experience pain in a missing appendage. Indeed,
sometimes the pain can be excruciating, made all the
worse by the amputee’s knowledge that the limb is not
there. If the lost limb is one of the arms, 51% of patients
experience phantom limb pain, whereas phantom limb
pain is experienced by more than 70% of patients if a leg
is lost (Kooijman, Dijkstra, Geertzen, Elzinga, & van der
Schans, 2000).
One way that phantom limb pain is experienced is as
if the amputated limb is painfully cramped. Think of a
never-ending muscle cramp in your calf that nothing you
can do will relax. There is a general consensus that the
pain being experienced is a top-down phenomenon that
is generated by the brain trying to deal with the missing
ISLE 14.6
Professor Ramachandran and
Phantom Limb Syndrome
Phantom limb syndrome: continued but illusory sensory
reception in a missing appendage
Phantom limb pain: refers to experiencing pain in a limb
that has been amputated
428 Sensation and Perception
input information. But there is also growing evidence
that the pain, like the phantom limb syndrome itself, is
generated by the remaining peripheral neurons (Vaso
et al., 2014). Traditional drug therapies for pain have not
proven terribly effective (Perry, Mercier, Pettifer, Cole, &
Tsao, 2014), and researchers have searched many alter-
native methods to help their patients. Given the difficulty
in treating phantom limb pain, researchers have tried
several alternative therapies to help the sufferers. Let us
look at a couple of these therapies that relate to topics we
discussed earlier.
One interesting therapy requires a combination of
using vision and proprioception to help ease the pain
of phantom limb pain sufferers. Consider a case in
which the patient has lost a hand. In this therapy, the
patient will put both arms into a box and look at the
side with the remaining limb. On the wall between the
two limbs there is a mirror facing the remaining limb.
The person cannot see the amputated limb but in the
mirror the remaining limb is reflected to look to be in
the position of the amputated counterpart. While in
this mirror box, the patient moves his remaining limb
around. It will appear as if the amputated limb is mov-
ing. Even people with both limbs intact may experience
the movement of the visible limb as the movement of
the hidden limb (you can try this at home). The visual
input seems to override proprioception in this situa-
tion. That is, seeing a limb move is more important
to our experience than the proprioceptive signals from
limb and muscle. If you try this yourself, you will feel
your hidden hand move, even though it is at rest and it
is really the other hand moving. Patients can now feel
as if the amputated hand is moving even though it is no
longer present. So how does this strange phenomenon
work as a therapy?
The exact movements done will depend upon the type
of pain being experienced, but let us use the example of
a person experiencing a painful cramp in an amputated
hand. The amputee will clench the remaining hand and
then slowly open it. The amputee will see his missing
hand open and may even feel the missing hand relax,
reducing the pain (Chan et al., 2007; Foell, Bekrater-
Bodmann, Diers, & Flor, 2014). Repeating this process
may eventually eliminate the pain altogether. You can see
a video of the use of mirror therapy for phantom limb
pain and instructions on how to make your own mirror
box in ISLE 14.7.
Another approach that has recently emerged is to use
virtual reality (refer back to the Application section in
Chapter 7). The approach of this therapy has some sim-
ilarities to the mirror therapy in that the missing limb is
replaced visually, only in this case the limb is replaced
digitally rather than through a mirror. Researchers use
virtual reality to replace the amputated limb while the
patient is in a virtual world. The patient can see and actu-
ally use the missing limb to accomplish tasks in the virtual
environment. Depending on the type of pain, the ampu-
tee might perform different tasks designed to reduce that
pain. Using the cramp example from earlier, the amputee
might be asked to mentally relax the amputated limb and
will see a virtual copy of the limb relax. As in the mirror
box, she will feel as if her own missing limb is performing
the actions of the virtual reality limb. Early results sug-
gest that the use of visual feedback can help the patient
experience reduced pain (Perry et al., 2014). With the new
virtual reality goggles discussed in Chapter 7, it might be
possible for patients to do their virtual reality exercises at
home as well as in the clinic. It might also help bring down
the cost of this technically demanding form of therapy.
ISLE 14.7 also has video
about a person using vir-
tual reality to deal with
phantom limb pain.
There are several other emerging therapies for this serious
issue, including directly injecting painkillers into the dorsal
root ganglion (Vaso et al., 2014), but the therapies we’ve
discussed are highlighted because of the interesting feature
of how the senses interact. In both cases, it seems that
vision dominated the information from proprioception.
We are visual animals, and sometimes vision can override
information from our other senses, a phenomenon called
visual capture (Pavani, Spence, & Driver, 2000). Visual
capture occurs when there is a conflict between the infor-
mation from two senses and our experience follows the
visual input rather than the other sense. In the therapies
discussed, either through the mirror or virtual reality,
visual input of a missing limb can overcome the proprio-
ceptive information that the limb is absent. Visual capture
does not always happen, and we need all of our senses, but
in these cases, the use of visual capture has been exploited
for therapeutic purposes.
ISLE 14.7
Treatment of Phantom Limb Pain
Visual capture: circumstances where visual input can
dominate the input from other senses when they conflict
429 Chapter 14: Touch and Pain
CHAPTER SUMMARY
14.1
Classify how touch perception is actually a num-
ber of senses served by a number of receptor
systems.
Our somatosensory system starts with receptors embedded
in the skin as well as in our muscles, joints, and tendons.
Unlike audition and vision, touch requires direct physical
contact with the object to be perceived. The somatosen-
sory system is also composed of several distinct senses.
Mechanoreceptors are embedded in our skin. The epider-
mis is the outer layer of the skin, housing touch receptors,
and the dermis is the inner layer of skin, also housing touch
receptors. Mechanoreceptors are sensory receptors in the
skin that transduce physical movement on the skin into neu-
ral signals, which are sent to the brain. They tell us what we
are touching and how to respond to it. Mechanoreceptors
are divided into four types: SAI mechanoreceptors, SAII
mechanoreceptors, FAI mechanoreceptors, and FAII
mechanoreceptors. SA refers to slow-adapting, whereas
FA refers to fast-adapting. “I” mechanoreceptors have
small receptive fields, whereas “II” mechanoreceptors
have larger receptive fields.
Proprioception is the perception of the movements and
position of our limbs. Proprioception gives us impor-
tant information about the placement of our bodies.
Proprioception is subserved by three kinds of receptors,
muscle spindles, joint receptors, and Golgi tendon organs.
Interestingly, an illusion of proprioception may occur in
amputees. When this occurs, they are said to have phan-
tom limb syndrome.
Thermoreceptors are the sensory receptors in the skin
that signal information about the temperature as measured
on the skin. Cold fibers are thermoreceptors that fire in
response to colder (30 °C and below) temperatures as mea-
sured on the skin. Warm fibers are different thermorecep-
tors that fire in response to warmer temperatures (above
36 °C) as measured on the skin. When the temperature is
abnormally cold, such as when liquid nitrogen is placed on
the skin, this extremely cold stimulus will also activate the
warm fibers, leading to a perception of heat (and pain).
Pain is the perception and the unpleasant experience of
actual or threatened tissue damage. As unpleasant as
it is, pain is a warning to avoid dangerous objects and
protect oneself against greater damage. Nociceptors
are sensory receptors in the epidermis and dermis that,
when activated, cause us to feel pain. Nociceptors
are divided into A-delta fibers, which conduct signals
rapidly and respond to both heat and pressure, and
C-fibers, which react more slowly and respond to pres-
sure, extreme degrees of either heat or cold, and toxic
chemicals.
14.2
Sketch the two main pathways from receptors
in the skin to the somatosensory cortex in the
brain.
The dorsal column–medial lemniscal pathway is the
pathway for the mechanoreceptors (tactile perception)
and the proprioceptors (muscle position). It travels up
the spinal column on the ipsilateral side and crosses to
the contralateral side in the medulla. The other tract for
the somatosensory system is the spinothalamic pathway,
which conducts information from the nociceptors (pain)
and the thermoreceptors (temperature). It travels up the
contralateral side of the spinal column. The somatosen-
sory cortex is an area in the parietal lobe of the cerebral
cortex devoted to processing the information coming from
the skin senses. It houses maps of the skin for the differ-
ent skin senses. Thus, a touch to an area of the body will
cause activation in these areas of the cortex. The maps
are also scaled for the number of receptors. Thus, there
is more space in the somatosensory cortex devoted to the
fingers than to the upper back.
Gate control theory is a model that allows for top-down
control of the pain signal coming up the spinal cord.
Indeed, activation in the anterior cingulate cortex of the
frontal lobe may initiate a sequence that reduces pain via
the gate control mechanism.
14.3
Examine the role of endogenous opioids in con-
trolling pain perception.
Pain may also be inhibited by endogenous opioids, which
are chemicals produced by the body that reduce pain
throughout the body.
Sensation and Perception430
14.4
Contrast the difference between pain and itch
and how they interact.
Recent research suggests that itch perception is separate
from pain perception. Itch induces scratching, whereas
pain induces movement away from the source of pain.
Pruriceptors are receptors in our skin that respond to mild
irritants by producing itch sensations.
14.5
Assess the role movement plays in enhancing
the perception of touch, allowing us to perceive
objects.
Haptic perception is the active use of touch to identify
objects. Haptic perception includes integrating infor-
mation from mechanoreceptors, proprioceptors, ther-
moreceptors, and perhaps nociceptors as well. Haptic
perception integrates movement and touch to determine
the shapes and identities of objects, known as exploratory
procedures. Braille reading uses tactile perception of
raised dots rather than visual letters. It allows completely
blind individuals to read. Braille readers have been shown
to have more area in the occipital lobe devoted to spa-
tial and somatosensory touch. Tactile agnosia may occur
after brain damage to the somatosensory cortex. People
with tactile agnosia can still feel texture and shape but
cannot identify objects by touch.
14.6
Illustrate how the vestibular system operates to
perceive head rotation and movement and interact
with other senses to help us maintain balance.
The vestibular system is the sensory system respon-
sible for the perception of balance and acceleration.
It is housed in the semicircular canals and otolith organs,
both located adjacent to the inner ear. The semicircular
canals are three tubes located in the inner ear respon-
sible for the signaling of head rotation. Otolith organs
are responsible for detecting acceleration of the head
and identifying when the head is being held at a tilted
angle. Both project to the parietal insular vestibular
cortex.
REVIEW QUESTIONS
1. What are mechanoreceptors? What are the four
kinds of mechanoreceptors, and what kinds of stim-
uli do they respond to?
2. What is proprioception? Where do we find the
receptors for proprioception?
3. What is phantom limb syndrome? How does it
manifest itself in both proprioception and the pain
domain?
4. What is thermoreception? What two fibers project
thermoreception information? What is the difference
between them?
5. What are nociceptors? What is the difference
between A-delta fibers and C-fibers? How do noci-
ceptors differ from pruriceptors?
6. What is a homunculus? What does it tell us about
the organization of the somatosensory cortex? What
are the subareas of S1 (the primary somatosensory
cortex)?
7. What is gate control theory? What anatomical
regions are associated with it? How does it differ
from regulating pain with opioids?
8. What are exploratory procedures? What do they tell
us about haptic perception?
9. What is the vestibular system? What are the impor-
tant anatomical correlates of the perception of bal-
ance in the vestibular system?
10. What is electroreception? What species use it?
What is the difference between passive and active
electroreception?
Chapter 14: Touch and Pain 431
PONDER FURTHER
1. The sensations that arise from the skin are unique in
that sensations can arise passively (i.e., a stimulus
comes in contact with the skin) or actively (i.e., we can
reach out with our hands and interact with objects).
How does this unique feature of our skin senses play a
role in how these sensations are experienced?
2. Create a categorical system to illustrate the different
sensations that arise from the skin.
KEY TERMS
Active electroreception, 425
A-delta fibers, 409
Afferent fibers, 407
Ampulla, 423
Ampullae of Lorenzini, 426
Analgesia, 417
Anterior cingulate cortex, 416
C-fibers, 409
Cold fibers, 408
Contralateral, 412
Crista, 423
Dermis, 403
Dorsal, 412
Dorsal column–medial
lemniscal pathway, 412
Dorsal horn, 415
Dorsal root, 411
Dorsal root ganglion, 411
Electroreception, 425
Endogenous opioids, 417
Endolymph, 423
Epidermis, 403
Exploratory procedures, 420
FAI mechanoreceptors, 404
FAII mechanoreceptors, 404
Gate control theory, 415
Golgi tendon organs, 407
Haptic perception, 419
Homunculus, 414
Ipsilateral, 412
Joint receptors, 406
Macula, 423
Mechanoreceptors, 404
Meissner corpuscles, 405
Merkel cells, 405
Muscle spindles, 406
Nociceptive pain, 409
Nociceptors, 409
Otolith organs, 423
Pacinian corpuscles, 406
Pain, 409
Parietal insular vestibular
cortex, 425
Passive electroreception, 425
Phantom limb pain, 427
Phantom limb syndrome, 427
Proprioception, 406
Pruriceptors, 418
Ruffini endings, 405
SAI mechanoreceptors, 404
SAII mechanoreceptors, 404
Semicircular canals, 423
Somatosensory cortex, 413
Somatotopic map, 414
Spinothalamic pathway, 413
Substantia gelatinosa, 415
Tactile agnosia, 421
Thermoreception, 408
Thermoreceptors, 408
Tuberous receptor, 426
Ventral, 412
Ventral posterior nucleus of the
thalamus, 413
Ventral root, 411
Vestibular complex, 425
Vestibular system, 423
Visual capture, 428
Warm fibers, 408
Sensation and Perception432
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
14.1 Classify how touch perception is actually a number of senses
served by a number of receptor systems.
How Do You Amputate a Phantom Limb?
V. S. Ramachandran’s Tales of the “Tell-Tale Brain”
14.2 Sketch the two main pathways from receptors in the skin to the
somatosensory cortex in the brain.
Feeling Better: Separate Pathways for Targeted
Enhancement of Spatial and Temporal Touch
Brain Implant Restores Sense of Touch to Paralyzed Man
14.3 Examine the role of endogenous opioids in controlling
pain perception.
How Is Pain Influenced by Cognition? Neuroimaging
Weighs In
In Pain Thou Shalt Bring Forth Children: The Peak-and-End
Rule in Recall of Labor Pain
Pain Really Is All in Your Head and Emotion Controls Intensity
14.4 Contrast the difference between pain and itch and how they
interact.
The Mystery and Power of the Itch
Scientists Identify “Itchy” Neurons in Mice
14.5 Assess the role movement plays in enhancing the perception of
touch, allowing us to perceive objects.
14.6 Illustrate how the vestibular system operates to perceive head
rotation and movement and interact with other senses to help
us maintain balance.
2-Minute Neuroscience: Vestibular System
Platypus Hunts With “Sixth Sense”
Six-Foot Electric Eel
Kai Tirkkonen/The Image Bank/Getty Images
15Olfaction and Taste
Will & Deni McIntyre / Science Source
LEARNING OBJECTIVES
15.1
Examine the role of the olfactory system in detecting
harmful and helpful substances.
15.2 Describe the anatomical and physiological bases for olfaction.
15.3
Appraise the nature of olfactory perception, olfactory imagery, and olfactory
illusions.
15.4 Explain the anatomical and physiological bases for taste perception.
INTRODUCTION
Karen is a guidance counselor and a swim coach at a local high school. She was a
competitive swimmer and still likes to get into the pool and demonstrate good form
to her athletes. She’s happily married to a science teacher and track coach, and they
have a 15-year-old daughter who excels at playing the flute. Karen and her family are
certainly a successful family, happy and secure. However, Karen suffers from migraines.
Migraines are terrible headaches that bring pain, nausea, and discomfort and can inca-
pacitate a person for days. Migraines can be triggered by stress, changes in weather
patterns, pollution, and, critical to our discussion, some odors. Karen seldom gets
migraines anymore, because she has been able to remove most of the triggers from her
daily life. However, when her husband and daughter took her out to dinner for her 50th
birthday, a perfume being worn by a woman at a nearby table triggered a migraine,
ruining her 50th birthday party. We can wonder why certain odors, particularly fra-
grant perfumes, induce migraines in some people, whereas for others, the smell is pleas-
ant enough to swathe one’s body in it. Perfume-induced migraines have become such a
problem for some people that migraine sufferers have attempted to use the Americans
with Disabilities Act to prevent coworkers from wearing strong, migraine-inducing per-
fumes (Oltman, 2009).
In contrast, think of the smell of one of your favorite foods or drinks—the aroma of
coffee, the flavor of chocolate melting in your mouth, the smell of bananas wafting off
a frying pan. In contrast to Karen, you might also find some perfumes to be very pleas-
ing. Think of the perfume your girlfriend wears or the cologne your boyfriend wears.
Even mentioning these odors and flavors in a textbook may induce some of you to take
a break from reading and head to the kitchen for a snack. Indeed, odors may induce
cravings for particular foods (Herz, 2007). Cravings may often seemingly force people
to desperately search for an open pizzeria, regardless of the time of day. And for many
of us, nothing is more pleasurable than eating our favorite foods.
ISLE EXERCISES
15.1 Brain Area for
Olfactory Bulbs
15.2 Posterior Piriform
Cortex
436 Sensation and Perception
In this chapter, we examine the sensory apparatus underlying our senses of olfaction
(smell) and gustation (taste), how they interact, and what functions they serve. We also
discuss the trigeminal nerve system, which is important to both smell and taste and also
receives input from the somatosensory system.
Together olfaction and gustation are considered chemical senses because their role
is to detect chemicals in the environment. Olfaction brings airborne chemicals to our
attention, whereas gustation alerts us to the chemical compositions of substances
brought into our mouths. Similar to vision and audition, olfaction is a distal sense,
detecting objects that may be some distance from a person. However, gustation is sim-
ilar to the somatosensory systems, in that the taste must be in direct contact with the
taste receptors in the mouth for gustation to detect it. Thus, when we encounter cof-
fee, our olfaction system detects the chemicals emanating from the beverage before we
ingest it, and our sense of taste samples it as it passes through our mouth. The chemical
senses may be the oldest senses in an evolutionary framework. Many unicellular organ-
isms have evolved to detect chemicals, either food or toxins, in their environment.
OLFACTION
15.1
Examine the role of the olfactory system in detecting harmful and helpful
substances.
Olfaction refers to our ability to detect odors. Odors are the perceptual experiences
that derive from the detection of odorants, which are airborne chemical molecules.
Odorants are volatile chemicals; that is, in order to be smelled, an odorant must be
able to float through the air and thus pass into our nose. Odorants must be repellent to
water and relatively small molecules in order to be detected by our olfactory systems. In
this way, our sense of smell is an early warning system, allowing us to detect potentially
harmful or helpful substances before we come into direct contact with them.
Our olfactory system does not respond to all airborne chemicals. Think of carbon
monoxide, a toxic chemical produced by car engines. We cannot smell this odor, so
we are unaware of the buildup of carbon monoxide. This is why sitting in a car in the
garage with its engine running is dangerous. The engine produces carbon monoxide,
which cannot escape because of the enclosed condition. Because we do not smell the
carbon monoxide, it can build up to lethal levels without any warning. Natural gas is
also odorless. But when it is used to heat homes, a chemical is added to give it a strong,
unpleasant odor. Why would you want to make something smell bad? Well, a natural
gas leak can be dangerous, but if the gas is odorless, it will not be detected. With the
additive, a leak will smell like rotten eggs, something that surely gets a person’s atten-
tion. Other unpleasant odors allow us to avoid dangerous situations. Rotting meat may
contain toxic bacteria that can make us very sick. Thus, we evolved to find this smell
putrid and unpleasant. In some cases, however, cultures may find ways to treat rotting
meat to avoid sickness, in which case people learn to appreciate the smell rather than
be repulsed by it (Herz, 2007).
Many plants and animals emit molecules into the air, some of which are intended to
be detected by themselves, other members of their own species, or other species (Figure
15.1). Many animals emit pheromones, which may indicate their mating status to other
members of their species. In other cases, animals may use odorants to mark their terri-
tory. Furthermore, in some cases, plants and animals may deliberately produce odorants
for self-defense. Think of the characteristic odor of skunks. Skunks deliberately produce
these odorants to deter predators, which are repelled by skunks’ odor (see Figure 15.1).
Olfaction: the sense of smell
Gustation: the sense of taste
Odors: the perceptual
experience of odorants, which
are airborne chemical stimuli
Odorants: molecules our
olfactory system responds to
when we detect them in
the air
437 Chapter 15: Olfaction and Taste
TEST YOUR KNOWLEDGE
1. What is olfaction, and how does it differ from gustation?
2. What is the difference between an odor and an odorant? How might animals
use odors to communicate with other members of their species or other
species?
THE ANATOMY AND PHYSIOLOGY
OF THE OLFACTORY SYSTEM
15.2 Describe the anatomical and physiological bases for olfaction.
The Nose
We have two nostrils in our nose, which serve as the entranceway into the nasal cavi-
ties. The nostrils are separated by a wall of cartilage called the nasal septum. Damage
to the nose, such as from a punch or a hard fall, can cause a deviated septum, in
which the wall of cartilage is no longer straight. A deviated septum can interfere with
©
iS
to
ck
ph
ot
o.
co
m
/L
yn
n_
By
st
ro
m
©
iS
to
ck
ph
ot
o.
co
m
/L
au
riP
at
te
rs
on
©
iS
to
ck
ph
ot
o.
co
m
/s
tr
ay
_c
at
©
iS
to
ck
ph
ot
o.
co
m
/c
ob
ra
ph
ot
o © iStockphoto.com
/atoss
©
iStockphoto.com
/sam
cam
FIGURE 15.1 Odors
Examine these photographs. Each is associated with a characteristic odor. Consider each object and think about the odor of that object. Is it pleasant
or unpleasant? Is it weak or strong?
Nasal septum: the wall of
cartilage that separates the
nostrils
438 Sensation and Perception
both proper breathing and the sense of smell.
The nasal septum may also be punctured or
perforated. For example, chronic cocaine use
can cause holes to form in the septum, which
can also interfere with breathing and olfac-
tion. In human beings, the two nasal cavities
are extremely close to each other, so they are
essentially sampling the same air. Thus, there
is no real analogy to the binocular vision our
two eyes can achieve or the ability of our audi-
tory system to integrate across ears, such as in
sound localization.
Inside the nasal cavity, turbinates serve to
disperse air. Turbinates are bony knots of tis-
sue that ensure that some air will be passed
upward through a space called the olfactory
cleft and land on an area of tissue called
the olfactory epithelium. Olfactory recep
tor neurons are located inside the olfactory
epithelium, and these neurons serve as the
transducers of the olfactory system. The olfac-
tory receptor neurons are pretty far into the
nasal cavity; indeed, they are just a couple of
centimeters behind each eye. The air passes
through the cleft and then rejoins the air being
sent through the pharynx toward the lungs.
Odorants from food find their way to the
olfactory epithelium through a passage in the
oral cavity in the back of the mouth. This is
illustrated in Figure 15.2.
The olfactory epithelium serves as the organ
of transduction, taking chemical stimulation and
transforming it into a neural signal. There is an
olfactory epithelium at the top of each nostril,
measuring about 1 to 2 cm2. In addition to the
olfactory receptor neurons, the olfactory epithelium contains supporting cells and basal
cells. Supporting cells provide metabolic supplies to the olfactory receptor neurons. Basal
cells create olfactory receptor neurons. Interestingly, olfactory receptor neurons die out
after about a month, so basal cells are continually resupplying the olfactory epithelium with
olfactory receptor neurons. It is estimated that olfactory receptor neurons are completely
regenerated every 28 days. The anatomy of the olfactory epithelium is shown in Figure 15.3.
The olfactory receptor neurons have cilia extending into the mucus covering of the
olfactory epithelium. These cilia contain the transducing elements of the cell on their
tips. As a particular molecule of a particular odorant comes into contact with the tip
of the cilium of the olfactory receptor neuron, a chain of chemical events is initiated,
ending with an action potential leaving the olfactory receptor neuron along an axon
heading toward the olfactory bulb. That is, the chemical triggers the cilia, causing a
neural signal to begin. As few as seven molecules of the same odorant can trigger an
action potential in an olfactory receptor neuron.
There are approximately 20 million olfactory receptor neurons in the human nose.
Although this is more sensory neurons than for any other human sensory modality,
it is much fewer olfactory receptor neurons than seen in other species. Dogs such
Olfactory bulb Olfactory cleft
Turbinates
Oral
cavity
Tongue
Pharynx
Cribriform plate
Olfactory epithelium
Nasal cavity
Odorant molecules
Odorant molecules
in olfactory mucosa
Olfactory bulb
Basal cell
Olfactory
sensory
neurons
Olfactory receptors
Glomerulus
Mitral cell
Tufted cell
Olfactory
epithelium
Cribriform
plate
Olfactory
mucosa
Supporting
cells
Olfactory
cilia
Bowman’s
gland
FIGURE 15.2
Gross Anatomy (No Pun Intended) of the Human Nose
Odorants enter the nasal cavity and make their way up to the olfactory epithelium. The
turbinates, which are bones covered with epithelial tissue, keep the air circulating up
toward the olfactory epithelium.
Turbinates: bony knots of
tissue that serve to disperse
air within the nasal cavity
Olfactory cleft: the channel
at the back of the nasal cavity
that funnels air up toward the
olfactory epithelium
Olfactory epithelium: a
mucous membrane inside
each nostril of the nose that
contains the receptor cells for
the olfactory system
Olfactory receptor neurons:
receptor cells located in the
olfactory epithelium that
detect specific chemicals in
the air and transduce them
into a neural signal
439 Chapter 15: Olfaction and Taste
as bloodhounds and basset hounds have as many as
10 times more olfactory receptor neurons than we do.
Grizzly bears may even have more olfactory receptor
neurons than dogs. Pigs also have large concentrations
of olfactory receptor neurons. The density of the olfac-
tory receptor neurons in these species gives these ani-
mals an enormously sensitive sense of smell. Grizzly
bears can detect the aroma of meat from nearly 20 miles
away (Figure 15.4). Bloodhounds can detect the pres-
ence of a specific animal even if that animal passed by
a location several days earlier. Pigs are trained to detect
truffles buried underground. Species, such as pigs, bears,
and dogs, that depend heavily on smell are called macro
smatic. Humans, who are more dependent on vision and
audition, are considered microsmatic. You can see some
illustrations of different animals’ brains and the space
devoted to olfaction on ISLE 15.1.
It is estimated that humans have about 350 different kinds of olfactory receptor
neurons. Each kind of olfactory receptor neuron responds to a relatively small class of
odorants. When we compare the olfactory system with the visual system, we find that
the 350 types of olfactory receptor neurons roughly correspond to the three cones and
one rod in the visual system. Thus, the function of identifying smells is a very different
process than how we identify color. Macrosmatic species may have as many as 1,000
different types of olfactory receptor neurons.
Genes and Olfaction
In 2004, neuroscientists Linda Buck and Richard Axel received a Nobel Prize for their
groundbreaking work on the genetics of transduction of olfactory receptor neurons.
FIGURE 15.4 Grizzly Bear
Grizzly bears have a tremendously sensitive sense of smell.
©
iStockphoto.com
/Zw
illing330
ISLE 15.1
Brain Area for Olfactory Bulbs
Supporting cells: cells that
provide metabolic supplies to
the olfactory receptor neurons
Basal cells: cells that create
olfactory receptor neurons
Macrosmatic: species that
are heavily dependent on their
olfactory system
FIGURE 15.3 Anatomy of the Olfactory Epithelium
(a) The olfactory receptor neurons are located beneath the mucous layer of the epithelium. The olfactory epithelium houses three types of cells:
olfactory receptor neurons, basal cells, and supporting cells. The olfactory receptor neurons are found beneath the olfactory epithelium. (b) The
location of the olfactory bulbs on the bottom of the sheep brain. They are much larger in sheep than human brains but lie in very similar locations in
the brain. Use your anaglyph glasses to view this image.
Olfactory bulb
Basal cell
Olfactory
receptor
neurons
Glomerulus
Mitral cell
Tufted cell
Olfactory
epithelium
Cribriform
plate
Olfactory
mucosa
Supporting cells Olfactory cilia Bowman’s gland
(a) (b)
440 Sensation and Perception
In 1991, Buck and Axel published an important paper that described
their discovery of a collection of genes that regulate the expression
of different olfactory receptor neurons (Buck & Axel, 1991). They
described a family of about 1,000 genes across mammalian spe-
cies that are involved in genetic coding for olfactory transduction.
However, in human beings, the majority of these genes are inactive.
Indeed, it is estimated that only about 350 of these genes actually code
for olfactory reception in humans (Malnic, Godfrey, & Buck, 2004).
In other species, such as the macrosmatic species (e.g., dogs, bears)
just described, far fewer of these genes will be inactive. In humans,
the number of active genes is a predictor of individual differences in
olfaction. Research suggests that when a person has more copies of a
particular gene active, she may be more sensitive to the odorant that
the gene maps onto. Moreover, if a gene that allows people to detect a
pleasant odor is absent, foods with that odor may not be as appealing
to them as they are to people in whom the gene is expressed (Menashe,
Man, Lancet, & Gilad, 2003). Thus, for example, if you lack a gene
that codes for lavender, you may not like certain perfumes.
The Trigeminal Nerve
Many odorants also have a second sensory component to them, which
often may be described as a feeling. Some odors burn, whereas oth-
ers soothe. Indeed, odorants such as ammonia (burning) and menthol (cooling) also
cause reactions in the somatosensory system. This aspect of olfaction is mediated by
the trigeminal nerve, which transmits information about the feel of an odorant (Figure
15.5). Trigeminal stimulation accounts for a number of the experiences associated with
eating food as well. For example, the burning sensation of chili peppers is the result of
trigeminal stimulation. It is also trigeminal stimulation that induces tears when we eat
or cut fresh onions.
TEST YOUR KNOWLEDGE
1. Describe the gross anatomy of the nose.
2. What is the trigeminal nerve? How does it bridge the gap between olfaction and
the somatosensory system?
The Pathway to the Brain
The olfactory receptor neurons project axons through little holes in the base of the
skull called the cribriform plate, a bone of the skull that separates the nose from the
brain. Because of its location and its perforated surface, the cribriform plate is sus-
ceptible to injury when the head receives a hard blow. Even a human punch can cause
the cribriform plate to become fractured. When it is fractured, it may sever the axons
coming from the olfactory receptor neurons, causing impairment to the sense of smell.
In some cases, anosmia may develop. Anosmia (or smell blindness) is the inability to
smell, usually caused by cribriform plate damage. Despite the regeneration of olfactory
receptor neurons, a fractured cribriform plate may scar over, preventing the new neu-
rons from projecting through it to the brain. Figure 15.6 shows the passage of axons
from the olfactory receptor neurons to the first areas of olfactory processing in the
brain. Sinus infection may also cause anosmia, either temporarily or permanently. We
return later, in the Exploration section of this chapter, to the causes and consequences
of anosmia.
Microsmatic: species that
are less dependent on their
olfactory system
Trigeminal nerve: a nerve
that is associated with the feel
of odorants; also known as the
fifth cranial nerve
Cribriform plate: a perforated
section of skull bone that
separates the nose from the
brain; axons from olfactory
receptor neurons pass through
to allow olfactory information
to enter regions in the brain
Anosmia (smell blindness):
the inability to smell, usually
caused by cribriform plate
damage
Olfactory nerve (first cranial
nerve): the axons of the
olfactory receptor neurons
that leave the nose and enter
the olfactory bulb
Olfactory bulb: a part of the
brain just behind the nose; it
is the first place in the brain
where olfactory information is
processed
Opthalmic
nerve
Mandibular nerve
Trigeminal nerve
(cranial nerve V)
Ethmoid
nerve (nose)
Ciliary
nerves
(cornea)
Maxillary
nerve
Lingual
nerve
(tongue)
Inferior alveolar
nerve (teeth)
FIGURE 15.5
Anatomy of the Trigeminal Nerve
The trigeminal nerve carries information from
somatosensory receptors in the nose to the thalamus.
The experience of “heat” when eating chili peppers is
caused by activation of the trigeminal nerve.
441 Chapter 15: Olfaction and Taste
The axons of the olfactory receptor neurons converge
to form the olfactory nerve, which exits through the
cribriform plate. The olfactory nerve (also known as the
first cranial nerve) consists of the axons of the olfactory
receptor neurons that leave the nose and enter the olfac-
tory bulb. The olfactory bulb is a part of the brain just
behind the nose. It is the first place in the brain where
olfactory information is processed. Once inside the olfac-
tory bulb, the axons from the olfactory receptor neurons
enter and synapse with dendrites in spherical structures
called glomeruli. There are two types of dendrites in
the glomeruli. One of the dendrites is from mitral cells,
whereas the other is from tufted cells. Mitral and tufted
cells have similar projections, but differ in that they
respond to different odorants, and mitral cells are more
likely to inhibit the olfactory process than are tufted
cells (Nagayama, Takahashi, Yoshihara, & Mori, 2004).
These two types of cells form the olfactory tract, which
projects olfactory information from the olfactory bulb to
other regions of the brain.
The olfactory bulb is one of the most forward (ante-
rior) parts of the human brain. It is found in humans
just above the nose and just behind the eyes. It is also a
primitive part of the brain, in the sense that our olfac-
tory bulbs do not differ greatly from other mammalian
olfactory bulbs. The beginning of olfactory processing
occurs in the glomeruli. The cells in the glomeruli form
an odorant map, organizing similarly structured odor-
ants together. This means that odorants from chemicals
with similar structures are processed adjacent to one another. This map is analogous
to frequency coding in the auditory cortex or spatial mapping in the visual brain. It
is worth noting that odorants with similar chemical structures may not have similar
subjective odors. Nonetheless, processing in the olfactory bulb is organized by chemical
structure. Information passes from the glomeruli to the mitral and tufted cells, which
then project to structures beyond the olfactory bulb.
The axons of the mitral cells and the tufted cells project further into the brain and
synapse in a variety of locations in the brain. Chief among these projections are con-
nections to the amygdala (an emotion area), the entorhinal cortex of the temporal lobe
(a memory area), and the piriform cortex, also in the temporal lobe (Figure 15.7). Of
particular interest is the piriform cortex, which is often considered the primary olfac-
tory cortex. The piriform cortex is devoted exclusively to olfaction, but the entorhinal
cortex is an important memory area of the brain, and the amygdala is an important
emotion area of the brain.
The fact that the olfactory bulb directly projects to these areas is critical in two
aspects of olfaction: its association with memory and its association with emotion. The
direct connection between the olfactory bulb and the entorhinal cortex is likely why
a particular odor can elicit an involuntary autobiographical memory so quickly. The
entorhinal cortex is deeply connected to the hippocampus, also a known memory area
of the brain. Many people will report that a particular smell will evoke strong memo-
ries, often of childhood, with striking regularity. For example, the smell of naphthalene
(or mothballs) always reminds one of your authors of his grandmother’s apartment
from when he was a child.
Glomerulus
Olfactory nerve
(cranial nerve I)
Mitral cell
Olfactory
sensory neuron
Receptor
Odorant molecules
Cribriform plate
Olfactory cilia
FIGURE 15.6 Olfactory Pathway
The pathway of odors from the olfactory receptor neurons to the brain.
Glomeruli: spherical
structures within the olfactory
bulb where the olfactory tract
forms synapses with mitral
cells and tufted cells
Mitral cells: neurons that start
in the glomeruli of the olfactory
bulb and project to other areas
of the brain; respond to different
odorants than do tufted cells.
Tufted cells: neurons that
start in the glomeruli of the
olfactory bulb and project to
other areas of the brain; they
respond to different odorants
than do mitral cells
Olfactory tract: the pathway
leading from the olfactory bulb
to other regions of the brain
Amygdala: an area of
the brain in the limbic
system, associated with
the experience of emotion,
particularly fear
442 Sensation and Perception
Moreover, the direct connection between the olfactory
bulb and the amygdala is most likely pivotal in the rapid
negative associations that occur when we smell an odor
in a negative situation. Even in microsmatic humans, one
up-close interaction with an angry skunk will leave you dis-
liking the musk of skunk for life. Similarly, one very positive
experience with a particular perfume or cologne, and you
may find that odor pleasant for life as well. The amygdala
projects directly to the hypothalamus, which is critical in
the regulation of activities such as hunger, thirst, and sexual
desire.
Representation Within the Piriform Cortex
The piriform cortex is found in the temporal lobe. It is adja-
cent to areas of the brain known as the limbic system, which
are critical in such functions as emotion and memory. The
piriform cortex has two main anatomical subdivisions: the
anterior piriform cortex and the posterior piriform cortex
(Kadohisa & Wilson, 2006). As the names suggest, the ante-
rior piriform cortex is located in the front portion of the
piriform cortex, and the posterior piriform cortex is located
in the back portion of the piriform cortex. The anterior piriform cortex is associated
with representing the chemical structures of odorants. That is, like the olfactory bulb,
the anterior piriform cortex creates a map of odorants organized by their chemical
structure. Moreover, neurons within the anterior region are narrowly tuned, responding
to a very small range of odorant molecules and not others. In contrast, the posterior
piriform cortex is associated with an odor’s quality, regardless of its chemical compo-
sition. That is, the posterior piriform cortex groups together odors that smell similar
to us, regardless of chemical origin. You can see the location of the piriform cortex in
Figure 15.7. You can see an interesting simulation of the posterior piriform cortex on
ISLE 15.2.
The posterior piriform cortex represents the subjective qualities of odors rather
than their chemical compositions. In the posterior piriform cortex, neurons are grouped
by subjective similarities between odors. For example, odors that smell “smoky” are
grouped together, regardless of the types of molecules that elicit them. Moreover, chem-
icals that are similar in their molecular structures may be represented in different areas
of the posterior piriform cortex if they elicit different olfactory experiences. In this
way, the posterior piriform cortex serves a similar function to the extrastriate cortex in
vision, processing the identities of odorants in the environment, just as areas such as V2
and V4 process the identity of visual stimuli.
An interesting study by Howard, Plailly, Grueschow, Haynes, and Gottfried (2009)
illustrates the difference between the anterior piriform cortex and the posterior piriform
cortex. Howard et al. recorded brain activity via functional magnetic resonance imag-
ing while participants were sampling three different odor categories (minty, woody, and
citrus). The odors within each category (e.g., minty) were subjectively similar but had
different chemical structures. The pattern of brain activity showed that the posterior
piriform cortex was similarly activated for odors that were subjectively similar; that is,
they all smelled minty. However, when looking at other regions of the brain responding
to odors, such as the anterior piriform cortex, this pattern was not seen. Therefore,
Howard et al. concluded that the posterior piriform cortex must be involved in identi-
fying the qualities of odorants.
Thalamus
Hippocampus
Hypothalamus
Entorhinal cortex
Amygdala
Piriform cortex
Olfactory
tract
Orbitofrontal
cortex
Olfactory
bulb
Olfactory receptor neurons
in olfactory epithelium
FIGURE 15.7 Areas of the Brain Receiving Input
From the Olfactory Bulb
The olfactory bulb is located just behind the nose. It sends
information to the piriform cortex (located in the temporal lobe), the
entorhinal cortex, and the amygdala. The piriform cortex projects to
the orbitofrontal cortex.
Entorhinal cortex: an area
in the medial temporal lobe,
associated with a number of
memory functions
Piriform cortex: an area
in the anterior region of the
temporal lobe that receives
input from the olfactory bulb
and is involved in olfactory
processing; often considered
the primary olfactory cortex
Anterior piriform cortex:
a structure located in the
front portion of the piriform
cortex that is associated with
representing the chemical
structures of odorants
Posterior piriform cortex: a
structure located in the back
portion of the piriform cortex
that is associated with an
odor’s quality, regardless of its
chemical composition
ISLE 15.2
Posterior Piriform Cortex
443 Chapter 15: Olfaction and Taste
The Orbitofrontal Cortex
Another important region of the brain that has an olfactory function is the orbi
tofrontal cortex, particularly the right orbitofrontal cortex. This area receives pro-
jections from both the piriform cortex and the limbic system. It is thought that this
area of the brain is critical in establishing the emotional nature of odors. Odors are
also fundamentally an emotional and affective experience (Herz, Eliassen, Beland, &
Souza, 2004). Certain odors (e.g., coffee, chocolate, certain perfumes) may elicit very
positive emotions, whereas others (e.g., skunk, rotting garbage, excrement) may elicit
very negative emotions. Thus, the affective values of odors are important, as positive
odors elicit approach and negative odors afford distancing. Much of this cognition
appears to be occurring in the orbitofrontal cortex. The orbitofrontal cortex is located
just behind and above our eyes, in the very most frontal part of the frontal cortex.
This area of the cortex appears to be critical in integrating olfaction and taste per-
ception of foods, allowing us to enjoy some foods and reject others. The right orbito-
frontal cortex is critical to the actual experience of an odor, that is, the “feeling” we
get when we smell an odor, or what philosophers call its qualia (Li, Lopez, Osher, &
Howard, 2010).
TEST YOUR KNOWLEDGE
1. Describe the neural pathways from the olfactory nerve through higher order
areas of the brain.
2. What are the functions of the anterior piriform cortex and the posterior piriform
cortex?
OLFACTORY PERCEPTION
15.3
Appraise the nature of olfactory perception, olfactory imagery, and olfactory
illusions.
Detection
We reviewed the anatomy of olfaction in the last section. Now we cover olfactory
psychophysics. Here, the questions concern exactly what our sense of smell can do.
In detection, we want to know how much of an odorant must be in the air for people
to detect that odorant. It turns out that the answer to this question depends on what
the molecule is. Some odors can be detected in much smaller quantities than others.
Of course, as concentrations of a particular odorant increase, so will the likelihood of
detection. Thus, just as the amount of light necessary to see depends on which wave-
length of light is available, different odorants require different concentrations for olfac-
tory detection. So, although our detection varies greatly from odor to odor, we can still
make some generalizations about odor detection.
The amount of odorant in the environment is typically measured as a function
of the number of molecules of that odorant per 1 million molecules of air. This is
known as parts per million, or ppm for short. If you recall from Chapter 2, thresholds
will vary depending on a number of characteristics. However, averaging over these
characteristics, we can discuss the mean ppm required to detect a particular odor.
To refresh the concept, an absolute threshold is the minimum amount of stimulus
intensity required to elicit a perception of that stimulus. Different odorants require
different concentrations to be detected. For example, we are extremely sensitive to the
Orbitofrontal cortex: a part
of the prefrontal cortex that
appears to be critical in the
emotional experience of odors
and integrating olfaction and
taste perception, among other
functions
444 Sensation and Perception
sweet smell of vanilla; it requires only 0.000035 ppm to detect it
(Figure 15.8). However, the smell of acetone, which many of us
know as nail polish remover, requires 15 ppm to detect (Devos,
Patte, Rouault, Laffort, & Van Gemert, 1990). We can also look
at the just-noticeable difference (JND) for any particular odor-
ant, that is, how much more odor we must add to the air for us to
detect a stronger concentration of that odor. This will also vary
among odors.
Identifying Odors
Imagine the following scenario. You arrive at a friend’s house
and smell a beautiful aroma of something cooking in the kitchen.
It smells wonderful, and you are sure you know the aroma, but
you cannot name it. What is that smell? It is familiar to you,
but you cannot put a name to it. This altogether common phe-
nomenon has been called the tipofthenose phenomenon,
very similar to the more common tip-of-the tongue phenomenon
(Jönsson & Olsson, 2012; Jönsson & Stevenson, 2014), and it
occurs when a person is familiar with an odor but cannot recall
its name, despite feeling as if he can. If your host tells you that
she is cooking a curry, you instantly recognize the aroma as being
that of curry and wonder why you did not identify the aroma
yourself in the first place (Figure 15.9). You can even try this
out with friends. Open up spice bottles for them and see if they can name the spices
by sniffing. You will be amazed at how few smells they will be able to name. But if
you give them multiple choices, they will be very accurate (Jönsson & Olsson, 2012;
Jönsson & Stevenson, 2014).
As we have discussed, there is an intimate connection between
olfaction and emotion. Odors elicit emotions, both positive and
negative. There is also a close connection between olfaction and
memory—some odors elicit specific memories. However, there
seems to be a disconnect between olfaction and language, ren-
dering it difficult to identify the names of certain odors, espe-
cially when these odorants are encountered in an unusual context
(Cain, 1979; Herz, 2007).
Research shows that when people are given odors to
sniff in a lab, they are poor at naming these odors (Figure
15.10). Indeed, in most experiments, most participants sel-
dom approach naming even half of the odors (Jönsson &
Olsson, 2012). However, this does not mean the odors are not
familiar and known to the participants—the problem is in labeling
them. This point is easy to demonstrate by giving participants a
recognition test in which they must identify the correct name of
an odor from among a list of alternatives. Under these circumstances, odor identification
increases tremendously. In one study, de Wijk and Cain (1994) found that young adults’
odor naming was just about 40% correct, but performance increased to above 80% cor-
rect when the participants were permitted to choose from a list of possible names.
Discrimination in psychophysics means distinguishing between two stimuli. In
most psychophysics experiments, the two stimuli to be discriminated will be closely
FIGURE 15.8 Vanilla Ice Cream
The extract known as vanillin that creates the vanilla smell and
taste is an odorant we are very sensitive to.
©
iS
to
ck
ph
ot
o.
co
m
/8
93
50
95
FIGURE 15.9 Foods and Their Smells
Would you recognize the aromas of these dishes?
©
iS
to
ck
ph
ot
o.
co
m
/m
uk
es
h-
ku
m
ar
Tipofthenose
phenomenon: a phenomenon
that occurs when a person
is familiar with an odor but
cannot recall its name, despite
feeling as if he or she can
445 Chapter 15: Olfaction and Taste
related in frequency or some other variable. We are
good at discriminating odors even when we cannot
name them. It is estimated that we can distinguish
more than a thousand different aromas and that pro-
fessionals (e.g., wine tasters and perfumists) can dis-
criminate as many as 100,000 different odors (Herz,
2007). There is some debate as to the advantages
experts have in the sense domain, but the ability to
discriminate is clearly demonstrable. Research shows
that experts are better able to identify odors by name
and identify subcomponents within an odor. However,
whether wine experts can reliably predict which
wines are of higher quality has been an issue of some
debate, often showing results quite embarrassing
to those experts.
Odor Imagery
A fascinating question in olfaction is why so few people are able to experience olfac-
tory imagery. By olfactory imagery, we mean the ability to experience the “smell” of
a particular odor when that odor is not physically present. Imagery is different from
hallucination because the person generates the imagery herself and knows that the
image is present only internally. In the visual domain and the auditory domain, it is
easy to experience a sensory experience known to be not actually present. Just sitting
there reading this text, you can make a mental visual image what a Sicilian pizza looks
like, and without so much as moving your lips or vibrating your vocal chords, you can
imagine your favorite song. But try coming up with an olfactory image of the smell
of that pizza or what your significant other’s perfume smells like. Most people report
being unable to experience olfactory images (Djordjevic et al., 2008). Thus, unlike the
senses of vision and audition, olfactory imagery is difficult for most of us. However,
there is some research that supports the idea that some people are able to make olfac-
tory images. One study showed that people who reported olfactory imagery showed
brain activity in the piriform cortex when engaged in olfactory imagery. Control partic-
ipants asked to make olfactory images did not show this activity (Djordjevic, Zatorre,
Petrides, Boyle, & Jones-Gotman, 2005).
Olfactory Illusions
Our chapters on vision and audition abound with the concept of illusions. Illusions are
situations in which what we perceive is not what is physically present. For example,
after staring at a waterfall, we see the world moving in the opposite direction, even
though we know this is not so. We hear scales continually becoming higher pitched even
though the frequencies do not get higher. Olfactory illusions exist, though unlike visual
and auditory illusions, we are seldom conscious of the dissociation of stimulus and
perception (Stevenson, 2011). Because we are seldom aware of these olfactory illusions,
they get less attention than visual and auditory illusions. Nonetheless, we consider a
few olfactory illusions here.
There are a number of illusions that arise from context effects. That is, the olfactory
environment that surrounds a particular odorant changes the way that odorant is per-
ceived. Lawless (1991), for example, used the odorant chemical called dihydromyrcenol.
FIGURE 15.10 Identifying Odors in a Lab
Phanie/A
lam
y Stock Photo
446 Sensation and Perception
When this chemical is surrounded by woody-smelling odors, it is perceived as smelling
like citrus. However, when it is surrounded by citrus smells, it is perceived as being
woody in character. This is like some of the center-surround illusions in vision, in which
the border of an image influences the perception of lightness or color of the image inside
that border. In Lawless’s illusion, the surrounding odor influences the perception of a
target odor. In a number of other cases, surrounding odors can affect the perception of
a target odor (Stevenson, 2011).
Verbal labeling can also cause olfactory illusions. In particular, the label for a per-
ceived odor will often affect whether the odor elicits a positive or negative emotion.
Imagine being presented with an odor and being told it was “aged parmesan cheese.”
It is likely that your reaction might be positive. But if you were told the same odor
was “vomit,” you might have a very different reaction. Indeed, in this case, the two
substances have odorants in common, so it is likely in this case that you would be
influenced by the verbal label. This was put to the empirical test by Herz and von
Clef (2001), who presented odors with both a positive label and a negative label but
examined the influence of which label was presented first. In this case, participants read
both positive and negative labels, but Herz and von Clef reasoned that the first label
would have a bigger impact on emotional reaction to the odor. For example, the odor of
pine trees was presented with either the label “Christmas tree” first or the label “toilet
cleaner” first. The independent variable was which label occurred first. Herz and von
Clef found an outsized role for the first label. If the “Christmas tree” label was given
first, the odor was rated more positively than if the “toilet cleaner” label was given first.
Thus, the same odor with the same labels received a different pleasantness judgment
depending on the order of the labeling. For this reason, Stevenson (2011) classified this
effect as an olfactory illusion.
Other sensory modalities can also influence the perception of odor. For example,
Engen (1972) showed participants colored or noncolored liquids. Participants were more
likely to report smelling something in the colored liquids even when there were no odor-
ants present in the liquids. In effect, the visual perception of a colored liquid induced an
olfactory illusion of an odor even though the liquid had no odorants in it.
The final olfactory illusion we consider is olfactory rivalry (Stevenson & Mahmut,
2013). Olfactory rivalry is analogous to binocular rivalry, the illusion created by pre-
senting one image to the left eye and a very different image to the right eye. In vision, we
see only one of the images at any one time, but the perception of which image it is may
vary, seemingly randomly, across time. In olfactory rivalry, one odorant is presented to
one nostril, and a different odor is presented to the other nostril. For example, the left
nostril might receive the smell of roses (phenylethyl alcohol), whereas the right nostril
might receive the smell of “permanent markers” (butanol). Using this procedure, Zhou
and Chen (2009) found an analog to binocular rivalry. There was a seeming randomized
likelihood that people would smell the roses or the markers. People reported smelling one
and then the other but not both at the same time. As with binocular rivalry, the perception
of odor would switch over time from one to the other, also in a seemingly random fash-
ion. Stevenson and Mahmut showed that this illusion can occur even when both nostrils
are receiving both odors.
TEST YOUR KNOWLEDGE
1. What is the tip-of-the-nose phenomenon? What does it tell us about the relation
of olfaction to other functions in the brain?
2. What are olfactory illusions? Can you describe one and how perception is
tricked?
447 Chapter 15: Olfaction and Taste
TASTE PERCEPTION
15.4 Explain the anatomical and physiological
bases for taste perception.
M. F. K. Fisher wrote a number of books about cook-
ing and eating throughout her illustrious career as a
writer. Born in Michigan, Fisher lived in France and
California and produced some of the most delectable
writing about eating. Cunning and clever, her essays
were equally about food and life. Even a passage about
cauliflower from more than 70 years ago may still stop
your reading in your tracks and send you off to the
kitchen. She wrote, “There in Dijon, the cauliflowers
were very small and succulent, grown in that ancient
soil. I separated the flowerlets and dropped them in boiling water for just a few min-
utes. Then I drained them and put them in a wide shallow casserole, and covered them
with heavy cream, and a thick sprinkling of freshly grated Gruyere, the nice rubbery
kind that didn’t come from Switzerland at all, but from the Jura. It was called râpé
in the market, and was grated while you watched, in a soft cloudy pile, onto your
piece of paper” (Fisher, 1943, p. 441). Most people eat cauliflower only because it
is healthy, but that description may cause you to look up a recipe for a cauliflower
casserole (Figure 15.11).
What we can see in Fisher is the eloquent way in which she expresses the pleasure
and joy food brings to us. Pick your favorite food—a slice of pepperoni pizza, poutine,
sushi, Belgian chocolate, hot and sour soup, chana masala, or a breakfast omelet loaded
with cheese and mushrooms—many foods bring us distinct joy.
In this section, we discuss both the anatomy of the receptors that transduce chemicals
in the mouth into taste sensations and the neural circuitry in the brain responsible for the
sense of taste. We also discuss the term flavor (a technical term here), which is used to
describe the combination of taste and olfactory sensations into a combined perception,
which is often what we are appreciating when enjoying good food.
Like the sense of smell, the sense of taste is a chemical detection system that prob-
ably evolved to help us sort edible foodstuffs from toxins. We want to bring into our
bodies only foods that are not toxic. So we have evolved to enjoy foods that bring nour-
ishment and reject foods that do not. Our tongues therefore serve both as a gateway
to nutrition and to warn us of toxic chemicals. The fact that food brings us pleasure
reinforces the need to eat and supply our body with nutrition.
There are basic similarities between the two chemical senses of olfaction (smell)
and gustation (taste). Both respond to molecules, but for the sense of taste, we respond
to molecules called tastants, which dissolve when in contact with our saliva. Like
odorants, tastants initiate a transduction response in the receptors in our tongues.
Taste, therefore, is the perception of the transduction of tastants along the surface
of the tongue. There are also taste buds in other areas of the mouth that detect taste.
However, what we typically crave when we think of our favorite food is its flavor.
Flavor refers to the combined sensory experience of a food, which combines its taste,
its odor, and its effect on the trigeminal nerve. If we think of the flavor of coffee, the
smell of coffee is more instrumental to the flavor of this beverage than is its taste. If
we think of the flavor of pizza, the smell of that pizza slice is as critical to flavor as is
its taste. Tastes can be broken down into five basic tastes, which correspond to specific
FIGURE 15.11 Cauliflower Casserole
Shutterstock.com
/m
inadezhda
Tastants: molecules
recognized by taste receptors
that induce responses in taste
receptors on the tongue
Taste: the perception of the
transduction of tastants along
the surface of the tongue
Flavor: the combined sensory
experience of a food, which
combines its taste, its odor, its
effect on the trigeminal nerve,
and even visual experience
448 Sensation and Perception
receptors along the surface of the tongue. The basic
tastes are sweet, salty, sour, bitter, and umami (savory)
(Figure 15.12).
Sweet, salty, and umami tastes alert us to foods with
needed nutrients. Sweet means sugar and therefore car-
bohydrates, which we need to survive. Salty foods obvi-
ously contain salt, which our bodies require as well, and
umami (a Japanese word meaning “savory”) is associ-
ated with the taste of proteins, which our bodies need to break down into amino acids
in order to build our own proteins. In contrast, though we may like sour and bitter
foods in small doses, it is likely that sour and bitter tastes evolved as warnings about
foods to avoid because they may be inedible or toxic. Young children tend to avoid
very sour and bitter foods because of this innate reaction to them. This is why young
children invariably reject bitter foods such as broccoli or coffee. Try giving a 3-year-
old an endive and kale salad, and you will have a tantrum on your hands. We slowly
acquire the pleasure of bitter foods, usually as we combine them with sweet, salty,
and savory tastes. We also find that many of the bitter foods others eat do not make
us sick after all and thus acquire a taste for them. Even so, an adult eating an endive
and kale salad probably puts a dressing on that salad that adds sweetness, saltiness,
or umami to it.
Sugars are the tastant molecules that give food its sweet taste. These include sucrose
(the sugar commonly used as table sugar), fructose (the sugar found in fruits and used
in many processed foods), and glucose (which is used as an energy source in the body).
Artificial sweeteners, such as aspartame, are built from amino acids but mimic the
actions of sugars along the tongue. The salty taste is elicited by foods that contain
the chemical associated with common table salt, sodium chloride (NaCl). The sodium
part of salt is necessary for a number of bodily functions, so a desire for salty foods
pushes us to seek out and eat salty foods. Sour tastes are caused by acids and may be
pleasurable at low concentrations. Many of us like sour foods such as grapefruits and
other citrus fruits, pickles, kimchi, and yogurt. Bitter tastes are elicited by a number of
different kinds of molecules. Most bitter tastes arise from plant substances that are used
to discourage animals from eating their leaves and other parts of the plants. Some salad
greens, such as endive and kale, have a bitter taste because those plants evolved to deter
would-be eaters by tasting bad. Ironically, these plants now thrive because humans like
their bitter taste.
Umami is now considered a basic taste, though its inclusion in that group is rela-
tively recent (Yasuo, Kusuhara, Yasumatsu, & Ninomiya, 2008). There is evidence that
umami receptors exist on the tongue that are anatomically distinct from other recep-
tors. These are activated by amino acids found in foods such as meats and mushrooms,
as well as by the chemical MSG (monosodium glutamate). Umami signals the presence
of amino acids, which we need in our diet to synthesize proteins. Traditionally, these
amino acids come from meat or dairy products, although many plant foods also contain
amino acids. These plant-based amino acids, such as in tomatoes and mushrooms, also
trigger umami responses.
Anatomy of the Tongue and Taste Coding
Tastants are detected by receptors, located mostly on the tongue but also on other
surfaces within the mouth. Most taste buds are on the tongue, but about 33% of taste
buds can be found on the epiglottis, the soft palate, and the upper esophagus. These
receptors, then, as we have seen with other sensory systems, transmit a neural signal to
Sweet Salty Sour Umami Bitter
FIGURE 15.12 The Five Basic Tastes
449 Chapter 15: Olfaction and Taste
the brain, which then interprets the signal and integrates it with other sensory informa-
tion. So here’s the anatomy that supports taste transduction, and then we will follow
the neural signal.
The human mouth contains approximately 10,000 taste buds (Bartoshuk, 1971),
most of which are found on the tongue (Figure 15.13). Taste buds are small structures
located along the surface of the tongue or mouth that contain the receptor cells. Taste
buds are found within papillae, which line the surface of the tongue and mouth. There
are four different kinds of papillae, three of which contain the taste buds. The four dif-
ferent kinds of papillae are referred to as fungiform papillae, foliate papillae, circum
vallate papillae, and filiform papillae. The fungiform papillae are located mostly along
the edges and top of the tongue. The foliate papillae are found along the side of the
tongue. The circumvallate papillae are found along the very back of the tongue, aligned
seemingly along a row. The filiform papillae are found all over the tongue. But rather
than taste buds, these papillae contain somatosensory receptors. See Figure 15.14 for
the anatomy of the tongue.
Each taste bud contains anywhere from 40 to just more than 100 taste receptor
cells, which are elongated neurons with cilia at the end. Taste receptor cells are the
cells within the taste buds that transduce tastants into a neural signal. As with the
olfactory receptors, taste receptor cells die off after about a week and are replaced
by new taste receptor cells that develop within the taste bud. Tastants come into con-
tact with the surface of the tongue, where they are felt by the cilia and transduction
may occur.
Our tongues contain two kinds of taste receptor cells. One type is simply called
receptor cells. Receptor cells transduce sweet tastes, umami tastes, and bitter tastes.
Anatomically distinct presynaptic cells are also receptor cells, but they transduce salty
FIGURE 15.13
An Actual Human Tongue
The little bumps are the papillae,
which contain the taste buds.
Shutterstock.com
/
Raw
pixel.com
Foliate
Circumvallate
Filiform
Fungiform
papilla
Fungiform
Taste pore
Taste bud
Taste cell
Nerve fiber
Receptor sites on
tip of taste cell
Bitter
Sweet Sour
Salt
Na+
H+
Taste buds
FIGURE 15.14 Anatomy of the Tongue
The human tongue contains four kinds of papillae, three of which contain taste buds. Circumvallate papillae
are located in a line along the back of the tongue. Foliate papillae are located along the sides of the tongue.
Fungiform papillae are widely distributed but more concentrated toward the front of the tongue.
Taste buds: small structures
located along the surface
of the tongue or mouth that
contain the receptor cells
Papillae: small structures that
contain the taste buds
Fungiform papillae: located
mostly along the edges
and top of the tongue; they
respond to all five basic tastes
Foliate papillae: found along
the side of the tongue; they
respond to all five basic tastes
Circumvallate papillae:
found along the very back of
the tongue in a virtual row;
they respond to all five basic
tastes
Filiform papillae: found all
over the tongue; they contain
somatosensory receptors
rather than taste buds, so
that they feel food rather than
taste it
Taste receptor cells: cells
within the taste buds that
transduce tastants into a
neural signal
Receptor cells: taste receptor
cells that transduce sweet
tastes, umami tastes, and
bitter tastes
Presynaptic cells: taste
receptor cells that transduce
salty and sour tastes
450 Sensation and Perception
and sour tastes. In receptor cells, the cilia contain receptors that respond to one and
only one kind of taste, but unlike earlier conceptions, the different tastes are mixed
across the surface of the tongue (Chandrashekar, Hoon, Ryba, & Zuker, 2006). Each
presynaptic cell can transduce both salty and sour tastes. Presynaptic cells are connected
to cranial nerve fibers, which transmit the signal to the brain. Receptor cells appear to
have specific responses they transmit to presynaptic cells, which then transmit the signal
to the brain, although this idea is still quite controversial (Yoshida & Ninomiya, 2010).
Information leaves the taste buds through the 7th, 9th, and 10th cranial nerves and
heads to the brain. It then synapses in the nucleus of the solitary tract in the medulla
and then travels to the ventral posterior medial nucleus of the thalamus before heading
to the cortex. The first area of the cortex that receives input from the taste system is the
anterior insular cortex (part of the area known as the insula), located in the frontal
lobe. The insular cortex has a variety of functions in addition to taste perception, but
it is sometimes called the gustatory cortex for its functions in taste perception. The
insular cortex also projects to the orbitofrontal cortex, where taste and olfaction mix to
create flavor perception. The orbitofrontal cortex also has a number of other functions,
including a role in emotion and emotional control. Figure 15.15 shows an anatomical
drawing of the brain’s network for taste.
Some interesting work has been done on how taste perception centers in the orbi-
tofrontal cortex. When rats eat food, we can see activity in the anterior insular cortex,
regardless of whether the rats are hungry or not. However, in the orbitofrontal cortex,
there is activity only when the rats are hungry (Rolls, 2006). Thus, it is thought that
the orbitofrontal cortex is largely responsible for the pleasure involved in the eating of
food. This is compounded by the fact that the orbitofrontal cortex also responds to a
number of other sensory modalities that process the quality of food.
TEST YOUR KNOWLEDGE
1. What does the term umami mean? What chemicals elicit its perception? How
does it differ from bitterness?
2. Describe the neural pathways from the tongue through higher order areas of
the brain.
Thalamus
Nucleus of
the solitary tract
Chorda tympani
(branch of the facial
nerve, CN VII)
Glossopharyngeal
nerve (CN IX)
Vagus nerve (CN X)
Primary taste
cortex (insula)
Brain stem
Tongue
Nerve fibers
innervating taste
receptor cells
Circumvallate
papillae
Foliate papillae
Fungiform papillae
Taste receptors:
FIGURE 15.15
Pathways of Taste to the Brain
Information from the tongue is sent
through the cranial nerves to the nucleus
of the solitary tract, then to the ventral
posterior medial nucleus of the thalamus,
then to the insula, and from there to the
orbitofrontal cortex as well as areas in
the limbic system.
Anterior insular cortex
(insula): a part of the frontal
lobe that serves as the primary
taste cortex
451 Chapter 15: Olfaction and Taste
Taste and Flavor
We have mentioned throughout this chapter
how important the interaction is between our
two chemical senses, taste and olfaction. Indeed,
the concept of flavor refers to the combination
of both of these senses and others in determining
the basic pleasantness of foods. Thus, we define
flavor as the total perceptual experience that
occurs during eating, which combines not only
taste and olfaction but also somatosensory expe-
rience and visual experience. For example, think
about drinking a cup of hot chocolate. Flavor
is composed of olfactory sensations—the smells
wafting up to the olfactory epithelium. It is also
composed of the response along the tongue, in
particular, the unique combination of sweet-
ness and bitterness evoked by chocolate. Also
important to flavor is the action of the somato-
sensory system. In this case, the hotness of the
hot chocolate is registered by thermoreceptors
in the mouth and thus contributes to flavor as
well. If there is a minty taste to your hot choco-
late, the trigeminal nerve contributes to flavor as
well. Finally, even vision and audition contribute
to flavor. The sight of the chocolaty liquid with
the marshmallows and cinnamon flakes on top
is part of the delight. The sound of crunchiness
may be an important part of flavor for some
foods (though not hot chocolate). We eat potato chips because we crave salt, but the
crunch they make in our mouth is important to flavor. Much of this integration takes
place in the orbitofrontal lobe (Figure 15.16).
Individual Differences in Taste Perception
As with other sensory modalities, there are individual differences in our ability to taste.
We probably notice these differences whenever we eat with friends and family. Some
may require more salt to make their food taste the way they want it, and some may
drown their food in chili pepper sauce. Some of these individual differences have a
genetic basis. Just as most of us have a three-cone visual system (but some of us have a
two-cone [or fewer] visual system), genetic differences affect taste perception as well. By
far the most widespread of these genetic differences is differences in our ability to taste
bitter foods. There is a particular gene, known as TAS2R38, that codes for bitter-taste
receptors. The TAS2R38 gene comes in two forms, the PAV form and the AVI form.
Most of us have the PAV form, which allows us to detect bitter tastes, especially those
that derive from two chemicals known as phenylthiocarbamide and propylthiouracil.
People with the PAV form of the gene who can detect these chemicals are called simply
tasters. Most of us are just plain tasters. However, a minority of about 25% of people,
who have the AVI form of the gene, are referred to as nontasters because they require
much higher doses of these chemicals in order to detect a bitter taste (Bartoshuk, Duffy,
& Miller, 1994). Nontasters will enjoy many bitter foods not because they sense the
bitter taste but rather because other tastes are more salient to them (Figure 15.17).
Hunger/thirst
Vision
Audition
OLFACTION
FLAVOR
TASTE
Onset/
aftertaste
Intensity Quality
Hedonics
Pleasant Unpleasant
Localization
“Mouth feel,” including
factors such as
• Texture (crispiness,
fattiness, grittiness, etc.)
• Temperature (cold to hot)
• Spiciness (as from chili
peppers)
• Coolness (as from mint)
• Dryness (astringency, as
from unripe fruit)
Sweet
Salty
Umami
Sour
Bitter
Mild
sour
Strong
sour
FIGURE 15.16 The Perception of Flavor
Taste and olfaction, as well as vision, audition, and the somatosensory system, all
contribute to our perception of flavor. Sweet, salty, and umami tastes alert us to
foods with needed nutrients. Sweet means sugar and therefore carbohydrates,
which we need to survive. Salty foods obviously contain salt, which our bodies
require, and umami (a Japanese word meaning “savory”) is associated with the
taste of proteins, which our bodies need to break down into amino acids in order to
build our own proteins.
Tasters: people who can
detect bitter compounds
Nontasters: people
who cannot detect bitter
compounds except at very
high concentrations
452 Sensation and Perception
There is also a class of people known
as supertasters, who have the PAV form
of the gene but who also have more fun-
giform papillae on their tongues than
normal tasters do, also from genetic
causes. Because of the genetic origins of
supertasters, there is a higher percent-
age of supertasters among populations
of non-European origins. Asians, for
example, are more likely to be super-
tasters than Europeans. In addition,
there is a sex difference. Women are
more likely than men to be supertasters.
However, recent data suggest that fun-
giform papillae density is not related to
being classified as a supertaster (Garneau et al., 2014). Thus, the neural, but not genetic,
basis of supertasters is now in some doubt.
Because of their high concentration of fungiform papillae, supertasters are highly
sensitive to bitter tastes and usually avoid them, as they find bitter tastes overwhelming.
Thus, supertasters tend to avoid bitter beverages, including beer, green tea, and cof-
fee, which contain many bitter compounds. In addition, supertasters may avoid bitter
foods, such as Brussels sprouts, kale, cabbage, olives, some soy products, and some
citrus fruit, such as grapefruits. Supertasters may also avoid spicy foods because the
fungiform papillae are innervated by the nerve fibers that send information about burn
and touch sensations on the tongue. Thus, supertasters may also avoid foods containing
chili peppers (Delwiche, Buletic, & Breslin, 2001). To summarize, there are individual
differences in the detection of tastes, some of which derive from genetic differences
among individuals.
Some research shows that these distinctions have health implications. Supertasters
avoid some healthy foods because they just taste too bitter. In support of this
view, Duffy, Lucchina, and Bartoshuk (2004) found that older supertasters had more
colon polyps (a precursor to colon cancer) than did control participants because
they avoided vegetables that lower the risk for these colon polyps. However, they also
found that because supertasters avoid fatty foods as well, they show lower risk for
cardiovascular disease.
The Wonderful World of Chili Peppers
In Chapter 2, we introduced the effect of chili peppers on taste perception as an exam-
ple of how psychophysics works in the real world. We discussed the Scoville scale and
how it measures our perception of capsaicin, the active ingredient in chili peppers that
causes them to be experienced as piquant or “spicy hot.” In this section, we briefly
describe the process by which we taste the capsaicin in chili peppers (Figure 15.18).
Capsaicin content varies in different peppers, from relatively small amounts in a banana
pepper to enough to cause a “heat” response in a habanero pepper to the specially bred
chili peppers of today with very high capsaicin content, such as the Carolina Reaper.
The painful or burning sensation caused by capsaicin in chili peppers is caused by
its activation of activity in the trigeminal nerve, which codes for heat in the mouth.
Capsaicin also stimulates taste receptors in the fungiform papillae, which contribute
to the sensation of heat on the tongue. It is the action along the fungiform papillae
that make supertasters more sensitive to capsaicin than are normal tasters. Despite the
feeling of pain that eating a very hot chili pepper may bring, it causes no actual physical
FIGURE 15.17
Receptors on the Tongues of (a) Nontasters and (b) Supertasters
The tips of the tongues of a nontaster (a) and a supertaster (b) (pink = fungiform papillae).
Supertasters: people who
are extremely sensitive to
bitter tastes; they usually do
not like foods with many bitter
compounds
FIGURE 15.18
The Joys of Chili Peppers
©
iS
to
ck
ph
ot
o.
co
m
/G
M
Vo
zd
453 Chapter 15: Olfaction and Taste
damage. There may be slight swelling or inflammation, but this is caused by the actions
of the nerves themselves, not the capsaicin. Interestingly, exposure to capsaicin causes
the receptors to desensitize to the chemical. Thus, if you accidentally eat a hot chili
pepper and wait until the burn subsides, you will find yourself curiously able to handle
another one (and impress your friends). This desensitization ironically allows capsaicin
to be used as a painkiller in some medical applications.
Development of Taste Perception
Infants are seemingly born with an attraction to foods
that are sugary and foods that are salty (Herz, 2007). As
any parent knows, sweet foods will elicit smiles in young
infants (Figure 15.19). Virtually every family has a photo-
graph of a happy baby whose face is covered in chocolate
cake. However, many of our taste preferences are condi-
tioned responses that develop as a function of experience
and reinforcement. For example, most infants and young
children avoid coffee, as it is too bitter for their tastes. We
acquire a liking for the taste of coffee as we associate it
with the sugar we put in it and the milk we put in it, as
well as the wakefulness that the caffeine in coffee causes.
Thus, by the time we reach adulthood, many of us enjoy
both the aroma and the taste of coffee, even when not
combined with milk or sugar. Similarly, most young chil-
dren will reject alcoholic beverages unless they are paired
with large concentrations of sugar. This is true for some adults as well. Beverages such
as rum and tequila are popular because they are very sweet as well as highly alcoholic.
And, of course, few parents would subject their infants to Scotch bonnet peppers. This
taste preference develops later in life.
Some research shows how a person’s early environment can affect taste perception.
For example, an early deficiency in salt intake can cause later cravings for and higher
intake of salts (Stein et al., 1996). Even when pregnant mothers do not receive adequate
salt in their diet, their offspring will show later salt cravings (Crystal & Bernstein,
1995). Similarly, our desire for fatty foods may also be influenced by early developmen-
tal experiences.
TEST YOUR KNOWLEDGE
1. How do taste perceptions interact with olfaction to create flavor?
2. What are the differences between tasters, nontasters, and supertasters?
FIGURE 15.19 Young Children Crave Sugary Foods
Shutterstock.com
/aaltair
EXPLORATION: Anosmia
Carl is a young man in his late teens. He attends the local
community college, where he made the dean’s list in his
first year. Carl is athletic, outgoing, and a dog enthusi-
ast. He never misses walking his family’s four dogs every
morning. Carl’s father was a champion professional
boxer and has trained Carl to box. Although Carl’s career
ambitions lie elsewhere, he frequently spars at the local
boxing gym with other young men. While sparring, Carl
was punched in the nose, breaking the cartilage and forc-
ing some of the cartilage up through his olfactory tract,
fracturing the cribriform plate and shearing the olfactory
nerve. Since then, Carl has had a condition called anosmia,
454 Sensation and Perception
the inability to perceive odor because of malfunctioning
olfactory perception. Carl has complained that food does
not taste as good, and he has lost a bit of weight. But he
now seeks out more high-calorie food to compensate for
his loss of appetite. Interestingly, he regrets not being able
to smell his dogs, but in general, he has adjusted to his
condition.
Anosmia such as this may be only temporary, or it may
be permanent, depending on the damage to the cribriform
plate and whether the olfactory nerve was just damaged
or completely cut. In some cases, as long as the olfactory
nerve is not severed, olfaction may eventually come back.
In addition to head trauma, anosmia may be caused by
inflammation in the nasal cavities, blockage of the nasal
passageways (in which case the anosmia may be tempo-
rary), or damage to the areas of the brain responsible
for olfactory perception (in which case the anosmia is
likely permanent). Temporary anosmia may also develop
in depressed patients receiving electroconvulsive shock
therapy. Anosmia may occur in progressive neurological
disorders such as Parkinson’s disease and Alzheimer’s dis-
ease (Attems, Walker, & Jellinger, 2014). Indeed, patients’
awareness of their anosmia may be one of the early clues
that lead doctors to make these more serious diagnoses.
There are also people who are born with an extremely rare
condition known as congenital anosmia. Such individuals
do not develop a normal sense of smell or any sense of
smell at all (Frasnelli, Fark, Lehmann, Gerber, & Hummel,
2013). Most people with congenital anosmia may not
realize it until well into adulthood, as in most situations,
they may compensate for it with their other senses.
Anosmia may result also from traumatic brain injury to
areas of the brain receiving input from the olfactory bulb.
In particular, given its location near the front of the skull
and behind the eyes, the orbitofrontal cortex may often
be damaged in accidents, such as car crashes. Damage to
the orbitofrontal cortex can result in anosmic symptoms
(Caminiti, Ciurleo, Bramanti, & Marino, 2013). Until
recently, the different causes of anosmia were grouped
together, but researchers have begun to notice differences
in the etiology resulting from damage to different sections
along the olfactory tract.
Think back to our discussion of different forms of visual
impairment. Damage to the eyes can cause blindness.
However, damage to the visual areas of the brain is more
complex. Damage to V1 causes blindness (except for areas
of blindsight), but damage to higher areas of the extra-
striate cortex can cause complex agnosias, such as the
inability to identify objects, even though a patient can see
them and describe them. A similar situation exists in the
olfactory system, though it is just being acknowledged and
investigated. Shearing of the olfactory nerve causes a loss
of olfactory sensation. People who, like Carl, have severed
olfactory nerves can no longer detect odors. Thus, they
are unable to recognize them, but it is likely that if they
possessed olfactory imagery, it might still exist. However,
recent research on anosmia in people with orbitofrontal
damage suggests that these people can still detect odors,
but they are extremely impaired in recognizing them rela-
tive to controls (Caminiti et al., 2013).
Thus, damage to the orbitofrontal cortex may be more
similar to a form of olfactory agnosia than anosmia. That
is, damage to the nose itself and the olfactory bulb pro-
duces deficits in the detection of odors, whereas damage
to the piriform cortex and orbitofrontal cortex produces
deficits in odor recognition and discrimination. For exam-
ple, Tranel and Welsh-Bohmer (2012) identified a patient
with extensive damage to his limbic system and orbito-
frontal cortex and found intact detection of odors but
severely impaired naming, recognition, and discrimination
of odors.
Anosmia may also occur in the normal process of aging.
It is estimated that by the age of 80 years, nearly half
of the population has experienced some deficit in their
sense of smell (Herz, 2007). Because this loss is gradual,
many older adults may not be aware that their senses
of smell have diminished. Although we cannot compen-
sate for olfactory loss (i.e., there is no such invention yet
as a smelling aid), awareness of the effects of anosmia
might help some older adults cope with the problems
caused by anosmia. For example, if the sense of smell is
compromised, food may not be as appealing, leading to
declines in caloric intake and proper nutrition. In fact,
Herz reported that older adults have fewer “cravings” for
specific foods than do younger adults, which may be due
partially to reduced olfactory abilities. Older adults may
also add more salt to their food, which in some cases can
result in increased blood pressure. Adding salt may com-
pensate for the loss of flavor due to lost olfactory sensitiv-
ity, but it may compromise their health. We can experience
something akin to this form of anosmia when we have a
very stuffed nose. When we have such a cold, food does
not have the same flavor, because we are not getting the
same olfactory input. With a cold, you may find that you
avoid foods that rely on olfaction for their flavor, such
as coffee, and prefer foods with heavy salt content (e.g.,
chicken soup).
455 Chapter 15: Olfaction and Taste
Anosmia is also linked with depression. The higher areas
of the olfactory system are closely linked to the limbic sys-
tem, which is involved in the regulation of emotions. Many
brain regions associated with olfaction, such as the orbi-
tofrontal cortex, are considered part of the limbic system.
Thus, the loss of smell may affect emotion (Herz, 2007).
It is likely that there is a causal direction between anos-
mia and depression because brain areas associated with
olfaction and emotion are connected, such that damage to
the olfactory regions also impairs emotional responding.
Some studies suggest that depression may develop gradu-
ally after the onset of anosmia.
There also exists a neurological condition called phan-
tosmia (Landis, Croy, & Haehner, 2012). Phantosmia
is a condition in which people smell odors that are not
physically present. In this sense, phantosmia is essen-
tially an olfactory hallucination, which can be quite dis-
tracting to patients who have it. It differs from olfactory
imagery because the person is not in control of olfactory
experience, nor is he aware that the experience is differ-
ent from real odor perception. Phantosmic smells occur
without any conscious control over them. Phantosmia
may occur during early Parkinson’s disease and in other
neurological disorders. Phantosmia may also occur as a
precursor to an epileptic seizure. Similarly, phantosmia
may also occur as part of an “aura” just before a patient
experiences a migraine. Fortunately, though, most bouts
of phantosmia tend to dissipate over time (Landis et al.,
2012). Thus, in most cases, phantosmia is not permanent
(though if the smell is of chocolate, one might want it to
last longer). Phantosmia is an interesting area, but it is one
that awaits further study. And in case you were wonder-
ing, ageusia is the term that describes a person who has
lost the ability to taste. It is an extremely rare condition,
especially for all tastes.
Phantosmia: hallucinatory perception of odors
Ageusia: loss of the ability to taste
APPLICATION: Artificial Sweeteners
and Taste Perception
As we have discussed previously, most people crave sweet
foods. In past times, this served humans well, as calories
were in short supply and sweet foods contained lots of cal-
ories. In today’s world (at least in the Western world), cal-
ories are abundant, and eating too many sweet foods is a
danger instead of being helpful. High-calorie foods, espe-
cially sweet foods, can lead to obesity, type 2 diabetes, and
various forms of heart disease (Frazier, 2018). As such,
many people now opt for diet foods with artificial sweet-
eners (Figure 15.20). Artificial sweeteners are intended to
impart fewer calories but provide the same or similar taste
of sweetness to people who use them. Our goal here is not
to debate their value for health but to understand how
artificial sweeteners, which are usually amino acid based
rather than sugar based, stimulate receptors on the tongue
and how they differ in perception from actual sugars (see
Swithers, 2016, for an empirical-based discussion of the
healthfulness of artificial sweeteners).
We define artificial sweeteners as sugar substitutes that
seek to duplicate the effect of sugar on our sense of taste,
but with fewer calories. Most artificial sweeteners work
because they hyperstimulate the taste bud receptor cells
that are responsible for sweet tastes. Artificial sweeteners
stimulate receptor proteins on the outer tips of the taste
cells that respond to sweetness and therefore induce an
experience of sweetness. That is, artificial sweeteners, such
as saccharin and aspartame, can be used as sweeteners
because they elicit a sweet response from our taste buds
but do so with far less of the chemical than standard nat-
ural sugars, such as sucrose or fructose. Because saccharin
can stimulate sweet receptors at lower levels, less of it is
needed, and, therefore, fewer calories are consumed by
the individual. Indeed, by weight, saccharin is many times
more powerful at eliciting sweet responses than is sucrose.
Some estimates hold that saccharin is 300 times more suc-
cessful at stimulating sweet receptors than actual sugars.
If this is so, it is natural to ask why is it that many of us
Artificial sweeteners: sugar substitutes that seek to
duplicate the effect of sugar on our sense of taste, but with
fewer calories
456 Sensation and Perception
still prefer the taste of sugars to that of artificial sweeten-
ers? Why do sugared sodas taste so much better than diet
sodas to so many of us?
As discussed earlier, the neural pathway for taste takes
information to the primary taste cortex in the anterior
insula. The anterior insular cortex, also known as the
primary gustatory cortex, projects to the orbitofrontal
cortex, where taste and olfaction mix to create flavor
perception. However, the primary taste cortex also pro-
jects to areas associated with reward pathways, such as
the amygdala and the caudate nucleus. These areas are
related to the release of dopamine, a neurotransmitter
associated with reward and pleasure. It turns out that
natural sugars promote activity in the amygdala and the
caudate nucleus, but artificial sweeteners do not (Frank
et al., 2008). Another reason that natural sugars taste bet-
ter than artificial sweeteners is that many artificial sweet-
eners also have a bitter taste, which interferes with the
experience of the sweetness (Rodrigues et al., 2016). For
this reason, some research is directed at eliminating the
bitterness from artificial sweeteners so that the sweetness
can be more effective.
Frank et al. (2008) used magnetic resonance imaging
(MRI) technology to compare the effects of sugar and
artificial sweeteners on various regions of the brain.
Participants were given drinks with either sugar or arti-
ficial sweetener (sucralose) and asked to rate them on a
scale in which 1 represented “did not taste good” and 9
represented “extremely enjoyable.” Frank et al. found that
both the sugar and the artificial sweeter activated the pri-
mary taste area in the insula, but only the sugar activated
the reward areas in the midbrain and caudate nucleus. This
suggests, as we know from earlier discussion, that there is
more to taste than just the response on the tongue. It is
likely that satiation mechanisms induce a feedback loop,
which results in the high-calorie sugars still tasting better,
even though the artificial sweeteners may be causing the
same or bigger response in the taste buds. However, some
research suggests that consistent use of artificial sweeten-
ers may eventually result in bigger responses in the mid-
brain, perhaps as people get used to the different internal
feedback from the artificial sweetener (Green & Murphy,
2012). Other factors may also play a role. For example,
Wang, Duncan, and Dietrich (2016) varied the mineral
content of water, that is, the presence of chemicals such
as iron or calcium in drinking water. Natural sugars were
judged as being more enjoyable when mixed with these
chemicals than artificial sweeteners. However, the data are
not always that sugars are more pleasant than artificial
sweeteners. Delogu et al. (2016) found that participants
in a blind taste test judged as more pleasant carbonated
beverages sweetened with artificial sweeteners. However,
it was unclear how this study accounted for the amount of
sweetener in each beverage because this study used com-
mercially available drinks. Nonetheless, it does suggest,
that in some circumstances, the artificial sweeteners may
be considered sweeter than natural sugars.
There are also a few natural nonsugar-based sweeteners,
that is, natural products that serve as “artificial sweet-
eners.” The most famous of these is the miracle fruit, or
Synsepalum dulcificum, as it is known in scientific lingo.
The miracle fruit itself has a low sugar content, but it also
has a chemical (called, aptly, miraculin) that activates the
FIGURE 15.20 Artificial Sweeteners
Artificial sweeteners are designed to provide eaters with the sweet taste they crave, but without an abundance of calories. Artificial sweeteners are
chemicals that highly stimulate receptors on the tongue responsible for sweet tastes.
©
iS
to
ck
ph
ot
o.
co
m
/N
oD
er
og (a)
Shutterstock.com
/SpeedKingz
(b)
Chapter 15: Olfaction and Taste 457
taste bud receptors responsible for sweet taste (Misaka,
2013). In particular, when it is eaten in combination with
sour foods, such as lemons or oranges, it causes the sour
taste of these foods to taste sweet because of this activation
of the sweet taste receptors. The effect of the miraculin
lasts up to about 30 minutes (see Rodrigues et al., 2016).
For example, Rodrigues et al. reported that unsweetened
lemonade tasted sweet to participants when miracle-fruit
juice was added. Currently, miraculin is not allowed to be
used as a sweetener in American markets, but it is avail-
able as a supplement in some European countries.
Artificial sweeteners are somewhat controversial. There
are those who think that the use of artificial sweeteners
will help people overcome obesity and diabetes by provid-
ing a low-calorie alternative to obtaining sweetness (but
see Swithers, 2016, for a dissenting view). High-impact
artificial sweeteners may also be useful for people expe-
riencing loss of appetite for one reason or another (e.g.,
chemotherapy). Thus, understanding how and why arti-
ficial sweeteners produce sweetness and how they can be
designed to mimic the taste of natural sugars is an inter-
esting applied issue in perception research.
CHAPTER SUMMARY
15.1
Examine the role of the olfactory system in
detecting harmful and helpful substances.
The chemical senses allow us to detect molecules either
in the air or in our mouths. Olfaction is the sense of smell,
whereas gustation is the sense of taste. Olfaction detects
odorants, volatile chemicals in the air that enter our nose.
Odors are the perceptual experience of odorants, which
are airborne chemical stimuli. Odorants enter our noses,
where they head up the two nostrils, which are separated
from each other by the nasal septum. Turbinates then
disperse air within the nasal cavity. The odorants rise to
the olfactory cleft, the channel at the back of the nasal cav-
ity that funnels air up toward the olfactory epithelium. The
olfactory epithelium is a mucous membrane inside each
nostril of the nose that contains the receptor cells for the
olfactory system. The olfactory receptor neurons are the
receptor cells located in the olfactory epithelium. When the
olfactory receptor neurons detect specific chemicals in the
air, they transduce them into a neural signal. The signal is
then sent to brain structures associated with the olfactory
system. The olfactory receptor neurons are replaced fre-
quently by the generation of new ones from the basal cells.
We have about 350 different kinds of olfactory receptors,
depending on how many genes we have activated to code
for different forms of olfactory receptors. Just internal to
the nose is the trigeminal nerve, also known as the fifth cra-
nial nerve, which is associated with the feel of odorants,
such as the burn of chili peppers.
15.2
Describe the anatomical and physiological bases
for olfaction.
The olfactory receptor neurons project axons through lit-
tle holes through the cribriform plate, which travel to the
olfactory bulb. If the olfactory tract is severed, anosmia,
a deficit in olfactory perception, may result. The olfactory
nerve starts with olfactory receptor neurons that leave
the nose and enter the olfactory bulb. The olfactory bulb is
a part of the brain just behind the nose. It is the first place
in the brain where olfactory information is processed. The
olfactory tract leaves the olfactory bulb to other regions of
the brain, including the amygdala, entorhinal cortex, and
piriform cortex. The piriform cortex is considered the pri-
mary olfactory cortex. The piriform cortex is divided into
two sections. The anterior piriform cortex is located in the
front portion of the piriform cortex and is associated with
representing the chemical structure of odorants. The pos-
terior piriform cortex is located in the back portion of the
piriform cortex and is associated with an odor’s quality,
regardless of its chemical composition. The piriform cor-
tex projects to the orbitofrontal cortex. The orbitofrontal
cortex is critical in the emotional experience of odors and
integrating olfaction and taste perception, among other
functions.
15.3
Appraise the nature of olfactory perception,
olfactory imagery, and olfactory illusions.
Detection thresholds vary across odorants, though in gen-
eral it does not take too many odorants to elicit an odor. We
are also good at discriminating odors, that is, telling one
from another. However, we appear not to be good at nam-
ing odors. The tip-of-the-nose phenomenon occurs when
a person is familiar with an odor but cannot recall its name,
despite feeling as if she can. This experience of finding an
odor familiar but being unable to name it is quite common.
Most individuals do not have olfactory imagery, although a
minority of people do. Those who do have olfactory imag-
ery show activity in the piriform cortex when engaging in
Sensation and Perception458
olfactory imagery. Olfactory illusions occur when our per-
ceptions of odorants change depending on the external
conditions. In one illusion, olfactory rivalry, one odorant is
presented to one nostril, and a different odor is presented
to the other nostril. In olfactory rivalry, we experience only
one odor at a time, even though both are present.
15.4
Explain the anatomical and physiological bases
for taste perception.
Taste perception (gustation) is also a chemical system
designed to make nutritious foods appealing and to make
us withdraw from potentially toxic foods. The term tastant
refers to molecules recognized by taste receptors that
induce responses in taste receptors on the tongue. Taste
is the perception of the transduction of tastants along the
surface of the tongue, whereas flavor is the combined
sensory experience of a food, which combines its taste, its
odor, and its effect on the trigeminal nerve. Sweet, salty,
and umami tastes alert us to foods with needed nutrients.
Sour and bitter tastes evolved as warnings about foods to
avoid because they may be inedible or toxic. However, in
many cultural contexts, we have learned to enjoy sour and
bitter foods as well. Taste buds are located along the sur-
face of the tongue or mouth and contain the receptor cells
that transduce the chemicals in foods into neural signals.
The papillae are small structures that house the taste buds.
There are four different kinds of papillae, distinguishable
by their shapes, the kinds of taste buds they contain, and
where along the tongue they are. Taste receptor cells are
the cells within the taste buds that transduce tastants into
a neural signal. There are two kinds of taste receptor cells.
Receptor cells transduce sweet tastes, umami tastes, and
bitter tastes, whereas presynaptic cells transduce salty
and sour tastes. Information leaves the taste buds through
the 7th, 9th, and 10th cranial nerves and then synapses in
the nucleus of the solitary tract in the medulla and then
travels to the ventral posterior medial nucleus of the thal-
amus. The first area of the cortex that receives input from
the taste system is the anterior insular cortex located in
the frontal lobe. The anterior insular cortex is known as
the primary gustatory cortex because of its functions in
taste perception. The anterior insular cortex also projects
to the orbitofrontal cortex, where taste and olfaction mix
to create flavor perception.
There are individual differences in taste perception, some
of which are genetic in origin. Much research has inves-
tigated the genes that code for the perception of bitter
tastes. People can be divided into normal tasters, who
can detect bitter compounds; nontasters, who cannot
detect bitter compounds except at very high concentra-
tions; and supertasters, who are extremely sensitive to
and repelled by bitter tastes. Anosmia is a deficit in the
detection or perception of odors. This condition can occur
from damage to both the nasal pathway and the brain
regions involved in olfaction. Phantosmia is the halluci-
natory perception of odors. Ageusia is a loss of the ability
to taste. Artificial sweeteners are sugar substitutes that
attempt to duplicate the effect of sugar on our sense of
taste, but with fewer calories. They do so by stimulating
the same taste receptors on the tongue as natural sugars.
However, the complexity of taste perception is such that
people still prefer natural sugars to artificial sweeteners.
REVIEW QUESTIONS
1. What are odorants? How do they differ from other
molecules? Why do we have chemical detection
systems?
2. What is the trigeminal nerve? How does it interact
with olfaction and gustation? What basic sensations
does it detect?
3. Describe the pathway from when an odorant enters
the nose to when it is processed in the frontal lobes
of the brain. Describe each step along the pathway.
4. What is the piriform cortex? What are the differ-
ent functions of the anterior and posterior piriform
cortices?
5. What is an olfactory illusion? Describe two olfac-
tory illusions and what they tell us about olfaction in
general.
6. Describe the gustatory pathway from when food is
felt on the tongue to when it is processed in the fron-
tal lobes of the brain. Describe each step along the
pathway.
7. What is the difference between taste perception and
flavor perception? What area of the brain seems to
be responsible for flavor perception?
8. What are the five basic tastes? How are they pro-
cessed on the tongue? Why is information about
each basic taste essential for survival?
Chapter 15: Olfaction and Taste 459
9. Describe the differences in genetics, anatomy,
and behavior among tasters, nontasters, and
supertasters.
10. What is anosmia? What causes anosmia to occur?
How does anosmia resulting from damage to the
nose differ from anosmia caused by damage to the
piriform cortex? What is phantosmia? How does it
differ from olfactory illusions?
PONDER FURTHER
1. It is said that people can smell fear. How could
this be? What would it take in order for human beings
to realistically detect fear when other people experi-
ence it?
2. Given that detecting poisons and seeking out calories
and nutrients are such fundamental aspects of the
sense of taste, how can it be that there is such amazing
cultural variety in what humans eat across the world?
KEY TERMS
Ageusia, 455
Amygdala, 441
Anosmia (smell blindness), 440
Anterior insular cortex (insula), 450
Anterior piriform cortex, 442
Artificial sweeteners, 455
Basal cells, 438
Circumvallate papillae, 449
Cribriform plate, 440
Entorhinal cortex, 441
Filiform papillae, 449
Flavor, 447
Foliate papillae, 449
Fungiform papillae, 449
Glomeruli, 441
Gustation, 436
Macrosmatic, 439
Microsmatic, 439
Mitral cells, 441
Nasal septum, 437
Nontasters, 451
Odorants, 436
Odors, 436
Olfaction, 436
Olfactory bulb, 441
Olfactory cleft, 438
Olfactory epithelium, 438
Olfactory nerve (first
cranial nerve), 441
Olfactory receptor neurons, 438
Olfactory tract, 441
Orbitofrontal cortex, 443
Papillae, 449
Phantosmia, 455
Piriform cortex, 441
Posterior piriform cortex, 442
Presynaptic cells, 449
Receptor cells, 449
Supertasters, 452
Supporting cells, 438
Tastants, 447
Taste, 447
Taste buds, 449
Taste receptor cells, 449
Tasters, 451
Tip-of-the-nose phenomenon, 444
Trigeminal nerve, 440
Tufted cells, 441
Turbinates, 438
Sensation and Perception460
Sharpen your skills with SAGE edge at edge.sagepub.com/schwartz2e
SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review,
study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.
Learning Objectives Digital Resources
15.1 Examine the role of the olfactory system in detecting harmful
and helpful substances.
Never Mind Eyesight, Your Nose Knows Much More
Jennifer Pluznick: You Smell With Your Body Not
Just Your Nose
15.2 Describe the anatomical and physiological bases for olfaction. Charting Plasticity in the Regenerating Maps of the
Mammalian Olfactory Bulb
Sniffing Out the Science of Smell
Smelling in Stereo: Human Sense Detailed in Study
15.3 Appraise the nature of olfactory perception, olfactory imagery,
and olfactory illusions.
Nostril Advantage in Trigeminal/Olfactory Perception and
Its Relation to Handedness
Anosmia
15.4 Explain the anatomical and physiological bases for taste
perception.
Leaving a Flat Taste in Your Mouth: Task Load Reduces
Taste Perception
The Representation of Taste Quality in the Mammalian
Nervous System
Study: When Soda Fizzes, Your Tongue Tastes It
Sushi Science: A 3-D View of the Body’s Wasabi Receptor
Sriracha Chemistry: How Hot Sauces Perk Up Your Food
and Your Mood
This Is an Orchestra Under the Influence of Chili Peppers
Glossary 461
GLOSSARY
Absolute threshold: the smallest amount
of a stimulus necessary to allow an
observer to detect its presence
Accommodation: the process of
adjusting the lens of the eye so that both
near and far objects can be seen clearly
Accretion: the gradual reappearance
of a moving object as it emerges from
behind another object
Acoustic reflex: a reflex that tightens
the tensor tympani and the stapedius in
response to chronic loud noise
Acoustic shadow: the area on the side of
the head opposite from the source of a
sound in which the loudness of a sound
is less because of blocked sound waves
Action: any motor activity
Active electroreception: the ability to
generate electric fields and then detect
disturbances or changes to those
electric fields caused by external events
Additive color mixing: the creation of a
new color by a process that adds one
set of wavelengths to another set of
wavelengths
A-delta fibers: myelinated nociceptors
that conduct signals rapidly and respond
to both heat and pressure
Afferent fibers: neural fibers that carry
sensory information to the central
nervous system
Affordance: information in the
visual world that specifies how that
information can be used
Aftereffect: a sensory experience that
occurs after prolonged experience of
visual motion in one particular direction
Afterimages: visual images that are seen
after an actual visual stimulus has been
removed
Ageusia: loss of the ability to taste
Agnosia: a deficit in some aspect of
perception as a result of brain damage
Akinetopsia (motion blindness): a rare
condition in which an individual is
unable to detect motion despite intact
visual perception of stationary stimuli,
caused by damage to area MT
Ames room: a specially constructed
room where two people of the same size
standing in the two back corners will
look very different in height
Amplitude: the difference between
maximum and minimum sound pressures
Ampulla: the structure at the base of
each semicircular canal that contains
the crista
Ampullae of Lorenzini: the organs
that contain the hair cells that detect
electric fields, used in passive
electroreception
Amusia: a condition in which brain
damage interferes with the perception
of music but does not interfere with
other aspects of auditory processing
Amygdala: an area of the brain in the
limbic system, associated with the
experience of emotion, particularly fear
Analgesia: processes that act to reduce
pain perception
Anomalous trichromacy: a condition
in which all three cone systems are
intact, but one or more has an altered
absorption pattern, leading to different
metameric matches than in the most
common type of trichromatic individuals
Anosmia (smell blindness): the inability
to smell, usually caused by cribriform
plate damage
Anterior chamber: the fluid-filled space
between the cornea and the iris
Anterior cingulate cortex: a region in the
prefrontal lobe of the brain associated
with the emotional experience of
unpleasantness during pain perception
Anterior insular cortex (insula): a part
of the frontal lobe that serves as the
primary taste cortex
Anterior intraparietal (AIP) area: a region
of the posterior parietal lobe involved in
the act of grasping
Anterior piriform cortex: a structure
located in the front portion of the
piriform cortex that is associated with
representing the chemical structures of
odorants
Aphasia: an impairment in language
production or comprehension brought
about by neurological damage
Apparent motion: the appearance of real
motion from a sequence of still images
Architectural acoustics: the study of
how physical spaces such as concert
halls affect how sounds are reflected in
a room
Artificial sweeteners: sugar substitutes
that seek to duplicate the effect of sugar
on our sense of taste, but with fewer
calories
Ascending series: a series in which a
stimulus gets increasingly larger along a
physical dimension
Astigmatism: a condition that develops
from an irregular shape of the cornea or
the lens, which makes it impossible for
the lens to accommodate a fully focused
image
Atmospheric perspective: a pictorial
depth cue that arises from the fact that
objects in the distance appear blurred
and tinged with blue
Attack: the beginning buildup of a note
in music
Attention: a set of processes that allow
us to select or focus on some stimuli
Attentional blink: the tendency to
respond more slowly or not at
all to the second appearance of a
target in an RSVP task when the second
target occurs within 500 ms of the first
target
Attentional capture: the process
whereby a salient stimulus causes us to
shift attention to that stimulus
Audiogram: a graph that illustrates
the thresholds for the frequencies as
measured by the audiometer
Audiologist: a trained professional
who specializes in diagnosing hearing
impairments
Sensation and Perception462
Audiometer: a device that can present
tones of different frequencies, from
low in pitch to high in pitch, at different
volumes from soft to loud
Auditory core region: an area of the
auditory cortex, consisting of the
primary auditory cortex, the rostral core,
and the rostrotemporal core
Auditory cortex: the areas in the
temporal cortex that process auditory
stimuli
Auditory scene analysis: the process
of identifying specific sound-producing
objects from a complex set of sounds
from different objects at varying and
overlapping frequencies
Automaticity: refers to those processes
that do not require attention
Azimuth: the left-right or side-to-side
aspect of sound localization
Bálint’s syndrome: a neurological
condition caused by damage to both left
and right posterior parietal lobes
Basal cells: cells that create olfactory
receptor neurons
Basilar membrane: the membrane that
separates the tympanic canal from the
middle canal; the organ of Corti lies on
the basilar membrane
Beat: spaced pulses that indicate if a
musical piece is fast or slow
Belt: a region of the auditory cortex that
wraps around the auditory core regions
Binocular cells: cells with two receptive
fields, one for each eye; their main
function is to match the images coming
to each eye
Binocular disparity: a binocular depth
cue because our two eyes are in
different locations in our head and
therefore have slightly different views of
the world
Binocular rivalry: a phenomenon that
occurs when a separate image is
presented to each eye
Biosonar: a process whereby animals
emit sounds and then use comparisons
of the emitted sounds and their returning
echoes to sense the world around them
Bistratified retinal ganglion cells (K
cells): retinal ganglion cells that project
to the koniocellular layer of the lateral
geniculate nucleus; they represent 10%
of ganglion cells, possess low sensitivity
to light, and are sensitive to wavelength
Blindsight: the presence of visual
abilities even though a person
experiences blindness because of
damage to V1
Blobs: groups of neurons within V1 that
are sensitive to color
Bottom-up processing: a process
whereby physical stimuli influence how
we perceive them
Brightness: the perceived intensity of
the light present
Broca’s aphasia: a form of aphasia
resulting from damage to Broca’s area,
causing a deficit in language production
Broca’s area: an important area in the
production of speech, located in the left
frontal lobe
Capsaicin: the active ingredient in chili
peppers that provides the experience of
hotness, piquancy, or spiciness
Cataracts: a condition that results from a
darkening of the lens
Catch trial: a trial in which the stimulus
is not presented
Categorical perception: the perception
of different acoustic stimuli as being
identical phonemes up to a point at
which perception flips to perceive
another phoneme
Center-surround receptive field: a
receptive field in which the center of
the receptive field responds opposite to
how the surround of the receptive field
responds; if the center responds with an
increase of activity to light in its area,
the surround responds with a decrease
in activity to light in its area
C-fibers: nonmyelinated nociceptors that
are slower and respond to pressure,
extreme degrees of either heat or cold,
and toxic chemicals
Change blindness: the difficulty we
experience in detecting differences
between two visual stimuli that are
identical except for one or more
changes to the image
Characteristic frequency: the frequency
to which any particular location along
the basilar membrane responds best
Chroma: the subjective quality of a pitch;
we judge sounds an octave apart to be
of the same chroma
Ciliary muscles: the small muscles
that change the curvature of the lens,
allowing accommodation
Circumvallate papillae: found along the
very back of the tongue in a virtual row;
they respond to all five basic tastes
Coarticulation: the phenomenon in
which one phoneme affects the acoustic
properties of subsequent phonemes
Cochlea: the snail-shaped structure of
the inner ear that houses the hair cells
that transduce sound into a neural signal
Cochlear implants: devices that are
designed to restore some hearing,
typically of spoken voices, to deaf
individuals; they stimulate the auditory
nerve artificially with an electronic system,
replacing the hair cells of the cochlea
Cochlear nucleus: a structure in the
brain stem that receives input from inner
hair cells
Cognitive impenetrability: perception is
not affected by cognitive factors, only
our reporting of perception is
Cognitive penetration: the view that
cognitive and emotional factors
influence the phenomenology of
perception
Cold fibers: thermoreceptors that fire in
response to colder (30 °C and below)
temperatures as measured on the skin
Color constancy: the ability to perceive
the color of an object despite changes in
the amount and nature of illumination
Color deficiency: the condition of
individuals who are missing one or more
of their cone systems
Color–music synesthesia: a form
of synesthesia that occurs when
particular pitches, notes, or chords elicit
experiences of particular visual colors
Glossary 463
Color-opponent cells: neurons that
are excited by one color in the center
and inhibited by another color in the
surround, or neurons that are inhibited
by one color in the center and excited
by another color in the surround
Complementary colors: colors on the
opposite side of the color wheel that
when added together in equal intensity
give a white or gray or black
Complex cells: neurons in V1 that
respond optimally to stimuli with
particular orientations; unlike simple
cells, they respond to a variety of stimuli
across different locations, particularly to
moving stimuli
Complex sound: a sound consisting of a
mix of frequencies
Compound eye: an eye that does not
have a single entrance but is made up
of many separate components called
ommatidia
Computational approach: an approach
to the study of perception in which the
necessary computations the brain would
need to carry out to perceive the world
are specified
Conductive hearing loss: the inability of
sound to be transmitted to the cochlea
Cone of confusion: a region of positions
in space in which sounds create the
same interaural time and interaural
level differences
Cone-opponent cells: neurons that are
excited by the input from one cone type
in the center but inhibited by the input
from another cone type in the surround
Cones: photoreceptors in the fovea of
the retina; they are responsible for color
vision and our high visual acuity
Congenital amusia: a condition in which
people are inherently poor at music
perception
Conjugate gaze palsies: neurological
disorders that affect the ability of the eyes to
coordinate their movements; this inability to
move together may affect eye movements in
both vertical and horizontal directions
Conjunction search: the search for a
target in which the target is specified by
a combination of features
Consonance: the perception of
pleasantness or harmony when two or
more musical notes are played; that is,
the notes fit with each other
Consonants: speech sounds made with
restricted airflow
Constancy: the ability to perceive an
object as the same under different
conditions
Constructivist approach: the idea that
perceptions are constructed using
information from our senses and
cognitive processes
Contralateral: literally, opposite
(contra) side (lateral), meaning, in
this context, that sensory information
is on the side of the nervous system
opposite the one from which it entered
Contralateral organization: opposite-side
organization; in the visual system, the
nasal retina projects to the opposite side
of the brain
Contralateral representation of visual
space: the arrangement whereby the left
visual world goes to the right side of the
brain, and the right visual world goes to
the left side of the brain
Convergence: the number of
photoreceptors that connect to each
ganglion cell; more convergence occurs
for rods than for cones
Cornea: the clear front surface of the
eye that allows light in; also a major
focusing element of the eye
Corollary discharge theory: the theory
that the feedback we get from our eye
muscles as our eyes track an object is
important to the perception of motion
Correct rejection: in signal detection
analysis, a correct rejection occurs
when a nonsignal is dismissed as not
present
Correspondence problem (depth
perception): the problem of determining
which image in one eye matches the
correct image in the other eye
Correspondence problem (motion
perception): how the visual system
knows if an object seen at Time 1 is the
same object at Time 2
Corresponding points: refers to a
situation in which a point on the left
retina and a point on the right retina
would coincide if the two retinae were
superimposed
Cortical achromatopsia: loss of color
vision due to damage to the occipital
lobe
Cortical magnification: the allocation
of more space in the cortex to some
sensory receptors than to others; the
fovea has a larger cortical area than the
periphery
Covert attention: when your visual
direction does not line up with your
direction of gaze
Cribriform plate: a perforated section of
skull bone that separates the nose from
the brain; axons from olfactory receptor
neurons pass through to allow olfactory
information to enter regions in the brain
Crista: the structure in the ampulla of
each semicircular canal that contains
the receptors
Criterion: a bias that can affect the rate
of hits and false alarms
Crossed disparity: the direction of
disparity for objects closer to the viewer
than the horopter (the image in the left
eye is to the right of the image of the
object in the right eye)
Crossover point: the point at which a
person changes from detecting to not
detecting a stimulus or vice versa
Cue approach to depth perception: the
system whereby depth perception
results from three sources of
information, monocular cues to depth
present in the image, binocular cues
from the comparison of images in each
eye, and cues from focusing the eyes,
such as vergence and accommodation
Cycle: in a sound wave, the amount of
time between one peak of high pressure
and the next
d′ (d-prime): a mathematical measure of
sensitivity
Dark adaptation: the process in the
visual system whereby its sensitivity to
low light levels is increased
Sensation and Perception464
Decay: how long the fundamental
frequency and harmonics remain at
their peak loudness until they start to
disappear
Decibel (dB): a physical unit that
measures sound amplitude
Deletion: the gradual occlusion of a
moving object as it passes behind
another object
Dermis: the inner layer of the skin, which
also houses touch receptors
Descending series: a series in which a
stimulus gets increasingly smaller along
a physical dimension
Deuteranopia: a lack of M-cones,
leading to red–green deficiency;
this trait is sex-linked and thus more
common in men
Difference threshold (JND): the smallest
difference between two stimuli that can
be reliably detected
Diplopia: double images, or seeing
two copies of the same image; usually
results from the images of an object
having too much disparity to lead to
fusion
Direct perception (Gibsonian approach):
the approach to perception that claims
that information in the sensory world is
complex and abundant, and therefore
the perceptual systems need only
directly perceive such complexity
Dishabituation: the process in which,
after habituation has occurred,
changing the stimulus causes the
organism to respond again
Dissonance: the perception of
unpleasantness or disharmony when
two or more musical notes do not fit
together
Distance: how far a sound is from the
listener and whether it is in front of or
behind the listener
Divided attention: the process of
attending to multiple sources of
information
Doctrine of specific nerve energies: the
argument that it is the specific neurons
activated that determine the particular
type of experience
Dorsal: in or toward the back of the
body; in the head, it means at the top or
toward the top
Dorsal column–medial lemniscal
pathway: a pathway for the
mechanoreceptors (tactile perception)
and proprioceptors (muscle position)
that travels up the spinal column on
the ipsilateral side and crosses to the
contralateral side in the medulla
Dorsal horn: an area of the spinal cord
that receives input from nociceptors and
feedback from the brain
Dorsal pathway: starts with parasol
retinal ganglion cells and continues
through the visual cortex into the
parietal lobe; often called the “where”
pathway, as it codes for the locations of
objects and their movement
Dorsal root: the end of the spinal nerve
where sensory information enters the
spinal cord
Dorsal root ganglion: a node on the spine
where one finds nerve cells carrying
signals from sensory organs toward the
somatosensory areas of the brain
Double-opponent cells: cells that have
a center, which is excited by one
color and inhibited by the other; in the
surround, the pattern is reversed
Dual target-cost: as the number of
objects searched for increases, the
likelihood of detecting one of those
objects decreases
Duplex theory of vision: the doctrine that
there are functionally two distinct ways
in which our eyes work, the photopic,
associated with the cones, and the
scotopic, associated with the rods
Dynamics: relative loudness and how
loudness changes across a composition
Ecological approach to perception: another
name for the direct perception view
Edge completion: the perception of a
physically absent but inferred edge,
allowing us to complete the perception
of a partially hidden object
Edge detection: the process of
distinguishing where one object ends
and the next begins, making edges as
clear as possible
Electroencephalography (EEG): using
electrodes to measure the electrical
output of the brain by recording electric
current at the scalp
Electromagnetic energy: a form of energy
that includes light that is simultaneously
both a wave and a particle
Electromagnetic spectrum: the complete
range of wavelengths of light and other
electromagnetic energy
Electroreception: the ability to detect
electric fields, seen in many species of fish
Elevation: the up-down dimension of
sound localization
Endogenous opioids: chemicals
produced by the body that reduce pain
throughout the body
Endolymph: fluid that fills the
semicircular canals
End-stopped neurons: neurons that
respond to stimuli that end within the
cell’s receptive field
Entorhinal cortex: an area in the
medial temporal lobe, associated
with a number of memory
functions
Epidermis: the outer layer of the skin
Equal-temperament scale: a tuning
system in which the difference between
each successive semitone is constant
both in pitch and in frequency
Eustachian tube: a thin tube that
connects the middle ear with the
pharynx and serves to equalize air
pressure on either side of the eardrum
Executive attention network: a system
that focuses on attention by the
inhibition of habitual responses and acts
as the top-down control of attention;
found in the frontal lobe
Exploratory procedures: hand
movements made in order to identify an
object
External auditory canal (external
auditory meatus): the channel that
conducts sound from the pinna to the
tympanic membrane
Extrastriate body area: an area within
the inferotemporal cortex that is
Glossary 465
activated when its cells view bodies or
body parts but not faces
Extrastriate cortex (secondary visual
cortex): the collective term for
visual areas in the occipital lobe
other than V1
FAI mechanoreceptors: fast-adapting
receptors, with Meissner corpuscle
endings and small receptive fields,
densely packed near the surface of the
skin
FAII mechanoreceptors: fast-adapting
receptors with Pacinian corpuscle
endings and large receptive fields,
more widely distributed, deeper in
the skin
False alarm: in signal detection analysis,
a false alarm is an error that occurs
when a nonsignal is mistaken for a
target signal
Familiar size: the cue whereby knowing
the retinal size of a familiar object at a
familiar distance allows us to use that
retinal size to infer distance
Feature integration theory: a theory
stipulating that some features can be
processed in parallel and quickly prior
to using attentional resources, whereas
other visual characteristics require us to
use attention and are done serially and
therefore less quickly
Feature search: the search for a target in
which the target is specified by a single
feature
Field of view: the part of the world you
can see without eye movements
Figure–ground organization: the
experience viewers have as to which
part of an image is in front and which
part of an image is in the background of
a particular scene
Filiform papillae: found all over the
tongue; they contain somatosensory
receptors rather than taste buds, so
that they feel food rather than taste it
Flavor: the combined sensory
experience of a food, which combines
its taste, its odor, its effect on the
trigeminal nerve, and even visual
experience
Focus of expansion: the destination point
in an optic flow display, from which point
perceived motion derives
Foliate papillae: found along the side of
the tongue; they respond to all five basic
tastes
Forced-choice method: a psychophysical
method in which a participant is
required to report when or where a
stimulus occurs instead of whether it
was perceived
Formants: frequency bands with higher
amplitudes among the harmonics of
a vowel sound; each individual vowel
sound has a specific pattern of formants
Fourier analysis: a mathematical
procedure for taking any complex
waveform and determining the simpler
waveforms that make up that complex
pattern; the simpler waves used are sine
waves
Fovea: an area on the retina that is
dense in cones but lacks rods; when we
look directly at an object, its image falls
on the fovea
Frequency: the number of waves per
unit of time; frequency is the inverse of
wavelength
Frequency (sound stimulus): the number
of cycles that occur in a second
Functional magnetic resonance imaging
(fMRI): a neuroimaging technique that
generates an image of the brain on the
basis of the blood levels in different
areas of the brain, which correlate with
activity levels in those regions
Fundamental frequency: the lowest
frequency in a complex sound, which
determines the perceived pitch of that
sound
Fungiform papillae: located mostly along
the edges and top of the tongue; they
respond to all five basic tastes
Fusiform face area: an area in the
inferotemporal area of the temporal lobe
that specializes in recognizing familiar
faces
Gate control theory: a model that allows
for top-down control of the pain signal
coming up the spinal cord
Gelb effect: a phenomenon whereby an
intensely lit black object appears to be
gray or white in a homogeneously dark
space
General-mechanism theories: theories
of speech perception that claim that
the mechanisms for speech perception
are the same as the mechanisms for
auditory perception in general
Geons: the basic units of objects,
consisting of simple shapes such as
cylinders and pyramids
Gestalt psychology: a school of thought
claiming that we view the world in terms
of general patterns and well-organized
structures rather than separable
individual elements
Glomeruli: spherical structures within
the olfactory bulb where the olfactory
tract forms synapses with mitral cells
and tufted cells
Golgi tendon organs: receptors in the
tendons that measure the force of a
muscle’s contraction
Gradient of flow: the difference in the
perception of the speeds of objects
moving past us in an optic flow display
Grouping: the process by which
elements in a figure are brought
together into a common unit or object
Gustation: the sense of taste
Habituation: the learning process in
which animals stop responding to a
repeated stimulus
Hair cells: cells that have stereocilia for
transducing the movement of the basilar
membrane into a neural signal
Haptic perception: the active use of
touch to identify objects
Harmonic coherence: when frequencies
present in the environment resemble
the possible pattern of a fundamental
frequency and higher harmonics
Harmonics: higher frequencies present
in a complex sound that are integer
multiples of the fundamental frequency
(main frequency)
Harmony: the pleasant sound that results
when two or more musical notes are
played together
Sensation and Perception466
Hearing aids: electronic devices that
amplify sound so that people with
hearing deficits can hear sounds
that otherwise would be below their
thresholds
Hemifield neglect (unilateral visual
neglect): a condition in which a person
fails to attend to stimuli on one side of
the visual world (usually the left) as a
consequence of neurological damage to
the posterior parietal lobe
Hertz (Hz): a unit of measure indicating
the number of cycles per second
Heterochromatic light: white light,
consisting of many wavelengths
Heterochromia: a condition in which a
person has irises of two different colors
Hit: in signal detection analysis, a hit
occurs when a signal is detected when
the signal is present
Homunculus: a drawing of a human in
which the proportions of the body parts
match the relative sizes each body part
has on the somatotopic map
Horopter: the region in space where
the two images from an object fall on
corresponding locations on the two
retinae
Hue: the color quality of light,
corresponding to the color names
we use, such as orange, green,
indigo, and cyan; hue is the quality of
color
Hue cancellation: an experiment
in which observers cancel out the
perception of a particular color by
adding light of the opponent color
Hypercolumn: a 1-mm block of V1
containing both the ocular dominance
and orientation columns for a particular
region in visual space
Hyperopia: a condition causing an
inability to focus on near objects, also
called farsightedness; occurs because
accommodation cannot make the lens
thick enough
Hyperpolarization: a change in the
voltage of a neuron whereby the inside
of the cell becomes more negative than
it is in its resting state
Illusory contours: perceptual edges that
exist because of edge completion but
are not actually physically present
Inattentional blindness: a phenomenon
in which people fail to perceive an
object or event that is visible but not
attended to
Incus: an ossicle in the middle ear;
receives vibrations from the malleus and
transmits them to the stapes
Induced motion: an illusion whereby one
moving object may cause another object
to look like it is moving
Inferior colliculus: a structure in the
midbrain that receives input from the
superior olive
Inferotemporal area: the area of the
temporal lobe involved in object
perception; it receives input from V4 and
other areas in the occipital lobe
Inferotemporal cortex: the region in the
temporal lobe that receives input from
the ventral visual pathway; one of its
functions is object identification
Information-processing approach: the
view that perceptual and cognitive
systems can be viewed as the flow of
information from one process to another
Inner hair cells: cells that are
responsible for transducing the neural
signal
Intensity: when referring to waves, the
height of a wave
Interaural level difference: the
difference in loudness and frequency
distribution between the two ears
Interaural time difference: the time
interval between when a sound enters
one ear and when it enters the other ear
Interblobs: groups of neurons that are
sensitive to orientation in vision
International Phonetic Alphabet: an
alphabetic convention that provides
a unique symbol for each and every
phoneme in use in human languages
Internuclear ophthalmoplegia: a
conjugate palsy resulting from damage
to the brain stem region known as the
medial longitudinal fasciculus
Ipsilateral: literally, same (ipsi) side
(lateral), meaning, in this context, that
sensory information is on the same side
of the nervous system as it entered
Ipsilateral organization: same-side
organization; in the visual system, the
temporal retina projects to the same
side of the brain
Iris: the colored part of the eye; a
muscle that controls the amount of light
entering through the pupil
Joint receptors: receptors found in each
joint that sense information about the
angle of the joint
Key: the tonic note (e.g., C in a C major
or minor scale) that gives a subjective
sense of arrival and rest in a musical
piece
Koniocellular layers: layers of the lateral
geniculate nucleus with very small cells
that receive input from K ganglion cells
(bistratified retinal ganglion cells)
Koniocellular pathway (K pathway): a
pathway that starts with bistratified
retinal ganglion cells and projects to
the koniocellular layers of the lateral
geniculate nucleus
Larynx (voice box): a structure that
affects the pitches of sounds being
made by the human vocal tract
Lateral geniculate nucleus: a bilateral
structure (one is present in each
hemisphere) in the thalamus that relays
information from the optic nerve to the
visual cortex
Lateral inhibition: the reduction of a
response of the eye to light stimulating
one receptor by stimulation of nearby
receptors, caused by inhibitory signals
in horizontal cells
Lateral intraparietal (LIP) area: an area
of the primate parietal cortex involved in
the control of eye movements
Law of common fate: the gestalt
grouping law that states that elements
that are moving together tend to be
perceived as a unified group
Law of good continuation: the gestalt
grouping law stating that edges that are
smooth are more likely to be seen as
Glossary 467
continuous than edges that have abrupt
or sharp angles
Law of proximity: the gestalt grouping
law stating that elements that are close
together tend to be perceived as a
unified group
Law of similarity: the gestalt grouping
law stating that elements that are similar
to one another tend to be perceived as a
unified group
Law of symmetry: the gestalt grouping
law that states that elements that are
symmetrical to each other tend to be
perceived as a unified group
L-cone: the cone with its peak sensitivity
to long-wavelength light, around 565 nm
(yellow)
Lens: the adjustable focusing element
of the eye, located right behind the iris;
also called the crystalline lens
Light adaptation: the process whereby
the visual system’s sensitivity is reduced
so that it can operate in higher light
levels
Lightness: the psychological experience
of the amount of light that gets reflected
by a surface
Lightness constancy: the ability to
perceive the relative reflectance of
objects despite changes in illumination
Linear perspective: the pictorial depth
cue that arises from the fact that parallel
lines appear to converge as they recede
into the distance
Loudness: the perceptual experience
of the amplitude or intensity of a sound
stimulus
Macrosmatic: species that are heavily
dependent on their olfactory system
Macula (Chapter 3): the center of the
retina; the macula includes the fovea but
is larger than it
Macula (Chapter 14): the structure in the
otolith organs that contain the receptors
Macular degeneration: a disease
that destroys the fovea and the area
around it
Magnetoencephalography (MEG): using
a magnetic sensor to detect the small
magnetic fields produced by electrical
activity in the brain
Magnitude estimation: a psychophysical
method in which participants judge
and assign numerical estimates to the
perceived strength of a stimulus
Magnocellular layers: layers of the
lateral geniculate nucleus with large
cells that receive input from M ganglion
cells (parasol retinal ganglion cells)
Magnocellular pathway (M pathway):
a pathway that starts with the parasol
retinal ganglion cells and projects to
the magnocellular layers of the lateral
geniculate nucleus
Malleus: the first ossicle in the middle
ear; it receives vibrations from the
tympanic membrane and transmits them
to the incus
Manner of articulation: how airflow
restriction in the vocal tract occurs
Masking: refers to the difficulty in seeing
one stimulus when it is quickly replaced
by a second stimulus that occupies the
same or adjacent spatial locations
McGurk effect: a phenomenon in which
vision influences the sounds people
report hearing
M-cone: the cone with its peak
sensitivity to medium-wavelength light,
around 535 nm (green)
Mechanoreceptors: the sensory
receptors in the skin that transduce
physical movement on the skin into
neural signals, which are sent to the
brain
Medial geniculate nucleus: a structure
in the thalamus that receives auditory
input from the inferior colliculus and
sends output to the auditory cortex
Medial intraparietal (MIP) area: an area
of the posterior parietal lobe involved
in the planning and control of reaching
movements of the arms
Meissner corpuscles: specialized
transduction cells in FAI
mechanoreceptors
Melody: a rhythmically organized
sequence of notes, which we perceive
as a single musical unit or idea
Merkel cells: specialized transduction
cells in SAI mechanoreceptors
Metamer: a psychophysical color match
between two patches of light that have
different sets of wavelengths
Meter: the temporal pattern of sound
across time
Method of adjustment: a method
whereby the observer controls the level
of the stimulus and “adjusts” it to be at
the perceptual threshold
Method of constant stimuli: a method
whereby the threshold is determined
by presenting the observer with a set of
stimuli, some above the threshold and
some below it, in a random order
Method of limits: stimuli are presented
in a graduated scale, and participants
must judge the stimuli along a certain
property that goes up or down
Microelectrode: a device so small that
it can penetrate a single neuron in the
mammalian central nervous system
without destroying the cell
Microsmatic: species that are less
dependent on their olfactory system
Middle canal (cochlear duct): one of
the three chambers in the cochlea;
separated from the tympanic canal by
the basilar membrane; contains the
organ of Corti
Midget retinal ganglion cells (P cells):
retinal ganglion cells that project to
the parvocellular layer of the lateral
geniculate nucleus; they represent 80%
of ganglion cells, possess low sensitivity
to light, and are sensitive to wavelength
Miss: in signal detection analysis, a
miss is an error that occurs when an
incoming signal is not detected
Mitral cells: neurons that start in the
glomeruli of the olfactory bulb and
project to other areas of the brain;
respond to different odorants than do
tufted cells
Monochromatic light: light consisting of
one wavelength
Monocular depth cues: depth cues that
require only one eye
Sensation and Perception468
Moon illusion: the illusion where the
moon looks larger when it is near the
horizon than it does when overhead
Motion: a change in position over time
Motion aftereffect: a motion-based visual
illusion in which a stationary object is
seen as moving in the opposite direction
of real or apparent motion just observed
Motion parallax: a monocular depth cue
arising from the relative velocities of
objects moving across the retinae of a
moving person
Motor theory of speech perception: the
theory that the core of speech perception
is that the system infers the sound from
the movements of the vocal tract
Movement-based cues: cues about
depth that can be seen with a single
eye in which the inference of distance
comes from motion
MT (V5): an area of the occipital lobe in
the dorsal pathway, specific to motion
detection and perception
Müller–Lyer illusion: the illusion where
a line that has two lines going away at
an angle looks longer than a line of the
same length but the end lines angle
back across the main line
Muscle spindles: receptors embedded
in the muscles that sense information
about muscle length and therefore
muscle action
Music: ordered sound made and
perceived by human beings, created in
meaningful patterns
Myopia: a condition causing an inability
to focus clearly on far objects, also
called nearsightedness; occurs because
accommodation cannot make the lens
thin enough
Nasal septum: the wall of cartilage that
separates the nostrils
Near point: the closest distance at
which an eye can focus
Neural response: the signal produced by
receptor cells that can then be sent to
the brain
Neuroimaging: technologies that allow
us to map living intact brains as they
engage in ongoing tasks
Neuropsychology: the study of the
relation of brain damage to changes in
behavior
Neuroscience: the study of the
structures and processes in the nervous
system and brain
Neurotransmitter: a chemical substance
neural cells release to communicate
with other neural cells
Nociceptive pain: pain that develops
from tissue damage that causes
nociceptors in the skin to fire
Nociceptors: sensory receptors in the
skin that, when activated, cause us to
feel pain; they are found in both the
epidermis and the dermis
Noncorresponding points: refers to a
situation in which a point on the left
retina and a point on the right retina
would not coincide if the two retinae
were superimposed
Nontasters: people who cannot detect
bitter compounds except at very high
concentrations
Object agnosia: an acquired deficit in
identifying and recognizing objects even
though vision remains intact
Occipital face area: an area of the brain
in the occipital lobe, associated with
recognizing faces as distinct from
other objects
Occlusion: a visual cue that occurs when
one object partially hides or obstructs
the view of a second object; we infer
that the hidden object is farther away
from us than the object that obstructs it
Octave: the interval between one
musical note and a note with either
double the frequency or half the
frequency of that note
Ocular dominance column: a column
within V1 that is made up of neurons that
receive input from only the left eye or
only the right eye
Odorants: molecules our olfactory
system responds to when we detect
them in the air
Odors: the perceptual experience of
odorants, which are airborne chemical
stimuli
Off-center receptive fields: retinal
ganglion cells that decrease their firing
rate (inhibition) when light is presented
in the middle of the receptive field and
increase their firing rate (excitation)
when light is presented in the outside or
surround of the receptive field
Olfaction: the sense of smell
Olfactory bulb: a part of the brain just
behind the nose; it is the first place in
the brain where olfactory information is
processed
Olfactory cleft: the channel at the back
of the nasal cavity that funnels air up
toward the olfactory epithelium
Olfactory epithelium: a mucous
membrane inside each nostril of the
nose that contains the receptor cells for
the olfactory system
Olfactory nerve (first cranial nerve): the
axons of the olfactory receptor neurons
that leave the nose and enter the
olfactory bulb
Olfactory receptor neurons: receptor
cells located in the olfactory epithelium
that detect specific chemicals in the air
and transduce them into a neural signal
Olfactory tract: the pathway leading from
the olfactory bulb to other regions of the
brain
On-center receptive fields: retinal
ganglion cells that increase their firing
rate (excitation) when light is presented
in the middle of the receptive field and
decrease their firing rate (inhibition)
when light is presented in the outside or
surround of the receptive field
Opponent-process theory of color
perception: the theory that color
perception arises from three opponent
mechanisms, for red–green, blue–
yellow, and black–white
Opsin: the protein portion of a
photopigment that captures the photon
of light and begins the process of
transduction; the variation in opsin
determines the type of visual receptor
Optic chiasm: the location in the optic
tract where the optic nerve from each
eye splits in half, with nasal retinae
crossing over and temporal retinae
Glossary 469
staying on the same side of the
optic tract
Optic disc: the part of the retina where
the optic nerve leaves the eye and
heads to the brain; along the optic disc,
there are no receptor cells
Optic flow: a motion depth cue that
involves the relative motion of objects as
an observer moves forward or backward
in a scene
Optic tract: the optic nerve starting at
the optic chiasm and continuing into the
brain
Optometrist: a trained professional
who specializes in diagnosing visual
impairments and diseases
Orbitofrontal cortex: a part of the
prefrontal cortex that appears to be
critical in the emotional experience of
odors and integrating olfaction and taste
perception, among other functions
Organ of Corti: a structure on the
basilar membrane that houses the hair
cells that transduce sound into a
neural signal
Orientation column: a column within V1
that is made up of neurons with similar
responses to the orientation of a shape
presented to those neurons
Orienting attention network (dorsal
attention network): a neural
system, located primarily in the
parietal lobe, that allows us to engage
in visual search and direct our visual
attention to different locations in
visual space
Orienting tuning curve: a graph that
demonstrates the typical response
of a simple cell to stimuli or different
orientations
Ossicles: three small bones in the
middle ear
Otolith organs: organs responsible for
detecting acceleration of the head and
identifying when the head is being held
at a tilted angle
Otosclerosis: an inherited bone disease
in which the ossicles, particularly the
stapes, may calcify and therefore be
less conductive of sound
Outer hair cells: cells that sharpen
and amplify the responses of the inner
hair cells
Overt attention: when your visual
attention lines up with your direction of
gaze, that is, your fovea
Pacinian corpuscles: specialized
transduction cells in FAII
mechanoreceptors
Pain: the perception and unpleasant
experience of actual or threatened
tissue damage
Panum’s area of fusion: the region of
small disparity around the horopter
where the two images can be fused into
a single perception
Papillae: small structures that contain
the taste buds
Parabelt: a region of the auditory cortex,
in addition to the belt area, that wraps
around the auditory core regions
Parahippocampal place area (PPA): an
area within the inferotemporal cortex
that appears to have the specific
function of scene recognition
Parasol retinal ganglion cells (M cells):
retinal ganglion cells that project to
the magnocellular layer of the lateral
geniculate nucleus; they represent
10% of ganglion cells and possess high
sensitivity to light
Parietal insular vestibular cortex: an
area in the parietal lobe that receives
input from the vestibular nerve and
is responsible for the perception of
balance and orientation
Parvocellular layers: layers of the
lateral geniculate nucleus with small
cells that receive input from P ganglion
cells (midget retinal ganglion cells)
Parvocellular pathway (P pathway): a
pathway characterized by the retinal
ganglion cells known as midget retinal
ganglion cells
Passive electroreception: the ability only
to detect electric fields
Perception: the process of creating
conscious perceptual experience from
sensory input
Perceptual bistability: a phenomenon
in which a static visual image leads to
alternating perceptions
Perceptual narrowing: the
developmental process whereby
regularly experienced phonemes
are homed in on, with simultaneous
diminishing of the ability to discriminate
unfamiliar phonemes
Perceptual organization: the process
by which multiple objects in the
environment are grouped, allowing us
to identify multiple objects in complex
scenes
Perilymph: the fluid that fills the
tympanic canal and the vestibular canal
Phantom limb pain: refers to
experiencing pain in a limb that has
been amputated
Phantom limb syndrome: continued but
illusory sensory reception in a missing
appendage
Phantosmia: hallucinatory perception of
odors
Pharynx: the top portion of the throat
Phase: the position in one cycle of a
wave; there are 360 degrees in a single
cycle of a wave
Phenomenology: our subjective
experience of perception
Phonemes: the basic units of sound in
human language
Phonemic restoration effect: an illusion
in which participants hear sounds that
are masked by white noise, but context
makes the missing sound apparent
Photon: a single particle of light
Photopic vision: the vision associated
with the cones; it is used in the daytime,
has good acuity in the fovea, and has
color vision
Photopigment: a molecule that absorbs
light and by doing so releases an
electric potential by altering the voltage
in the cell
Pictorial cues: information about depth
that can be inferred from a static picture
Pinna: the structure that collects sound
and funnels it into the auditory canal
Sensation and Perception470
Piriform cortex: an area in the anterior
region of the temporal lobe that receives
input from the olfactory bulb and is
involved in olfactory processing; often
considered the primary olfactory cortex
Pitch: the subjective experience of
sound that is most closely associated
with the frequency of a sound stimulus;
related to the experience of whether the
sound is high or low, such as the two
ends of the keyboard of a piano
Place code theory: the view that
different locations along the basilar
membrane respond to different
frequencies
Place of articulation: the point along
the vocal tract at which the airflow is
constricted
Point of subjective equality (PSE): the
settings of two stimuli at which the
observer experiences them as identical
Point-light walker display: an
experiment in which small lights are
attached to the body of a person or an
animal, which is then filmed moving
in an otherwise completely dark
environment
Ponzo illusion: the illusion in which two
horizontal lines are drawn one above
the other; both lines are on top of two
inwardly angled vertical lines; the top
line, where the two vertical lines are
closer together, looks longer
Posterior chamber: the space between
the iris and the lens; it is filled with fluid
known as aqueous humor
Posterior piriform cortex: a structure
located in the back portion of the
piriform cortex that is associated with
an odor’s quality, regardless of its
chemical composition
Presbyopia: a condition in which
incoming light focuses behind the retina,
leading to difficulty focusing on close-up
objects; common in older adults, in
whom the lens becomes less elastic
Presynaptic cells: taste receptor cells
that transduce salty and sour tastes
Primary auditory cortex: the first area
in the auditory cortex, which receives
input from the medial geniculate nucleus
Primary visual cortex (V1): the area of
the cerebral cortex that receives input
from the lateral geniculate nucleus,
located in the occipital lobe and
responsible for early visual processing
Proprioception: the perception of the
movements and position of our limbs
Prosopagnosia: face agnosia, resulting
in a deficit in perceiving faces
Protanopia: a lack of L-cones, leading to
red–green deficiency; this trait is sex-
linked and thus more common in men
Pruriceptors: receptors in our skin that
respond to mild irritants by producing
itch sensations
Psychophysical scale: a scale on
which people rate their psychological
experiences as a function of the level of
a physical stimulus
Psychophysics: the study of the relation
between physical stimuli and perception
events
Pupil: an opening in the middle of the iris
Pupillary reflex: an automatic process
by which the iris contracts or relaxes in
response to the amount of light entering
the eye; the reflex controls the size of
the pupil
Pure tone: a sound wave in which
changes in air pressure follow a sine
wave pattern
Purkinje shift: the observation that
short wavelengths tend to be relatively
brighter than long wavelengths in
scotopic vision versus photopic vision
Quality: a value that changes but does
not make the value larger or smaller
Random-dot stereograms: stereograms in
which the images consist of a randomly
arranged set of black and white dots,
with the left-eye and right-eye images
arranged identically except that some of
the dots are moved to the left or the right
in one of the images, creating either a
crossed or an uncrossed disparity
Rapid serial visual presentation (RSVP)
paradigm: a method of studying attention
in which a series of stimuli appear
rapidly in time at the same point in visual
space
Rate of approach: the measure of
whether a predator is approaching a
target or receding from it
Real motion: motion in the world created
by continual change in the position
of an object relative to some frame of
reference
Receiver-operating characteristic (ROC)
curve: in signal detection theory, a
plot of false alarms versus hits for any
given sensitivity, indicating all possible
outcomes for a given sensitivity
Receptive field: a region of adjacent
receptors that will alter the firing rate
of a cell that is higher up in the sensory
system; the term can also apply to the
region of space in the world to which a
particular neuron responds
Receptor cells: taste receptor cells that
transduce sweet tastes, umami tastes,
and bitter tastes
Receptors: specialized sensory neurons
that convert physical stimuli into neural
responses
Recognition: the ability to match a
presented item with an item in memory
Recognition by components: a theory
stating that object recognition occurs
by representing each object as a
combination of basic units (geons) that
make up that object; we recognize an
object by the relation of its geons
Reichardt detectors: neural circuits that
enable the determination of direction
and speed of motion by delaying input
from one receptive field, to determine
speed, to match the input of another
receptive field, to determine direction
Reissner’s membrane: the membrane
that separates the vestibular and middle
canals
Relative height: a visual cue in which
objects closer to the horizon are seen as
more distant
Relative size: the fact that the more
distant an object is, the smaller the
image will be on the retina
Repetition blindness: the failure to detect
the second target in an RSVP task when
the second target is identical to the first
Glossary 471
one; like attentional blink, it occurs when
the second target is presented 500 ms or
less after the first target
Representation: the storage and/or
reconstruction of information in memory
when that information is not in use
Response compression: as the strength
of a stimulus increases, so does the
perceptual response, but the perceptual
response does not increase by as much
as the stimulus increases
Response expansion: as the strength
of a stimulus increases, the perceptual
response increases even more
Retina: the paper-thin layer of cells at
the back of the eye where transduction
takes place
Retinal: a derivative of vitamin A that is
part of a photopigment
Retinal image: the light projected onto
the retina
Retinitis pigmentosa: an inherited
progressive degenerative disease of the
retina that may lead to blindness
Retinotopic map: a point-by-point
relation between the retina and V1
Reverberation time: the difference
between the onset of direct sound and
the first onset of indirect sound
Rhythm: the temporal patterning of
music, including the tempo, the beat,
and the meter
Rods: photoreceptors at the periphery of
the retina; they are very light sensitive
and specialized for night vision
Rostral core: an area in the auditory
core region of the auditory cortex
Rostrotemporal core: an area, in addition
to the rostral core, in the auditory core
region of the auditory cortex
Round window: a soft tissue substance
at the base of the tympanic canal whose
function is as an “escape” valve for
excess pressure from loud sounds that
arrive in the cochlea
Ruffini endings: specialized transduction
cells in SAII mechanoreceptors
SAI mechanoreceptors: slow-adapting
receptors using Merkel cells, with small
receptive fields, densely packed near
the surface of the skin
SAII mechanoreceptors: slow-adapting
receptors using Ruffini endings, with
large receptive fields, more widely
distributed, deeper in the skin
Saccades: the most common and
rapid of eye movements; sudden eye
movements that are used to look from
one object to another
Saturation: the purity of light
Scale: a set of ordered notes starting at
one note and ending at the same note
one octave higher
Sclera: the outside surface of the eye;
a protective membrane covering the
eye that gives the eye its characteristic
white appearance
S-cone: the cone with its peak sensitivity
to short-wavelength light, around 420
nm (blue)
Scotoma: an area of partially or
completely destroyed cells, resulting in
a blind spot in a particular region of the
visual field
Scotopic vision: the operation of the
visual system associated with the rods;
it has relatively poor acuity and no color
ability but is very sensitive to light
Scoville scale: a measure of our
detection of the amount of an ingredient
called capsaicin in chili peppers
Segregation: the process of
distinguishing two objects as being
distinct or discrete
Selective attention: the processes of
attention that allow us to focus on one
source when many are present
Semicircular canals: three tubes located
in the inner ear responsible for the
signaling of head rotation
Semitones: the 12 equivalent intervals or
notes within each octave
Sensation: the registration of physical
stimuli on sensory receptors
Sensitivity: the ability to perceive a
particular stimulus; it is inversely related
to threshold
Sensitivity (signal detection theory): the
ease or difficulty with which an observer
can distinguish signal from noise
Sensorineural hearing loss: permanent
hearing loss caused by damage to the
cochlea or auditory nerve or the primary
auditory cortex
Shadows: a depth cue arising because
an object is in front of its shadow;
the angle of the shadow can provide
information about how far the object is
in front of the background
Signal detection theory: the theory
that in every sensory detection or
discrimination, there is both sensory
sensitivity to the stimulus and a criterion
used to make a cognitive decision
Simple cells: V1 neurons that respond
to stimuli with particular orientations to
objects within their receptive field; the
preferred orientation of a simple cell is
the stimulus orientation that produces
the strongest response
Simultagnosia: a deficit in perceiving
more than one object at a time
Simultaneous color contrast: a
phenomenon that occurs when our
perception of one color is affected by a
color that surrounds it
Size constancy: the perception of an
object as having a fixed size, despite the
change in the size of the visual angle
that accompanies changes in distance
Size–arrival effect: bigger approaching
objects are seen as being more likely
to collide with the viewer than smaller
approaching objects
Size–distance invariance: the relation
between perceived size and perceived
distance, whereby the perceived size
of an object depends on its perceived
distance, and the perceived distance of an
object may depend on its perceived size
Smooth-pursuit eye movements:
voluntary tracking eye movements
Somatosensory cortex: an area in the
parietal lobe of the cerebral cortex
devoted to processing the information
coming from the skin senses
Somatotopic map: a feature whereby the
skin of the body maps onto the surface
of the primary somatosensory cortex in
a systematic way
Sensation and Perception472
Sound stimulus: the periodic variations
in air pressure traveling out from the
source of the variations
Sound waves: the waves of pressure
changes that occur in the air as a
function of the vibration of a source
Spatial segregation: the process whereby
sounds that are coming from the same
location are grouped together, whereas
sounds that are coming from different
locations are not grouped together
Special-mechanism theories: theories
of speech perception that claim that
the mechanisms for speech perception
are distinct and unique relative to
the mechanisms for auditory perception
in general
Spectral reflectance: the ratio of
light reflected by an object at each
wavelength
Spectral segregation: the process
whereby sounds that overlap in
harmonic structure are grouped
together, whereas sounds that do not
overlap in harmonic structure are not
grouped together
Spectral shape cue: the change in a
sound’s frequency envelope created
by the pinnae; it can be used to provide
information about the elevation of a
sound source
Spinothalamic pathway: a pathway
for the nociceptors (pain) and
thermoreceptors (temperature) that
travels up the contralateral side of the
spinal column; it does not synapse in the
brain until the ventral posterior nucleus
of the thalamus
Stapedius: the muscle that is attached to
the stapes
Stapes: an ossicle in the middle ear; it
receives vibrations from the incus and
transmits them to the oval window of
the inner ear
Stereocilia: the hairlike parts of the hair
cells on the top of the inner and outer
hair cells
Stereopsis: the sense of depth we
perceive from the visual system’s
processing of the comparison of the two
different images from each retina
Stevens’s power law: a mathematical
formula that describes the relationship
between stimulus intensity and our
perception; it allows for both response
compression and response expansion
Stimulus: an element of the world
around us that impinges on our sensory
systems
Stimulus onset asynchrony: the
difference in time between the
occurrence of one stimulus and the
occurrence of another, in this case, the
cue and the target
Stimulus salience: refers to the features
of objects in the environment that attract
our attention
Substantia gelatinosa: the region in the
dorsal horn where neurons meet
Subtractive color mixing: color mixing
in which a new color is made by the
removal of wavelengths from a light with
a broad spectrum of wavelengths
Superior colliculus: a structure located
at the top of the brain stem, just beneath
the thalamus, whose main function in
mammals (including humans) is the
control of eye movements
Superior olive: a structure in the brain
stem that receives input from the
inner hair cells and from the cochlear
nucleus
Supertasters: people who are extremely
sensitive to bitter tastes; they usually
do not like foods with many bitter
compounds
Supporting cells: cells that provide
metabolic supplies to the olfactory
receptor neurons
Synesthesia: a condition in which a
stimulus in one modality consistently
triggers a response in another modality
Tactile agnosia: an inability to identify
objects by touch
Tapetum: a reflective layer behind the
receptors of nocturnal animals that
bounces light not caught by receptors
back into the retina
Target range: the distance of a predator
from its potential target, determined by
timing an echo’s return
Tastants: molecules recognized by taste
receptors that induce responses in taste
receptors on the tongue
Taste: the perception of the transduction of
tastants along the surface of the tongue
Taste buds: small structures located
along the surface of the tongue or mouth
that contain the receptor cells
Taste receptor cells: cells within the
taste buds that transduce tastants into a
neural signal
Tasters: people who can detect bitter
compounds
Tectorial membrane: a membrane that
rests above the hair cells within the
organ of Corti
Tempo: the pace at which a piece of
music is played
Temporal code theory: the view that
frequency representation occurs
because of a match between sound
frequency and the firing rates of the
auditory nerve
Temporal segregation: the process
whereby sounds that are linked in time
are grouped together, whereas sounds
that are not correlated with one another
are not grouped together
Tensor tympani: the muscle that is
attached to the malleus
Texture gradient: a monocular depth cue
that occurs because textures become
finer as they recede in the distance
Thermoreception: the ability to sense
changes in temperature on the skin
Thermoreceptors: the sensory receptors
in the skin that signal information about
the temperature as measured on the skin
Timbre: the perceived sound differences
between sounds with the same pitch but
possessing different higher harmonics
Time to collision: the estimate of the
time it will take for an approaching
object to contact another
Tinnitus: a condition in which people
perceive sounds even when none are
present
Tip-of-the-nose phenomenon: a
phenomenon that occurs when a
Glossary 473
person is familiar with an odor but
cannot recall its name, despite feeling
as if he or she can
Tonotopic organization: the organization
of neurons within a region in the brain
according to the different frequencies to
which they respond
Top-down processing: a process whereby
our existing knowledge of objects
influences how we perceive them
Topographic agnosia: a deficit in
recognizing spatial landscapes, related
to damage to the parahippocampal
place area
Trachea (windpipe): the tube bringing air
to and from the mouth
Transduction: the process of
converting a physical stimulus into an
electrochemical signal
Transmagnetic stimulation (TMS):
a procedure in which a magnetic coil is
used to stimulate electrically a specific
region of the brain
Transposition: the process through
which one can create multiple versions
of a melody that start on different
notes but contain the same intervals or
sequence of changes in notes
Trapezoid body: a structure in the brain
stem that plays a role in determining the
direction of sounds
Trichromatic theory of color vision:
the theory that the color of any light is
determined by the output of the three
cone systems in our retinae
Trigeminal nerve: a nerve that is
associated with the feel of odorants;
also known as the fifth cranial nerve
Tritanopia: a lack of S-cones, leading to
blue–yellow color deficiency; this trait is
rare and is not sex-linked
Tuberous receptor: the organ that
contains the hair cells that detect
electric fields, used in active
electroreception
Tufted cells: neurons that start in the
glomeruli of the olfactory bulb and
project to other areas of the brain; they
respond to different odorants than do
mitral cells
Turbinates: bony knots of tissue that
serve to disperse air within the nasal
cavity
Two-point touch threshold: the minimum
distance at which two touches are
perceived as two touches and not one
Tympanic canal: one of the three
chambers in the cochlea; separated
from the middle canal by the basilar
membrane
Tympanic membrane: a thin elastic sheet
that vibrates in response to sounds
coming through the external auditory
canal; commonly known as the eardrum
Unconscious inference: perception
is not adequately determined by
sensory information, so an inference
or educated guess is part of the
process; this inference is not the result
of active problem solving but rather a
nonconscious cognitive process
Uncrossed disparity: the direction of
disparity for objects that are farther from
the viewer than the horopter (the image
of the object in the left eye is to the left
of the position of the image of the object
in the right eye)
Unilateral dichromacy: the presence
of dichromacy in one eye but normal
trichromatic vision in the other
Unique colors: colors that can be
described only with a single color
term—red, green, blue, and yellow
Univariance: the principle whereby any
single cone system is colorblind, in the
sense that different combinations of
wavelength and intensity can result in the
same response from the cone system
Unvoiced consonant: a consonant that
is produced without using the vocal
chords
Uvula: a flap of tissue at the top of the
throat that can close off the nasal cavity
V2: the second area in the visual cortex
that receives input; often considered the
area that starts with visual associations
rather than processing the input
(sometimes called the prestriate cortex)
V4: an area of the occipital lobe
involved in both color vision and shape
perception
Ventral: in or toward the front of the
body; in the head, it means at the bottom
or toward the bottom
Ventral pathway: starts with midget
and bistratified retinal ganglion cells
and continues through the visual
cortex into the inferotemporal cortex
in the temporal lobe; often called
the “what” pathway, as it codes for
object identification as well as
color vision
Ventral posterior nucleus of the
thalamus: an area in the thalamus that
receives input from both the dorsal
column–medial lemniscal pathway and
the spinothalamic pathway
Ventral root: the end of the spinal cord
where motor information leaves the
spinal cord
Vergence: the inward bending of the
eyes when looking at closer objects
Vestibular canal: one of the three
chambers in the cochlea; separated
from the middle canal by Reissner’s
membrane
Vestibular complex: a brain stem area
that receives input from the vestibular
nerve and sends the information to the
forebrain
Vestibular system: the sensory system
responsible for the perception of
balance and acceleration, housed in the
semicircular canals and otolith organs,
both located adjacent to the inner ear
Viewpoint invariance: the perception
that an object does not change when
an observer sees the object from a new
vantage point
Virtual reality: a computer-generated
photograph, image, or environment that
can be interacted with in an apparently
real way
Visual angle: the angle of an object
relative to the observer’s eye
Visual capture: circumstances where
visual input can dominate the input from
other senses when they conflict
Visual search: looking for a specific
target among distracting objects
Visual spectrum (visible spectrum):
the band of wavelengths from 400
Sensation and Perception474
to 700 nm that people with the most
common classes of cones vision can
detect
Voice area: an area located in the
superior temporal sulcus that responds
to the sound of the human voice, but
less so to other stimuli
Voiced consonant: a consonant
that is produced using the vocal chords
Voicing: whether the vocal cords are
vibrating or not
Voicing-onset time: the production
of certain consonants (called stop
consonants) in which there is a
difference between the first sound
of the phoneme and the movement of
the vocal cords (called voicing)
Vowels: speech sounds made with
unrestricted airflow
Warm fibers: thermoreceptors that fire
in response to warmer temperatures
(above 36 °C) as measured on the skin
Wavelength: the distance between two
adjacent peaks in a repeating wave;
different forms of electromagnetic energy
are classified by their wavelengths
Weber’s law: a just-noticeable
difference between two stimuli is
related to the magnitude or strength of
the stimuli
Wernicke’s aphasia: a form of aphasia
resulting from damage to Wernicke’s
area, causing a deficit in language
comprehension
Wernicke’s area: an important area in
speech comprehension, located in the
left temporal lobe
Word segmentation: the ability of
speakers of a language to correctly
perceive boundaries between words
Zero disparity: the situation in which
retinal images fall along corresponding
points, which means that the object is
along the horopter
Zonule fibers: fibers that connect the
lens to the choroid membrane
References 475
REFERENCES
Abdelaziz, A. H., & Kolossa, D. (2016). General hybrid
framework for uncertainty-decoding-based automatic
speech recognition systems. Speech Communication,
79, 1–13.
Adelson, E. H. (1993). Perceptual organization and the
judgment of brightness. Science, 262, 2042–2044.
Aladdin, Y., Scozzafava, J., Muayqil, T., & Saqqur, M. (2008).
Pearls & oysters: Oculopalatal tremor with one-and-a-
half syndrome after pontine hemorrhage. Neurology,
71, 39–41.
Albright, T. D. (1984). Direction and orientation selectivity of
neurons in visual area MT of the macaque. Journal of
Neurophysiology, 52, 1106–1130.
Alkaladi, A., & Zeil, J. (2014). Functional anatomy of the
fiddler crab compound eye (Uca vomeris: Ocypodidae,
Brachyura, Decapoda). Journal of Comparative
Neurology, 522, 1264–1283.
Alpern, M., Kitahara, K., & Krantz, D. H. (1983). Perception
of color in unilateral tritanopia. Journal of Physiology,
335, 683–697.
Alpern, M., Lee, G. B., Maaseidvaag, F., & Miller, S. S.
(1971). Colour vision in blue-cone “monochromacy.”
Journal of Physiology, 212, 211–233.
Alvarado, J. C., Vaughan, J. W., Stanford, T. R., & Stein, B.
E. (2007). Multisensory versus unisensory integration:
Contrasting modes in the superior colliculus. Journal of
Neurophysiology, 97, 3193–3205.
Ambady, N., & Bharucha, J. J. (2009). Culture and the
brain. Current Directions in Psychological Science, 18,
342–345.
Anderson, B. A., Laurent, P. A., & Yantis, S. (2013). Reward
predictions bias attentional selection. Frontiers in
Human Neuroscience, 7, 262.
Anderson, B. A., & Yantis, S. (2013). Persistence of value-
driven attentional capture. Journal of Experimental
Psychology: Human Perception and Performance, 39, 6–9.
Anderson, S., White-Schwoch, T., Parbery-Clark, A., &
Kraus, N. (2013). A dynamic auditory-cognitive system
supports speech-in-noise perception in older adults.
Hearing Research, 300, 18–32.
Anstis, S. (2012). The furrow illusion: Peripheral motion
becomes aligned with stationary contours. Journal of
Vision, 12, 1–11.
Anstis, S., & Rogers, B. (2011). Illusory rotation of a spoked
wheel. i-Perception, 2, 720–723.
Arroyo, J. G. (2006). A 76-year-old man with macular
degeneration. JAMA, 295, 2394–2406.
Atkinson, J., Braddick, O., & Moar, K. (1977). Development
of contrast sensitivity over the first 3 months of life in
the human infant. Vision Research, 17(9), 1037–1044.
Attems, J., Walker, L., & Jellinger, K. A. (2014). Olfactory
bulb involvement in neurodegenerative diseases. Acta
Neuropathologica, 127, 459–475.
Babadi, B., Casti, A., Xiao, Y., Kaplan, E., & Paninski, L.
(2010). A generalized linear model of the impact of direct
and indirect inputs to the lateral geniculate nucleus.
Journal of Vision, 10, 22.
Balkwill, L.-L., & Thompson, W. F. (1999). A cross-cultural
investigation of the perception of emotion in music:
Psychophysical and cultural cues. Music Perception, 17,
43–64.
Banks, M. S., & Bennett, P. J. (1988). Optical and
photoreceptor immaturities limit the spatial and chromatic
vision of human neonates. JOSA A, 5(12), 2059–2079.
Bannister, J. (2016). Chili peppers 101. Retrieved from
https://cpi.nmsu.edu/chile-pepper-news-and-info-center
Barlow, H. B. (1953). Summation and inhibition in the frog’s
retina. Journal of Physiology, 119, 69–88.
Barlow, H. B. (1995). The neuron in perception. In M. S.
Gazzaniga (Ed.), The cognitive neurosciences (pp.
415–434). Cambridge, MA: MIT Press.
Barlow, H. B., Blakemore, C., & Pettigrew, J. D. (1967). The
neural mechanism of binocular depth discrimination.
Journal of Physiology, 193, 327–342.
Barry, M. P., & Dagnelie, G. (2016). Hand-camera
coordination varies over time in users of the Argus®
II retinal prosthesis system. Frontiers in Systems
Neuroscience, 10, 41.
Bartoshuk, L. M. (1971). The chemical senses: I. Taste. In
J. W. Kling & L. A. Riggs (Eds.), Experimental psychology
(3rd ed.). New York, NY: Holt, Rinehart & Winston.
Bartoshuk, L. M., Duffy, V. B., & Miller, I. J. (1994). PTC/
PROP tasting: Anatomy, psychophysics, and sex effects.
Physiology & Behavior, 56, 1165–1171.
Beck, D. M., Muggleton, N., Walsh, V., & Lavie, N. (2006).
Right parietal cortex plays a critical role in change
blindness. Cerebral Cortex, 16, 712–717.
Beckers, G., & Zeki, S. (1995). The consequences of
inactivating areas V1 and V5 on visual motion
perception. Brain, 118, 49–60.
Belin, P., Bestelmeyer, P. E. G., Latinus, M., & Watson, R.
(2011). Understanding voice perception. British Journal
of Psychology, 102, 711–725.
Bellugi, U., Klima, E. S., & Hickok, G. (2010). Brain
organization: Clues from deaf signers with left or right
hemisphere lesions. In L. Clara (Ed.), Gesture and word
(pp. 2–17). Lisbon, Portugal: Editorial Caminho.
Benedetti, F. (1985). Processing of tactile spatial information
with crossed fingers. Journal of Experimental Psychology:
Human Perception and Performance, 11, 517–525.
Sensation and Perception476
Bennett, C. M., Wolford, G. L., & Miller, M. B. (2009). The
principled control of false positives in neuroimaging.
Social, Cognitive, and Affective Neuroscience, 4,
417–422.
Beran, M. J. (2012). We cannot know what it is like to be a
bat, but we can know better what it is like to see like a
bat. PsychCRITIQUES, 57, 38.
Beranek, L. L. (2003). Subjective rank-orderings and
acoustical measurements for fifty-eight concert halls.
Acta Acustica Acustica, 89, 494–508.
Bhalla, M., & Proffitt, D. R. (1999). Visual-motor
recalibration in geographical slant perception. Journal
of Experimental Psychology: Human Perception and
Performance, 25, 1076–1096.
Biederman, I. (1987). Recognition-by-components: A theory
of human image understanding. Psychological Review,
94, 115–147.
Birch, E. E. (1993). Introduction to binocular vision. In K.
Simons (Ed.), Early visual development: Normal and
abnormal. New York, NY: Oxford University Press.
Birch, J. (2001). Diagnosis of defective colour vision (2nd
ed.). New York, NY: Elsevier.
Bisiach, E., & Luzzatti, C. (1978). Unilateral neglect of
representational space. Cortex, 14, 129–133.
Blackwell, H. R. (1953). Psychophysical thresholds:
Experimental studies of methods of measurement
(Bulletin No. 36). Ann Arbor: University of Michigan
Engineering Research Institute.
Blake, R., & Shiffrar, M. (2007). Perception of human
motion. Annual Review of Psychology, 58, 47–73.
Blake, R., Cool, S. J., & Crawford, M. L. J. (1974). Visual
resolution in the cat. Vision Research, 14(11), 1211–1217.
Bleyenheuft, Y., & Thonnard, J. L. (2009). Development of
touch. Scholarpedia, 4(11), 7958.
Bohn, K. M., Smarsh, G. C., & Smotherman, M. S. (2013).
Social context evokes rapid changes in bat song syntax.
Animal Behavior, 85, 1485–1491.
Born, R. T., & Bradley, D. C. (2005). Structure and function
of visual area MT. Annual Review of Neuroscience, 28,
157–189.
Bornstein, M. H., Kessen, W., & Weiskopf, S. (1976). Color
vision and hue categorization in young human infants.
Journal of Experimental Psychology: Human Perception
and Performance, 2(1), 115–129.
Bouchard, S., Côté, S., St-Jacques, J., Robillard, G.,
& Renaud, P. (2006). Effectiveness of virtual reality
exposure in the treatment of arachnophobia using 3D
games. Technology and Health Care, 14(1), 19–27.
Bowmaker, J. K. (1998). Visual pigments and molecular
genetics of color blindness. News in Physiological
Science, 13, 63–69.
Bregman, A. S. (1990). Auditory scene analysis: The perceptual
organization of sound. Cambridge, MA: Bradford.
Bregman, A. S. (2005). Auditory scene analysis and the
role of phenomenology in experimental psychology.
Canadian Psychology, 46, 32–40.
Breitmeyer, B. G., & Hanif, W. (2008). “Change of mind”
within and between nonconscious (masked) and
conscious (unmasked) visual processing. Consciousness
and Cognition, 17, 254–266.
Brendel, E., DeLucia, P. R., Hecht, H., Stacy, R. L., & Larsen,
J. T. (2012). Threatening pictures induce shortened
time-to-contact estimates. Attention, Perception, &
Psychophysics, 74, 979–987.
Bressler, N. M. (2004). Age-related macular degeneration is
the leading cause of blindness. JAMA, 291, 1900–1901.
Brett, J. A. (2016). Thinking local about self-driving
cars: A local framework for autonomous vehicle
development in the United States. Master’s thesis,
University of Washington. Retrieved from https://
digital.lib.washington.edu/researchworks/bitstream/
handle/1773/36852/Brett_washington_0250O_16021
?sequence=1&isAllowed=y
Bridgeman, B., & Stark, L. (1991). Ocular proprioception
and efference copy in registering visual direction. Vision
Research, 31, 1903–1913.
Brincat, S., & Connor, C. E. (2004). Underlying principles
of visual shape selectivity in posterior inferotemporal
cortex. Nature Neuroscience, 7, 880–886.
Brown, A. M., & Teller, D. Y. (1989). Chromatic opponency in
3-month-old human infants. Vision Research, 29(1), 37–45.
Bruce, C., Desimone, R., & Gross, C. G. (1981). Visual
properties of neurons in a polysensory area in
superior temporal sulcus of the macaque. Journal of
Neurophysiology, 46, 369–384.
Buck, L. B., & Axel, R. (1991). A novel multigene family may
encode odorant receptors: A molecular basis for odor
recognition. Cell, 65, 175–187.
Buetti, S., Tamietto, M., Hervais-Adelman, A., Kerzel, D., de
Gelder, B., & Pegna, A. J. (2013). Dissociation between
goal-directed and discrete response localization in
a patient with bilateral cortical blindness. Journal of
Cognitive Neuroscience, 25, 1769–1775.
Busch, N. A. (2013). The fate of object memory traces under
change detection and change blindness. Brain Research,
1520, 107–115.
Busigny, T., & Rossion, B. (2011). Holistic processing
impairment can be restricted to faces in acquired
prosopagnosia: Evidence from the global/local Navon
effect. Journal of Neuropsychology, 5, 1–14.
Buzás, P., Kóbor, P., Petykó, Z., Telkes, I., Martin, P. R., &
Lénárd, L. (2013). Receptive field properties of color
opponent neurons in the cat lateral geniculate nucleus.
Journal of Neuroscience, 33, 1451–1461.
Cain, W. S. (1979). To know with the nose: Keys to odor
identification. Science, 203, 467–470.
References 477
Cain Miller, C., & Wald, M. L. (2013, May 30). Self-driving
cars for testing are supported by the U.S. The New York
Times. Retrieved from http://www.nytimes
.com/2013/05/31/technology/self-driving-cars-for-testing-
are-supported-by-us.html?pagewanted=all&_r=0
Caminiti, F., Ciurleo, R., Bramanti, P., & Marino, S. (2013).
Persistent anosmia in a traumatic brain injury patient:
Role of orbitofrontal cortex. Brain Injury, 27, 1715–1718.
Carroll, J., Neitz, M., Hofer, H., Neitz, J., & Williams, D. R.
(2004). Functional photoreceptor loss revealed with
adaptive optics: An alternate cause of color blindness.
Proceedings of the National Academy of Sciences of the
United States of America, 101, 8461–8466.
Cartwright, M. (2013). Ancient Greek music. In Ancient
history encyclopedia. Retrieved from https://www
.ancient.eu/Greek_Music
Centers for Disease Control and Prevention. (2017). Hearing
loss in children: Data and statistics. Retrieved from
https://www.cdc.gov/ncbddd/hearingloss/data.html
Chabris, C., & Simons, D. (2009). The invisible gorilla. New
York, NY: Broadway.
Chan, B. L., Witt, R., Charrow, A. P., Magee, A., Howard,
R., Pasquina, P. F., Heilman, K. M., & Tsao, J. W. (2007).
Mirror therapy for phantom limb pain. New England
Journal of Medicine, 357(21), 2206–2207.
Chandrashekar, J., Hoon, M. A., Ryba, N. J. P., & Zuker, C.
S. (2006). The receptors and cells for mammalian taste.
Nature, 444, 288–294.
Chasin, M. (2011, May). Setting hearing aids differently for
different languages. Seminars in Hearing, 32(2), 182–188.
Chasin, M. (2012). Sentence final hearing aid gain
requirements of some non-English languages.
Ajustements spécifiques de gain des appareils auditifs
pour les finales de phrases de certaines langues autres
que l’anglais. Canadian Journal of Speech-Language
Pathology and Audiology, 36(3), 196–203.
Chasin, M., & Hockley, N. S. (2014). Some characteristics
of amplified music through hearing aids. Hearing
Research, 308, 2–12.
Chen, M.-C., Tsai, P.-L., Huang, Y.-T., & Lin, K. (2013). Pleasant
music improves visual attention in patients with
unilateral neglect after stroke. Brain Injury, 27, 75–82.
Cherry, E. C. (1953). Some experiments on the recognition
of speech, with one and with two ears. Journal of the
Acoustical Society of America, 25, 975–979.
Chino, Y. M., Smith, E. L., III, Hatta, S., & Cheng, H. (1997).
Postnatal development of binocular disparity sensitivity
in neurons of the primate visual cortex. Journal of
Neuroscience, 17, 296–307.
Chiu, Y.-C., & Yantis, S. (2009). A domain-independent
source of cognitive control for task sets: Shifting spatial
attention and switching categorization rules. Journal of
Neuroscience, 29, 3930–3938.
Chow, A., Chow, V., Packo, K., Pollack, J., Peyman, G.,
& Schuchard, R. (2004). The artificial silicone retina
microchip for the treatment of vision loss from retinitis
pigmentosa. Archives of Ophthalmology, 122, 1156–1157.
Chrastil, E. R. (2013). Neural evidence supports a novel
framework for spatial navigation. Psychonomic Bulletin
& Review, 20, 208–227.
Chun, M. M., Golomb, J. D., & Turke-Browne, N. B. (2011).
A taxonomy of external and internal attention. Annual
Review of Psychology, 62, 73–101.
Coben, J. H., & Zhu, M. (2013). Keeping an eye on
distracted driving. JAMA, 309(9), 877–878.
Colby, C. L., Duhamel, J.-R., & Goldberg, M. E. (1996).
Visual, pre-saccadic, and cognitive activation of single
neurons in monkey lateral intraparietal area. Journal of
Neurophysiology, 76, 2841–2851.
Cole, B. L. (2016). Colour vision and driving. Clinical
Experimental Ophthalmology, 99, 484–487.
Collignon, O., Dormal, G., Albouy, G., Vandewalle, G., Voss,
P., Phillips, C., & Lepore, F. (2013). Impact of blindness
onset on the functional organization and the connectivity
of the occipital cortex. Brain, 136, 2769–2783.
Colombo, J. (2002). Infant attention grows up: The
emergence of a developmental cognitive neuroscience
perspective. Current Directions in Psychological
Science, 11, 196–200.
Compton, W. M., Jones, C. M., & Baldwin, G. T. (2016).
Relationship between nonmedical prescription-opioid
use and heroin use. New England Journal of Medicine,
374(2), 154–163.
Conard, N. J., Malina, M., & Münzel, S. C. (2009). New
flutes document the earliest musical tradition in
southwestern Germany. Nature, 460, 737–740.
Coren, S., & Girgus, J. S. (1978). Seeing is deceiving: The
psychology of visual illusions. Hillsdale, NJ: Erlbaum.
Cornsweet, T. N. (1970). Visual perception. New York, NY:
Academic Press.
Crystal, S. R., & Bernstein, I. L. (1995). Morning sickness:
Impact on offspring salt preference. Appetite, 25, 231–240.
Culham, J. C., Cavina-Pratesi, C., & Singhal, A. (2006). The
role of parietal cortex in visuomotor control: What have
we learned from neuroimaging? Neuropsychologia, 44,
2668–2684.
Curcio, C. A., Sloan, K. R., Kalina, R. E., & Hendrickson, A.
E. (1990). Human photoreceptor topography. Journal of
Comparative Neurology, 292, 497–523.
Curtiss, S. (2014). Genie: A psycholinguistic study of a
modern-day wild child. New York, NY: Academic Press.
Dai, P., & Soon, I. Y. (2013). An improved model of masking
effects for robust speech recognition system. Speech
Communication, 55(3), 387–396.
Davis, K. D., Taylor, S. J., Crawley, A. P., Wood, M. L.,
& Mikulis, D. J. (1997). Functional MRI of pain- and
Sensation and Perception478
attention-related activations in the human cingulate
cortex. Journal of Neurophysiology, 77, 3370–3380.
Daw, N. (2009). The foundations of development and
deprivation in the visual system. Journal of Physiology,
587, 2769–2773.
Day, R. H. (1990). The Bourdon illusion in haptic space.
Perception and Psychophysics, 47, 400–404.
de Gelder, B. (2010). Uncanny sight in the blind. Scientific
American, 302, 60–65.
de Gelder, B., Tamietto, M., van Boxtel, G., Goebel, R.,
Sahraie, A., Van den Stock, J., . . . Pegna, A. (2008). Intact
navigation skills after bilateral loss of striate cortex.
Current Biology, 18, R1128–R1129.
De Valois, R. L. (1960). Color vision mechanisms in the
monkey. Journal of General Physiology, 43, 115–128.
De Valois, R. L. (1965). Behavioral and electrophysiological
studies of primate vision. In W. D. Ness (Ed.),
Contributions to sensory physiology (Vol. 1). New York,
NY: Academic Press.
De Valois, R. L. (2004). Neural coding of color. In L. M.
Chalupa & J. S. Werner (Eds.), The visual neurosciences
(Vol. 2, pp. 1003–1016). Cambridge, MA: MIT Press.
De Valois, R. L., Abramov, I., & Jacobs, G. H. (1966).
Analysis of response patterns of LGN cells. Journal of
the Optical Society of America, 56, 966–977.
de Wijk, R. A., & Cain, W. S. (1994). Odor quality:
Discrimination versus free and cued identification.
Perception and Psychophysics, 56, 12–18.
DeCasper, A. J., & Fifer, W. P. (1980). Of human bonding:
Newborns prefer their mothers’ voices. Science, 208,
1174–1176.
Delk, J. L., & Fillenbaum, S. (1965). Differences in perceived
color as a function of characteristic color. American
Journal of Psychology, 78, 290–293.
Delogu, F., Huddas, C., Steven, K., Hachem, S., Lodhia, L.,
Fernandez, R., & Logerstedt, M. (2016). A dissociation
between recognition and hedonic value in caloric
and non-caloric carbonated soft drinks. Frontiers in
Psychology, 7, 36.
DeLucia, P. R. (2013). Effects of size on collision
perception and implications for perceptual theory
and transportation safety. Current Directions in
Psychological Science, 22, 199–204.
DeLucia, P. R., Meza-Arroyo, M., Baures, R., Ranjit, M.,
Hsiang, S., & Gorman, J. C. (2016). Continuous response
monitoring of relative time-to-contact judgments: Does
effective information change during an approach event?
Ecological Psychology, 28, 1–22.
Delwiche, J. F., Buletic, Z., & Breslin, P. A. S. (2001).
Covariation in individuals’ sensitivities to bitter
compounds: Evidence supporting multiple
receptor/transduction mechanisms. Perception and
Psychophysics, 63, 761–776.
DeMarco, P. J., Jr., Yarbrough, G. L., Yee, C. W., McLean, G.
Y., Sagdullaev, B. T., Ball, S. L., & McCall, M. A. (2007).
Stimulation via a subretinally placed prosthetic elicits
central activity and induces a trophic effect on visual
responses. Investigative Ophthalmology & Visual
Science, 48, 916–926.
Dennett, D. C. (1991). Consciousness explained. Boston,
MA: Little, Brown.
Deutsch, D. (1974). An auditory illusion. Nature, 251, 307–309.
Deutsch, D. (1975a). Musical illusions. Scientific American,
233, 92–104.
Deutsch, D. (1975b). Two-channel listening to musical scales.
Journal of the Acoustical Society of America, 57, 1156–1160.
Deutsch, D. (1986). A musical paradox. Music Perception, 3,
275–280.
Deutsch, D. (2013). The psychology of music (3rd ed.). San
Diego, CA: Elsevier.
Devos, M., Patte, F., Rouault, J., Laffort, P., & Van Gemert,
L. J. (1990). Standardized human olfactory thresholds.
Oxford, UK: Oxford University Press.
Dewald, A. D., Sinnett, S., & Doumas, L. A. A. (2013).
A window of perception when diverting attention?
Enhancing recognition for explicitly presented,
unattended, and irrelevant stimuli by target alignment.
Journal of Experimental Psychology: Human Perception
and Performance, 39(5), 1304–1312.
DeWitt, L. A., & Samuel, A. G. (1990). The role of
knowledge-based expectation in music perception:
Evidence for musical restoration. Journal of
Experimental Psychology: General, 119, 123–144.
DeYoe, E. A., & Van Essen, D. C. (1988). Concurrent
processing streams in monkey visual cortex. Trends in
Neurosciences, 11, 219–226.
Diehl, R. L., Lotto, A. J., & Holt, L. L. (2004). Speech
perception. Annual Review of Psychology, 55, 149–179.
Djordjevic, J., Lundstrom, J. N., Clement, F., Boyle, J.
A., Pouliot, S., & Jones-Gotman, M. (2008). A rose by
any other name: Would it smell as sweet? Journal of
Neurophysiology, 99, 386–393.
Djordjevic, J., Zatorre, R. J., Petrides, M., Boyle, J., &
Jones-Gotman, M. (2005). Functional neuroimaging of
odor imagery. NeuroImage, 24, 791–801.
Doerschner, K., Kersten, D., & Schrater, P. (2009). Rapid
classification of surface reflectance from image
velocities. Computer Analysis of Images and Patterns,
Lecture Notes in Computer Science, 5702, 856–864.
Domínguez-Borràs, J., Armony, J. L., Maravita, A., Driver,
J., & Vuilleumier, P. (2013). Partial recovery of visual
extinction by Pavlovian conditioning in a patient with
hemispatial neglect. Cortex, 49, 891–898.
Downing, P. E., Jiang, Y., Shuman, M., & Kanwisher, N.
(2001). Cortical area selective for visual processing of
the human body. Science, 293, 2470–2473.
References 479
Drew, T., Võ, M.L.-H., & Wolfe, J. M. (2013). The invisible
gorilla strikes again: Sustained inattentional blindness in
expert observers. Psychological Science, 24, 1848–1853.
Duchaine, B. C., & Nakayama, K. (2006). Developmental
prosopagnosia: A window to content-specific face
processing. Current Opinion in Neurobiology, 16, 166–173.
Duffy, V. B., Lucchina, L. A., & Bartoshuk, L. M. (2004).
Genetic variation in taste: Potential biomarker for
cardiovascular disease risk? In J. Prescott & B. J.
Tepper (Eds.), Genetic variation in taste sensitivity:
Measurement, significance, and implications (pp.
195–228). New York, NY: Marcel Dekker.
Ealy, G. T. (1994). Of ear trumpets and a resonance
plate: Early hearing aids and Beethoven’s hearing
perception. 19th-Century Music, 17, 262–273.
Eggenberger, E. R. (2014). Supranuclear eye movement
abnormalities. Continuum: Lifelong Learning in
Neurology, 20, 981–992.
Egly, R., Driver, J., & Rafal, R. D. (1994). Shifting visual
attention between objects and locations: Evidence
from normal and parietal lesion subjects. Journal of
Experimental Psychology: General, 123, 161–177.
Eimas, P. D., & Corbit, J. D. (1973). Selective adaptation of
linguistic feature detectors. Cognitive Psychology, 4,
99–109.
Engen, T. (1972). The effect of expectation on judgments of
odor. Acta Psychologica, 36, 450–458.
Enns, J. T., & Di Lollo, V. (1997). Object substitution:
A new form of masking in unattended visual
locations. Psychological Science, 8(2), 135–139.
doi:10.1111/j.1467-9280.1997.tb00696.x
Epstein, R. (2005). The cortical basis of visual scene
processing. Visual Cognition, 12, 954–978.
Epstein, R., & Kanwisher, N. (1998). A cortical
representation of the local visual environment. Nature,
392, 598–601.
Fain, G. L. (2003). Sensory transduction. Sunderland, MA:
Sinauer.
Farina, F. R., Mitchell, K. J., & Roche, R. A. P. (2017).
Synaesthesia lost and found: Two cases of person-
and music-colour synaesthesia. European Journal of
Neuroscience, 45, 472–477.
Fechner, G. T. (1966). Elements of psychophysics (H. E.
Adler, Trans., D. H. Howes & E. G. Boring, Eds.). New
York, NY: Holt, Rinehart. (Original work published 1860)
Fedderson, W. E., Sandel, T. T., Teas, D. C., & Jeffress, L. A.
(1957). Localization of high frequency tones. Journal of
the Acoustical Society of America, 28, 988–991.
Feynman, R. P. (1985). QED: The strange theory of light and
matter. Princeton, NJ: Princeton University Press.
Feynman, R. P. (1995). Six easy pieces: Essentials of physics
explained by its most brilliant teacher. Reading, MA:
Perseus.
Fields, R. D. (2007). The shark’s electric sense. Scientific
American, 297, 74–81.
Findling, D. (2017). CNBC took BMW’s new self-driving
car out for a spin. Here’s what it was like. CNBC News.
Retrieved from http://www.cnbc.com/2017/01/13/cnbc-
took-bmws-new-self-driving-car-out-for-a-spin-heres-
what-it-was-like.html
Firestone, C., & Scholl, B. J. (2016). Cognition does not
affect perception: Evaluating the evidence for “top-
down” effects. Behavioral and Brain Sciences, 39, e229.
doi:10.1017/S0140525X15000965
Fisher, M. F. K. (1943). The gastronomical me. New York, NY:
Duell, Sloan & Pearce.
Foell, J., Bekrater-Bodmann, R., Diers, M., & Flor, H. (2014).
Mirror therapy for phantom limb pain: Brain changes
and the role of body representation. European Journal
of Pain, 18(5), 729–739.
Foldvari, M., & Chen, D.W. (2016). The intricacies of
neurotrophic factor therapy for retinal ganglion cell
rescue in glaucoma: A case for gene therapy. Neural
Regeneration Research, 11, 875–877.
Foster, D. H. (2011). Color constancy. Vision Research, 51,
674–700.
Fowler, C. A., & Dekle, D. J. (1991). Listening with eye and
hand: Cross-modal contributions to speech perception.
Journal of Experimental Psychology: Human Perception
and Performance, 17, 816–828.
Fowler, C. A., & Thompson, J. M. (2010). Listeners’
perception of “compensatory shortening.” Attention,
Perception, & Psychophysics, 72, 481–491.
Frank, G. K. W., Oberndorfer, T. A., Simmons, A. N., Paulus,
M. P., Fudge, J. L., Yang, T. T., & Kaye, W. H. (2008).
Sucrose activates human taste pathways differently
from artificial sweetener. NeuroImage, 39(4), 1559–1569.
Fraser, A., & Wilcox, K. J. (1979). Perception of illusory
movement. Nature, 281, 565–566.
Frasnelli, J., Fark, T., Lehmann, J., Gerber, J., & Hummel,
T. (2013). Brain structure is changed in congenital
anosmia. Neuroimage, 83, 1074–1080.
Frazier, L. D. (2018). Health psychology. New York, NY:
Worth.
Freeman, S., Yu, R., Egorova, N., Chen, X., Kirsch, I.,
Claggett, B., Kaptchuk, T. J., . . . Kong, J. (2015). Distinct
neural representations of placebo and nocebo effects.
Neuroimage, 112, 197–207.
Froehlich, J. C. (1997). Opioid peptides. Alcohol Research
and Health, 21(2), 132.
Fromkin, V., Krashen, S., Curtiss, S., Rigler, D., & Rigler, M.
(1974). The development of language in Genie: A case of
language acquisition beyond the “critical period.” Brain
and Language, 1(1), 81–107.
Furl, N., Garrido, L., Dolan, R. J., Driver, J., & Duchaine,
B. (2011). Fusiform gyrus face selectivity relates to
Sensation and Perception480
individual differences in facial recognition ability.
Journal of Cognitive Neuroscience, 23, 1723–1740.
Galanter, E. (1962). Direct measurement of utility and
subjective probability. American Journal of Psychology,
75, 208–220.
Galantucci, B., Fowler, C. A., & Turvey, M. T. (2006).
The motor theory of speech perception reviewed.
Psychonomic Bulletin & Review, 13, 361–377.
Galletti, C., & Fattori, P. (2003). Neuronal mechanisms
for detection of motion in the field of view.
Neuropsychologia, 41, 1717–1727.
Gallivan, J. P., McLean, D. A., Flanagan, J. R., & Culham,
J. C. (2013). Where one hand meets the other: Limb-
specific and goal-dependent movement plans decoded
from preparatory signals in single human parieto-frontal
brain areas. Journal of Neuroscience, 33, 1991–2008.
Gamito, P., Oliveira, J., Rosa, P., Morais, D., Duarte,
N., Oliveira, S., & Saraiva, T. (2010). PTSD elderly
war veterans: A clinical controlled pilot study.
Cyberpsychology, Behavior, and Social Networking,
13(1), 43–48.
Garneau, N. L., Nuessle, T. M., Sloan, M. M., Santorico,
S. A., Coughlin, B. C., & Hayes J. E. (2014, May 27).
Crowdsourcing taste research: Genetic and phenotypic
predictors of bitter taste perception as a model.
Frontiers in Integrative Neuroscience. Retrieved
from http://journal.frontiersin.org/Journal/10.3389/
fnint.2014.00033/abstract
Gatzia, D. E., & Schwartz, B. L. (2016). I think it’s going
to hurt: The effects of cognition on pain perception.
Presented at the meeting of the Southern Society of
Philosophy and Psychology, March 12, 2016,
Louisville, KY.
Gelbard-Sagiv, H., Mukamel, R., Harel, M., Malach, R.,
& Fried, I. (2008). Internally generated reactivation of
single neurons in human hippocampus during free
recall. Science, 322, 96–101.
Gelfand, S. A. (2009). Essentials of audiology (3rd ed.). New
York, NY: Thieme Medical.
Gerstmann, J. (2001). Pure tactile agnosia. Cognitive
Neuropsychology, 18, 267–274.
Gibson, E. J. (2001). Perceiving the affordances: A portrait
of two psychologists. Hillsdale, NJ: Erlbaum.
Gibson, J. J. (1950). The perception of the visual world.
Boston, MA: Houghton Mifflin.
Gibson, J. J. (1979). The ecological approach to visual
perception. Hillsdale, NJ: Erlbaum.
Gilbert, S. F. (2000). Developmental biology (6th ed.).
Sunderland, MA: Sinauer Associates.
Gilchrist, A., Kossyfidis, C., Bonato, F., Agostini, T., Cataliotti,
J., Li, X., . . . Economou, E. (1999). An anchoring theory
of lightness perception. Psychological Review, 106,
795–834.
Godwin, H. J., Houpt, J. W., Walenchok, S. C., Hout, M.
C., & Goldinger, S. D. (2015). Faster than the speed of
rejection: Object identification processes during visual
search for multiple targets. Journal of Experimental
Psychology: Human Perception and Performance, 41,
1007–1020.
Godwin, H. J., Menneer, T., Cave, K. R., Helman, S., Way,
R. L., & Donnelly, N. (2010). The impact of relative
prevalence on dual-target search for threat items from
airport X-ray screening. Acta Psychologica, 134, 79–84.
Goldberg, S., & Trattler, W. (2015). Ophthalmology made
ridiculously simple. Miami, FL: Medmaster.
Goldwater, S., Jurafsky, D., & Manning, C. D. (2010). Which
words are hard to recognize? Prosodic, lexical, and
disfluency factors that increase speech recognition error
rates. Speech Communication, 52(3), 181–200.
Goodale, M. A., Milner, A. D., Jakobsen, L. S., & Carey, D. P.
(1991). A neurological dissociation between perceiving
objects and grasping them. Nature, 349, 154–156.
Graham, C. H., & Hsia, Y. (1958). Color defect and color
theory. Science, 127, 675–682.
Grant, P., Spencer, L., Arnoldussen, A., Hogle, R., Nau,
A., Szlyk, J., . . . Seiple W. (2016). The functional
performance of the brainport v100 device in persons
who are profoundly blind. Journal of Visual Impairment
& Blindness (Online), 110(2), 77.
Granville, W. C. (1990). Colors do look different after a lens
implant! Color Research & Application, 15(1), 59–62.
Graven, S. N., & Browne, J. V. (2008). Auditory
development in the fetus and infant. Newborn and
Infant Nursing Review, 8, 187–193.
Green, D. M., & Swets, J. (1966). Signal detection theory
and psychophysics. New York, NY: Wiley.
Green, E., & Murphy, C. (2012). Altered processing of sweet
taste in the brain of diet soda drinkers. Physiology &
Behavior, 107(4), 560–567.
Greenwood, V. (2012, July–August). The humans with
super human vision. Discover. Retrieved from http://
discovermagazine.com/2012/jul-aug/06-humans-with-
super-human-vision
Gregory, R. L. (1966). Eye and brain. New York, NY:
McGraw-Hill.
Grill-Spector, K., Knouf, N., & Kanwisher, N. (2004).
The fusiform face area subserves face perception,
not generic within-category identification. Nature
Neuroscience, 7, 555–562.
Grimault, N., Bacon, S. P., & Micheyl, C. (2002).
Auditory stream segregation on the basis of
amplitude-modulation rate. Journal of the Acoustical
Society of America, 113, 1340–1348.
Grossman, E. D., Battelli, L., & Pascual-Leone, A. (2005).
Repetitive TMS over STS disrupts perception of
biological motion. Vision Research, 45, 2847–2853.
References 481
Grüsser, O.-J. (1993). The discovery of the psychophysical
power law by Tobias Mayer in 1754 and the
psychophysical hyperbolic law by Ewald Hering in 1874.
Behavioral and Brain Sciences, 16, 142–144.
Guyton, A. C. (1991). Textbook of medical physiology (8th
ed.). Philadelphia, PA: Saunders.
Habibi, A., Cahn, R., Damasio, A., & Damasio, H. (2016).
Neural correlates of accelerated auditory processing
in children engaged in music training. Developmental
Cognitive Neuroscience, 21, 1–14.
Habibi, A., Wirantana, V., & Starr, A. (2013). Cortical
activity during perception of musical pitch: Comparing
musicians and nonmusicians. Music Perception, 30,
463–479.
Hahnel, U. J. J., & Hecht, H. (2012). The impact of rear-view
mirror distance and curvature on judgements relevant
to road safety. Ergonomics, 55, 23–26.
Hansen, J. H., & Arslan, L. M. (1995, May). Foreign accent
classification using source generator based prosodic
features. In IEEE International Conference on Acoustics,
Speech, and Signal Processing, 1995 (Vol. 1, pp.
836–839).
Hansen, T., Olkkonen, M., Walter, S., & Gegenfurtner, K. R.
(2006). Memory modulates color appearance. Nature
Neuroscience, 9(11), 1367–1368.
Harley, T. A. (2014). The psychology of language: From data
to theory (4th ed.). New York, NY: Psychology Press.
Hartline, H. K., & Ratliff, F. (1958). Spatial summation of
inhibitory influences in the eye of Limulus and the
mutual interaction of receptor units. Journal of General
Physiology, 41, 1049–1066.
Hartong, D. T., Berson, E. L., & Dryja, T. P. (2006). Retinitis
pigmentosa. Lancet, 368, 1795–1809.
Håstad, O., Victorsson, J., & Ödeen, A. (2005). Differences
in color vision make passerines less conspicuous in the
eyes of their predators. PNAS, 102(18), 6391–6394.
Hastorf, A. H., & Cantril, H. (1954). They saw a game: A case
study. Journal of Abnormal and Social Psychology, 49,
129–134.
He, J. (2003). Corticofugal modulation of the auditory
thalamus. Experimental Brain Research, 153, 579–590.
Hecht, H., & Savelsbergh, G. J. P. (2004). Time-to-contact.
Amsterdam, The Netherlands: Elsevier.
Hecht, S., Schlaer, S., & Pirenne, M. H. (1942). Energy,
quanta, and vision. Journal of General Physiology, 39,
651–673.
Hedges, J. H., Gartshteyn, Y., Kohn, A., Rust, N. C.,
Shadlen, M. N., Newsome, W. T., & Movshon, J. A.
(2011). Dissociation of neuronal and psychophysical
responses to local and global motion. Current Biology,
21, 2023–2028.
Held, R. (1965). Plasticity in sensory-motor systems.
Scientific American, 213, 84–94.
Held, R. (1980). The rediscovery of adaptability in the visual
system: Effects of extrinsic and intrinsic chromatic
dispersion. In C. S. Harris (Ed.), Visual coding and
adaptability (pp. 69–94). Hillsdale, NJ: Erlbaum.
Held, R., & Hein, A. (1963). Movement-produced
stimulation in the development of visually guided
behavior. Journal of Comparative and Physiological
Psychology, 56, 872–876.
Heller, M. A., Brackett, D. D., Wilson, K., Yoneyama, K.,
Boyer, A., & Steffen, H. (2002). The haptic Müller-Lyer
illusion in sighted and blind people. Perception, 31(10),
1263–1274.
Hendry, S. H. C., & Reid, R. C. (2000). The koniocellular
pathway in primate vision. Annual Review of
Neuroscience, 23, 127–153.
Henry, B. A., Turner, C. W., & Behrens, A. (2005). Spectral
peak resolution and speech recognition in quiet: Normal
hearing, hearing impaired, and cochlear implant
listeners. Journal of the Acoustical Society of America,
118, 1111–1121.
Hershenson, M., & Samuels, S. M. (1999). An airplane
illusion: Apparent velocity determined by apparent
distance. Perception, 28, 433–436.
Herz, R. (2007). The scent of desire. New York, NY:
HarperCollins.
Herz, R. S., & von Clef, J. (2001). The influence of verbal
labelling on the perception of odors: Evidence for
olfactory illusions? Perception, 30, 381–391.
Herz, R. S., Eliassen, J. C., Beland, S. L., & Souza, T.
(2004). Neuroimaging evidence for the emotional
potency of odor-evoked memory. Neuropsychologia,
42, 371–378.
Hickok, G., & Poeppel, D. (2007). The cortical organization
of speech processing. Nature Reviews Neuroscience, 8,
393–401.
Hof, P. R., & van der Gucht, E. (2007). Structure of the
cerebral cortex of the humpback whale, Megaptera
novaeangliae (Cetacea, Mysticeti, Balaenopteridae).
Anatomical Record, 290, 1–31.
Hofeldt, A. J., & Hoefle, F. B. (1993). Stereophotometric
testing for Pulfrich’s phenomenon in professional
baseball players. Perceptual and Motor Skills, 77,
407–416.
Hofeldt, A. J., Hoefle, F. B., & Bonafede, B. (1996). Baseball
hitting, binocular vision, and the Pulfrich phenomenon.
Archives of Ophthalmology, 114, 1490–1494.
Hoffman, P. M., Van Riswick, J. G., & Van Opstal, A. J. (1998).
Relearning sound localization with new ears. Nature
Neuroscience, 1, 417–421.
Hollins, M., Bensmaia, S., & Washburn, S. (2001).
Vibrotactile adaptation impairs discrimination of fine,
but not coarse, textures. Somatosensory and Motor
Research, 18, 253–262.
Sensation and Perception482
Holt, L. L. (2005). Temporally non-adjacent non-linguistic
sounds affect speech categorization. Psychological
Science, 16, 305–312.
Holt, L. L., & Lotto, A. J. (2010). Speech perception as
categorization. Attention, Perception, & Psychophysics,
72, 1218–1227.
Holway, A. H., & Boring, E. G. (1941). Determinants of
apparent visual size with distance variant. American
Journal of Psychology, 54, 21–37.
Horridge, A. (2012). Visual discrimination by the honeybee
(Apis mellijera). In O. F. Lazareva, T. Shimizu, &
E. A. Wasserman (Eds.), How animals see the world:
Comparative behavior, biology, and evolution of vision
(pp. 165–190). New York, NY: Oxford University Press.
Horswill, M., Helman, S., Ardiles, P., & Wann, J. P. (2005).
Motorcycle accident risk could be inflated by a time
to arrival illusion. Optometry and Vision Science, 82,
740–746.
Howard, I. P., & Rogers, B. J. (2002). Seeing in depth: Vol. 2.
Depth perception. Toronto, Canada: Porteus.
Howard, J. D., Plailly, J., Grueschow, M., Haynes, J. D.,
& Gottfried, J. A. (2009). Odor quality coding and
categorization in human posterior piriform cortex.
Nature Neuroscience, 12, 932–938.
Hsiao, S. (2008). Central mechanisms of tactile shape
perception. Current Opinion in Neurobiology, 18, 418–424.
Hua, L. H., Strigo, I. A., Baxter, L. C., Johnson, S. C.,
& Craig, A. D. (2005). Anteroposterior somatotopy
of innocuous cooling activation focus in human
dorsal posterior insular cortex. American Journal of
Physiology: Regulatory, Integrative, and Comparative
Physiology, 289, R319–R325.
Huang, Q., & Tang, J. (2010). Age-related hearing loss
or presbycusis. European Archives of Oto-Rhino-
Laryngology, 267(8), 1179–1191.
Hubbard, E. M., Brang, D., & Ramachandran, V. S.
(2011). The cross-activation theory at 10. Journal of
Neuropsychology, 5, 155–177.
Hubel, D. H., & Wiesel, T. N. (1959). Receptive fields of
single neurons in the cat’s striate cortex. Journal of
Physiology, 148, 574–591.
Hubel, D. H., & Wiesel, T. N. (1962). Receptive fields,
binocular interaction and functional architecture in the
cat’s visual cortex. Journal of Physiology, 160, 106–154.
Hubel, D. H., & Wiesel, T. N. (1965). Receptive fields and
functional architecture in two nonstriate visual areas
(18 and 19) of the cat. Journal of Neurophysiology, 28,
229–289.
Hubel, D. H., & Wiesel, T. N. (1979). Brain mechanisms and
vision. Scientific American, 241, 150–162.
Hubel, D. H., & Wiesel, T. N. (2005). Brain and visual
perception: The story of a 25-year collaboration. New
York, NY: Oxford University Press.
Hughes, H. C. (1999). Sensory exotica: A world beyond
experience. Cambridge, MA: MIT Press.
Hughes, H. C., & Zimba, L. D. (1985). Spatial maps of directed
visual attention. Journal of Experimental Psychology:
Human Perception and Performance, 11, 409–430.
Humayun, M. S., Dorn, J. D., da Cruz, L., Dagnelie, G.,
Sahel, J. A., Stanga, P. E., . . . Greenberg, R. J. Argus
II Study Group. (2012). Interim results from the
international trial of Second Sight’s visual prosthesis.
Ophthalmology, 119, 779–788.
Hurvich, L. M., & Jameson, D. (1957). An opponent-process
theory of color vision. Psychological Review, 64,
384–404.
Hutchinson, W. D., Davis, K. D., Lozano, A. M., Tasker, R. R.,
& Dostrovsky, J. O. (1999). Pain-related neurons in the
human cingulate cortex. Nature Neuroscience, 2, 403–405.
Huttenlocher, P. R., & de Courten, C. (1987). The
development of synapses in striate cortex of man.
Human Neurobiology, 6, 1–9.
Hyde, K., Peretz, I., & Zatorre, R. (2008). Evidence for the
role of the right auditory cortex in fine pitch resolution.
Neuropsychologia, 46, 632–639.
Irons, J., & Remington, R. (2013). Can attentional
control settings be maintained for two color-location
conjunctions? Evidence from an RSVP task. Attention,
Perception, & Psychophysics, 75, 862–875.
Isaacs, L. D. (1981). Relationship between depth perception
and basketball-shooting performance over a competitive
season. Perceptual and Motor Skills, 53, 554.
Jacquin-Cortois, S., O’Shea, J., Luaté, J., Pisella, L.,
Revol, P., . . . Rossetti, Y. (2013). Rehabilitation of spatial
neglect by prism adaptation: A peculiar expansion
of sensorimotor after-effects to spatial cognition.
Neuroscience and Biobehavioral Reviews, 37, 594–609.
James, W. (1890). The principles of psychology. New York,
NY: Holt.
Jameson, K. A., Highnote, S., & Wasserman, L. (2001).
Richer color experience in observers with multiple
photopigment opsin genes. Psychonomic Bulletin &
Review, 8, 244–261.
Janata, P., Birk, J. L., Van Horn, J. D., Leman, M., Tillmann,
B., & Bharucha, J. J. (2002). The cortical topography of
tonal structures underlying Western music. Science,
298, 2167–2170.
Johansson, G. (1973). Visual perception of biological
motion and a model for its analysis. Perception and
Psychophysics, 14, 195–204.
Johnson, E. N., Hawken, M. J., & Shapley, R. (2001). The
spatial transformation of color in the primary visual
cortex of the macaque monkey. Nature Neuroscience,
4, 409–413.
Johnsrude, I. S., Mackey, A., Hakyemez, H., Alexander,
E., Trang, H. P., & Carylon, R. P. (2013). Swinging at a
References 483
cocktail party: Voice familiarity aids speech perception
in the presence of a competing voice. Psychological
Science, 24, 1995–2004.
Jones, F. N. (1956). A forced-choice method of limits.
American Journal of Psychology, 69, 672–673.
Jönsson, F. U., & Olsson, M. J. (2012). Knowing what we
smell. In G. M. Zucco, R. S. Herz, & B. Schaal (Eds.),
Olfactory cognition: From perception and memory to
environmental odours and neuroscience (pp. 115–136).
Amsterdam, The Netherlands: John Benjamins.
Jönsson, F. U., & Stevenson, R. J. (2014). Odor knowledge,
odor naming and the “tip of the nose” experience.
In B. L. Schwartz & A. S. Brown (Eds.), Tip-of-the-
tongue states and related phenomena (pp. 305–326).
Cambridge, UK: Cambridge University Press.
Jordan, G., Deeb, S. S., Bosten, J. M., & Mollon, J. D.
(2010). The dimensionality of color vision in carriers of
anomalous trichromacy. Journal of Vision, 10, 1–19.
Juang, B. H., & Rabiner, L. R. (2005). Automatic speech
recognition: A brief history of the technology
development. Georgia Institute of Technology. Atlanta
Rutgers University and the University of California.
Santa Barbara, 1, 67.
Julesz, B. (1971). Foundations of cyclopean perception.
Chicago, IL: University of Chicago Press.
Kaas, A., Weigelt, S., Roebroeck, A., Kohler, A., & Muckli, L.
(2010). Imagery of a moving object: The role of occipital
cortex and human MT/V5+. Neuroimage, 49, 794–804.
Kadohisa, M., & Wilson, D. A. (2006). Separate encoding
of identity and similarity of complex familiar odors in
piriform cortex. Proceedings of the National Academy
of Sciences of the United States of America, 103,
15206–15211.
Kallus, K. W., Tropper, K., & Boucsein, W. (2011). The
importance of motion cues in spatial disorientation
training for VFR-pilots. International Journal of Aviation
Psychology, 21, 135–152.
Kandil, F. I., Rotter, A., & Lappe, M. (2010). Car drivers
attend to different gaze targets when negotiating closed
vs. open bends. Journal of Vision, 10, 1–11.
Kanizsa, G. (1979). Organization in vision: Essays on gestalt
perception. New York, NY: Praeger.
Kanwisher, N., & Dilks, D. (2013). The functional
organization of the ventral visual pathway in humans.
In L. Chalupa & J. Werner (Eds.), The new visual
neurosciences (pp. 733–748). Cambridge, MA: MIT
Press.
Kanwisher, N., McDermott, J., & Chun, M. M. (1997). The
fusiform face area: A module in human extrastriate
cortex specialized for face perception. Journal of
Neuroscience, 17, 4302–4311.
Kanwisher, N., & Yovel, G. (2006). The fusiform face area:
A cortical region specialized for the perception of faces.
Philosophical Transactions of the Royal Society of
London, Series B: Biological Sciences, 361, 2109–2128.
Kapoula, Z., Bernotas, M., & Haslwanter, T. (1999). Listing’s
plane rotation with convergence: Role of disparity,
accommodation, and depth perception. Experimental
Brain Research, 126(2), 175–186.
Kau, S., Strumpf, H., Merkel, C., Stoppel, C. M., Heinze,
H. J., Hopf, J. M., & Schoenfeld, M. A. (2013). Distinct
neural correlates of attending speed vs. coherence of
motion. Neuroimage, 64, 299–307.
Kawahara, J. I., & Sato, H. (2013). The effect of fatigue
on the attentional blink. Attention, Perception, &
Psychophysics, 75, 1096–1102.
Keane, A. G. (2011, December 8). U.S. highway deaths
decline for a fifth year, longest streak since 1899.
Bloomberg News. Retrieved from https://www
.bloomberg.com/news/articles/2011-12-08/u-s-highway-
deaths-decline-2-9-falling-for-fifth-year-1-
Kirchhof, H. (1950). A method for the objective
measurement of accommodation speed of the human
eye. American Journal of Optometry, 27, 163–178.
Kitaoka, A. (2005). Trick eyes graphics. Tokyo, Japan: Kanzen.
Klatzky, R. L., Loomis, J. M., Lederman, S. J., Wake, H., &
Fujita, N. (1993). Haptic identification of objects and
their depictions. Perception and Psychophysics, 54,
170–178.
Klüver, H., & Bucy, P. C. (1939). Preliminary analysis of
function of the temporal lobes in monkeys. Archives of
Neurology and Psychiatry, 42, 979–1000.
Kochkin, S. (2005). MarkeTrak VII: Customer satisfaction
with hearing instruments in the digital age. Hearing
Journal, 58, 30–44.
Kooijman, C. M., Dijkstra, P. U., Geertzen, J. H. B., Elzinga,
A., & van der Schans, C. P. (2000). Phantom pain and
phantom sensations in upper limb amputees: An
epidemiological study. Pain, 87, 33–41.
Krantz, J. H., Silverstein, L. D., & Yeh, Y.-Y. (1992). Visibility
of transmissive liquid crystal displays under dynamic
lighting conditions. Human Factors, 34, 615–632.
Krings, T., Töpper, R., Foltys, H., Erberich, S., Sparing,
R., Willmes, K., & Thron, A. (2000). Cortical activation
patterns during complex motor tasks in piano
players and control subjects: A functional magnetic
resonance imaging study. Neuroscience Letters, 278,
189–193.
Kristjánsson, A. (2013). The case for causal influences
of action videogame play upon vision and attention.
Attention, Perception, & Psychophysics, 75, 667–672.
Kuffler, S. W. (1953). Discharge patterns and functional
organization of mammalian retina. Journal of
Neurophysiology, 16, 37–68.
LaMotte, R. H., Shimada, S. G., Green, B. G., & Zelterman,
D. (2009). Pruritic and nociceptive sensations and
Sensation and Perception484
dysesthesias from a spicule of cowhage. Journal of
Neurophysiology, 101, 1430–1443.
Land, E. H. (1977). The retinex theory of color vision.
Scientific American, 237, 108–128.
Landis, B. N., Croy, I., & Haehner, A. (2012). Long lasting
phantosmia treated with venlafaxine. Neurocase, 18,
112–114.
Landry, S. P., Shiller, D. M., & Champoux, F. (2013). Short-
term visual deprivation improves the perception of
harmonicity. Journal of Experimental Psychology:
Human Perception and Performance, 39, 1503–1507.
Langenheim, J. (2010, September 17). The last of the sea
nomads. The Guardian. Retrieved from http://www
.theguardian.com/environment/2010/sep/18/last-sea-
nomads
Larsen, A., Madsen, K. H., Lund, T. E., & Bundesen, C. (2006).
Images of illusory motion in primary visual cortex.
Journal of Cognitive Neuroscience, 18, 1174–1180.
Lawless, H. T. (1991). A sequential contrast effect in odor
perception. Bulletin of the Psychonomic Society, 29,
317–319.
Lederman, S. J., & Klatzky, R. L. (2009). Haptic perception:
A tutorial. Attention, Perception, & Psychophysics, 71,
1439–1459.
Leek, M. R., & Molis, M. R. (2009). Beyond audibility:
Hearing loss and the perception of speech. ASHA
Leader, 14, 14–17.
Lettvin, J. Y., Maturana, H. R., McCulloch, W. S., & Pitts,
W. H. (1968). What the frog’s eye tells the frog’s brain.
In W. C. Corning & M. Baladan (Eds.), The mind:
Biological approaches to its functions (pp. 233–258).
New York, NY: Interscience.
Li, W., Lopez, L., Osher, J., & Howard, J. D. (2010). Right
orbitofrontal cortex mediates conscious olfactory
perception. Psychological Science, 21, 1454–1463.
Liang, M., Mouraux, A., Hu, L., & Iannetti, G. D. (2013).
Primary sensory cortices contain distinguishable
spatial patterns of activity for each sense. Nature
Communications, 4, 1979.
Liberman, A. M., & Mattingly, I. G. (1985). The motor theory
of speech perception. Cognition, 21, 1–36.
Limb, C. J., & Roy, A. T. (2014). Technological, biological, and
acoustical constraints to music perception in cochlear
implant users. Hearing Research, 308, 13–26.
Liu, J., Harris, A., & Kanwisher, N. (2010). Perception of face
parts and face configurations: An fMRI study. Journal of
Cognitive Neuroscience, 22, 203–211.
Livadas, C., Lygeros, J., & Lynch, N. A. (2000). High-
level modeling and analysis of the traffic alert and
collision avoidance system (TCAS). Proceedings of the
IEEE, 88(7), 926–948.
Livingstone, M. (2002). Vision and art: The biology of
seeing. New York, NY: Abrams.
Livingstone, M. S., & Hubel, D. H. (1984). Anatomy and
physiology of a color system in the primate visual
cortex. Journal of Neuroscience, 4, 309–356.
Lokki, T., & Patynen, J. (2015). The acoustics of a concert hall
as a linear problem. Europhysics News, 46, 15–18.
Looser, C. E., & Wheatley, T. (2010). The tipping point of
animacy: How, when, and where we perceive life in a
face. Psychological Science, 21, 1854–1862.
Loui, P., Zamm, A., & Schlaug, G. (2012). Absolute pitch
and synesthesia: Two sides of the same coin?
Shared and distinct neural substrates of music
listening. Paper presented at the 12th International
Conference for Music Perception and Cognition,
Thessaloniki, Greece.
Lowenfield, B., & Abel, G. L. (1977). Methods of teaching
Braille reading efficiency of children in lower senior
classes. Birmingham, UK: Research Centre for the
Education of the Visually Handicapped.
Mack, A., & Rock, I. (1998). Inattentional blindness.
Cambridge, MA: MIT Press.
MacMahon, M. K. C. (1996). Phonetic notation. In P. T.
Daniels & W. Bright (Eds.), The world’s writing systems
(pp. 821–846). New York, NY: Oxford University Press.
Maertens, M., & Pollmann, S. (2005). fMRI reveals a
common neural substrate of illusory and real contours
in V1 after perceptual learning. Journal of Cognitive
Neuroscience, 17, 1553–1564.
Malnic, B., Godfrey, P. A., & Buck, L. B. (2004). The human
olfactory receptor gene family. Proceedings of the
National Academy of Sciences of the United States of
America, 101, 2584–2589.
Marchi, F., & Newen, A. (2015). Cognitive penetrability
and emotion recognition in human facial expressions.
Frontiers in Psychology, 6, 828. doi:10.3389/
fpsyg.2015.00828
Marr, D. (1982). Vision. San Francisco, CA: W. H. Freeman.
Masland, R. H. (2012). The tasks of amacrine cells. Visual
Neuroscience, 29, 3–9.
Mason, C., & Kandel, E. R. (1991). Central visual pathways.
In E. R. Kandel, J. H. Schwartz, & T. M. Jessel (Eds.),
Principles of neural science (3rd ed., pp. 420–439).
Norwalk, CT: Appleton & Lange.
Mattys, S. L., Barden, K., & Samuel, A. G. (2014). Extrinsic
cognitive load impairs low-level speech perception.
Psychonomic Bulletin & Review, 21, 748–754.
Maurer, D., & Werker, J. F. (2014). Perceptual narrowing
during infancy: A comparison of language and faces.
Developmental Psychobiology, 56, 154–178.
May, P. J. (2006). The mammalian superior colliculus:
Laminar structure and connections. Progress in Brain
Research, 151, 321–378.
Mayer, D. L., & Dobson, V. (1982). Visual acuity
development in infants and young children, as assessed
References 485
by operant preferential looking. Vision Research, 22(9),
1141–1151.
Mazyn, L. I. N., Lenoir, M., Montagne, G., & Savelsbergh,
G. J. (2004). The contribution of stereo vision to one-
handed catching. Experimental Brain Research, 157,
383–390.
McCarley, J. S., Kramer, A. F., Wickens, C. D., Vidoni,
E. D., & Boot, W. R. (2004). Visual skills in airport-
security screening. Psychological Science, 15, 302–306.
McGurk, H., & MacDonald, T. (1976). Hearing lips and seeing
voices. Nature, 264, 746–748.
McKeegan, N. (2013, February 18). Argus II becomes first
“bionic eye” to gain approval for sale in the U.S. New
Atlas. Retrieved from http://newatlas.com/argus-ii-
becomes-first-bionic-eye-to-gain-approval-for-sale-in-
us/26295
Melzack, R., & Wall, P. D. (1988). The challenge of pain (2nd
ed.). New York, NY: Penguin.
Menashe, I., Man, O., Lancet, D., & Gilad, Y. (2003). Different
noses for different people. Nature Genetics, 34, 143–144.
Mendez, M. F., & Cherrier, M. M. (2003). Agnosia for scenes
in topographagnosia. Neuropsychologia, 41, 1387–1395.
Meng, M., Remus, D. R., & Tong, F. (2005). Filling-in
of visual phantoms in the human brain. Nature
Neuroscience, 8, 1248–1254.
Menneer, T., Stroud, M., Cave, K. R., Donnelly, N., & Rayner,
K. (2008). Eye movements in search for multiple targets.
In K. Rayner, D. Shen, X. Bai, & G. Yan (Eds.), Cognitive
and cultural influences on eye movements (pp. 197–
208). London, UK: Psychology Press.
Meyer, R. (2009). Acoustics and the performance of music.
New York, NY: Springer.
Meyer, R., Palmer, C., & Mazo, M. (1998). Affective and
coherence responses to Russian laments. Music
Perception, 16, 135–150.
Mignault-Goulet, G., Moreau, P., Robitaille, N., & Peretz,
I. (2012). Congenital amusia persists in the developing
brain after daily music listening. PLoS ONE, 7, e36860.
Miller, L. R., & Miller, F. G. (2015). Understanding placebo
effects: Implications for nursing practice. Nursing
Outlook, 63(5), 601–606. doi:10.1016/j
.outlook.2015.03.002
Misaka, T. (2013). Molecular mechanisms of the action of
miraculin, a taste-modifying protein. Seminars in Cell &
Developmental Biology, 24, 222–225.
Mishkin, M., Ungerleider, L. G., & Macko, K. A. (1983).
Object vision and spatial vision: Two cortical pathways.
Trends in Neurosciences, 6, 414–417.
Møller, J. (2006). Hearing: Anatomy, physiology, and
disorders of the auditory system (2nd ed.). Amsterdam,
The Netherlands: Elsevier.
Mollon, J. (1992). Worlds of difference. Nature, 356,
378–379.
Monnier, P. (2008). Standard definitions of chromatic
induction fail to describe induction with S-cone patterned
backgrounds. Vision Research, 48, 2708–2714.
Moore, B. C. J. (2012). Effects of bandwidth,
compression speed, and gain at high frequencies
on preferences for amplified music. Trends in
Amplification, 16, 159–172.
Moran, J., & Desimone, R. (1985). Selective attention gates
visual processing in extrastriate cortex. Science, 229,
782–784.
Moreau, P., Jolicoeur, P., & Peretz, I. (2013). Pitch
discrimination without awareness in congenital amusia:
Evidence from event-related potentials. Brain and
Cognition, 81, 337–344.
Morgan, M. J., Adam, A., & Mollon, J. D. (1992). Dichromats
detect colour-camouflaged objects that are not detected
by trichromats. Proceedings of the Royal Society of
London, Series B: Biological Sciences, 248(1323),
291–295.
Moscovitch, M., & Moscovitch, D. (2000). Super face-
inversion effects for isolated internal or external
features, and for fractured faces. Cognitive
Neuropsychology, 17, 201–219.
Mountcastle, V. B. (2005). The sensory hand: Neural
mechanisms of somatic sensation. Cambridge, MA:
Harvard University Press.
Murphy, G., & Kovach, J. K. (1972). Historical introduction
to modern psychology (3rd ed.). New York, NY: Harcourt
Brace.
Nagata, T., Koyanagi, M., Tsukamoto, H., Saeki, S., Isono, K.,
Shichida, Y., . . . Terakita, A. (2012). Depth perception from
image defocus in a jumping spider. Science, 335, 469–471.
Nagayama, S., Takahashi, Y. K., Yoshihara, Y., & Mori, K.
(2004). Mitral and tufted cells differ in the decoding
manner of odor maps in the rat olfactory bulb. Journal of
Neurophysiology, 91, 2532–2540.
Nassi, J. J., & Callaway, E. M. (2009). Parallel processing
strategies of the primate visual system. Nature Reviews
Neuroscience, 10, 360–372.
Nathans, J., Piantanida, T., Eddy, R., Shows, T., & Hogness,
D. (1986). Molecular genetics of inherited variation in
human color vision. Science, 232, 203–210.
National Institute on Deafness and Other Communication
Disorders. (2016). Cochlear implants (NIH Publication
No. 11-4798). Bethesda, MD: Author.
National Institutes of Health. (n.d.). Hearing loss: A
common problem for older adults. Retrieved from http://
nihseniorhealth.gov/hearingloss/hearinglossdefined/01
.html
Neisser, U. (1979). The control of information pickup in
selective looking. In A. D. Pick (Ed.), Perception and its
development: A tribute to Eleanor Gibson (pp. 201–219).
Hillsdale, NJ: Erlbaum.
Sensation and Perception486
Neitz, J., & Jacobs, G. (1986). Polymorphism of the long-
wavelength cone in normal human colour vision.
Nature, 323, 623–625.
Neitz, J., & Jacobs, G. (1990). Polymorphism in normal
human color vision and its mechanism. Vision Research,
30, 620–636.
Neumeyer, C., & Arnold, K. (1989). Tetrachromatic color
vision in the goldfish becomes trichromatic under white
adaptation light of moderate intensity. Vision Research,
29(12), 1719–1727.
Newsome, W. T., Britten, K. H., & Movshon, J. A. (1989).
Neuronal correlates of a perceptual decision. Nature,
341, 52–54.
Newsome, W. T., & Paré, E. B. (1988). A selective
impairment of motion perception following lesions
of the middle temporal visual area (MT). Journal of
Neuroscience, 8, 2201–2211.
Newsome, W. T., Shadlen, M. N., Zohary, E., Britten, K. H.,
& Movshon, J. A. (1995). Visual motion: Linking
neuronal activity to psychophysical performance. In
M. S. Gazzaniga (Ed.), The cognitive neurosciences
(pp. 401–414). Cambridge, MA: MIT Press.
Nilsson, D.-E. (1989). Vision, optics, and evolution.
Bioscience, 39(5), 298–307.
Nodine, C. F., Krupinski, E. A., & Kundel, H. L. (1993).
Visual processing and decision making in search and
recognition of targets embedded in pictorial scenes.
In D. Brogan & A. G. Gale (Eds.), Visual search (pp.
239–249). Philadelphia, PA: Taylor & Francis.
Nooij, S. A. E., & Groen, E. L. (2011). Rolling into spatial
disorientation: Simulator demonstration of the
post-roll (Gillingham) illusion. Aviation, Space, and
Environmental Medicine, 82, 505–512.
Olausson, H., Wessberg, J., Morrison, I., McGlone, F., &
Valbo, A. (2010). The neurophysiology of unmyelinated
tactile afferents. Neuroscience and Behavioral Reviews,
34, 185–191.
Oltman, M. (2009). Migraines, perfume, and the Americans
with Disabilities Act. Retrieved from http://www
.healthcentral.com/migraine/c/11175/67623/disabilities-act
Opriş, D., Pintea, S., García-Palacios, A., Botella, C.,
Szamosközi, Ş., & David, D. (2012). Virtual reality
exposure therapy in anxiety disorders: A quantitative
meta-analysis. Depression and Anxiety, 29(2), 85–93.
Orban, G. A., Kennedy, H., & Butler, J. (1986). Velocity
sensitivity and direction sensitivity of neurons in areas
V1 and V2 of monkeys: Influence of eccentricity. Journal
of Neurophysiology, 56, 462–480.
Otero-Millan, J., Macknik, S. L., & Martinez-Conde, S.
(2012). Microsaccades and blinks trigger illusory
rotation in the “rotating snakes” illusion. Journal of
Neuroscience, 32, 6043–6051.
Overy, K., Peretz, I., Zatorre, R., Lopez, L., & Majno, M.
(Eds.). (2012, April). The neurosciences and music IV:
Learning and memory [Special issue]. Annals of the
New York Academy of Sciences, 1252.
Parker, A. J. (2007). Binocular depth perception and the
cerebral cortex. Nature Reviews Neuroscience, 8, 379–391.
Parkinson, C., Walker, T., Memmi, S., & Wheatley T. (2017).
Emotions are understood from biological motion across
remote cultures. Emotion, 16, 459–477.
Partanen, E., Kujalaa, T., Näätänen, R., Litola, A., Sambeth,
A., & Huotilainen, M. (2013). Learning-induced neural
plasticity of speech processing before birth. Proceedings
of the National Academy of Sciences of the United
States of America, 110, 15145–15150.
Pasley, B., David, S. V., Mesgarani, N., Flinker, A.,
Shamma, S. A., Crone, N. E., . . . Chang, E. F. (2012).
Reconstructing speech from human auditory cortex.
PLoS Biology, 10, 1–13.
Pasternak, T., Bisley, J. W., & Calkins, D. (2003). Visual
processing in the primate brain. In M. Gallagher &
R. J. Nelson (Eds.), Handbook of psychology: Biological
psychology (Vol. 3, pp. 139–185). Hoboken, NJ: Wiley &
Sons.
Pasupathy, A., & Connor, C. E. (2002). Population coding of
shape in V4. Nature Neuroscience, 5, 1332–1338.
Patel, A. D. (2008). Music, language, and the brain. New
York, NY: Oxford University Press.
Patel, A. D. (2013). Sharing and nonsharing of brain
resources for language and music. In M. Arbib
(Ed.), Language, music, and the brain (pp. 329–355).
Cambridge, MA: MIT Press.
Patynen, J., & Lokki, T. (2016). Perception of music
dynamics in concert hall acoustics. Journal of the
Acoustical Society of America, 140, 3787–3798.
Pavani, F., Spence, C., & Driver, J. (2000). Visual capture of
touch: Out-of-the-body experiences with rubber gloves.
Psychological Science, 11(5), 353–359.
Pegna, A. J., Khateb, A., Lazeyras, F., & Seghier, M. (2005).
Discriminating emotional faces without the primary
visual cortices involves the right amygdala. Nature
Neuroscience, 8, 24–25.
Pei, Y. C., Hsiao, S. S., Craig, J. C., & Bensmaia, S. J. (2011).
Neural mechanisms of tactile motion integration in
somatosensory cortex. Neuron, 69, 536–547.
Penfield, W., & Rasmussen, T. (1950). The cerebral cortex of
man: A clinical study of localization and function. New
York, NY: Macmillan.
Peretz, I. (2008). Musical disorders: From behavior to
genes. Current Directions in Psychological Science, 17,
329–333.
Peretz, I. (2013). The biological foundations of music:
Insights from congenital amusia. In D. Deutsch (Ed.),
References 487
The psychology of music (pp. 551–564). New York, NY:
Elsevier.
Peretz, I., & Hyde, K. L. (2003). What is specific to music
processing? Insights from congenital amusia. Trends in
Cognitive Sciences, 7, 362–367.
Perlman, M., & Krumhansl, C. L. (1996). An experimental
study of internal interval standards in Javanese and
Western musicians. Music Perception, 14, 95–116.
Perry, B. N., Mercier, C., Pettifer, S. R., Cole, J., & Tsao, J. W.
(2014). Virtual reality therapies for phantom limb pain.
European Journal of Pain, 18(7), 897–899.
Peterson, M. A., & Salvagio, E. (2008). Inhibitory
competition in figure-ground perception: Context and
convexity. Journal of Vision, 8, 1–13.
Petry, S., & Meyer, G. E. (1987). The perception of illusory
contours. New York, NY: Springer.
Pettigrew, J. D. (1999). Electroreception in monotremes.
Journal of Experimental Biology, 202, 1447–1454.
Pinckers, A. J. L. G. (1980). Color vision and age.
Ophthalmologica, 181(1), 23–30.
Pinker, S. (1994). The language instinct. New York, NY:
William Morrow.
Plantinga, J., & Trainor, L. J. (2005). Memory for melody:
Infants use a relative pitch code. Cognition, 98, 1–11.
Posner, M. I. (1980). Orienting of attention. Quarterly
Journal of Experimental Psychology, 32, 3–25.
Posner, M. I., & Rothbart, M. K. (2013). Development of
attention networks. In B. R. Kar (Ed.), Cognition and
brain development: Converging evidence from various
methodologies (pp. 61–83). Washington, DC: American
Psychological Association.
Proctor, R. W., & Van Zandt, T. (2008). Human factors in
simple and complex systems (2nd ed.). Boca Raton, FL:
CRC Press.
Ptito, A., & Leh, S. E. (2007). Neural substrates of blindsight
after hemispherectomy. Neuroscientist, 13, 506–518.
Quiroga, R. Q., Reddy, L., Kreiman, G., Koch, C., & Fried, I.
(2005). Invariant visual representation by single neurons
in the human brain. Nature, 435, 1102–1107.
Quiroga, R. Q., Reddy, L., Kreiman, G., Koch, C., & Fried, I.
(2008). Sparse but not “grandmother-cell” coding in the
medial temporal lobe. Trends in Cognitive Sciences, 12,
87–91.
Quiroga, R. Q., Snyder, L. H., Batista, A. P., Cui, H., &
Andersen, R. A. (2006). Movement intention is better
predicted than attention in the posterior parietal cortex.
Journal of Neuroscience, 26, 3615–3620.
Radtke, N. D., Aramant, R. B., Petry, H. M., Green, P. T.,
Pidwell, D. J., & Seiler, M. J. (2008). Vision improvement
in retinal degeneration patients by implantation
of retina together with retinal pigment epithelium.
American Journal of Ophthalmology, 146, 177–182.
Rainville, P., Duncan, G. H., Price, D. D., Carrier, B., &
Bushnell, M. C. (1997). Pain affect encoded in human
anterior cingulate, but not somatosensory cortex.
Science, 277, 968–971.
Ramachandran, V. S. (1992). Filling in the blind spot.
Nature, 356, 115.
Ramachandran, V. S., & Hirstein, W. (1998). The perception
of phantom limbs: The D. O. Hebb lecture. Brain, 121,
1603–1630.
Rauschecker, J. P., & Scott, S. K. (2009). Maps and streams
in the auditory cortex: Nonhuman primates illuminate
human speech processing. Nature Neurosciences, 12,
718–724.
Raymond, J. E., Shapiro, K. L., & Arnell, K. M. (1992).
Temporary suppression of visual processing in an RSVP
task: An attentional blink? Journal of Experimental
Psychology: Human Perception and Performance, 18(3),
849–860.
Read, J. C. A. (2005). Early computational processing in
binocular vision and depth perception. Progress in
Biophysics and Molecular Biology, 87, 77–108.
Reed, C. L., Caselli, R. J., & Farah, M. J. (1996). Tactile
agnosia: Underlying impairment and implications for
normal tactile object recognition. Brain, 119, 875–888.
Reichardt, W. (1969). Movement perception in insects. In W.
Reichardt (Ed.), Processing of optical data by organisms
and by machines. New York, NY: Academic Press.
Rensink, R. A., O’Regan, J. K., & Clark, J. (1997). To see or
not to see: The need for attention to perceive changes in
scenes. Psychological Science, 8, 368–373.
Richards, J. E., Reynolds, G. D., & Courage, M. L. (2010).
The neural bases of infant attention. Current Directions
in Psychological Science, 19, 41–46.
Robinson, A. K., Laning, J., Reinhard, J., & Mattingley,
J. B. (2016). Odours reduce the magnitude of object
substitution masking for matching visual targets in
females. Attention, Perception, & Psychophysics, 78,
1702–1711.
Rodieck, R. W. (1998). The first steps in seeing. Sunderland,
MA: Sinauer.
Rodrigues, J. F., da Silva Andrade, R., Bastos, S. C., Coelho,
S. B., & Pinheiro, A. C. M. (2016). Miracle fruit: An
alternative sugar substitute in sour beverages. Appetite,
107, 645–653.
Rolls, E. T. (2006). Brain mechanisms underlying flavour and
appetite. Philosophical Transactions of the Royal Society
of London, Series B: Biological Sciences, 361, 1123–1136.
Rolls, E. T., & Tovee, M. J. (1995). Sparseness of the neuronal
representation of stimuli in the primate temporal visual
cortex. Journal of Neurophysiology, 73, 713–726.
Rosch, E. H. (1973). Natural categories. Cognitive
Psychology, 4, 328–350.
Sensation and Perception488
Rossi, E. A., & Roorda, A. (2010). The relationship between
visual resolution and cone spacing in the human fovea.
Nature Neuroscience, 13(2), 156.
Rothbaum, B. O., Hodges, L., Alarcon, R., Ready, D.,
Shahar, F., Graap, K., . . . Baltzell, D. (1999). Virtual reality
exposure therapy for PTSD Vietnam veterans: A case
study. Journal of Traumatic Stress, 12(2), 263–271.
Royster, J. D., Royster, L. H., & Killion, M. C. (1991). Sound
exposures and hearing thresholds of symphony
orchestra musicians. Journal of the Acoustical Society
of America, 89, 2793–2803.
Ruggeri, M., Major, J. C., Jr., McKeown, C., Knighton, R.
W., Puliafito, C. A., & Jiao, S. (2010). Retinal structure of
birds of prey revealed by ultra-high resolution spectral-
domain optical coherence tomography. Investigative
Ophthalmology & Visual Science, 51, 5789–5795.
Rupp, M. A., McConnell, D. S., & Smither, J. A. (2016).
Examining the relationship between action video game
experience and performance in a distracted driving task.
Current Psychology, 35(4), 527–539.
Rushton, W. A. (1965). Visual adaptation. Proceedings of the
Royal Society of London, Series B: Biological Sciences,
162, 20–46.
Rutstein, R. P., & Daum, K. M. (1998). Anomalies of
binocular vision: Diagnosis & management. St. Louis,
MO: Mosby.
Sabine, W. C. (1922). Collected papers on acoustics.
Cambridge, MA: Harvard University Press.
Sacks, O. (1985). The man who mistook his wife for a hat
and other clinical tales. New York, NY: HarperPerennial.
Sacks, O. (1998). The island of the colorblind. New York, NY:
Vintage Books.
Sacks, O. (2007). Musicophilia: Tales of music and the brain.
New York, NY: Knopf.
Sakurai, K., Kurita, T., Takeda, Y., Shiraishi, H., & Kusumi,
I. (2013). Akinetopsia as epileptic seizure. Epilepsy &
Behavior Case Reports, 1, 74–76.
Salomão, S. R., Ejzenbaum, F., Berezovsky, A., Sacai, P. Y., &
Pereira, J. M. (2008). Age norms for monocular grating
acuity measured by sweep-VEP in the first three years
of age. Arquivos Brasileiros de Oftalmologia, 71(4),
475–479.
Salvi, S. M., Akhtar, S., & Currie, Z. (2006). Ageing changes
in the eye. Postgraduate Medical Journal, 82(971),
581–587.
Sandberg, K., Bahrami, B., Kanai, R., Barnes, G. R.,
Overgaard, M., & Rees, G. (2013). Early visual responses
predict conscious face perception within and between
subjects during binocular rivalry. Journal of Cognitive
Neuroscience, 25, 969–985.
Schachar, R. A. (2006). The mechanism of accommodation
and presbyopia. International Ophthalmology Clinics,
46, 39–61.
Schacter, D. L. (2001). Forgotten ideas, neglected pioneers:
Richard Semon and the story of memory. Philadelphia,
PA: Psychology Press.
Schädler, M. R., Warzybok, A., Hochmuth, S., & Kollmeier,
B. (2015). Matrix sentence intelligibility prediction
using an automatic speech recognition system.
International Journal of Audiology, 54(Suppl. 2),
100–107.
Schenk, T., Ellison, A., Rice, N., & Milner, A. D. (2005). The
role of V5/MT+ in the control of catching movements: An
rTMS study. Neuropsychologia, 43, 189–198.
Schenk, T., Mai, N., Ditterich, J., & Zihl, J. (2000). Can
a motion-blind patient reach for moving objects?
European Journal of Neuroscience, 12, 3351–3360.
Schiells, R. A., & Falk, G. (1987). Joro spider venom:
Glutamate agonist and antagonist on the rod retina of
the dogfish. Neuroscience Letters, 77, 221–225.
Schink, T., Kreutz, G., Busch, V., Pigeot, I., & Ahrens,
W. (2014). Incidence and relative risk of hearing
disorders in professional musicians. Occupational and
Environmental Medicine, 71(7), 472–476.
Schmidt, J. H. (2011). Sound exposure of symphony
orchestra musicians. Annals of Occupational Hygiene,
55(8), 893–905.
Schoenlein, R. W., Peteanu, L. A., Mathies, R. A., &
Shank, C. V. (1991). The first step in vision:
Femtosecond isomerization of rhodopsin. Science, 254,
412–415.
Schultz, D. P., & Schultz, S. E. (1992). A history of modern
psychology (5th ed.). New York, NY: Harcourt Brace.
Schwartz, B. L. (2017). Memory: Foundations and
applications (3rd ed.). Thousand Oaks, CA: Sage.
Schwartz, D. A., & Purves, D. (2004). Pitch is determined by
naturally occurring periodic sounds. Hearing Research,
194, 31–46.
Schweizer, T., Kan, K., Hung, Y., Tam, F., Naglie, G., &
Graham, S. (2013). Brain activity during driving with
distraction: An immersive fMRI study. Frontiers in
Human Neuroscience, 7(53), 1–11.
Scott, M. A., van der Kamp, J., Savelsbergh, G. J.,
Oudejans, R.R.D., & Davids, K. (2004). Object rotation
effects on the timing of a hitting action. Research
Quarterly for Exercise and Sport, 75, 130–137.
Seger, C. A., Spiering, B. J., Sares, A. G., Quraini, S. I.,
Alpeter, C., David, J., & Thaut, M. H. (2013). Corticostriatal
contributions to musical expectancy perception. Journal
of Cognitive Neuroscience, 25, 1062–1077.
Setliff, A. E., & Courage, M. L. (2011). Background television
and infants’ allocation of their attention during toy play.
Infancy, 16, 611–639.
Shepard, R. N. (1964). Circularity in judgements of relative
pitch. Journal of the Acoustical Society of America, 36,
2346–2353.
References 489
Shepard, R. N. (1982). Geometrical approximations to the
structure of musical pitch. Psychological Review, 89,
305–333.
Silverstein, L. D., & Merrifield, R. M. (1985). The
development and evaluation of color systems for
airborne applications (DOT/FAA Technical Report No.
DOT/FAA/PM-85-19). Washington, DC: U.S. Department
of Transportation.
Simmons, J. A. (2012). Bats use a neuronally implemented
computational acoustic model to form sonar images.
Current Opinion in Neurobiology, 22, 311–319.
Simner, J., Mulvenna, C., Sagiv, N., Tsakanikos, E.,
Witherby, S. A., Fraser, C., . . . Ward, J. (2006).
Synaesthesia: The prevalence of atypical cross-modal
experiences. Perception, 35, 1024–1033.
Simons, D. J., & Chabris, C. F. (1999). Gorillas in our midst:
Sustained inattentional blindness for dynamic events.
Perception, 28, 1059–1074.
Simons, D. J., & Levin, D. T. (1997). Change blindness.
Trends in Cognitive Science, 1, 261–267.
Singer, T., Seymour, B., O’Doherty, J., Kaube, H., Dolan, R.
J., & Frith, C. D. (2004). Empathy for pain involves the
affective but not sensory components of pain. Science,
303, 1157–1162.
Slater, J., Azem, A., Nicol, T., Swedenborg, B., & Kraus, N.
(2017). Variations on the theme of musical expertise:
Cognitive and sensory processing in percussionists,
vocalists and non-musicians. European Journal of
Neuroscience, 45, 952–963.
Smith, J. D., Redford, J. S., Washburn, D. A., &
Taglialatela, L. A. (2005). Specific-token effects
in screening tasks: Possible implications for
aviation security. Journal of Experimental
Psychology: Learning, Memory, and Cognition, 31,
1171–1185.
Smith, V. C., & Pokorny, J. (2003). Color matching and color
discrimination. In S. K. Shevell (Ed.), The science of
color (pp. 103–148). New York, NY: Elsevier.
Snyder, J. S., & Large, E. W. (2005). Gamma-band activity
reflects the metric structure of rhythmic tone sequences.
Cognitive Brain Research, 24, 117–126.
Snyder, L. H., Batista, A. P., & Anderson, R. A. (2000).
Intention-related activity in the posterior parietal cortex:
A review. Vision Research, 40, 1433–1441.
Sokol, S. (1978). Measurement of infant visual acuity from
pattern reversal evoked potentials. Vision Research,
18(1), 33–39.
Sommer, M. A., & Wurtz, R. H. (2008). Brain circuits for the
internal monitoring of movements. Annual Review of
Neuroscience, 31, 317–338.
Stavrinos, D., Jones, J. L., Garner, A. A., Griffin, R., Franklin,
C. A., Ball, D., Welburn, S. C., Ball, K. K., Sisiopiku, V.
P., & Fine, P. R. (2013). Impact of distracted driving on
safety and traffic flow. Accident Analysis & Prevention,
61, 63–70.
Stein, B. E., & Meredith, M. A. (1993). The merging of the
senses. Cambridge, MA: MIT Press.
Stein, L. J., Cowart, B. J., Epstein, A. N., Pilot, L. J., Laskin,
C. R., & Beauchamp, G. K. (1996). Increased liking for
salty foods in adolescents exposed during infancy to a
chloride-deficient feeding formula. Appetite, 27, 65–77.
Stevens, K. A., & Brookes, A. (1988). The concave cusp as a
determiner of figure-ground. Perception, 17, 35–42.
Stevens, S. S. (1956). The direct estimation of sensory
magnitudes: Loudness. American Journal of
Psychology, 69, 1–25.
Stevens, S. S. (1957). On the psychophysical law.
Psychological Review, 64, 153–181.
Stevens, S. S. (1961). To honor Fechner and repeal his law.
Science, 133, 80–86.
Stevenson, R. J. (2011). Olfactory illusions: Where are they?
Consciousness and Cognition, 20, 1887–1898.
Stevenson, R. J., & Mahmut, M. K. (2013). Detecting
olfactory rivalry. Consciousness and Cognition, 22,
504–516.
Stone, E. M. (2007). Macular degeneration. Annual Review
of Medicine, 58, 477–490.
Strayer, D. L., Watson, J. M., & Drews, F. A. (2011). Cognitive
distraction while multitasking in the automobile. In B. H.
Ross (Ed.), The psychology of learning and motivation:
Advances in research and theory (Vol. 54, pp. 29–58).
San Diego, CA: Academic Press.
Streri, A., Lhote, M., & Dutilleul, S. (2000). Haptic
perception in newborns. Developmental Science, 3(3),
319–327.
Stroop, J. R. (1935). Studies of interference in serial verbal
reactions. Journal of Experimental Psychology, 18(6),
643–662.
Sunami, K., Ishii, A., Takano, S., Yamamoto, H., Sakashita, T.,
Tanaka, M., . . .Yamane, H. (2013). Neural mechanisms
of phonemic restoration for speech comprehension
revealed by magnetoencephalography. Brain Research,
1537, 164–173.
Susilo, T., & Duchaine, B. (2013). Advances in
developmental prosopagnosia research. Current
Opinion in Neurobiology, 23, 423–429.
Swaminathan, S. K., Masse, N. Y., & Freedman, D. J.
(2013). A comparison of lateral and medial intraparietal
areas during a visual categorization task. Journal of
Neuroscience, 33, 13157–13170.
Swettenham, J., Remington, A., Laing, K., Fletcher, R.,
Coleman, M., & Gomez, J. C. (2013). Perception of
pointing from biological motion point-light displays
in typically developing children and children with
autism spectrum disorder. Journal of Autism and
Developmental Disorders, 43, 1437–1446.
Sensation and Perception490
Swiller, J. (2007). The unheard: A memoir of deafness and
Africa. New York, NY: Henry Holt.
Swithers, S. E. (2016). Not-so-healthy sugar substitutes?
Current Opinion in Behavioral Sciences, 9, 106–110.
Szycik, G. R., Stadler, J., Tempelmann, C., & Münte, T. F.
(2012). Examining the McGurk illusion using high-field 7
tesla functional MRI. Frontiers in Human Neuroscience,
6, 95.
Tamber-Rosenau, B. J., Esterman, M., Chiu, Y.-C., & Yantis,
S. (2011). Cortical mechanism of cognitive control
for shifting attention in vision and working memory.
Journal of Cognitive Neuroscience, 23, 2905–2919.
Tamietto, M., Cauda, F., Corazzini, L. L., Savazzi, S., Marzi,
C. A., Goebel, R., . . . de Gelder, B. (2010). Collicular
vision guides non-conscious behavior. Journal of
Cognitive Neuroscience, 22, 888–902.
Tan, S.-L., Pfordresher, P., & Harre, R. (2010). Psychology
of music: From sound to significance. New York, NY:
Psychology Press.
Tapia, E., & Breitmeyer, B. G. (2011). Visual consciousness
revisited: Magnocellular and parvocellular contributions
to conscious and nonconscious vision. Psychological
Science, 22, 934–942.
Teller, D. Y. (1983). Scotopic vision, color vision, and
stereopsis in infants. Current Eye Research, 2, 199–210.
Temperley, D. (2000). Meter and grouping in African music:
A view from music theory. Ethnomusicology, 44, 65–96.
Terenius, L. (2000). From opiate pharmacology to opioid
peptide physiology. Upsala Journal of Medical Sciences,
105(1), 1–15.
Thornton, B., Faires, A., Robbins, M., & Rollins, E. (2014).
The mere presence of a cell phone may be distracting:
Implications for attention and task performance. Social
Psychology, 45(6), 479–488.
Tomita, T. (1970). Electrical activity of vertebrate
photoreceptors. Quarterly Review of Biophysiology, 3,
179–222.
Tong, F., Meng, M., & Blake, R. (2006). Neural bases of
binocular rivalry. Trends in Cognitive Science, 10,
502–511.
Tong, F., Nakayama, K., Vaughan, J. T., & Kanwisher, N.
(1998). Binocular rivalry and visual awareness in human
extrastriate cortex. Neuron, 21, 753–759.
Toppila, E., Koskinen, H., & Pykkö, I. (2011). Hearing loss
among classical-orchestra musicians. Noise and Health,
13, 45–50.
Tramo, M. J. (2001). Biology and music: Enhanced: Music
of the hemispheres. Science, 291, 54–56.
Tranel, D., & Welsh-Bohmer, K. A. (2012). Pervasive
olfactory impairment after bilateral limbic system
destruction. Journal of Clinical and Experimental
Neuropsychology, 34, 117–125.
Treisman, A., & Gelade, G. (1980). A feature-integration
theory of attention. Cognitive Psychology, 12, 97–136.
Tremblay, P., Dick, A. S., & Small, S. L. (2011). New insights
into the neurobiology of language from functional brain
imaging. In H. Duffau (Ed.), Brain mapping: From neural
basis of cognition to surgical applications (pp. 131–144).
New York, NY: Springer.
Troje, N. F. (2013). What is biological motion? Definition,
stimuli and paradigms. In M. D. Rutherford & V. A.
Kuhlmeier (Eds.), Social perception: Detection and
interpretation of animacy, agency, and intention (pp.
13–36). Cambridge, MA: MIT Press.
Troje, N. F., & Westhoff, C. (2006). The inversion effect
in biological motion perception: Evidence for a “life
detector”? Current Biology, 16, 821–824.
Troncoso, X. G., Macknik, S. L., & Martinez-Conde, S.
(2008). Microsaccades counteract perceptual filling-in.
Journal of Vision, 8, 151–159.
Turner, R. S. (1977). Hermann von Helmholtz and the
empiricist vision. Journal of the History of the
Behavioral Sciences, 13, 48–58.
Turner, R. S. (1993). Vision studies in Germany: Helmholtz
versus Hering. Osiris, 8, 80–103.
Vaso, A., Adahan, H. M., Gjika, A., Zahaj, S., Zhurda, T.,
Vyshka, G., & Devor, M. (2014). Peripheral nervous
system origin of phantom limb pain. PAIN, 155(7),
1384–1391.
Vasterling, J. J., Proctor, S. P., Amoroso, P., Kane, R.,
Heeren, T., & White, R. F. (2006). Neuropsychological
outcomes of army personnel following deployment to
the Iraq war. JAMA, 206, 519–529.
Venrooij, J., Mulder, M., Abbink, D. A., van Paassen, M. M.,
van der Helm, F. C. T., & Bülthoff, H. H. (2013). A new
view on biodynamic feedthrough analysis: Unifying the
effects on forces and positions. IEEE Transactions on
Systems, Man, and Cybernetics, Part B: Cybernetics, 43,
129–142.
Verstraten, F. A. J. (1996). On the ancient history of the
direction of the motion aftereffect. Perception, 25,
1177–1187.
Võ, M. L., & Henderson, J. M. (2009). Does gravity matter?
Effects of semantic and syntactic inconsistencies on the
allocation of attention during scene perception. Journal
of Vision, 9, 1–15.
Võ, M. L., & Henderson, J. M. (2011). Object-scene
inconsistencies do not capture gaze: Evidence from the
flash-preview moving-window paradigm. Attention,
Perception, & Psychophysics, 73, 1742–1753.
von Arx, S. W., Müri, R. M., Heinemann, D., Hess, C.
W., & Nyffeler, T. (2010). Anosognosia for cerebral
achromatopsia: A longitudinal case study.
Neuropsychologia, 48, 970–977.
References 491
von Békésy, G. (1960). Vibratory pattern of the basilar
membrane. In E. G. Wever (Trans. & Ed.), Experiments in
hearing (pp. 404–429). New York, NY: McGraw-Hill.
von der Heydt, R., Peterhans, E., & Baumgartner, G. (1984).
Illusory contours and cortical neuron responses.
Science, 244, 1260–1262.
Voss, P., & Zatorre, R. J. (2012). Organization and
reorganization of sensory-deprived cortex. Current
Biology, 22, R168–R173.
Wade, A., Augath, M., Logothetis, N., & Wandell, B. (2008).
fMRI measurements of color in macaque and human.
Journal of Vision, 8, 1–19.
Wade, N. J. (1996). Descriptions of visual phenomena from
Aristotle to Wheatstone. Perception, 25, 1137–1175.
Wade, N. J., & Brožek, J. (2001). Purkinje’s vision: The
dawning of neuroscience. Mahwah, NJ: Erlbaum.
Wald, G. (1968). The molecular basis of visual excitation.
Nature, 219, 800–807.
Walls, G. L. (1963). The vertebrate eye and its adaptive
radiation. Bloomfield Hills, MI: Cranbrook Institute of
Science.
Walsh, E., Long, C., & Haggard, P. (2015). Voluntary control
of a phantom limb. Neuropsychologia, 75, 341–348.
Wang, A., Duncan, S. E., & Dietrich, A. M. (2016). Effect of
iron on taste perception and emotional response of
sweetened beverage under different water conditions.
Food Quality and Preference, 54, 58–66.
Wang, C., & Yao, H. (2011). Sensitivity of V1 neurons to
direction of spectral motion. Cerebral Cortex, 21,
964–973.
Wang, Q., Schoenlein, R. W., Peteanu, L. A., Mathies,
R. A., & Shank, C. V. (1994). Vibrationally coherent
photochemistry in the femtosecond primary event of
vision. Science, 266, 422–424.
Wang, Y.-U., Chen, S.-A., & Lin, C.-T. (2014). An EEG-based
brain–computer interface for dual task driving detection.
Neurocomputing, 129, 85–93.
Ward, L., Wright, E., & McMahon, S. B. (1996). A
comparison of the effects of noxious and innocuous
counterstimuli on experimentally induced itch and pain.
Pain, 64, 129–138.
Warren, R. M. (1970). Perceptual restoration of missing
speech sounds. Science, 167, 392–393.
Warren, W. H., Kay, B. A., Zosh, W. D., Duchon, A. P., &
Sahuc, S. (2001). Optic flow is used to control human
walking. Nature Neuroscience, 4, 213–216.
Watanabe, M., & Rodieck, R. W. (1989). Parasol and
midget ganglion cells in the primate retina. Journal of
Comparative Neurology, 289, 434–454.
Weeks, S. R., Anderson-Barnes, V. C., & Tsao, J. (2010).
Phantom limb pain: Theories and therapies. Neurologist,
16, 277–286.
Weigelt, S., Singer, W., & Kohler, A. (2013). Feature-based
attention affects direction-selective fMRI adaptation in
hMT+. Cerebral Cortex, 23, 2169–2178.
Weiskrantz, L. (1986). Blindsight: A case study and
implications. Oxford, UK: Clarendon.
Weiskrantz, L. (1996). Blindsight revisited. Current Opinion
in Neurobiology, 6, 215–220.
Weiskrantz, L. (2009). Blindsight: A case study spanning
35 years and new developments. Oxford, UK: Oxford
University Press.
Weiskrantz, L., Warrington, E. K., Sanders, M. D., &
Marshall, J. (1974). Visual capacity in the hemianopic
field following a restricted occipital ablation. Brain, 97,
709–728.
Weitzmann, K. (1970). Illustrations in roll and codex.
Princeton, NJ: Princeton University Press.
Werker, J. (2012). Perceptual foundations of bilingual
acquisition in infancy. Annals of the New York
Academy of Sciences: The Year in Cognitive
Neuroscience, 1251, 50–61.
Werker, J. F., & Gervain, J. (2013). Language acquisition:
Perceptual foundations in infancy. In P. Zelazo (Ed.), The
Oxford handbook of developmental psychology (pp.
909–925). Oxford, UK: Oxford University Press.
Wert, K. J., Davis, R. J., Sancho-Pelluz, J., Nishina, P. M.,
& Tsang, S. H. (2013). Gene therapy provides long-
term visual function in a pre-clinical model of retinitis
pigmentosa. Human Molecular Genetics, 22, 558–567.
Wertheimer, M. (1938). Laws of organization in perceptual
forms. In W. Ellis (Ed.), A source book of gestalt
psychology (pp. 71–88). London: Routledge & Kegan
Paul. (Original work published 1923)
Westhoff, C., & Troje, N. F. (2007). Kinematic cues for person
identification from biological motion. Perception and
Psychophysics, 69, 241–253.
Wever, E. G., & Bray, C. W. (1937). The perception of low
tones and the resonance-volley theory. Journal of
Psychology, 3, 101–114.
Wheatley, T., Weinberg, A., Looser, C. E., Moran, T., &
Hajcak, G. (2011). Mind perception: Real but not artificial
faces sustain neural activity beyond the N170/VPP. PLoS
ONE, 6, e17960.
Wiesel, T. N., & Hubel, D. H. (1963). Single cell responses
in striate cortex of kittens deprived of vision in one eye.
Journal of Neurophysiology, 26, 1003–1017.
Wiesel, T. N., & Hubel, D. H. (1965). Comparison of the
effects of unilateral and bilateral eye closure on cortical
unit responses in kittens. Journal of Neurophysiology,
28, 1029–1040.
Wilbiks, J. M. P., Vuvan, D. T., Girard, P.-Y., Peretz, I., & Russo,
F. A. (2016). Effects of vocal training in a musicophile with
congenital amusia. Neurocase, 22, 526–537.
Sensation and Perception492
Williams, S. J., & Purves, D. (2001). Neuroscience.
Sunderland, MA: Sinauer Associates.
Wolfe, J. M. (2012). Saved by a log: How do humans
perform hybrid visual and memory search?
Psychological Science, 23, 698–703.
Wong, A. O., & Wong, L. L. (2004). Tone perception of
Cantonese-speaking prelingually hearing-impaired
children with cochlear implants. Otolaryngology—Head
and Neck Surgery, 130(6), 751–758.
Wong-Riley, M. T. (1979). Changes in the visual system of
monocularly sutured or enucleated cats demonstrable
with cytochrome oxidase histochemistry. Brain
Research, 171, 11–28.
Woods, C. B., & Krantz, J. H. (2001). Sensation and
perception: A window into the brain and mind. In
J. S. Halonen & S. F. Davis (Eds.), The many faces
of psychological research in the 21st century (Chap.
5). Retrieved from http://teachpsych.org/Resources/
Documents/ebooks/faces2001
Xiao, M., & Hendrickson, A. (2000). Spatial and temporal
expression of short, long/medium, or both opsins in
human fetal cones. Journal of Comparative Neurology,
425(4), 545–559.
Xie, W.-J., Yu, H.-Q., Wang, Y.-H., Liu, Q., & Meng, H.-M.
(2016). A case report of eight and a half syndrome.
Neurological Sciences, 37, 821–822.
Xu, X., Bonds, A. B., & Casagrande, V. A. (2002). Modeling
receptive-field structure of koniocellular, magnocellular,
and parvocellular LGN cells in the owl monkey (Aotus
trivigatus). Visual Neuroscience, 19, 703–711.
Xue, J., Peng, G., Yang, J. S., Ding, Q., & Cheng, J. (2013).
Predictive factors of brain metastasis in patients with
breast cancer. Medical Oncology, 30, 337.
Yabuta, N. H., & Callaway, E. M. (1998). Functional streams
and local connections of layer 4C neurons in primary
visual cortex of the macaque monkey. Journal of
Neuroscience, 11, 1352–1360.
Yang, H., & Xu-Friedman, M. A. (2013). Stochastic
properties of neurotransmitter release expand the
dynamic range of synapses. Journal of Neuroscience,
33, 14406–14416.
Yasuaki, T., & Seno, T. (2015). Roles of size, position, and
speed of stimulus in vection with stimuli projected on
a ground surface. Aerospace Medicine and Human
Performance, 86, 794–802.
Yasuo, T., Kusuhara, Y., Yasumatsu, K., & Ninomiya, Y. (2008).
Multiple receptor systems for glutamate detection in the
taste organ. Biological & Pharmaceutical Bulletin, 31,
1833–1837.
Yin, T. C., & Chan, J. C. (1990). Interaural time
sensitivity in medial superior olive of cat. Journal of
Neurophysiology, 65, 465–488.
Yoshida, R., & Ninomiya, Y. (2010). New insights into the
signal transmission from taste cells to gustatory nerve
fibers. International Review of Cell and Molecular
Biology, 279, 101–134.
Yost, W. A. (2007). Fundamentals of hearing: An
introduction (5th ed.). New York, NY: Academic Press.
Zakis, J. A., Fulton, B., & Steele, B. R. (2012). Preferred
delay and phase-frequency response of open-
canal hearing aids with music at low insertion gain.
International Journal of Audiology, 51, 906–913.
Zamm, A., Schlaug, G., & Eagleman, D. M. (2013).
Pathways to seeing music: Enhanced structural
connectivity in colored-music synesthesia. Neuroimage,
74, 359–366.
Zanos, T. P., Mineault, P. J., Guitton, D., & Pack, C. C. (2016).
Mechanisms of saccadic suppression in primate cortical
area V4. Journal of Neuroscience, 36(35), 9227–9239.
Zeki, S. (1993). A vision of the brain. Oxford, UK: Blackwell.
Zheng, J., Zhang, B., Bi, H., Maruko, I., Watanabe, I.,
Nakasata, C., . . . Chino, Y. M. (2007). Development of
temporal response properties and contrast sensitivity
of V1 and V2 neurons in macaque monkeys. Journal of
Neurophysiology, 97, 3905–3916.
Zhou, W., & Chen, D. (2009). Binaral rivalry between
the nostrils and in the cortex. Current Biology, 19,
1561–1565.
Zihl, J., von Cramon, J. D., & Mai, N. (1983). Selective
disturbance of movement vision after bilateral brain
damage. Brain, 106, 313–340.
Zivony, A., & Lamy, D. (2014). Attentional engagement
is not sufficient to prevent spatial capture. Attention,
Perception, & Psychophysics, 76, 19–31.
Zokoll, M. A., Wagener, K. C., Brand, T., Buschermöhle,
M., & Kollmeier, B. (2012). Internationally comparable
screening tests for listening in noise in several
European languages: The German digit triplet test as
an optimization prototype. International Journal of
Audiology, 51, 697–707.
Zucco, G. M., Aiello, L., Turuani, L., & Koster, E. (2012).
Odor-evoked autobiographical memories: Age and
gender differences along the life span. Chemical
Senses, 37(2), 179–189. doi:10.1093/chemse/bjr089
Author Index 493
AUTHOR INDEX
Abbink, D. A., 16
Abdelaziz, A. H., 365
Abel, G. L., 421
Abramov, I., 164
Adahan, H. M., 428
Adam, A., 180
Adelson, E. H., 177
Agostini, T., 178
Ahrens, W., 394
Aiello, L., 45
Akhtar, S., 62
Aladdin, Y., 117
Alarcon, R., 221
Albouy, G., 421
Alexander, E., 342
Alkaladi, A., 83
Alpern, M., 171, 174
Alpeter, C., 384
Amoros, P., 18
Andersen, R. A., 245
Anderson, B. A., 265
Anderson, R. A., 245
Anderson, S., 363
Anderson-Barnes, V. C., 427
Anstis, S., 248
Ardiles, P., 22
Armony, J. L., 277
Arnell, K. M., 257
Arnold, K., 152
Arnoldussen, A., 86
Arroyo, J. G., 80
Atkinson, J., 72
Attems, J., 454
Augath, M., 175
Axel, R., 439–440
Azem, A., 385
Babadi, B., 97
Bacon, S. P., 330
Bahrami, B., 281
Baldwin, G. T., 417
Balkwill, L.-L., 391
Ball, D., 282
Ball, K. K., 282
Ball, S. L., 452
Baltzell, D., 221
Banks, M. S., 72
Bannister, J., 27
Barden, K., 354
Barlow, H. B., 138, 210, 232
Barnes, G. R., 281
Barry, M. P., 85
Bartoshuk, L. M., 449, 451, 452
Bastos, S. C., 456–457
Batista, A. P., 245
Battelli, L., 242
Baumgartner, G., 135
Baures, R., 22
Baxter, L. C., 415
Beauchamp, G. K., 453
Beck, D. M., 270
Beckers, G., 239
Bekrater-Bodmann, R., 428
Belin, P., 361
Bennett, C. M., 19
Bennett, P. J., 72
Bensmaia, S., 420
Beran, M. J., 56
Beranek, L. L., 336
Berezovsky, A., 72
Bernotas, M., 199
Bernstein, I. L., 453
Berson, E. L., 81
Bestelmeyer, P. E. G., 361
Bhalla, M., 21
Bi, H., 211
Biederman, I., 136
Birch, E. E., 170, 210
Bisiach, E., 276
Bisley, J. W., 106
Blackwell, H. R., 36
Blake, R., 82, 241, 281
Blakemore, C., 210
Bleyenheuft, Y., 422
Bohn, K. M., 334
Bonafede, B., 218–219
Bonato, F., 178
Bonds, A. B., 97
Boot, W. R., 146–147
Boring, E. G., 211–212
Born, R. T., 110
Bornstein, M. H., 168
Bosten, J. M., 152, 174
Botella, C., 221
Bouchard, S., 221
Boucsein, W., 250
Bowmaker, J. K., 66
Boyer, A., 215
Boyle, J., 445
Brackett, D. D., 215
Braddick, O., 72
Bradley, D. C., 110
Bramanti, P., 454
Brand, T., 48
Brang, D., 386
Bray, C. W., 305
Bregman, A. S., 327, 328, 342
Breitmeyer, B. G., 44, 232
Brendel, E., 22
Breslin, P. A. S., 452
Bressler, N. M., 80
Brett, J. A., 21
Bridgeman, B., 235
Brincat, S., 137
Britten, K. H., 237, 238
Brookes, A., 132
Brown, A. M., 169
Browne, J. V., 330
Brozek, J., 69
Bruce, C., 109
Buck, L. B., 439–440
Bucy, P. C., 137–138
Buetti, S., 281
Buletic, Z., 452
Bülthoff, H. H., 16
Bundesen, C., 231
Busch, N. A., 270
Busch, V., 394
Buschermöhl, M., 48
Bushnell, M. C., 416
Busigny, T., 139
Butler, J., 233
Buzás, P., 152
Cahn, R., 384
Cain, W. S., 444
Cain Miller, C., 125
Calkins, D., 106
Callaway, E. M., 98
Caminiti, F., 454
Cantril, H., 4
Carey, D. P., 109
Carrier, B., 416
Carroll, J., 171
Cartwright, M., 372
Carylon, R. P., 342
Casagrande, V. A., 97
Casti, A., 97
Cataliotti, J., 178
Cauda, F., 115, 281
Cave, K. R., 146
Cavina-Pratesi, C., 110
Centers for Disease Control and
Prevention, 306
Chabris, C. F., 263
Champoux, F., 385
Chan, B. L., 428
Chan, J. C., 323
Chandrashekar, J., 450
Chang, E. F., 361–362, 367
Charrow, A. P., 428
Chasin, M., 363, 395–396
Chen, D., 446
Chen, D. W., 98
Chen, M.-C., 277
Chen, S.-A., 283
Chen, X., 20
Cheng, H., 210–211
Cheng, J., 42
Cherrier, M. M., 140
Cherry, E. C., 342
Chino, Y. M., 210–211
Chiu, Y.-C., 273, 274 (figure)
Chow, A., 85
Chow, V., 85
Chrastil, E. R., 244
Chun, M. M., 138, 257
Ciurleo, R., 454
Claggett, B., 20
Clark, J., 270
Coben, J. H., 282
Coe, S. B., 456–457
Colby, C. L., 245
Cole, B. L., 180
Cole, J., 428
Collignon, O., 421
Sensation and Perception494
Colombo, J., 278
Compton, W. M., 417
Conard, N. J., 372
Connor, C. E., 109, 137
Cool, S. J., 82
Corazzini, L. L., 115, 281
Corbit, J. D., 350
Cornsweet, T. N., 71
Côté, S., 221
Coughlin, B. C., 452
Courage, M. L., 278, 279, 285
Cowart, B. J., 453
Craig, A. D., 415
Craig, J. C., 420
Crawford, M. L. J., 82
Crawley, A. P., 416
Crone, N. E., 361–362, 367
Croy, I., 455
Crystal, S. R., 453
Cui, H., 245
Culham, J. C., 110, 246
Curcio, C. A., 64
Currie, Z., 62
Curtiss, S., 358
Da Cruz, L., 85
Dagnelie, G., 85
Dai, P., 366
Damasio, A., 384
Damasio, H., 384
Da Silva Andrade, R., 456–457
Daum, K. M., 61
David, D., 221
David, J., 384
David, S. V., 361–362, 367
Davids, K., 219
Davis, K. D., 416
Davis, R. J., 81
Daw, N., 113
DeCasper, A. J., 330
De Courten, C., 113
Deeb, S. S., 152, 174
De Gelder, B., 113–114, 115, 281
Dekle, D. J., 352
Delk, J. L., 20
Delogu, F., 456
DeLucia, P. R., 22
Delwiche, J. F., 452
DeMarco, P. J., Jr., 85
Dennett, D. C., 111
Desimone, R., 109, 275, 284
Deutsch, D., 392–394
De Valois, R. L., 164, 166
Devor, M., 428
Devos, M., 444
Dewald, A. D., 257
De Wijk, R. A., 444
DeWitt, L. A., 383
DeYoe, E. A., 107
Dick, A. S., 18
Diehl, R. L., 355
Diers, M., 428
Dijkstra, P. U., 427
Dilks, D., 138
Di Lollo, V., 44
Ding, Q., 42
Ditterich, J., 239
Djordjevic, J., 445
Dobson, V., 72
Doerschner, K., 16
Dolan, R. J., 140, 416
Dominguez-Borràs, J., 277
Donnelly, N., 146
Dormal, G., 421
Dorn, J. D., 85
Dostrovsky, J. O., 416
Doumas, L. A. A., 257
Downing, P. E., 140
Drew, T., 264
Drews, F. A., 256
Driver, J., 140, 261–262, 277, 428
Dryja, T. P., 81
Duarte, N., 221
Duchaine, B. C., 110, 139–140
Duchon, A. P., 244
Duffy, V. B., 451, 452
Duhamel, J.-R., 245
Duncan, G. H., 416
Dutilleul, S., 422
Eagleman, D. M., 386
Economou, E., 178
Eddy, R., 64
Eggenberger, E. R., 116
Egly, R., 261–262
Egorova, N., 20
Eimas, P. D., 350
Ejzenbaum, F., 72
Ellison, A., 110
Elzinga, A., 427
Engen, T., 446
Enns, J. T., 44
Epstein, A. N., 453
Epstein, R., 140
Erberich, S., 385
Esterman, M., 273, 274 (figure)
Fain, G. L., 66
Faires, A., 283
Falk, G., 67
Farina, F. R., 386
Fark, T., 454
Fattori, P., 235
Fechner, G. T., 13
Fedderson, W. E., 323
Fernandez, R., 456
Feynman, R. P., 55
Fields, R. D., 426
Fifer, W. P., 330
Fillenbaum, S., 20
Findling, D., 125, 126
Fine, P. R., 282
Firestone, C., 20–21
Fisher, M. F. K., 447
Flanagan, J. R., 246
Flinker, A., 361–362, 367
Flor, H., 428
Foell, J., 428
Foldvari, M., 98
Foltys, H., 385
Foster, D. H., 176
Fowler, C. A., 352, 355, 356
Frank, G. K. W., 456
Franklin, C. A., 282
Fraser, A., 247
Fraser, C., 386
Frasnelli, J., 454
Frazier, L. D., 455
Freedman, D. J., 246
Freeman, S., 20
Fried, I., 110, 141, 142
Frith, C. D., 416
Froehlich, J. C., 417
Fromkin, V., 358
Fudge, J. L., 456
Fujita, N., 419
Fulton, B., 395
Furl, N., 140
Galantucci, B., 355
Galletti, C., 235
Gallivan, J. P., 246
Gamito, P., 221
Garcia-Palacios, A., 221
Garneau, N. L., 452
Garner, A. A., 282
Garrido, L., 140
Gartshteyn, Y., 237
Gatzia, D. E., 20
Geertzen, J. H. B., 427
Gegenfurtner, K. R., 20
Gelade, G., 267
Gelbard-Sagiv, H., 142
Gelfand, S. A., 32
Gerber, J., 454
Gerstmann, J., 421
Gervain, J., 357
Gibson, E. J., 15
Gibson, J. J., 5, 194, 198, 243, 356
Gilad, Y., 440
Gilbert, S. F., 62
Gilchrist, A., 178
Girard, P.-Y., 387
Gjika, A., 428
Godfrey, P. A., 440
Godwin, H. J., 146–147
Goebel, R., 115, 281
Goldberg, M. E., 245
Goldberg, S., 116–117
Goldinger, S. D., 146–147
Goldwater, S., 365
Golomb, J. D., 257
Goodale, M. A., 109
Gorman, J. C., 22
Gottfried, J. A., 442
Graap, K., 221
Graham, C. H., 174
Graham, S., 283
Grant, P., 86
Granville, W. C., 169
Graven, S. N., 330
Green, B. G., 418
Green, D. M., 38
Green, E., 456
Greenberg, R. J., 85
Author Index 495
Greenwood, V., 152
Gregory, R. L., 214
Griffin, R., 282
Grill-Spector, K., 138
Grimault, N., 330
Groen, E. L., 250
Gross, C. G., 109
Grossman, E. D., 242
Grueschow, M., 442
Grüsser, O.-J., 11
Guitton, D., 259
Habibi, A., 384
Hachem, S., 456
Haehner, A., 455
Haggard, P., 427
Hahnel, U. J. J., 22
Hajcak, G., 144
Hakyemez, H., 342
Hanif, W., 44
Hansen, T., 20
Harel, M., 142
Harley, T. A., 357, 358
Harre, R., 381–382, 390
Harris, A., 138
Hartline, H. K., 76, 84
Hartong, D. T., 81
Haslwanter, T., 199
Håstad, O., 56
Hastorf, A. H., 4
Hatta, S., 210–211
Hawken, M. J., 167
Hayes, J. E., 452
Haynes, J. D., 442
He, J., 319
Hecht, H., 22
Hecht, S., 67
Hedges, J. H., 237
Heeren, T., 18
Heilman, K. M., 428
Hein, A., 112
Heinemann, D., 175
Heinze, H. J., 19
Held, R., 112
Heller, M. A., 215
Helman, S., 22
Henderson, J. M., 266
Hendrickson, A. E., 64, 168
Hendry, S. H. C., 95
Hershenson, M., 250
Hervais-Adelman, A., 281
Herz, R., 435–436, 444–445, 453–455
Herz and von clef, 446
Herz eliassen beland and souza, 443
Hess, C. W., 175
Hickok, G., 361
Highnote, S., 68, 174
Hirstein, W., 427
Hochmuth, S., 365
Hockley, N. S., 395–396
Hodges, L., 221
Hoefle, F. B., 218–219
Hof, P. R., 411
Hofeldt, A. J., 218–219
Hofer, H., 171
Hoffman, P. M., 325
Hogle, R., 86
Hogness, D., 64
Hollins, M., 420
Holt, L. L., 355, 356
Holway, A. H., 211–212
Hoon, M. A., 450
Hopf, J. M., 19
Horridge, A., 56
Horswill, M., 22
Houpt, J. W., 146–147
Hout, M. C., 146–147
Howard, I. P., 205
Howard, J. D., 442, 443
Howard, R., 428
Hsia, Y., 174
Hsiang, S., 22
Hsiao, S., 414–415
Hsiao, S. S., 420
Hu, L., 385
Hua, L. H., 415
Huang, Q., 364
Huang, Y.-T., 277
Hubbard, E. M., 386
Hubel, D. H., 17, 91, 103–104, 105, 112–113, 209
Huddas, C., 456
Hughes, H. C., 260–261, 334, 426
Humayun, M. S., 85
Hummel, T., 454
Hung, Y., 283
Huotilainen, M., 330
Hurvich, L. M., 165
Hutchinson, W. D., 416
Huttenlocher, P. R., 113
Hyde, K., 384, 386
Iannetti, G. D., 385
Irons, J., 271
Isaacs, L. D., 219
Ishii, A., 354
Isono, K., 188
Jacobs, G., 64
Jacobs, G. H., 164
Jacquin-Cortois, S., 277
Jakobsen, L. S., 109
James, W., 278
Jameson, D., 165
Jameson, K. A., 68, 174
Jeffress, L. A., 323
Jellinger, K. A., 454
Jiang, Y., 140
Jiao, S., 65
Johansson, G., 241
Johnson, E. N., 167
Johnson, S. C., 415
Johnsrude, I. S., 342
Jolicoeur, P., 387
Jones, C. M., 417
Jones, F. N., 36
Jones, J. L., 282
Jones-Gotman, M., 445
Jönsson, F. U., 444
Jordan, G., 152, 174
Juang, B. H., 365
Julesz, B., 208–209
Jurafsky, D., 365
Kaas, A., 238
Kadohisa, M., 442
Kalina, R. E., 64
Kallus, K. W., 250
Kan, K., 283
Kanai, R., 281
Kandel, E. R., 101
Kandil, F. I., 244
Kane, R., 18
Kanizsa, G., 135
Kanwisher, N., 110, 138, 140, 281
Kaplan, E., 97
Kapoula, Z., 199
Kaptchuk, T. J., 20
Kau, S., 19
Kaube, H., 416
Kawahara, J. I., 272
Kay, B. A., 244
Kaye, W. H., 456
Keane, A. G., 21
Kennedy, H., 233
Kersten, D., 16
Kerzel, D., 281
Kessen, W., 168
Khateb, A., 116, 281
Killion, M. C., 395
Kirchhof, H., 61
Kirsch, I., 20
Kitahara, K., 174
Kitaoka, A., 247
Klatzky, R. L., 419
Klüver, H., 137–138
Knighton, R. W., 65
Knouf, N., 138
Kóbor, P., 152
Koch, C., 110, 141
Kochkin, S., 362
Kohler, A., 238
Kohn, A., 237
Kollmeier, B., 48, 365
Kolossa, D., 365
Kong, J., 20
Kooijman, C. M., 427
Koskinen, H., 395
Kossyfidis, C., 178
Koster, E., 45
Kovach, J. K., 10
Koyanagi, M., 188
Kramer, A. F., 146–147
Krantz, D. H., 174
Krantz, J. H., 72, 170
Krashen, S., 358
Kraus, N., 363, 385
Kreiman, G., 110, 141
Kreutz, G., 394
Krings, T., 385
Kristjánsson, A., 272, 283
Krumhansl, C. L., 390
Krupinski, E. A., 146
Kuffler, S. W., 17, 73–74, 76, 82
Kujalaa, T., 330
Kundel, H. L., 146
Sensation and Perception496
Kurita, T., 239
Kusumi, I., 239
Laffort, P., 444
LaMotte, R. H., 418
Lancet, D., 440
Land, E. H., 177
Landis, B. N., 455
Landry, S. P., 385
Langenheim, J., 298
Laning, J., 44–45
Lappe, M., 244
Large, E. W., 385
Larsen, A., 231
Larsen, J. T., 22
Laskin, C. R., 453
Latinus, M., 361
Laurent, P. A., 265
Lavie, N., 270
Lawless, H. T., 445
Lazeyras, F., 116, 281
Lederman, S. J., 419
Lee, G. B., 171
Leek, M. R., 364
Leh, S. E., 116
Lehmann, J., 454
Lénárd, L., 152
Lenoir, M., 219
Lepore, F., 421
Lettvin, J. Y., 232
Levin, D. T., 269
Lhote, M., 422
Li, W., 443
Li, X., 178
Liang, M., 385
Liberman, A. M., 355
Limb, C. J., 396
Lin, C.-T., 283
Lin, K., 277
Litola, A., 330
Liu, J., 138
Liu, Q., 117
Livadas, C., 250
Livingstone, M., 105, 179
Lodhia, L., 456
Logerstedt, M., 456
Logothetis, N., 175
Lokki, T., 335
Long, C., 427
Loomis, J. M., 419
Looser, C. E., 143–145, 144
Lopez, L., 384, 443
Lotto, A. J., 355, 356
Loui, P., 386
Lowenfield, B., 421
Lozano, A. M., 416
Luaté, J., 277
Lucchina, L. A., 452
Lund, T. E., 231
Luzzatti, C., 276
Lygeros, J., 250
Lynch, N. A., 250
Maaseidvaag, F., 171
MacDonald, T., 351–352
Mack, A., 263, 264 (figure)
Mackey, A., 342
Macknik, S. L., 247, 248
Macko, K. A., 107–109
MacMahon, M. K. C., 346
Madsen, K. H., 231
Maertens, M., 135
Magee, A., 428
Mahmut, M. K., 446
Mai, N., 239
Majno, M., 384
Major, J. C., Jr., 65
Malach, R., 142
Malina, M., 372
Malnic, B., 440
Man, O., 440
Manning, C. D., 365
Maravita, A., 277
Marchi, F., 20
Marino, S., 454
Marr, D., 16
Marshall, J., 114
Martin, P. R., 152
Martinez-Conde, S., 247, 248
Maruko, I., 211
Marzi, C. A., 115, 281
Masland, R. H., 232
Mason, C., 101
Masse, N. Y., 246
Mathies, R. A., 67
Mattingley, J. B., 44–45
Mattingly, I. G., 355
Mattys, S. L., 354
Maturana, H. R., 232
Maurer, D., 357
Mayer, D. L., 72
Mazo, M., 391
Mazyn, L. I. N., 219
McCall, M. A., 452
McCarley, J. S., 146–147
McConnell, D. S., 283
McCulloch, W. S., 232
McDermott, J., 138
McGlone, F., 406
McGurk, H., 351–352
McKeegan, N., 85
McKeown, C., 65
McLean, D. A., 246
McLean, G. Y., 452
McMahon, S. B., 418
Melzack, R., 410, 415
Memmi, S., 241
Menashe, I., 440
Mendez, M. F., 140
Meng, H.-M., 117
Meng, M., 281
Menneer, T., 146
Mercier, C., 428
Merkel, C., 19
Merrifield, R. M., 159
Mesgarani, N., 361–362, 367
Meyer, G. E., 135
Meyer, R., 336, 391
Meza-Arroyo, M., 22
Micheyl, C., 330
Mignault-Goulet, G., 387
Mikulis, D. J., 416
Miller, F. G., 20
Miller, I. J., 451
Miller, L. R., 20
Miller, M. B., 19
Miller, S. S., 171
Milner, A. D., 109, 110
Mineault, P. J., 259
Misaka, T., 457
Mishkin, M., 107–109
Mitchell, K. J., 386
Moar, K., 72
Molis, M. R., 364
Møller, J., 308
Mollon, J. D., 152, 161, 174, 180
Monnier, P., 179
Montagne, G., 219
Moore, B. C. J., 396
Morais, D., 221
Moran, J., 275, 284
Moran, T., 144
Moreau, P., 387
Morgan, M. J., 180
Morrison, I., 406
Moscovitch, D., 139
Moscovitch, M., 139
Mountcastle, V. B., 421
Mouraux, A., 385
Movshon, J. A., 237, 238
Muayqil, T., 117
Muckli, L., 238
Muggleton, N., 270
Mukamel, R., 142
Mulder, M., 16
Mulvenna, C., 386
Münte, T. F., 352
Münzel, S. C., 372
Müri, R. M., 175
Murphy, C., 456
Murphy, G., 10
Näätänen, R., 330
Nagata, T., 188
Naglie, G., 283
Nakasata, C., 211
Nakayama, K., 139–140, 281
Nassi, J. J., 98
Nathans, J., 64
National Institutes of Health, 46
Nau, A., 86
Neisser, U., 263
Neitz, J., 64, 171
Neitz, M., 171
Neumeyer, C., 57, 152
Newen, A., 20
Newsome, W. T., 237–238
Nicol, T., 385
Nilsson, D.-E., 83
Ninomiya, Y., 450
Nishina, P. M., 81
Nodine, C. F., 146
Nooij, S. A. E., 250
Nuessle, T. M., 452
Nyffeler, T., 175
Author Index 497
Oberndorfer, T. A., 456
Ödeen, A., 56
O’Doherty, J., 416
Olausson, H., 406
Oliveira, J., 221
Oliveira, S., 221
Olkkonen, M., 20
Olsson, M. J., 444
Oltman, M., 435
Opris, D., 221
Orban, G. A., 233
O’Regan, J. K., 270
O’Shea, J., 277
Osher, J., 443
Otero-Millan, J., 247
Oudejans, R. R. D., 219
Overgaard, M., 281
Overy, K., 384
Pack, C. C., 259
Packo, K., 85
Palmer, C., 391
Paninski, L., 97
Parbery-Clark, A., 363
Paré, E. B., 237–238
Parker, A. J., 210
Parkinson, C., 241
Partanen, E., 330
Pascual-Leone, A., 242
Pasley, B., 361–362, 367
Pasquina, P. F., 428
Pasternak, T., 106
Pasupathy, A., 109, 137
Patel, A. D., 388–389
Patte, F., 444
Patynen, J., 335
Paulus, M. P., 456
Pavani, F., 428
Pegna, A. J., 116, 281
Pei, Y. C., 420
Penfield, W., 413
Peng, G., 42
Pereira, J. M., 72
Peretz, I., 384, 386, 387
Perlman, M., 390
Perry, B. N., 428
Peteanu, L. A., 67
Peterhans, E., 135
Peterson, M. A., 132
Petrides, M., 445
Petry, S., 135
Pettifer, S. R., 428
Pettigrew, J. D., 210
Petykó, Z., 152
Peyman, G., 85
Pfordresher, P., 381–382, 390
Phillips, C., 421
Piantanida, T., 64
Pigeot, I., 394
Pilot, L. J., 453
Pinckers, A. J. L. G., 169
Pinheiro, A. C. M., 456–457
Pinker, S., 347
Pintea, S., 221
Pirenne, M. H., 67
Pisella, L., 277
Pitts, W. H., 232
Plailly, J., 442
Plantinga, J., 381
Poeppel, D., 361
Pokorny, J., 173
Pollack, J., 85
Pollmann, S., 135
Posner, M., 260–262, 273–274
Price, D. D., 416
Proctor, R. W., 180
Proctor, S. P., 18
Proffitt, D. R., 21
Ptito, A., 116
Puliafito, C. A., 65
Purves, D., 296, 409
Pykkö, I., 395
Quiroga, R. Q., 110, 141, 245
Quraini, S. I., 384
Rabiner, L. R., 365
Radtke, N. D., 85
Rafal, R. D., 261–262
Rainville, P., 416
Ramachandran, V. S., 65, 386, 427
Ranjit, M., 22
Rasmussen, T., 413
Ratliff, F., 76, 84
Rauschecker, J. P., 321
Raymond, J. E., 257
Rayner, K., 146
Read, J. C. A., 104
Ready, D., 221
Reddy, L., 110, 141
Reed caselli farah, 421
Rees, G., 281
Reid, R. C., 95
Reinhard, J., 44–45
Remington, R., 271
Remus, D. R., 281
Renaud, P., 221
Rensink, R. A., 270
Revol, P., 277
Reynolds, G. D., 278, 285
Rice, N., 110
Richards, J. E., 278, 285
Rigler, D., 358
Rigler, M., 358
Robbins, M., 283
Robillard, G., 221
Robinson, A. K., 44–45
Robitaiile, N., 387
Roche, R. A. P., 386
Rock, I., 263, 264 (figure)
Rodieck, R. W., 66, 73
Rodrigues, J. F., 456–457
Roebroeck, A., 238
Rogers, B., 248
Rogers, B. J., 205
Rollins, E., 283
Rolls, E. T., 450
Rolls and tovee, 138
Roorda, A., 70, 72
Rosa, P., 221
Rosch, E. H., 164
Rossetti, Y., 277
Rossi, E. A., 70, 72
Rossion, B., 139
Rothbart, M. K., 273
Rothbaum, B. O., 221
Rotter, A., 244
Rouault, J., 444
Roy, A. T., 396
Royster, J. D., 395
Royster, L. H., 395
Ruggeri, M., 65
Rupp, M. A., 283
Russo, F. A., 387
Rust, N. C., 237
Rutstein, R. P., 61
Ryba, N. J. P., 450
Sabine, W. C., 335
Sacai, P. Y., 72
Sacks, O., 123, 171, 276
Saeki, S., 188
Sagdullaev, B. T., 452
Sagiv, N., 386
Sahel, J. A., 85
Sahuc, S., 244
Sakashita, T., 354
Sakurai, K., 239
Salomão, S. R., 72
Salvagio, E., 132
Salvi, S. M., 62
Sambeth, A., 330
Samuel, A. G., 354, 383
Samuels, S. M., 250
Sancho-Pelluz, J., 81
Sandberg, K., 281
Sandel, T. T., 323
Sanders, M. D., 114
Santorico, S. A., 452
Saqqur, M., 117
Saraiva, T., 221
Sares, A. G., 384
Sato, H., 272
Savazzi, S., 115, 281
Savelsbergh, G. J. P., 22, 219
Schachar, R. A., 200
Schacter, D. L., 141
Schädler, M. R., 365
Schenk, T., 110, 239
Schiells, R. A., 67
Schink, T., 394
Schlaer, S., 67
Schlaug, G., 386
Schmidt, J. H., 395
Schoenfeld, M. A., 19
Schoenlein, R. W., 67
Scholl, B. J., 20–21
Schrater, P., 16
Schultz, D. P., 13
Schultz, S. E., 13
Schwartz, B. L., 20, 110, 127
Schwartz, D. A., 296
Schweizer, T., 283
Scott, M. A., 219
Scott, S. K., 321
Sensation and Perception498
Scozzafava, J., 117
Seger, C. A., 384
Seghier, M., 116, 281
Seiple, W., 86
Seno, T., 250
Setliff, A. E., 279, 285
Seymour, B., 416
Shadlen, M. N., 237
Shahar, F., 221
Shamma, S. A., 361–362, 367
Shank, C. V., 67
Shapiro, K. L., 257
Shapley, R., 167
Shepard, R. N., 375 (figure), 392
Shichida, Y., 188
Shiffrar, M., 241
Shiller, D. M., 385
Shimada, S. G., 418
Shiraishi, H., 239
Shows, T., 64
Shuman, M., 140
Silverstein, L. D., 72, 159
Simmons, A. N., 456
Simmons, J. A., 331
Simner, J., 386
Simons, D. J., 263, 269
Singer, T., 416
Singer, W., 238
Singhai, A., 110
Sinnett, S., 257
Sisiopiku, V. P., 282
Slater, J., 385
Sloan, K. R., 64
Sloan, M. M., 452
Small, S. L., 18
Smarsh, G. C., 334
Smith, E. L., III, 210–211
Smith, V. C., 173
Smither, J. A., 283
Smith redford washburn and
taglialatela, 146
Smotherman, M. S., 334
Snyder, J. S., 385
Snyder, L. H., 245
Sokol, S., 72
Sommer, M. A., 235
Soon, I. Y., 366
Sparing, R., 385
Spence, C., 428
Spencer, L., 86
Spiering, B. J., 384
Stacy, R. L., 22
Stadler, J., 352
Stark, L., 235
Starr, A., 384
Stavrinos, D., 282
Steele, B. R., 395
Steffen, H., 215
Stein, L. J., 453
Steven, K., 456
Stevens, K. A., 132
Stevens, S. S., 34, 35
Stevenson, R. J., 444–446
St-Jacques, J., 221
Stone, E. M., 80
Stoppel, C. M., 19
Stranga, P. A., 85
Strayer, D. L., 256
Streri, A., 422
Streri lhote dutilleul, 422
Strigo, I. A., 415
Stroop, J. R., 258
Stroud, M., 146
Strumpf, H., 19
Sunami, K., 354
Susilo, T., 110
Swaminathan, S. K., 246
Swedenborg, B., 385
Swets, J., 38
Swiller, J., 306
Swithers, S. E., 455, 457
Szamosközi, S., 221
Szlyk, J., 86
Szycik, G. R., 352
Takano, S., 354
Takeda, Y., 239
Tam, F., 283
Tamber-Rosenau, B. J., 273, 274 (figure)
Tamietto, M., 115, 281
Tan, S.-L., 381–382, 390
Tanaka, M., 354
Tang, J., 364
Tan pfordresher harre, 373
Tapia, E., 232
Tasker, R. R., 416
Taylor, S. J., 416
Teas, D. C., 323
Telkes, I., 152
Teller, D. Y., 169, 210
Tempelmann, C., 352
Temperley, D., 390
Terakita, A., 188
Terenius, L., 417
Thaut, M. H., 384
Thompson, J. M., 356
Thompson, W. F., 391
Thonnard, J. L., 422
Thornton, B., 283
Thron, A., 385
Tomita, T., 67
Tong, F., 281
Töpper, R., 385
Toppila, E., 395
Trainor, L. J., 381
Tramo, M. J., 385
Tranel, D., 454
Trang, H. P., 342
Trattler, W., 116–117
Treisman, A., 267
Tremblay, P., 18
Troje, N. F., 241, 242
Troncoso, X. G., 248
Tropper, K., 250
Tsai, P.-L., 277
Tsakanikos, E., 386
Tsang, S. H., 81
Tsao, J., 427
Tsao, J. W., 428
Tsukamoto, H., 188
Turke-Browne, N. B., 257
Turner, R. S., 11, 12
Turuani, L., 45
Turvey, M. T., 355
Ungerleider, L. G., 107–109
Valbo, A., 406
Van der Gucht, E., 411
Van der Helm, F. C. T., 16
Van der Kamp, J., 219
Van der Schans, C. P., 427
Vandewalle, G., 421
Van Essen, D. C., 107
Van Gemert, L. J., 444
Van Opstal, A. J., 325
Van Paassen, M. M., 16
Van Riswick, J. G., 325
Van Zandt, T., 180
Vaso, A., 428
Vasterling, J. J., 18
Vaughan, J. T., 281
Venrooij, J., 16
Verstraten, F. A. J., 10
Victorsson, J., 56
Vidoni, E. D., 146–147
Vo, M. L.-H., 264, 266
Von Arx, S. W., 175
Von Cramon, J. D., 239
Von der Heydt, R., 135
Voss, P., 421
Vuilleumier, P., 277
Vuvan, D. T., 387
Vyshka, G., 428
Wade, A., 175
Wade, N. J., 10, 69
Wagener, K. C., 48
Wake, H., 419
Wald, G., 67
Wald, M. L., 125
Walenchok, S. C., 146–147
Walker, L., 454
Walker, T., 241
Wall, P. D., 410, 415
Walls, G. L., 65
Walsh, E., 427
Walsh, V., 270
Walter, S., 20
Wandell, B., 175
Wang, C., 233
Wang, Y.-H., 117
Wang, Y.-U., 283
Wang duncan dietrich, 456
Wang schoenlein peteanu mathies
andshank, 67
Wann, J. P., 22
Ward, J., 386
Ward, L., 418
Warren, R. M., 354
Warren, W. H., 244
Warrington, E. K., 114
Warzybok, A., 365
Washburn, S., 420
Wasserman, L., 68, 174
Author Index 499
Watanabe, I., 211
Watanabe, M., 73
Watson, J. M., 256
Watson, R., 361
Weeks, S. R., 427
Weigelt, S., 238
Weinberg, A., 144
Weiskopf, S., 168
Weiskrantz, L., 18, 114–115, 281
Weitzmann, K., 10
Welburn, S. C., 282
Welsh-Bohmer, K. A., 454
Werker, J. F., 357
Wert, K. J., 81
Wertheimer, M., 132–133
Wessberg, J., 406
Westhoff, C., 241
Wever, E. G., 305
Wheatley, T., 143–145, 144, 241
White, R. F., 18
White-Schwoch, T., 363
Wickens, C. D., 146–147
Wiesel, T. N., 17, 91, 103–104, 112–113, 209
Wilbiks, J. M. P., 387
Wilcox, K. J., 247
Williams, D. R., 171
Williams, S. J., 409
Willmes, K., 385
Wilson, D. A., 442
Wilson, K., 215
Wirantana, V., 384
Witherby, S. A., 386
Witt, R., 428
Wolfe, J. M., 264, 267
Wolford, G. L., 19
Wong-Riley, M. T., 105
Wood, M. L., 416
Woods, C. B., 170
Wright, E., 418
Wurtz, R. H., 235
Xiao, M., 168
Xiao, Y., 97
Xie, W.-J., 117
Xu, X., 97
Xue, J., 42
Xu-Friedman, M. A., 318
Yamamoto, H., 354
Yamane, H., 354
Yang, H., 318
Yang, J. S., 42
Yang, T. T., 456
Yantis, S., 265, 273, 274 (figure)
Yao, H., 233
Yarbrough, G. L., 452
Yasuaki, T., 250
Yee, C. W., 452
Yeh, Y.-Y., 72
Yin, T. C., 323
Yoneyama, K., 215
Yoshida, R., 450
Yost, W. A., 307
Yovel, G., 110
Yu, H.-Q., 117
Yu, R., 20
Zahaj, S., 428
Zakis, J. A., 395
Zamm, A., 386
Zanos, T. P., 259
Zatorre, R. J., 384, 421, 445
Zeil, J., 83
Zeki, S., 106, 109, 111, 239
Zelterman, D., 418
Zhang, B., 211
Zheng, J., 211
Zhou, W., 446
Zhu, M., 282
Zhurda, T., 428
Zihl, J., 239
Zimba, L. D., 260, 261
Zohary, E., 237
Zokoll, M. A., 48
Zosh, W. D., 244
Zucco, G. M., 45
Zuker, C. S., 450
Sensation and Perception500
SUBJECT INDEX
Absolute threshold, 30, 31 (figure)
stars as, 31, 31 (figure)
Accommodation (eye), 60–61, 199
Accretion, 197, 198 (figure)
Acoustic reflex, 301
Acoustic shadow, 324, 324 (figure)
Acoustics of music
consonance and dissonance in, 376–377
dynamics and rhythm in, 377–378,
378 (figure)
melody in, 380–383, 380 (figure),
382–383 (figure)
pitch, chroma, and the octave in,
373–376, 374–376 (figure)
timbre in, 378–379, 379 (figure)
Acoustics of phonemes, 347–348 (figure),
347–355, 350–353 (figure)
Action, 8, 8 (figure), 242–246
Active electroreception, 425–426
Acuity, visual, 70
infant, 72–73, 73 (figure)
Adaptation, dark and light, 70–72,
71 (figure), 72 (figure)
Additive color mixing, 157–158,
157–158 (figure)
A-delta fibers, 409
Afferent fibers, 407
Affordances, 242–246, 243 (figure)
Aftereffects, 10, 10 (figure)
motion, 239–240, 240 (figure)
Afterimages, 164–165
Ageusia, 455
Aging
basilar membrane of ear and, 306
color perception and, 169
hearing loss with, 306–307
Agnosia, 18
object, 109, 124, 139
tactile, 421–422
topographic, 140
Airplane pilots, motion perception in,
249–250
Airport screening, 145–147, 146 (figure),
270 (figure)
Akinetopsia, 239
Ames room illusion, 215–216, 216 (figure)
Amplitude and loudness, 292–294,
293–294 (figure)
Ampulla, 423
Ampullae of Lorenzini, 426
Amusia, 18
Amygdala, 441
Analgesia, 417
Animacy, 143–145, 143–145 (figure)
Animals
affordances and, 242–246, 243 (figure)
awareness in, 279 (figure)
biosonar in, 331–334, 332–334 (figure)
electroreception in, 425–426, 426 (figure)
eyes of, 82–83 (figure), 82–84
Anomalous trichromacy, 173–174, 174 (table)
Anosmia, 440, 453–455
Anterior chamber of eye, 60
Anterior cingulate cortex, 416
Anterior insular cortex, 450
Anterior intraparietal (AIP) area, 246
Anterior piriform cortex, 442
Aphasia, 359
Apparent motion, 230–231 (figure), 230–232
Architectural acoustics, 335
Aristotle, 10
Aristotle illusion, 10, 10 (figure)
Armstrong, Louis, 378, 378 (figure)
Artificial sweeteners, 455–457, 456 (figure)
Ascending series, 31
Astigmatism, 79–80, 80 (figure)
Atmospheric perspective, 194–195,
195 (figure)
Attack, 379
Attention
anatomy and physiology of, 272–277,
273–277 (figure)
attentional blink and rapid serial visual
presentation, 270–272, 271 (figure)
awareness and visual consciousness,
279–282, 279–282 (figure)
covert, 259–260, 260 (figure)
defined, 257
developmental aspects of, 278–279
and direction of gaze in space, 259–262,
259–262 (figure)
divided, 258, 258 (figure)
effects on the visual brain, 274–275,
275 (figure)
feature integration theory, 267,
268 (figure)
inattentional blindness and, 262–264,
263–264 (figure), 265 (figure)
infants and, 278–279, 278–279 (figure)
introduction to, 255–257, 256–257 (figure)
neuropsychology of, 275–277,
276–277 (figure)
over time, 268–272, 269–271 (figure)
selective, 258
spatial limits of, 259–264, 259–264 (figure)
spotlight model of, 261, 262 (figure)
stimulus features that draw, 264–267,
265–266 (figure)
visual search and, 266–267, 267 (figure),
268 (figure)
Attentional blink, 270–272, 271 (figure)
Attentional capture, 265, 265 (figure),
266 (figure)
Audiograms, 47, 47 (figure)
Audiologists, 46, 47 (figure)
Audiometers, 47
Auditory brain
anatomy and pathway of hearing in,
318–321, 319–321 (figure)
auditory scene analysis, 326–330,
327–331 (figure)
introduction to, 317–318, 318 (figure)
localizing sound, 321–326,
322–326 (figure)
neuroanatomy of music and, 384–385,
384–385 (figure)
speech perception and, 358–362,
359–362 (figure)
Auditory core region, 320
Auditory cortex, 320–321, 321 (figure)
Auditory development, 330
Auditory nerve fibers, 318–320,
319–320 (figure)
Auditory system, 7, 289–290, 290 (figure)
anatomy of the ear and, 298–306,
298–306 (figure)
hearing loss and, 306–308
sound as stimulus and, 290–297,
290–297 (figure)
tests of, 45–49
See also Auditory brain
Auto collisions, 21–22
Automaticity, 258
Awareness and visual consciousness,
279–282, 279–282 (figure)
Axel, Richard, 439–440
Azimuth, sound, 322
Balance, perception of, 423–425, 424 (figure)
Bálint’s syndrome, 277
Basal cells, 438
Basilar membrane of the cochlea, 302–304,
302–304 (figure)
Bats, biosonar in, 331–334, 332–334 (figure)
Beat, 378
Bell, Joshua, 255–256, 256 (figure)
Belt and parabelt regions, 320
Benham’s top, 13, 13 (figure)
Biases, personal, 3–4
Binocular cells, 209–210
Binocular cues to depth, 200–201
Binocular disparity, 201, 201 (figure)
Binocular rivalry, 280–281, 280 (figure)
Biosonar in bats and dolphins, 331–334,
332–334 (figure)
Bistability, 280–281, 280–282 (figure)
Bistratified retinal ganglion cells (K cells), 95
Blindness
change, 268–270, 269–270 (figure)
inattentional, 262–264, 263–264 (figure),
265 (figure)
repetition, 272
smell, 440
Blindsight, 113–116, 115 (figure),
282, 282 (figure)
Blobs, V1, 105
Bottom-up processing, 126–128,
127–128 (figure)
Braille, 420–421, 420 (figure)
Braille, Louis, 420
Brain, auditory
anatomy and pathway of hearing in,
318–321, 319–321 (figure)
auditory scene analysis, 326–330,
327–331 (figure)
introduction to, 317–318, 318 (figure)
Subject Index 501
localizing sound, 321–326,
322–326 (figure)
neuroanatomy of music and, 384–385,
384–385 (figure)
speech perception and, 358–362,
359–362 (figure)
Brain, visual, 91–92
anatomy and physiology of attention
and, 272–277, 273–277 (figure)
blindsight and, 113–116, 115 (figure)
conjugate gaze palsy and, 116–117
damage and neuropsychology, 18
development of vision and, 111–113
executive attention network, 273–274,
274 (figure)
functional pathways in visual cortex of,
107–110, 108–109 (figure)
how attention affects, 274–275,
275 (figure)
lateral geniculate nucleus, 94–98,
95–97 (figure)
lobes, 100, 100 (figure)
mapping the eye on the, 101–102,
101–102 (figure)
MT as movement area of, 236–239,
237–239 (figure)
object perception in, 137–142,
137–142 (figure)
optic nerve and chiasm, 92–94, 93 (figure)
orienting attention network, 273,
273 (figure)
primary visual cortex, 99–106
superior colliculus, 98–99, 98 (figure)
V2 and beyond, 106–107, 106 (figure)
where vision comes together in, 111
Brain pathways
in olfaction, 440–443
in pain, 410–416, 411–416 (figure)
Brightness, 156
Broca, Pierre, 359, 359 (figure)
Broca’s aphasia, 359
Broca’s area, 359
Buck, Linda, 439–440
Capsaicin, 27, 28 (figure)
Cataracts, 80
Catch trials, 35–36
Categorical perception, 349–351, 350 (figure)
Cats
affordances and, 242–246, 243 (figure)
awareness in, 279 (figure)
eyes of, 82–83, 82–83 (figure)
Center-surround receptive fields,
74, 75 (figure)
C-fibers, 409
Change blindness, 268–270, 269–270 (figure)
Characteristic frequency, 303
Chili peppers, 452–453, 452 (figure)
Chroma, 375
Ciliary muscles, 61
Circumvallate papillae, 449
Closure (music), 383, 383 (figure)
Coarticulation, 348–349, 348 (figure)
Cochlea, 302, 302 (figure)
basilar membrane of, 302–304,
302–304 (figure)
Cochlear duct, 302
Cochlear implants, 308–311, 309–311 (figure)
Cochlear nucleus, 319
Cognitive impenetrability, 20
Cognitive penetration, 19–21
Cold fibers, 408
Collisions, 21–22
Color, complementary, 165
Color circle, 156, 156 (figure)
Color constancy, 175–177, 175–177 (figure)
Color deficiency, 169–175, 170 (figure),
172 (table), 173 (figure), 174 (table)
Color-matching experiments, 158–159,
159 (figure)
Color-music synesthesia, 386, 386 (figure)
Color-opponent cells, 167, 167 (figure)
Color perception, 151–153
additive and subtractive color mixing
and, 156–160, 157–159 (figure)
aging and, 169
constancy in, 175–178, 175–178 (figure)
deficiency, 169–175, 170 (figure),
172 (table), 173 (figure), 174 (table),
180–181, 180–181 (figure)
development of, 168–169, 168 (figure)
hue, saturation, lightness, and brightness
in, 155–156, 155–156 (figure)
opponent-process theory of, 163–167,
163–167 (figure)
purple, 178–179, 179 (figure)
retina and, 160–162, 161 (figure)
trichromatic theory of color vision and,
162–163, 163 (figure)
wavelengths of light and color and,
153–155, 154 (figure)
Comic books, 129, 129 (figure)
Complementary colors, 165
Complex cells, V1, 103–104, 103–104 (figure)
Complex sounds, 296
Compound eye, 83–84, 84 (figure)
Computational approach, 16–17
Computerized tomographic (CT) scans, 42
Computer speech recognition, 364–366,
365 (figure)
Concert hall acoustics and hearing,
335–336, 335 (figure)
Conductive hearing loss, 46, 307
Cone of confusion, 324, 325 (figure)
Cone-opponent cells, 166–167
Conjugate gaze palsy, 116–117
Conjunction search, 267
Consonance and dissonance, 376–377
Consonants and vowels, 343–344,
344 (figure)
Constructivist approach, 11
Continuation (music), 383
Contralateral organization, 93
Contralateral representation of visual
space, 93
Contralateral side, 412
Convergence, 70, 199–200, 200 (figure)
Convexity, 132, 132 (figure)
Cornea, 59, 59 (figure)
Corollary discharge theory, 234–235,
234–235 (figure)
Correct rejection, 37
Correspondence problem, 206
motion and, 231, 231 (figure)
Corresponding points, 202–206,
203–205 (figure)
Cortical achromatopsia, 174–175
Cortical magnification, 101
Covert attention, 259–260, 260 (figure)
Cribriform plate, 440
Crista, 423
Criterion, 37, 40
Crossed disparity, 203
Crossover point, 31
Cue approach to depth perception, 189
Culture and music perception, 389–391,
390–391 (figure)
Cycles, 291
Dark adaptation, 70–72, 71 (figure),
72 (figure)
Decay, 379
Decibels (dB), 293–294
Deletion, 197, 198 (figure)
Depth, visual illusions of, 213–217
Depth perception
binocular cues to, 200–201
cue approach to, 189
introduction to, 187–189, 188 (figure)
monocular depth cues to, 189–199,
190–198 (figure)
oculomotor cues to, 199–200, 200 (figure)
stereograms and, 207–210 (figure),
207–211
Dermis, 403
Descending series, 31
Detection
of distance, 325–326
olfactory, 443–444
Deuteranopia, 172–173
Dichromacy, 172–174, 173 (figure),
174 (table), 180–181, 180–181 (figure)
Difference threshold, 30
Diplopia, 203
Direct perception, 15
Dishabituation, 168
Dissonance and consonance, 376–377
Distance, sound, 322
detecting, 325–326
Distracted driving, 256 (figure), 282–283
Divided attention, 258, 258 (figure)
Doctrine of specific nerve energies, 11
Dolphins, biosonar in, 331–334, 332 (figure)
Doppler shifts, 333, 334 (figure)
Dorsal attention network, 273, 273 (figure)
Dorsal column-medial lemniscal
pathway, 412
Dorsal horn, 415
Dorsal pathway, 107, 109 (figure), 110
Dorsal root ganglion, 411–412, 411 (figure)
Double-opponent cells, 167
Driving, distracted, 256 (figure), 282–283
Dual-stream model of speech perception,
360–361, 360 (figure)
Dual-target cost, 146
Duplex theory of vision, 68–73
Dynamics and rhythm, 377–378,
378 (figure)
Sensation and Perception502
Ear(s)
anatomy of, 298–306, 298–306 (figure)
basilar membrane of the cochlea,
302–304, 302–304 (figure)
inner, 301–302, 301 (figure)
middle, 299–301, 300 (figure)
organ of Corti, 303, 304–306, 305 (figure)
outer, 298, 299 (figure)
piercing of, 325, 326 (figure)
protection of, 290 (figure)
See also Auditory system
Ebbinghaus, Hermann, 13
Ecological approach to perception, 15
Edge completion, 134–135, 134 (figure)
Edge detection/enhancement, 74, 76–77,
77 (figure)
Electroencephalography (EEG), 43
Electromagnetic energy, 55
Electromagnetic spectrum, 56, 56 (figure)
Electroreception in fish, 425–426,
426 (figure)
Elevation, sound, 322
perception, 325, 325 (figure)
Endogenous opioids, 417
Endolymph, 423
End-stopped neurons, 104
Entorhinal cortex, 441
Epidermis, 403
Equal-temperament scale, 376
Eustachian tube, 300
Executive attention network, 273–274,
274 (figure)
External auditory canal, 298
External auditory meatus, 298
Extrastriate body area, 140
Eye(s), 57–62
anatomy of, 58–61, 59–61 (figure)
in animals, 82–83 (figure), 82–84
emerging and aging of, 61–62
field of view of, 58, 58 (figure)
lens of, 60–61, 61 (figure)
mapping on the brain, 101–102,
101–102 (figure)
movements of, 235–236
refractive errors and diseases of, 77–81
retina of, 59 (figure), 62–68, 62 (figure)
vision prostheses for, 85–86, 86 (figure)
visually guided movements of, 244–245,
245 (figure)
See also Visual system
Face agnosia, 18
FAII mechanoreceptors, 404, 405 (figure), 406
FAI mechanoreceptors, 404, 405–406,
405 (figure)
False alarms, 37, 37 (figure), 41 (figure), 42
Familiar size, 192–193, 192–193 (figure)
Farsightedness, 78–79, 79 (figure)
Feature integration theory, 267, 268 (figure)
Feature search, 267
Fechner, Gustav, 12–13, 12 (figure)
Field of view, 58, 58 (figure)
Figure-ground organization, 129–131,
129–131 (figure)
Filiform papiallae, 449
First cranial nerve, 441
Fish, electroreception in, 425–426,
426 (figure)
Fisher, M. F. K., 447
Five-sense approach, 4–5, 4 (table)
Flavor, 447, 451, 451 (figure)
See also Taste
Foliate papillae, 449
Forced-choice method, 36, 36 (figure)
Formants, 343–344, 344 (figure)
Form perception and biological motion,
241–242, 241–242 (figure)
Fourier analysis, 296
Fovea, 64–65
Frequency, wave, 55
Frequency and pitch, 294–295, 295 (figure)
Functional MRI (fMRI), 18–19, 19 (figure), 43
Fundamental frequency, 296
Fungiform papillae, 449
Furrow illusion, 248–249, 249 (figure)
Fusiform face area (FFA), 110, 138–139,
138 (figure), 139 (figure)
Gate control theory, 415, 416 (figure)
Gaze in space, 259–262, 259–262 (figure)
Gelb effect, 178
General-mechanism theories, 355–356
Genes
olfaction and, 439–440
taste perception and, 451
Geons, 136, 136 (figure)
Gestalt psychology, 13–15
figure-ground organization in, 129–131,
129–131 (figure)
laws of, 14 (figure)
laws of perceptual grouping, 132–134,
132–134 (figure)
melody and, 381–383
perceptual interpolation and, 134–135,
134–135 (figure)
perceptual organization and, 128–135,
129–135 (figure)
rules that govern what we see as figure
and what we see as ground in,
131–132, 131–132 (figure)
Gibsonian approach, 15
Glomeruli, 441
Golgi tendon organs, 407
Grandmother cells, 140–142
Grasping, visually guided, 245–246
Grouping, 128, 128 (figure)
laws of perceptual, 132–134,
132–134 (figure)
Gustation, 436
Habituation, 168
Hair cells, 304
Hand clapping, 290–291, 291 (figure)
Haptic reception, 419–420 (figure), 419–422
Harmonic coherence, 329
Harmonics, 296
Harmony, 377
Hearing aids, 308–311, 309–311 (figure)
Hearing loss, 306–308
conductive, 46, 307
music perception with, 394–396,
395–396 (figure)
sensorineural, 46, 307–308
speech perception and, 362–364
Helmholtz, Hermann von, 11–12, 11 (figure),
162–163, 163 (figure)
Hemifield neglect, 276–277, 277 (figure)
Hering, Ewald, 12, 12 (figure), 164
Hertz (Hz), 294–295
Heterochromatic light, 153
Heterochromia, 60
Hit, 37
Homunculus, 414
Hooke, Robert, 11
Horopter, 202–203, 204 (figure)
Hubel, David, 91–92, 92 (figure)
Hue, 155–156
cancellation, 165–166, 166 (figure)
Human voice as stimulus, 342–347,
343–345 (figure), 346 (table)
Hyperocolumns, V1, 105, 105 (figure)
Hyperopia, 78–79, 79 (figure)
Hyperpolarization, 67
Illusions
motion, 246–249, 247–249 (figure)
musical, 391–394, 392–394 (figure)
octave, 392, 393 (figure)
olfactory, 445–446
scale, 393, 393 (figure)
Illusory contours, 135, 135 (figure)
Illusory rotation, 248, 248 (figure)
Imagery, odor, 445
Inattentional blindness, 262–264,
263–264 (figure), 265 (figure)
Incus, 299
Induced motion, 231–232
Infants
attention in, 278–279, 278–279 (figure)
auditory development in, 330
color perception in, 168–169, 168 (figure)
phoneme perception in, 357–358
stereopsis in, 210–211
taste development in, 453, 453 (figure)
visual acuity in, 72–73, 73 (figure)
Inferior colliculus, 319
Inferotemporal area, 137–138, 137 (figure)
Inferotemporal cortex, 109, 140–142
Information-processing approach, 15–16,
16 (figure)
Inner ear, 301–302, 301 (figure)
Inner hair cells, 304
Insula, 450
Intensity, wave, 55
Interaural level difference, 324, 324 (figure)
Interaural time difference, 322–323,
323 (figure)
Interblobs, V1, 105
International Phonetic Alphabet, 346–347,
346 (table)
Internuclear ophthalmoplegia, 117
Interpolation, perceptual, 134–135,
134–135 (figure)
Intersensory perception, 44–45, 45 (figure)
Ipsilateral organization, 93
Subject Index 503
Iris of eye, 60, 60 (figure)
Ishihara plate, 170, 170 (figure)
Itch, 418, 418 (figure)
James, William, 13
Joint receptors, 406–407
Just-noticeable difference (JND), 12–13,
28, 30
Kanizsa triangle, 13–14, 14 (figure)
Keys and scales, 380–381
Knowledge influence on perception and
sensation, 4
Koffka, Kurt, 128
Köhler, Wolfgang, 15, 15 (figure), 128
Koniocellular layers, 94–95
Koniocellular pathway (K pathway), 96
Kuffler, Stephen, 74, 82, 91–92
Language and music, 388–389
Larynx, 343, 343 (figure)
Lateral geniculate nucleus, 94–98,
95–97 (figure)
opponent cells in, 166–167, 167 (figure)
Lateral inhibition, 76–77
Lateral intraparietal (LIP) area, 245,
245 (figure)
Law of closure, 14 (figure)
Law of common fate, 14 (figure), 134
Law of good continuation, 14 (figure),
133, 133 (figure)
Law of proximity, 14 (figure), 133
Law of similarity, 14 (figure), 133, 133 (figure)
Law of symmetry, 133–134, 134 (figure)
Laws of perceptual grouping, 132–134,
132–134 (figure)
L-cone, 160–161, 161 (figure)
Lens of eye, 60–61, 61 (figure)
Light, 55–57, 57 (figure)
adaptation, 71–72
color and wavelengths of, 153–155,
154 (figure)
mixing, 157–158, 157–158 (figure)
transduction of, 6, 66–67
Lightness, 156
Lightness constancy, 177–178, 178 (figure)
Linear perspective, 193–194, 193–194 (figure)
Localizing of sound, 321–326,
322–326 (figure)
Loudness and amplitude, 292–294,
293–294 (figure)
Mach, Ernst, 76
Mach bands, 76, 77 (figure)
Macrosmatic species, 439
Macula, 64, 423
Macular degeneration, 80, 81 (figure)
Magnetic resonance imaging (MRI), 18,
43, 43 (figure)
Magnetoencephalography (MEG),
42 (figure), 43
Magnitude estimation, 34–35, 35 (table)
Magnocellular layers, 94–95
Magnocellular pathway (M pathway), 96
Malleus, 299
Manner of articulation, 344
“Mary Had a Little Lamb,” 381
McGurk effect, 351–352, 351–352 (figure)
M-cone, 160, 161 (figure)
Mechanoreception, 404–406, 405 (figure)
Medial geniculate nucleus, 319
Medial intraparietal (MIP) area, 246
Melody, 380–383, 380 (figure),
382–383 (figure)
Metamer, 159, 159 (figure)
Meter, 378
Method of adjustment, 33–34
Method of constant stimuli, 32–33,
33 (figure)
Method of limits, 29–32, 30 (figure)
Microelectrodes, 17
Microsomatic species, 439
Middle canal, 302
Middle ear, 299–301, 300 (figure)
Midget retinal ganglion cells (P cells), 95
Mitral cells, 441
Monochromacy, rod and cone, 171–172,
172 (table)
Monochromatic light, 153
Monocular depth cues, 189–199,
190–198 (figure)
atmospheric perspective, 194–195,
195 (figure)
familiar size, 192–193, 192–193 (figure)
linear perspective, 193–194,
193–194 (figure)
motion cues, 196–199, 197–198 (figure)
occlusion, 190, 190 (figure)
relative height, 191, 191 (figure)
relative size, 191–192
shadows and shading, 195–196,
196 (figure)
texture gradients, 194, 194 (figure)
Moon illusion, 216–217, 217 (figure)
Motion
aftereffects, 239–240, 240 (figure)
airline pilots and perception of, 249–250
complexity of, 232–233, 233–234 (figure)
corollary discharge theory, 234–235,
234–235 (figure)
defined, 228
eye movements, 235–236
form perception and biological, 241–242,
241–242 (figure)
how we perceive, 228–232,
229–231 (figure)
illusions of, 246–249, 247–249 (figure)
induced, 231–232
MT as movement area of the brain and,
236–239, 237–239 (figure)
neuroscience of vision and, 232–240,
233–235 (figure), 237–240 (figure)
real and apparent, 230–231 (figure),
230–232
Motion blindness, 239
Motion cues, 196–199, 197–198 (figure)
Motion parallax, 196–197, 197 (figure)
Motion thresholds, 228–229, 229 (figure)
Motor theory of speech perception, 355
Movement-based cues, 189, 190 (figure)
MT (middle temporal) region, 110
as movement area of the brain, 236–239,
237–239 (figure)
Mueller, Johannes, 11
Müller-Lyer illusion, 214–215, 214 (figure),
215 (figure)
Muscle spindles, 406
Music
acoustics of, 373–383, 374–376 (figure),
378–380 (figure), 382–383 (figure)
introduction to, 371–373, 371–373 (figure)
language and, 388–389
learning, culture, and perception of,
388–391
neuroanatomy of, 384–385,
384–385 (figure)
neuropsychology of, 386–388, 387 (figure)
neuroscience of, 383–388,
384–387 (figure)
perception in hearing-impaired listeners,
394–396, 395–396 (figure)
synesthesia, 385–386, 386 (figure)
Musical illusions, 391–394, 392–394 (figure)
Musical notation, 380, 380 (figure)
Myopia, 48–49, 78, 78 (figure)
Narrowing, perceptual, 357–358
Nasal septum, 437–438
Nautilus, 83, 83 (figure), 84 (figure)
Near point (eye focus), 61, 61 (figure)
Nearsightedness, 48–49, 78, 78 (figure)
Necker cube, 135, 135 (figure)
Neural pathways of pain, 410–416,
411–416 (figure)
Neural response, 6–7, 7 (figure)
Neurochemistry of pain, 417
Neuroimaging, 18
Neuroimaging techniques, 42–43,
42–43 (figure)
Neuropsychology, 18
of attention, 275–277, 276–277 (figure)
of music, 386–388, 387 (figure)
Neuroscience
of music, 383–388, 384–387 (figure)
in sensation and perception, 17–19
of vision and motion, 232–240,
233–235 (figure), 237–240 (figure)
Neurotransmitters, 67
Nociception, 409–410, 410 (figure)
Nociceptors, 409
Noncorresponding points, 202–206,
203–205 (figure)
Nontasters, 451, 452 (figure)
Nose, 437–439, 438–439 (figure)
Object agnosia, 109, 124, 139
Object perception, 123–124
airport screening and, 145–147,
146 (figure)
animacy and, 143–145, 143–145 (figure)
gestalt psychology, 128–135,
129–135 (figure)
introduction to, 124–126, 124–126 (figure)
neuroanatomy and physiology of,
137–142, 137–142 (figure)
Sensation and Perception504
recognition by components,
136, 136 (figure)
top-down processing and bottom-up
processing, 126–128,
127–128 (figure)
Occipital face area (OFA), 138, 138 (figure)
Occlusion, 190, 190 (figure)
Octave, 375, 375 (figure)
Octave illusion, 392, 393 (figure)
Ocular dominance columns, V1, 104
Oculomotor cues, 199–200, 200 (figure)
Oddball procedure, 278
Odors, 436, 437 (figure)
identifying, 444–445, 444–445 (figure)
imagery, 445
Off-center receptive fields, 75
Old-sightedness, 61, 61 (figure), 62, 78–79
Olfaction, 436, 437 (figure)
anatomy and physiology, 437–443
brain pathways, 440–443
genes and, 439–440
identifying odors, 444–445,
444–445 (figure)
illusions, 445–446
introduction to, 435–436
perception, 443–446
trigeminal nerve, 440
Olfactory bulb, 441, 442 (figure)
Olfactory cleft, 438
Olfactory epithelium, 438, 439 (figure)
Olfactory nerve, 441
Olfactory receptor neurons, 438
Olfactory tract, 441
On-center receptive fields, 75
Opioids, endogenous, 417
Opponent-process theory of color
perception, 163–167, 163–167 (figure)
Opsins, 66, 66 (figure)
Optic disc, 65
Optic flow, 198–199, 198 (figure)
Optic nerve and chiasm, 92–94, 93 (figure)
Optic tract, 93
Optometrists, 29, 29 (figure), 48
Orbitofrontal cortex, 443
Organ of Corti, 303, 304–306, 305 (figure)
Orientation columns, V1, 104
Orienting attention network, 273, 273 (figure)
Orienting tuning curves, 103
Ossicles, 299–300
Otolith organs, 423
Otosclerosis, 307
Outer ear, 298, 299 (figure)
Outer hair cells, 304
Pain. See Touch and pain
Paints, mixing, 158, 158 (figure)
Paley, William, 58
Panum’s area of fusion, 203
Papillae, 449
Parahippocampal place area (PPA),
140, 140 (figure)
Parasol retinal ganglion cells (M cells), 95
Parietal insular vestibular cortex, 425
Parvocellular layers, 94
Parvocellular pathway (P pathway), 96
Passive electroreception, 425
Patient T. N., 113–116
Penfield, Wilder, 413
Perception
basics of, 5–9
biases in, 3–4
categorical, 349–351, 350 (figure)
color (See Color perception)
defined, 5
depth (See Depth perception)
differentiated from sensation, 5–6
direct, 15
elevation, 325, 325 (figure)
history of, 9–23
intersensory, 44–45, 45 (figure)
introduction to, 1–3
knowledge influence on, 4
music (See Music)
myth of the five senses and, 4–5,
4 (table)
neuroscience in, 17–19
object (See Object perception)
as part of psychology, 3–4
size, 211–212
speech (See Speech perception)
Perceptual bistability, 280–281,
280–282 (figure), 280 (figure)
Perceptual interpolation, 134–135,
134–135 (figure)
Perceptual narrowing, 357–358
Perceptual organization, 128, 128 (figure)
gestalt psychology and, 128–135,
129–135 (figure)
Perilymph, 303
Phantom limbs, 427–428
Phantosmia, 455
Pharynx, 343, 343 (figure)
Phase, sound, 297, 297 (figure)
Phenomenology, 8–9, 8 (figure)
Phonemes, 345, 346 (table)
perception, development of, 357–358
variability in the acoustics of,
347–348 (figure), 347–355,
350–353 (figure)
Phonemic restoration effect, 353–355
Photons, 56–57
Photopic system, 68, 69 (table)
Photopigments, 66–67, 67 (figure)
Pictorial cues, 189, 190 (figure)
Piercing, ear, 325, 326 (figure)
Pinna, 298, 299 (figure)
Piriform cortex, 441, 442
Pitch, 373–376, 374–376 (figure)
frequency and, 294–295, 295 (figure)
Pitch class circle, 394, 394 (figure)
Place code theory, 305
Place of articulation, 344
Point-light walker display, 241, 242 (figure)
Point of subjective equality (PSE), 33
Ponzo illusion, 215, 215 (figure)
Pop-out search, 267
Posner cuing paradigm, 261, 261 (figure)
Posterior chamber of eye, 60
Posterior piriform cortex, 442
Presbycusis, 306–307
Presbyopia, 61, 61 (figure), 62, 78–79
Presynaptic cells, 449
Primary auditory cortex, 320–321,
321 (figure)
Primary visual cortex, 99–106
Private experience, phenomenology as, 9
Proprioception, 406–407, 407 (figure)
Prosopagnosia, 18, 139–140
Prostheses, vision, 85–86, 86 (figure)
Protanopia, 172, 173 (figure)
Proximity (music), 382
Pruriceptors, 418
Psychology
gestalt, 13–15, 128–135, 129–135 (figure)
information-processing approach in,
15–16
sensation and perception as, 3–4
Psychophysical scales, 27–29
catch trials and their use, 35–36
magnitude estimation, 34–35, 35 (table)
method of adjustment, 33–34
method of constant stimuli, 32–33,
33 (figure)
method of limits, 29–32
neuroimaging techniques, 42–43,
42–43 (figure)
signal detection theory, 36–37, 36–42,
37–42 (figure), 37 (figure), 37 (table),
39 (table)
Psychophysics, 12–13
in assessment, 45–49
discrimination in, 444–445
measures and methods of, 29–49
scales, 27–29
Pupillary reflex, 60, 60 (figure)
Pupils, 60
Pure tones, 292, 292 (figure)
Purkinje shift, 69–70
Purple (color), 178–179, 179 (figure)
Quality (of hue), 155
Random-dot stereograms, 208–209,
209 (figure)
Rapid serial visual presentation (RSVP),
270–272, 271 (figure)
Rate of approach, 333
Real and apparent motion, 230–231 (figure),
230–232
Receiver-operating characteristic (ROC)
curve, 41–42, 41 (figure)
Receptive fields (vision), 73–75 (figure),
73–77, 77 (figure)
Receptors, 6, 68, 69 (table), 449
Recognition, 127, 127 (figure)
by components, 136, 136 (figure)
Reichardt detectors, 233, 234 (figure)
Reintal (vitamin A), 66–67
Reissner’s membrane, 302
Relative height, 191, 191 (figure)
Relative size, 191–192
Repetition blindness, 272
Representation, 127, 127 (figure)
Response compression, 34
Response expansion, 34–35
Retina, 59 (figure), 62–68, 62 (figure)
anatomy of, 63, 63 (figure), 64 (table)
color and, 160–162, 161 (figure)
Subject Index 505
motion detection in, 232
physiology, 65–68
receptors, 64, 68, 69 (table)
Retinal ganglion cells, 73–75 (figure),
73–77, 77 (figure)
Retinal image, 62
Retinitis pigmentosa, 80–81, 81 (figure)
Retinoptic map, 101, 101 (figure)
Reverberation time, 335
Rhythm and dynamics, 377–378, 378 (figure)
Robots, 9
Rods and cones of eye, 64–65, 65 (figure)
monochromacy, 171–172, 172 (table)
wavelength sensitivity of, 68 (figure)
Rostral core, 320
Rostrotemporal core, 320
Rotating snakes illusion, 247–248, 247 (figure)
Round window, 302
Saccades, 99, 236
SAII mechanoreceptors, 404, 405,
405 (figure)
SAI mechanoreceptors, 404, 405,
405 (figure)
Salience, stimulus, 265–266
Saturation, 155–156, 155 (figure)
Scale illusion, 393, 393 (figure)
Scales and keys, 380–381
Scanning, 259, 259 (figure)
Sclera, 60
S-cone, 160, 161 (figure)
Scotoma, 114–115
Scotopic system, 68, 69 (table)
Scoville, Wilbur, 28
Scoville scale, 27–28, 28 (figure)
Search, visual, 266–267, 267 (figure),
268 (figure)
Segregation, 128, 128 (figure)
Selective attention, 258
Semicircular canals, 423
Semitones, 375
Sensation
biases in, 3–4
defined, 5
differentiated from perception, 5–6
history of, 9–23
introduction to, 1–3
knowledge influence on, 4
myth of the five senses and, 4–5
neuroscience in, 17–19
as part of psychology, 3–4
Senses, myth of five, 4–5, 4 (table)
Sensitivity, 34, 40 (figure), 41–42
Sensitivity of detection, 44–45, 45 (figure)
Sensorineural hearing loss, 46, 307–308
Sensory neurons, 17, 17 (figure)
Shadows and shading, 195–196, 196 (figure)
Shepard tones, 392, 392 (figure)
Signal detection theory, 36–42, 37–42 (figure),
37 (table), 39 (table)
Sign language, 306, 307 (figure)
Similarity (music), 382
Simple cells, V1, 103, 103 (figure)
Simultagnosia, 277
Simultaneous color contrast,
165, 165 (figure)
Size, visual illusions of, 213–217
Size-arrival effect, 22
Size constancy, 212–213, 213 (figure)
Size-distance invariance, 211–212
Size perception, 211–212
Skin, 403, 403 (figure)
mechanoreception, 404–406, 405 (figure)
proprioception, 406–407, 407 (figure)
thermoreception, 407–409, 408 (figure)
Smell blindness, 440
Smooth-pursuit eye movements, 98–99,
235 (figure), 236
Snellen chart, 48, 48 (figure)
Sobriety testing, 407, 407 (figure)
Somatosensory cortex, 413–414,
413–414 (figure)
suborganization of, 414–415, 415 (figure)
Somatotopic map, 414, 414 (figure)
Sound
amplitude and loudness of, 292–294,
293–294 (figure)
biosonar in bats and dolphins, 331–334,
332–334 (figure)
complex, 296
concert hall acoustics and hearing,
335–336, 335 (figure)
cone of confusion, 324, 325 (figure)
elevation perception, 325, 325 (figure)
frequency and pitch, 294–295,
295 (figure)
interaural level difference, 324,
324 (figure)
interaural time difference, 322–323,
323 (figure)
localizing, 321–326, 322–326 (figure)
phase, 297, 297 (figure)
phonemic restoration effect, 353–355
relation of physical and perceptual
attributes of, 292, 292 (figure)
spatial segregation, 329
spectral segregation, 329–330,
330 (figure), 331 (figure)
speed of, 291–292, 292 (figure)
as stimulus, 290–297, 290–297 (figure)
temporal segregation, 328–329,
328 (figure)
top-down processing, 126–128,
127–128 (figure), 352–353,
353 (figure)
waveform and timbre, 295–297,
296 (figure)
See also Auditory system
Sound waves, 55, 291, 291 (figure)
Spatial limits of attention, 259–264,
259–264 (figure)
Spatial segregation, 329
Spatial summation and acuity, 70
Special-mechanism theories, 355
Spectral reflectance, 153
Spectral segregation, 329–330, 330 (figure),
331 (figure)
Spectral sensitivity, 69–70
Spectral shape cue, 325
Speech, 344–347, 345 (figure), 346 (table)
computer recognition of, 364–366,
365 (figure)
Speech perception
and the brain, 358–362, 359–362 (figure)
effect of vision on, 351–352,
351–352 (figure)
hearing loss and, 362–364
human voice as stimulus and, 342–347,
343–345 (figure), 346 (table)
introduction to, 341–342
theories of, 355–358, 356 (figure)
top-down processing and, 352–353,
353 (figure)
vowels and consonants in, 343–344,
344 (figure)
Speed of sound, 291–292, 292 (figure)
Spinothalamic pathway, 413
Sports and stereopsis, 218–219, 219 (figure)
Spotlight model of attention, 261, 262 (figure)
Stapedius, 301
Stapes, 299
Stars, 31, 31 (figure)
Stereocilia, 304
Stereograms, 207–210 (figure), 207–211
Stereopsis, 200–201, 201–202 (figure)
developmental issues in, 210–211
sports and, 218–219, 219 (figure)
Steven’s power law, 35, 35 (figure), 35 (table)
Stimulus, 5
attention-drawing, 264–267,
265–266 (figure)
human voice as, 342–347,
343–345 (figure), 346 (table)
salience of, 265–266
sound as, 290–297, 290–297 (figure)
Stimulus onset asynchrony, 260
Substantia gelatinosa, 415
Subtractive color mixing, 158, 158 (figure)
Superior colliculus, 98–99, 98 (figure)
Superior olive, 319
Supertasters, 452
Supporting cells, 438
Symmetry, 131, 131 (figure)
Synesthesia, 385–386, 386 (figure)
Tactile agnosia, 421–422
Tapetum, 82
Target range, 333
Tastants, 447
Taste, 7, 447–448, 447–448 (figure)
anosmia and, 440, 453–455
artificial sweeteners and perception of,
455–457, 456 (figure)
of chili peppers, 452–453, 452 (figure)
coding and anatomy of the tongue,
448–450, 449–450 (figure)
flavor and, 451, 451 (figure)
perception, individual differences in,
451–452, 452 (figure)
perception development, 453, 453 (figure)
Taste buds, 449
Taste receptor cells, 449
Tasters, 451, 452 (figure)
Tectorial membrane, 304
Tempo, 377–378
Temporal code theory, 305
Temporal segregation, 328, 328 (figure)
Tensor tympani, 300–301
Sensation and Perception506
Texting while driving, 256 (figure), 282–283
Texture gradients, 194, 194 (figure)
Thermoreception, 407–409, 408 (figure)
Thermoreceptors, 408
Timbre, 378–379, 379 (figure)
waveforms and, 295–297, 296 (figure)
Time
attention over, 268–272, 269–271 (figure)
to collision, 22
reverberation, 335
Tinnitus, 308, 308 (figure)
Tip-of-the-nose phenomenon, 444
Tones, pure, 292, 292 (figure)
Tongue, 448–450, 449–450 (figure)
Tonotopic organization, 320
Top-down processing, 126–128,
127–128 (figure), 352–353, 353 (figure)
Topographic agnosia, 140
Touch and pain
haptic perception, 419–420 (figure),
419–422
introduction to, 401–403, 402 (figure)
mechanoreception, 404–406, 405 (figure)
neural pathways, 410–416,
411–416 (figure)
neurochemistry of, 417
nociception and perception of, 409–410,
410 (figure)
perception of itch and, 418, 418 (figure)
phantom limbs and, 427–428
proprioception, 406–407, 407 (figure)
skin and its receptors and, 403–410,
403 (figure), 405 (figure),
407–410 (figure)
somatosensory cortex, 413–415,
413–415 (figure)
thermoreception, 407–409, 408 (figure)
vestibular system and perception of
balance, 423–425, 424 (figure)
Trachea, 343, 343 (figure)
Transduction, 6, 66–67
Transmagnetic stimulation (TMS),
43, 43 (figure)
Transposition, 381
Trapezoid body, 319
Traveling wave, 303
Triangle, 135, 135 (figure)
Trichromatic theory of color vision,
162–163, 163 (figure)
Trigeminal nerve, 440
Tritanopia, 173
Tritone paradox, 394, 394 (figure)
Tuberous receptors, 426
Tufted cells, 441
Turbinates, 438
Two-point touch threshold, 31–32
Tympanic canal, 302
Tympanic membrane, 298
Unconscious inference, 11–12
Uncrossed disparity, 204
Unilateral dichromacy, 174
Unilateral visual neglect, 276–277,
277 (figure)
Unique colors, 166
Univariance, 161–162
Unvoiced consonant, 344
U.S.S. Vincennes, 37–39, 37 (figure)
Uvula, 343, 343 (figure)
Van Beethoven, Ludwig, 394–395,
395 (figure)
Vanilla, 443–444, 444 (figure)
Vehicle collisions, 21–22
Ventral pathway, 107, 109–110, 109 (figure)
object perception in, 137–142,
137–142 (figure)
See also Brain, visual
Ventral posterior nucleus of the
thalamus, 413
Vergence, 199–200, 200 (figure), 235–236
Veridicality, 6
Vestibular canal, 302
Vestibular complex, 425
Vestibular system, 423–425, 424 (figure)
Viewpoint invariance, 136
Virtual reality and therapy, 219–221,
220–221 (figure)
Virtual reality exposure therapy (VRET), 221
Visible spectrum, 153
Vision, neuroscience of motion and,
232–240, 233–235 (figure),
237–240 (figure)
Vision prostheses, 85–86, 86 (figure)
Visual angle, 212, 212 (figure)
Visual brain, 91–92
anatomy and physiology of attention
and, 272–277, 273–277 (figure)
blindsight and, 113–116, 115 (figure)
conjugate gaze palsy and, 116–117
damage and neuropsychology, 18
development of vision and, 111–113
executive attention network, 273–274,
274 (figure)
functional pathways in visual cortex of,
107–110, 108–109 (figure)
how attention affects, 274–275,
275 (figure)
lateral geniculate nucleus, 94–98,
95–97 (figure)
lobes, 100, 100 (figure)
mapping the eye on the, 101–102,
101–102 (figure)
MT as movement area of, 236–239,
237–239 (figure)
object perception in, 137–142,
137–142 (figure)
optic nerve and chiasm, 92–94,
93 (figure)
orienting attention network, 273,
273 (figure)
primary visual cortex, 99–106
superior colliculus, 98–99, 98 (figure)
V2 and beyond, 106–107, 106 (figure)
where vision comes together in, 111
Visual capture, 428
Visual consciousness and awareness,
279–282, 279–282 (figure)
Visual detection, 38
Visual illusions of size and depth, 213–217
Visually guided eye movements, 244–245,
245 (figure)
Visually guided grasping, 245–246
Visual search, 266–267, 267 (figure),
268 (figure)
Visual spectrum, 153
Visual system, 7, 53
development of, 111–113
duplex theory of vision and, 68–73
light and, 55–57
refractive errors and diseases of the
eye, 77–81
retinal ganglion cells and receptive
fields, 73–75 (figure), 73–77,
77 (figure)
role of the eye in, 57–62
as source of joy, 54, 54 (figure)
tests of, 45–49
vision prostheses for, 85–86, 86 (figure)
See also Eye(s)
Voice area, 361, 361 (figure)
Voice box, 343, 343 (figure)
Voiced consonant, 344
Voicing, 344
Voicing-onset time, 349–350, 350 (figure)
Von Békésy, Georg, 305, 306 (figure)
Vowels and consonants, 343–344,
344 (figure)
V1 region, 101–102, 101–102 (figure)
belt and parabelt regions, 321
complex cells, 103–104, 103–104 (figure)
opponent cells in, 166–167, 167 (figure)
organization of, 104–106, 105 (figure)
receptive fields, 102
simple cells, 103, 103 (figure)
V2 region, 106–107, 106 (figure)
V4 region, 137
attention and, 275, 275 (figure)
cortical achromatopsia and, 174–175
V5 region, 110
Warm fibers, 408–409
Waterfall illusion, 10 (figure), 239–240,
240 (figure)
Waveform and timbre, 295–297,
296 (figure)
Wavelength, 55–56, 56 (figure)
of light and color, 153–155, 154 (figure)
Waves, sound, 55, 291, 291 (figure)
traveling, 303
Weber, Ernst Heinrich, 12, 31
Weber’s law, 12–13
Wernicke, Carl, 359, 359 (figure)
Wernicke’s aphasia, 360
Wernicke’s area, 359–360, 359 (figure)
Wertheimer, Max, 128, 132–133
Wiesel, Torsten, 91–92, 92 (figure)
Windpipe, 343, 343 (figure)
Word segmentation, 353
Wundt, Wilhelm, 13
Young, Thomas, 11, 162–163, 163 (figure)
Zero disparity, 204
Zonule fibers, 61
SENSATION & PERCEPTION- FRONT COVER
SENSATION & PERCEPTION
COPYRIGHT
BRIEF CONTENTS
DETAILED CONTENTS
ISLE ACTIVITIES
PREFACE
ACKNOWLEDGMENTS
ABOUT THE AUTHORS
CHAPTER 1- WHAT IS PERCEPTION?
CHAPTER 2- RESEARCH METHODOLOGY
CHAPTER 3- VISUAL SYSTEM: THE EYE
CHAPTER 4- VISUAL SYSTEM: THE BRAIN
CHAPTER 5- OBJECT PERCEPTION
CHAPTER 6- COLOR PERCEPTION
CHAPTER 7- DEPTH AND SIZE PERCEPTION
CHAPTER 8- MOVEMENT AND ACTION
CHAPTER 9- VISUAL ATTENTION
CHAPTER 10- THE AUDITORY SYSTEM
CHAPTER 11- THE AUDITORY BRAIN AND SOUND LOCALIZATION
CHAPTER 12- SPEECH PERCEPTION
CHAPTER 13- MUSIC PERCEPTION
CHAPTER 14- TOUCH AND PAIN
CHAPTER 15- OLFACTION AND TASTE
GLOSSARY
REFERENCES
AUTHOR INDEX
SUBJECT INDEX
Order an Essay Now & Get These Features For Free:
Turnitin Report
Formatting
Title Page
Citation
Outline
