Brains as Engines of Association

Dale Purves is Geller Professor of Neurobiology Emeritus at Duke University, where he moved in 1990 as the founding chair of the Department of Neurobiology. He was subsequently Director of Duke's Center for Cognitive Neuroscience and the Director of the Neuroscience and Behavioral Disorders Program at the Duke-NUS Graduate Medical School in Singapore. His research has sought to explain why we see and hear what we do. He is a member of the National Academy of Sciences, the American Academy of Arts and Sciences, and the National Academy of Medicine.

Preface

PART I. What Nervous Systems Do for Animals

Chapter 1. Putting the Question in Perspective
Introduction
Life on Earth
Defining life
Energy
Evolution
Mechanisms
Teleology
Conclusion
Suggested Reading

Chapter 2. Organisms without Nervous Systems
Introduction
Bacteria
Protists
Plants
The general strategy
Conclusion
Suggested Reading

Chapter 3. Organisms with Nervous Systems
Introduction
Defining nervous systems
The emergence of nervous systems
The emergence of central nervous systems
What do nervous systems add?
What do brains add?
Conclusion
Suggested Reading

PART II. Neural Systems as Engines of Association

Chapter 4. The Organization of Nervous Systems
Introduction
Stimuli
Pre-neural processing
Neural processing
Behavioral output
Neural systems and subsystems are interactive
Conclusion
Suggested Reading

Chapter 5. The Problem
Introduction
Vision as an example
The basic challenge
The answer in general terms
Qualia determined by empirical ranking
Perceptual discrepancies
Mechanisms
Other modalities
The meaning of 'illusions'
Conclusion
Suggested Reading

Chapter 6. Neural Associations
Introduction
Associations wrought be evolution
Associations wrought by lifetime learning
Associations wrought by culture
Behavioral categories of associations
Reward
Behavioral responses as reflexes
What gets associated?
Counterarguments
Conclusion
Suggested Reading

PART III. Evidence that Neural Systems Operate EMPIRICALLY

Chapter 7. Evidence from Lightness and Color
Introduction
Luminance and lightness
Analyzing the occurrence of luminance patterns
Effects of other luminance patterns
Spectral energy and color
The general strategy
Conclusion
Suggested Reading

Chapter 8. Evidence from Geometry
Introduction
Seeing intervals
Seeing angles
Seeing object sizes in 2-D
Seeing object sizes in 3-D
Seeing stereo depth
Conclusion
Suggested Reading

Chapter 9. Evidence from Motion
Introduction
Apparent motion
The perception of speed
Implications for the perception of time
The perception of direction
Conclusion
Suggested Reading

Chapter 10. Evidence from Audition
Introduction
Sound signals
Sources of tones
Sound signal spectra
The problem in audition
An empirical approach
Evidence from speech
Evidence from music
Implications for any sensory system
Conclusion
Suggested Reading

PART IV. alternative Concepts Neural Function

Chapter 11. The Major Options
Introduction
Neural function as feature detection
Neural function as statistical inference
Neural function as efficient coding
Neural function as computation
Conclusion
Suggested Reading

Chapter 12. Summing Up
Introduction
A way around some fundamental obstacles
Empirical ranking
Insight from games
Artificial intelligence
Consequences for neuroscience
The status of reasoning
Novel situations
Choice
Culture
The frequency of stimuli
Conclusion
Suggested Reading

Bibliography
Glossary
Index
Acknowledgments