Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics

Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics

by Paul W. Glimcher
     
 

ISBN-10: 0262072440

ISBN-13: 9780262072441

Pub. Date: 03/01/2003

Publisher: MIT Press

In this provocative book, Paul Glimcher argues that economic theory may provide an alternative to the classical Cartesian model of the brain and behavior. Rene Descartes (1596-1650) believed that all behaviors could be divided into two categories, the simple and the complex. Simple behaviors were those in which a given sensory event gave rise deterministically to an

Overview

In this provocative book, Paul Glimcher argues that economic theory may provide an alternative to the classical Cartesian model of the brain and behavior. Rene Descartes (1596-1650) believed that all behaviors could be divided into two categories, the simple and the complex. Simple behaviors were those in which a given sensory event gave rise deterministically to an appropriate motor response. Complex behaviors were those in which the relationship between stimulus and response was unpredictable. These behaviors were the product of a process that Descartes called the soul, but that a modern scientist might call cognition or volition.

Glimcher argues that Cartesian dualism operates from the false premise that the reflex is able to describe behavior in the real world that animals inhabit. A mathematically rich cognitive theory, he claims, could solve the most difficult problems that any environment could present, eliminating the need for dualism by eliminating the need for a reflex theory. Such a mathematically rigorous description of the neural processes that connect sensation and action, he explains, will have its roots in microeconomic theory. Economic theory allows physiologists to define both the optimal course of action that an animal might select and a mathematical route by which that optimal solution can be derived. Glimcher outlines what an economics-based cognitive model might look like and how one would begin to test it empirically. Along the way, he presents a fascinating history of neuroscience. He also discusses related questions about determinism, free will, and the stochastic nature of complex behavior.

Product Details

ISBN-13:
9780262072441
Publisher:
MIT Press
Publication date:
03/01/2003
Series:
Bradford Books Series
Pages:
395
Product dimensions:
6.00(w) x 9.00(h) x 1.25(d)

Table of Contents

Acknowledgmentsxiii
Further Readingxv
Economicsxv
Behavioral Ecologyxv
Prefacexvii
IHistorical Approaches1
1Rene Descartes and the Birth of Neuroscience3
Vaucanson's Duck3
Rene Descartes5
Understanding the Ancients9
The Renaissance16
Francis Bacon19
William Harvey22
Descartes's Synthesis27
2Inventing the Reflex33
Enlightenment Views of Determinism in the Physical and Biological World33
Determinism in Geometrical Mathematics and Geometrical Physics33
Determinism and Behavior36
Nondeterministic Behavior38
The Birth of Analytic Mathematics: The End of Geometric World Models40
Beyond Clockworks: Analytic Models of the Determinate Brain44
Vaucanson's Duck in a Deterministic, but Analytic, World51
3Charles Sherrington and the Propositional Logic of Reflexes55
Testing the Limits of Determinate Analytic Mathematics55
Charles Scott Sherrington: The Confluence of Logic and Physiology60
Sherrington's System: The Logic of the Nervous System63
Dualism68
The Godel Theorem: Finding the Limits of Determinate Mathematics72
Alan Turing and Computability73
4Finding the Limits of the Sherringtonian Paradigm77
Reflexes: Empirical Fact, Philosophical Paradigm, or Both?78
The Reflex Model Is Not Adequate to Account for All Determinate Behavior. Additional Mechanisms Are Required80
Sherrington's Cat80
T. Graham Brown and Internal Rhythms82
Erik Von Holtz: Adding to Reflex Theory87
Reflexes Are Not, as Sherrington Argued, the Organizational Element for Behavior. Behavior May Be Structured Hierarchically95
Paul Weiss95
Nickolai Bernstein104
Beyond Reflexes108
5Neurobiology Today: Beyond Reflexology?111
NetTalk, a Neural Network That Reads Aloud113
Classical Networks113
The NetTalk System117
Deciding Where to Look122
6Global Computation: An Alternative to Sherrington?131
David Marr133
Perceptrons and Computation135
Marr's Approach137
Vision139
Unresolved Problems with Marr's Approach143
7Modularity and Evolution145
Modules146
Psychological Modules149
Neurobiological Modules150
Evolution151
Gould and Lewontin153
The Need for an Optimal Benchmark: Defining the Evolutionary Goals of Neural Computation154
Achieving a Defined Goal: Phototransduction156
Convergent Evolution: Cichlid Fishes159
Generalizing to Complex Systems?164
Marr, Evolution, and Modules: The Road Ahead166
IINeuroeconomics169
8Defining the Goal: Extending Marr's Approach171
The Goal of Behavior171
Replacing Minimal Complexity: Inclusive Fitness172
Replacing Determinate Models: Probability Theory175
Uncertainty, Value, and Economics177
The Birth of Probability Theory178
Pascal's Idea: Combining Value and Probability187
A Critical Advance in Valuation: Bernoulli189
A Critical Advance in Probability: Bayes and Laplace192
Thomas Bayes193
Pierre-Simon Laplace197
Valuation, Probability, and Decision: Foundations of Modern Economic Theory199
Evolving Optimal Solutions or Optimal Brains?200
Summary202
9Evolution, Probability, and Economics205
Behavioral Ecology as a Theoretical Approach206
Foraging Theory208
The Prey Model211
Empirical Tests of Foraging Economics217
Conclusions from Testing the Prey Model221
Summary222
10Probability, Valuation, and Neural Circuits: A Case Study225
An Overview of Visual-Saccadic Processing226
Visual Processing in the Primate Brain226
Eye Movements and the Primate Brain229
Linking Vision and Saccades231
The Visual-Saccadic Function of Parietal Cortex233
The Command Hypothesis234
Attentional Enhancement237
Attention Versus Intention242
Resolving the Attention-Intention Debate?250
The Cued Saccade and Distributed Cue Experiment251
An Alternative Approach: Goals, Probability, and Valuation255
Encoding Probability256
Encoding Valuation261
Variables That Guide Choice Behavior263
Summary266
Falling into the Dualist Trap268
11Irreducible Uncertainty and the Theory of Games271
Irreducible Uncertainty in a Populated World273
Billiard Balls273
Flipping a Laplacian Coin275
The Theory of Games276
An Introduction to Game Theory278
Opponent Actions and Expected Utility281
John Nash and Modern Game Theory282
Limitations of the Equilibrium Approach287
Biology and the Theory of Games288
The Hawk-Dove Game289
Can Animals Really Produce Unpredictable Behaviors?293
Applying Game Theory to Animal Behavior294
Summary297
12Games and the Brain299
Volition, Free Will, and Mathematical Games299
Playing the Inspection Game300
Theory301
Behavior304
Summary309
Shifting to a Single Player309
Game-Playing Monkeys311
The Physiology of a Complex Behavior313
Summary317
13Putting It All Together I. Behavior and Physiology319
The Neuroeconomic Program319
Using Neuroeconomics321
Neuroeconomic Examples322
Example 1Visual Attention323
Example 2Evaluating Visual Motion328
Example 3Learning Prior Probabilities330
Example 4Learning About Values332
Limits of the Theory: Will It Be Good Enough?334
Summary336
14Putting It All Together II. Philosophical Implications337
Classical Dualism and Physiological Monism337
Alternatives to Classical Dualism and Physiological Monism338
Free Will340
Consciousness342
Finis344
References347
Index355

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