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Foundations of Neuroeconomic Analysis$
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Paul W. Glimcher

Print publication date: 2010

Print ISBN-13: 9780199744251

Published to Oxford Scholarship Online: January 2011

DOI: 10.1093/acprof:oso/9780199744251.001.0001

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The Implications of Neuronal Stochasticity and Cortical Representation for Behavioral Models of Choice

The Implications of Neuronal Stochasticity and Cortical Representation for Behavioral Models of Choice

Chapter:
(p.225) 10 The Implications of Neuronal Stochasticity and Cortical Representation for Behavioral Models of Choice
Source:
Foundations of Neuroeconomic Analysis
Author(s):

Paul W. Glimcher

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199744251.003.0010

The central premise of the neuroeconomic endeavor is that the iterative process of reductively linking neuroscience, psychology, and economics through theoretical modifications to each discipline will maximize predictive power. This chapter examines further neurobiological, psychological, and economic constraints on the choice mechanism to test that premise. First, it examines in greater detail the relationship between expected subjective value and expected utility, focusing on the interrelationship between neuronal and behavioral stochasticity as revealed by existing psychological models. Second, it looks at the precise nature of cortical representation in the nervous system. Theories of cortical representation anchored to normative models of efficient coding identify constraints all neural representations must acknowledge. These constraints predict a specific class of choice behaviors that violate traditional Soft-REU, behaviors that have already been observed but not yet linked to the structure of the choice mechanism. This suggests that a version of Hard-REU that incorporates these constraints has significantly greater predictive power at both the neural and behavioral levels than a model more closely aligned with traditional Soft-REU. These are the final issues that need to be engaged.

Keywords:   neuroeconomics, choice mechanism, subjective value, expected utility, cortical representation, stochasticity

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