Efficient coding and the neural representation of value

Kenway Louie, Paul Glimcher

Research output: Contribution to journalArticle

Abstract

To survive in a dynamic environment, an organism must be able to effectively learn, store, and recall the expected benefits and costs of potential actions. The nature of the valuation and decision processes is thus of fundamental interest to researchers at the intersection of psychology, neuroscience, and economics. Although normative theories of choice have outlined the theoretical structure of these valuations, recent experiments have begun to reveal how value is instantiated in the activity of neurons and neural circuits. Here, we review the various forms of value coding that have been observed in different brain systems and examine the implications of these value representations for both neural circuits and behavior. In particular, we focus on emerging evidence that value coding in a number of brain areas is context dependent, varying as a function of both the current choice set and previously experienced values. Similar contextual modulation occurs widely in the sensory system, and efficient coding principles derived in the sensory domain suggest a new framework for understanding the neural coding of value.

Original languageEnglish (US)
Pages (from-to)13-32
Number of pages20
JournalAnnals of the New York Academy of Sciences
Volume1251
Issue number1
DOIs
StatePublished - Mar 2012

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Brain
Networks (circuits)
Neurosciences
Action Potentials
Neurons
Cost-Benefit Analysis
Economics
Research Personnel
Modulation
Psychology
Costs
Experiments

Keywords

  • Context dependence
  • Decision making
  • Efficient coding
  • Neuroeconomics
  • Reward

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • History and Philosophy of Science

Cite this

Efficient coding and the neural representation of value. / Louie, Kenway; Glimcher, Paul.

In: Annals of the New York Academy of Sciences, Vol. 1251, No. 1, 03.2012, p. 13-32.

Research output: Contribution to journalArticle

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