title: Value normalization in decision making: theory and evidence.
abstract: A sizable body of evidence has shown that the brain computes several types of value-related signals to guide decision making, such as stimulus values, outcome values, and prediction errors. A critical question for understanding decision-making mechanisms is whether these value signals are computed using an absolute or a normalized code. Under an absolute code, the neural response used to represent the value of a given stimulus does not depend on what other values might have been encountered. By contrast, under a normalized code, the neural response associated with a given value depends on its relative position in the distribution of values. This review provides a simple framework for thinking about value normalization, and uses it to evaluate the existing experimental evidence.
authors.affiliation: Division of the Humanities and Social Sciences, California Institute of Technology, MC 228-77 Pasadena, CA 91125, United States. rangel@hss.caltech.edu
authors.forename: Antonio
authors.initials: A
authors.lastname: Rangel
authors.forename: John A
authors.initials: JA
authors.lastname: Clithero
mesh_terms: D002755:Choice Behavior / Q000502:physiology; D003657:Decision Making / Q000502:physiology*; D006801:Humans; D008960:Models, Psychological; D011582:Psychological Theory; D011594:Psychometrics / Q000379:methods*; D012677:Sensation / Q000502:physiology*