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Published December 2012 | Accepted Version
Journal Article Open

Value normalization in decision making: theory and evidence


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.

Additional Information

© 2012 Elsevier B.V. Available online 29 August 2012. We would like to thank Wolfram Schultz for very useful comments. This research was supported by the NSF (SES-0851408, SES-0926544, SES-0850840), NIH (R01 AA018736, R21 AG038866), the Betty and Gordon Moore Foundation, and the Lipper Foundation.

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Accepted Version - nihms448944.pdf


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