Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6267258 | Current Opinion in Neurobiology | 2012 | 12 Pages |
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.
⺠A key question is whether the brain computes value signals using a normalized code. ⺠Absolute value signals are independent of the value of other stimuli. ⺠Normalized value signals depend on their relative position in the distribution of values. ⺠We provide a framework for thinking about value normalization and evaluating the existing evidence.