Dienstag, 29. März 2016

Discrete Coding of Reward Probability and Uncertainty by Dopamine Neurons

Discrete Coding of Reward Probability and Uncertainty by Dopamine Neurons
Christopher D. Fiorillo, Philippe N. Tobler, Wolfram Schultz (2003)


Abstract

Uncertainty is critical in the measure of information and in assessing the accuracy of predictions. It is determined by probability P, being maximal at P 0.5 and decreasing at higher and lower probabilities. Using distinct stimuli to indicate the probability of reward, we found that the phasic activation of dopamine neurons varied monotonically across the full range of probabilities, supporting past claims that this response codes the discrepancy between predicted and actual reward. In contrast, a previously unobserved response covaried with uncertainty and consisted of a gradual increase in activity until the potential time of reward. The coding of uncertainty suggests a possible role for dopamine signals in attention-based learning and risk-taking behavior.



"The brain continuously makes predictions and compares outcomes (or inputs) with those predictions. Predictions are fundamentally concerned with the probability that an event will occur within a specified time period. It is only through a rich representation of probabilities that an animal can infer the structure of its environment and form associations between correlated events."

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