Discrete Coding of Reward Probability and Uncertainty by Dopamine Neurons

TLDR

Uncertainty, which peaks at probability 0.5 and decreases toward extremes, is essential for measuring information and prediction accuracy. The study used distinct stimuli to signal reward probability and examined dopamine neuron phasic activation, finding it varied monotonically across probabilities, indicating coding of prediction error. Additionally, a novel response correlated with uncertainty rose gradually toward reward time, implying dopamine signals may influence attention‑based learning and risk‑taking behavior.

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.