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 ϭ 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.

It is important for animals to estimate the value of rewards as accurately as possible. Because the number of potential reward values is very large, it is necessary that the brain's limited resources be allocated so as to discriminate better among more likely reward outcomes at the expense of less likely outcomes. We found that midbrain dopamine neurons rapidly adapted to the information provided by reward-predicting stimuli. Responses shifted relative to the expected reward value, and the gain adjusted to the variance of reward value. In this way, dopamine neurons maintained their reward sensitivity over a large range of reward values.

Midbrain dopamine neurons are activated when reward is greater than predicted, and this error signal could teach target neurons both the value of reward and when it will occur. We used the dopamine error signal to measure how the expectation of reward was distributed over time. Animals were trained with fixed-duration intervals of 1-16 s between conditioned stimulus onset and reward. In contrast to the weak responses that have been observed after short intervals (1-2 s), activations to reward increased steeply and linearly with the logarithm of the interval. Results with varied stimulus-reward intervals suggest that the neural expectation was substantial after just half an interval had elapsed. Thus, the neural expectation of reward in these experiments was not highly precise and the precision declined sharply with interval duration. The neural precision of expectation appeared to be at least qualitatively similar to the precision of anticipatory licking behavior.