AbstractDopamine neurons drive learning by coding reward prediction errors (RPEs), which are formalized as subtractions of predicted values from reward values. Subtractions accommodate point estimate predictions of value, such as the average value. However, point estimate predictions fail to capture many features of choice and learning behaviors. For instance, reaction times and learning rates consistently reflect higher moments of probability distributions. Here, we demonstrate that dopamine

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... E responses code probability distributions. We presented monkeys with rewards that were drawn from the tails of normal and uniform reward size distributions to generate rare and common RPEs, respectively. Behavioral choices and pupil diameter measurements indicated that monkeys learned faster and registered greater arousal from rare RPEs, compared to common RPEs of identical magnitudes. Dopamine neuron recordings indicated that rare rewards amplified RPE responses. These results demonstrate that dopamine responses reflect probability distributions and suggest a neural mechanism for the amplified learning and enhanced arousal associated with rare events.