Topic: Bayesian posterior estimates

A popular model of the basal ganglia uses the theory of reinforcement learning (RL), where phasic dopamine activity encodes reward prediction errors to drive the learning of reward associations. In contrast to classical RL, however, where relevant state information is always provided to the agent, animals must find optimal behaviors using only incomplete state information. One theoretical observation is that animals (or agents) can solve these partially observable tasks by forming "beliefs," or optimal Bayesian posterior estimates of the state of the task. However, it is unknown whether animal