Topic: mouse cortex

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

Understanding how sensory information is represented, processed, and leads to generation of complex behavior is the major goal of systems neuroscience. However, the ability to detect and manipulate such large-scale functional circuits has been hampered by the lack of appropriate tools and methods that allow for parallel recording of neuronal population activity at high spatial and temporal resolutions. We have recently demonstrated near-simultaneous recording from over 1 million neurons distributed across both hemispheres and different layers of the mouse cortex at cellular resolution. At the