An opponent striatal circuit for distributional reinforcement learning.

ABSTRACT: Machine learning research has achieved large performance gains on a wide range of tasks by expanding the learning target from mean rewards to entire probability distributions of rewards-an approach known as distributional reinforcement learning (RL)¹. The mesolimbic dopamine system is thought to underlie RL in the mammalian brain by updating a representation of mean value in the striatum², but little is known about whether, where and how neurons in this circuit encode information about higher-order moments of reward distributions³. Here, to fill this gap, we used high-density probes (Neuropixels) to record striatal activity from mice performing a classical conditioning task in which reward mean, reward variance and stimulus identity were independently manip

SUBMITTER: Lowet AS 

PROVIDER: S-EPMC12007193 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature