Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4334261 | Current Opinion in Neurobiology | 2011 | 6 Pages |
Accumulating evidence shows that the neural network of the cerebral cortex and the basal ganglia is critically involved in reinforcement learning. Recent studies found functional heterogeneity within the cortico-basal ganglia circuit, especially in its ventromedial to dorsolateral axis. Here we review computational issues in reinforcement learning and propose a working hypothesis on how multiple reinforcement learning algorithms are implemented in the cortico-basal ganglia circuit using different representations of states, values, and actions.
► We review computational issues and possible algorithms for decision making. ► We review recent findings on the neural correlates of the variables in those algorithms. ► Then we propose a hypothesis about parallel and hierarchical modules in the striatum.