Cortexbasal ganglia interaction and attractor states
We propose a set of hypotheses about how the basal ganglia contribute to information processing in cortical networks and how the cortex and basal ganglia interact during learning and behavior. We introduce a computational model on the level of system of networks. We suggest that the basal ganglia control cortical activity by pushing a local cortical network into a new attractor state, thereby selecting certain attractors over others. The ideas of temporal difference learning and convergence of corticostriatal fibers from multiple cortical areas within the striatum are combined in a modular learning system capable of acquiring behavior with sequential structure.
attractor state basal ganglia modeling striatum loops recurrent networks