We review the contributions of biologically constrained computational models to our
understanding of motor and cognitive deficits in Parkinson's disease (PD). The loss of
dopaminergic neurons innervating the striatum in PD, and the well-established role of
dopamine (DA) in reinforcement learning (RL), enable neural network models of the basal
ganglia (BG) to derive concrete and testable predictions. We focus in this review on one
simple underlying principle–the notion that reduced DA increases activity and causes long …