ABSTRACT
A neural network model of handwriting generation is used to explain Parkinson’s micrographia, a motor impairment characterized by a progressive decrease in letter size, handwriting baseline, and a general slowness of movement. The goal is to understand the neurophysiological and neuropharmacologics bases of this disease, and its effects on movement production. Simulations support the view that the basal ganglia are responsible for (1) defining the degrees of freedom used during a movement task, (2) controlling the build-up of signals that modulate global movement speed and size, (3) rapid resetting of these signals upon movement completion, and (4) spatiotemporal modulation of these gating signals. Parkinson’s disease is simulated in terms of these gating signals, and the results correspond with the clinical observations demonstrating the predictive value of the model.
