A Predictive Switching Model of Cerebellar Movement Control
We present a hypothesis about how the cerebellum could participate in regulating movement in the presence of significant feedback delays without resorting to a forward model of the motor plant. We show how a simplified cerebellar model can learn to control end-point positioning of a nonlinear spring-mass system with realistic delays in both afferent and efferent pathways. The model's operation involves prediction, but instead of predicting sensory input, it directly regulates movement by reacting in an anticipatory fashion to input patterns that include delayed sensory feedback.