A Predictive Switching Model of Cerebellar Movement Control

Part of Advances in Neural Information Processing Systems 8 (NIPS 1995)

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Andrew Barto, James Houk


We present a hypothesis about how the cerebellum could partici(cid:173) pate 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(cid:173) point positioning of a nonlinear spring-mass system with realistic delays in both afferent and efferent pathways. The model's opera(cid:173) tion 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.