A Cortico-Cerebellar Model that Learns to Generate Distributed Motor Commands to Control a Kinematic Arm

Part of Advances in Neural Information Processing Systems 4 (NIPS 1991)

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N. Berthier, S. P. Singh, A. G. Barto, J. C. Houk


A neurophysiologically-based model is presented that controls a simulated kinematic arm during goal-directed reaches. The network generates a quasi-feedforward motor command that is learned using training signals generated by corrective movements. For each target, the network selects and sets the output of a subset of pattern generators. During the move(cid:173) ment, feedback from proprioceptors turns off the pattern generators. The task facing individual pattern generators is to recognize when the arm reaches the target and to turn off. A distributed representation of the mo(cid:173) tor command that resembles population vectors seen in vivo was produced naturally by these simulations.