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A Neural Net Model for Adaptive Control of Saccadic Accuracy by Primate Cerebellum and Brainstem

Accurate saccades require interaction between brainstem circuitry and the cerebellum. A model of this interaction is described, based on Kawato's principle of feedback-error-learning. In the model a part of the brainstem (the superior colliculus) acts as a simple feedback controller with no knowledge of initial eye position, and provides an error signal for the cerebellum to correct for eye-muscle nonlinearities. This teaches the cerebellum, modelled as a CMAC, to adjust appropriately the gain on the brainstem burst-generator's internal feedback loop and so alter the size of burst sent to the motoneurons. With direction-only errors the system rapidly learns to make accurate horizontal eye movements from any starting position, and adapts realistically to subsequent simulated eye-muscle weakening or displacement of the saccadic target.