A theory of cerebellar cortex and adaptive motor control based on two types of universal function approximation capability

Neural Networks : the Official Journal of the International Neural Network Society
M Fujita

Abstract

Lesions of the cerebellum result in large errors in movements. The cerebellum adaptively controls the strength and timing of motor command signals depending on the internal and external environments of movements. The present theory describes how the cerebellar cortex can control signals for accurate and timed movements. A model network of the cerebellar Golgi and granule cells is shown to be equivalent to a multiple-input (from mossy fibers) hierarchical neural network with a single hidden layer of threshold units (granule cells) that receive a common recurrent inhibition (from a Golgi cell). The weighted sum of the hidden unit signals (Purkinje cell output) is theoretically analyzed regarding the capability of the network to perform two types of universal function approximation. The hidden units begin firing as the excitatory inputs exceed the recurrent inhibition. This simple threshold feature leads to the first approximation theory, and the network final output can be any continuous function of the multiple inputs. When the input is constant, this output becomes stationary. However, when the recurrent unit activity is triggered to decrease or the recurrent inhibition is triggered to increase through a certain mechanism (meta...Continue Reading

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Citations

Jul 20, 2020·Journal of Computational Neuroscience·Mohamed ElkasabyAasef G Shaikh
May 4, 2021·Human Movement Science·Keying ZhangChunmei Cao

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