Expansion coding and computation in the cerebellum: 50 years after the Marr–Albus codon theory. (11th February 2020)

• Record Type: Journal Article
• Authors: Sanger, Terence D.; Yamashita, Okito; Kawato, Mitsuo
• Is Part Of: Journal of physiology. Volume 598:Number 5(2020)
• Page Start: 913
• Page End: 928
• Publication Date: 2020-02-11
• Subjects: cerebellum -- control theory -- dynamics -- feedback control -- motor control -- motor learning -- neural control; Physiology -- Periodicals; 612.005
• DOI: 10.1113/JP278745
• Languages: English
• ISSNs: 0022-3751

Abstract

Abstract: Fifty years ago, David Marr and James Albus proposed a computational model of cerebellar cortical function based on the pioneering circuit models described by John Eccles, Masao Ito and Janos Szentagothai. The Marr–Albus model remains one of the most enduring and influential models in computational neuroscience, despite apparent falsification of some of the original predictions. We re‐examine the Marr–Albus model in the context of the modern theory of computational neural networks and in the context of expanded interpretations of the connectivity and function of cerebellar cortex within the full motor system. By doing so, we show that the original elements of the codon theory continue to make important predictions for cerebellar mechanism, and we show that evidence appearing to contradict the original model is based on an artificially narrow interpretation of cerebellar structure and motor function. Abstract : Overall structure of the cerebro‐cerebellum. We propose that the role of the cerebellar cortex and Purkinje cells is to modulate and select signals from incoming mossy fibres for transmission through the dentate nucleus to a highly compressed representation on the outgoing fibres projecting to frontal cortex. Inferior olive (IO) provides the training signals for plasticity.