Internal Models in the Cerebellum: A Coupling Scheme for Online and Offline Learning in Procedural Tasks View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2010

AUTHORS

David Hutchison , Takeo Kanade , Josef Kittler , Jon M. Kleinberg , Friedemann Mattern , John C. Mitchell , Moni Naor , Oscar Nierstrasz , C. Pandu Rangan , Bernhard Steffen , Madhu Sudan , Demetri Terzopoulos , Doug Tygar , Moshe Y. Vardi , Gerhard Weikum , Jean-Baptiste Passot , Niceto Luque , Angelo Arleo

ABSTRACT

The cerebellum plays a major role in motor control. It is thought to mediate the acquisition of forward and inverse internal models of the bodyenvironment interaction [1]. In this study, the main processing components of the cerebellar microcomplex are modelled as a network of spiking neural populations. The model cerebellar circuit is shown to be suitable for learning both forward and inverse models. A new coupling scheme is put forth to optimise online adaptation and support offline learning. The proposed model is validated on two procedural tasks and the simulation results are consistent with data from human experiments on adaptive motor control and sleep-dependent consolidation [2, 3]. This work corroborates the hypothesis that both forward and inverse internal models can be learnt and stored by the same cerebellar circuit, and that their coupling favours online and offline learning of procedural memories. More... »

PAGES

435-446

Book

TITLE

From Animals to Animats 11

ISBN

978-3-642-15192-7
978-3-642-15193-4

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-15193-4_41

DOI

http://dx.doi.org/10.1007/978-3-642-15193-4_41

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1052381366


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