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dc.contributor.authorBullock, Danielen_US
dc.contributor.authorContreras-Vidal, Jose L.en_US
dc.contributor.authorGrossberg, Stephenen_US
dc.date.accessioned2011-11-14T18:19:18Z
dc.date.available2011-11-14T18:19:18Z
dc.date.issued1993-01en_US
dc.identifier.urihttp://hdl.handle.net/2144/1986
dc.description.abstractThis paper shows how a minimal neural network model of the cerebellum may be embedded within a sensory-neuro-muscular control system that mimics known anatomy and physiology. With this embedding, cerebellar learning promotes load compensation while also allowing both coactivation and reciprocal inhibition of sets of antagonist muscles. In particular, we show how synaptic long term depression guided by feedback from muscle stretch receptors can lead to trans-cerebellar gain changes that are load-compensating. It is argued that the same processes help to adaptively discover multi-joint synergies. Simulations of rapid single joint rotations under load illustrates design feasibility and stability.en_US
dc.description.sponsorshipNational Science Foundation (IRI-90-24877, IRI-87-16960); Office of Naval Research (N00014-92-J-1309); Consejo Nacional de Ciencia y Technología (63462); Air Force Office of Scientific Research (F49620-92-J-0499); Defense Advanced Research Projects Agency (AFOSR 90-0083, ONR N00014-92-J-4015)en_US
dc.language.isoen_USen_US
dc.publisherBoston University Center for Adaptive Systems and Department of Cognitive and Neural Systemsen_US
dc.relation.ispartofseriesBU CAS/CNS Technical Reports;CAS/CNS-TR-1993-009en_US
dc.rightsCopyright 1993 Boston University. Permission to copy without fee all or part of this material is granted provided that: 1. The copies are not made or distributed for direct commercial advantage; 2. the report title, author, document number, and release date appear, and notice is given that copying is by permission of BOSTON UNIVERSITY TRUSTEES. To copy otherwise, or to republish, requires a fee and / or special permission.en_US
dc.titleCerebellar Learning in an Opponent Motor Controller for Adaptive Load Compensation and Synergy Formationen_US
dc.typeTechnical Reporten_US
dc.rights.holderBoston University Trusteesen_US


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