| Computational mechanisms of sensorimotor control. | |
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MedLine Citation:
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PMID: 22078503 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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In order to generate skilled and efficient actions, the motor system must find solutions to several problems inherent in sensorimotor control, including nonlinearity, nonstationarity, delays, redundancy, uncertainty, and noise. We review these problems and five computational mechanisms that the brain may use to limit their deleterious effects: optimal feedback control, impedance control, predictive control, Bayesian decision theory, and sensorimotor learning. Together, these computational mechanisms allow skilled and fluent sensorimotor behavior. |
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Authors:
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David W Franklin; Daniel M Wolpert |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Neuron Volume: 72 ISSN: 1097-4199 ISO Abbreviation: Neuron Publication Date: 2011 Nov |
Date Detail:
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Created Date: 2011-11-14 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8809320 Medline TA: Neuron Country: United States |
Other Details:
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Languages: eng Pagination: 425-42 Citation Subset: IM |
Copyright Information:
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Copyright © 2011 Elsevier Inc. All rights reserved. |
Affiliation:
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Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UK. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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