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J Physiol Volume 578, Number 2, 387-396, January 15, 2007 DOI: 10.1113/jphysiol.2006.120121
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Topical Review

Computational principles of sensorimotor control that minimize uncertainty and variability

Paul M. Bays1 and Daniel M. Wolpert2

1 Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AR, UK
2 Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK

Sensory and motor noise limits the precision with which we can sense the world and act upon it. Recent research has begun to reveal computational principles by which the central nervous system reduces the sensory uncertainty and movement variability arising from this internal noise. Here we review the role of optimal estimation and sensory filtering in extracting the sensory information required for motor planning, and the role of optimal control, motor adaptation and impedance control in the specification of the motor output signal.

(Received 29 August 2006; accepted after revision 27 September 2006; first published online 28 September 2006)
Corresponding author P. M. Bays: Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AR, UK. Email: p.bays{at}ion.ucl.ac.uk




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