Computational Principles of Sensorimotor Control That Minimize Uncertainty and Variability

Overview

Journal J Physiol

Specialty Physiology

Date 2006 Sep 30

PMID 17008369

Citations 126

Authors

Paul M Bays

Daniel M Wolpert

Affiliations

Soon will be listed here.

Abstract

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.

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