Bayesian approaches to sensory integration for motor control

Max Berniker, Konrad Kording*

*Corresponding author for this work

Research output: Contribution to journalArticle

27 Scopus citations

Abstract

The processing of sensory information is fundamental to the basic operation of the nervous system. Our nervous system uses this sensory information to gain knowledge of our bodies and the world around us. This knowledge is of great importance as it provides the coherent and accurate information necessary for successful motor control. Yet, all this knowledge is of an uncertain nature because we obtain information only through our noisy sensors. We are thus faced with the problem of integrating many uncertain pieces of information into estimates of the properties of our bodies and the surrounding world. Bayesian approaches to estimation formalize the problem of how this uncertain information should be integrated. Utilizing this approach, many studies make predictions that faithfully predict human sensorimotor behavior.

Original languageEnglish (US)
Pages (from-to)419-428
Number of pages10
JournalWiley Interdisciplinary Reviews: Cognitive Science
Volume2
Issue number4
DOIs
StatePublished - Jul 1 2011

ASJC Scopus subject areas

  • Neuroscience(all)
  • Psychology(all)

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