Abstract
Motor control is fundamental to the nervous system: only through our movements do we interact with the world. Successful motor control requires the integration of a myriad of pieces of information. Yet all this information is of an uncertain nature because we only obtain noisy information in a changing world. We are thus faced with the problem of integrating many uncertain pieces of information into a relatively precise estimate of the properties of our bodies and the surrounding world. Bayesian models of motor control formalize the problem of how uncertain information should be integrated and make predictions that often well describe human movement behavior.
Original language | English (US) |
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Title of host publication | Encyclopedia of Neuroscience |
Publisher | Elsevier Ltd |
Pages | 127-133 |
Number of pages | 7 |
ISBN (Print) | 9780080450469 |
DOIs | |
State | Published - Jan 1 2009 |
Keywords
- Bayesian statistics
- Cost function
- Cue combination
- Feedback control
- Kalman filters
- Motor control
- Normative models
- Optimal control
- Psychophysics
- Sensorimotor integration
- Stochastic modeling
ASJC Scopus subject areas
- General Neuroscience