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Bayesian BrainProbabilistic Approaches to Neural Coding$
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Bayesian Brain: Probabilistic Approaches to Neural Coding

Kenji Doya, Shin Ishii, Alexandre Pouget, and Rajesh P.N. Rao

Print publication date: 2006

Print ISBN-13: 9780262042383

Published to MIT Press Scholarship Online: August 2013

DOI: 10.7551/mitpress/9780262042383.001.0001

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PRINTED FROM MIT PRESS SCHOLARSHIP ONLINE (www.mitpress.universitypressscholarship.com). (c) Copyright The MIT Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in MITSO for personal use.date: 27 February 2021

Bayesian Models of Sensory Cue Integration

Bayesian Models of Sensory Cue Integration

Chapter:
(p.189) 9 Bayesian Models of Sensory Cue Integration
Source:
Bayesian Brain
Author(s):

David C. Knill

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262042383.003.0009

This chapter discusses how the Bayesian probability theory can be used as a framework in integrating multiple sensory cues, introduces elements of Bayesian theories of perception, and describes some psychophysical tests of Bayesian cue integration.

Keywords:   Bayesian probability theory, probability, sensory cues, perception, psychophysical tests, Bayesian cue integration

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