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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, 2020. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in MITSO for personal use.date: 09 April 2020

A Probability Primer

A Probability Primer

Chapter:
(p.2) (p.3) 1 A Probability Primer
Source:
Bayesian Brain
Author(s):

Kenji Doya

Shin Ishii

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262042383.003.0001

This chapter introduces the Bayesian theorem of probability, highlights its importance in our understanding of how the brain processes information, and also discusses probability distribution and density and the Kullback-Leibler divergence for measuring the difference of probability distributions. It furthermore considers how the Bayesian theorem is useful in the process of perception or perceptual inference.

Keywords:   Bayesian theorem, probability, probability distribution, density, Kullback-Leibler divergence, perception, perceptual inference

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