Jump to ContentJump to Main Navigation
Bayesian BrainProbabilistic Approaches to Neural Coding$
Users without a subscription are not able to see the full content.

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

Show Summary Details
Page of

PRINTED FROM MIT PRESS SCHOLARSHIP ONLINE (www.mitpress.universitypressscholarship.com). (c) Copyright The MIT Press, 2022. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in MITSO for personal use.date: 26 June 2022

A Probability Primer

A Probability Primer

(p.2) (p.3) 1 A Probability Primer
Bayesian Brain

Kenji Doya

Shin Ishii

The MIT Press

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

MIT Press Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs, and if you can't find the answer there, please contact us.