Bayesian Brain: Probabilistic Approaches to Neural Coding

by Kenji Doya (Editor), Shin Ishii (Editor), Alexandre Pouget (Editor)

Experimental and theoretical neuroscientists use Bayesian approaches to analyze the brain mechanisms of perception, decision-making, and motor control. A Bayesian approach can contribute to an understanding of the brain on multiple levels, by giving normative predictions about how an ideal sensory system should combine prior knowledge and observation, by providing mechanistic interpretation of the dynamic functioning of the brain circuit, and by suggesting optimal ways of deciphering experimental data. Bayesian Brain brings together contributions from both experimental and theoretical neuroscientists that examine the brain mechanisms of perception, decision making, and motor control according to the concepts of Bayesian estimation.After an overview of the mathematical concepts, including Bayes' theorem, that are basic to understanding the approaches discussed, contributors discuss how Bayesian concepts can be used for interpretation of such neurobiological data as neural spikes and functional brain imaging. Next, contributors examine the modeling of sensory processing, including the neural coding of information about the outside world. Finally, contributors explore dynamic processes for proper behaviors, including the mathematics of the speed and accuracy of perceptual decisions and neural models of belief propagation.

Genres: Neuroscience, Science

340 pages, Paperback

First published December 22, 2006

Reviews

[Andrew · Rating 4 out of 5]

Key book on my shelf--bayesian approaches to modeling perception. Key question: How does the brain deal with the uncertainty in the world??

[Eric · Rating 5 out of 5]

A very good book for entry level probabilistic neural models.

[Jovany Agathe · Rating 2 out of 5]

great book.