Bayesian Brain : Probabilistic Approaches to Neural Coding Paperback / softback
Edited by Kenji Doya, Shin Ishii, Alexandre Pouget, Rajesh P. N. Rao
Part of the Computational Neuroscience Series series
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.
- Format: Paperback / softback
- Pages: 344 pages, 10 color illus., 92 black & white illus.; 102 Illustrations, unspecified
- Publisher: MIT Press Ltd
- Publication Date: 21/01/2011
- Category: Neurology & clinical neurophysiology
- ISBN: 9780262516013