Bayesian Brain: Probabilistic Approaches to Neural Coding

Doya, Kenji

ISBN 10: 026204238X / ISBN 13: 9780262042383

Edité par MIT Press, 2007

A propos de cet article

This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,800grams, ISBN:026204238X.

N° de réf. du vendeur 5958541

Détails bibliographiques

• Titre: Bayesian Brain: Probabilistic Approaches to Neural Coding
• Éditeur: MIT Press
• Date de parution: 2007
• Langue: anglais
• ISBN à 10 chiffres: 026204238X
• ISBN à 13 chiffres: 9780262042383
• Reliure: Couverture rigide
• État de l'article: Good
• Catalogues du vendeur:
  • Science & Technology

A propos de ce titre

Synopsis

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.

À propos de l?auteur

Kenji Doya is Principal Investigator in the Neural Computation Unit in the Initial Research Project at the Okinawa Institute of Science and Technology, Japan.

Shin Ishii is Professor in the Graduate School of Information Science, Nara Institute of Science and Technology, Japan.

Alexandre Pouget is Associate Professor in the Brain and Cognitive Science Department at the University of Rochester and Head of the Laboratory of Computational Cognitive Neuroscience.

Rajesh P. N. Rao is Associate Professor in the Department of Computer Science and Engineering, a Faculty Member of the Neurobiology and Behavior Program at the University of Washington.