Probabilistic Models of the Brain: Perception and Neural Function (Neural Information Processing)

Rajesh P N. Rao; Bruno A. Olshausen; Michael S. Lewicki

ISBN 10: 0262182246 / ISBN 13: 9780262182249

Edité par A Bradford Book / MIT Press, 2002

A propos de cet article

Oversized cloth hardcover, x + 324 pages, NOT ex-library. Weight 1065g. Gentle handling wear, book is clean and bright with unmarked text, free of inscriptions and stamps. Lightly shelfworn, untorn dust jacket.

N° de réf. du vendeur 008358

Détails bibliographiques

• Titre: Probabilistic Models of the Brain: Perception and Neural Function (Neural Information Processing)
• Éditeur: A Bradford Book / MIT Press
• Date de parution: 2002
• Langue: anglais
• ISBN à 10 chiffres: 0262182246
• ISBN à 13 chiffres: 9780262182249
• Reliure: Hardcover
• État de l'article: Very Good
• État de la jaquette: Very Good

A propos de ce titre

Synopsis

A survey of probabilistic approaches to modeling and understanding brain function.

Neurophysiological, neuroanatomical, and brain imaging studies have helped to shed light on how the brain transforms raw sensory information into a form that is useful for goal-directed behavior. A fundamental question that is seldom addressed by these studies, however, is why the brain uses the types of representations it does and what evolutionary advantage, if any, these representations confer. It is difficult to address such questions directly via animal experiments. A promising alternative is to use probabilistic principles such as maximum likelihood and Bayesian inference to derive models of brain function.

This book surveys some of the current probabilistic approaches to modeling and understanding brain function. Although most of the examples focus on vision, many of the models and techniques are applicable to other modalities as well. The book presents top-down computational models as well as bottom-up neurally motivated models of brain function. The topics covered include Bayesian and information-theoretic models of perception, probabilistic theories of neural coding and spike timing, computational models of lateral and cortico-cortical feedback connections, and the development of receptive field properties from natural signals.

À propos de l?auteur

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.

Bruno A. Olshausen is Associate Professor in the Department of Psychology and the Center for Neuroscience at the University of California, Davis.

Michael S. Lewicki is Assistant Professor in the Department of Computer Science and the Center for the Neural Basis of Cognition at Carnegie Mellon University.