Computational Neuroscience: Theoretical Insights into Brain Function (Progress in Brain Research)

Trevor Drew (Herausgeber), John Kalaska (Herausgeber), Paul Cisek (Herausgeber:

ISBN 10: 0444528237 / ISBN 13: 9780444528230

Edité par Elsevier Science & Technology, 2007

A propos de cet article

570 Seiten Buch ist leicht verlagert (schief), kleine Lagerspuren am Buch, Inhalt einwandfrei und ungelesen Sprache: Englisch Gewicht in Gramm: 1670.

N° de réf. du vendeur 113390

Détails bibliographiques

• Titre: Computational Neuroscience: Theoretical Insights into Brain Function (Progress in Brain Research)
• Éditeur: Elsevier Science & Technology
• Date de parution: 2007
• Langue: anglais
• ISBN à 10 chiffres: 0444528237
• ISBN à 13 chiffres: 9780444528230
• Reliure: Gebundene Ausgabe
• État de l'article: Sehr gut
• Poids: 1670 grammes
• Catalogues du vendeur:
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Synopsis

Computational neuroscience is a relatively new but rapidly expanding area of research which is becoming increasingly influential in shaping the way scientists think about the brain. Computational approaches have been applied at all levels of analysis, from detailed models of single-channel function, transmembrane currents, single-cell electrical activity, and neural signaling to broad theories of sensory perception, memory, and cognition. This book provides a snapshot of this exciting new field by bringing together chapters on a diversity of topics from some of its most important contributors. This includes chapters on neural coding in single cells, in small networks, and across the entire cerebral cortex, visual processing from the retina to object recognition, neural processing of auditory, vestibular, and electromagnetic stimuli, pattern generation, voluntary movement and posture, motor learning, decision-making and cognition, and algorithms for pattern recognition. Each chapter provides a bridge between a body of data on neural function and a mathematical approach used to interpret and explain that data. These contributions demonstrate how computational approaches have become an essential tool which is integral in many aspects of brain science, from the interpretation of data to the design of new experiments, and to the growth of our understanding of neural function.

Présentation de l'éditeur

Computational neuroscience is a relatively new but rapidly expanding area of research which is becoming increasingly influential in shaping the way scientists think about the brain. Computational approaches have been applied at all levels of analysis, from detailed models of single-channel function, transmembrane currents, single-cell electrical activity, and neural signaling to broad theories of sensory perception, memory, and cognition. This book provides a snapshot of this exciting new field by bringing together chapters on a diversity of topics from some of its most important contributors. This includes chapters on neural coding in single cells, in small networks, and across the entire cerebral cortex, visual processing from the retina to object recognition, neural processing of auditory, vestibular, and electromagnetic stimuli, pattern generation, voluntary movement and posture, motor learning, decision-making and cognition, and algorithms for pattern recognition. Each chapter provides a bridge between a body of data on neural function and a mathematical approach used to interpret and explain that data. These contributions demonstrate how computational approaches have become an essential tool which is integral in many aspects of brain science, from the interpretation of data to the design of new experiments, and to the growth of our understanding of neural function.

· Includes contributions by some of the most influential people in the field of computational neuroscience
· Demonstrates how computational approaches are being used today to interpret experimental data
· Covers a wide range of topics from single neurons, to neural systems, to abstract models of learning