Information Theory And The Brain

Par : Peter Földiàk, Roland Baddeley, Peter Hancock

Formats :

    • Nombre de pages344
    • PrésentationRelié
    • Poids0.645 kg
    • Dimensions16,1 cm × 24,2 cm × 2,4 cm
    • ISBN0-521-63197-1
    • EAN9780521631976
    • Date de parution23/06/2000
    • ÉditeurCambridge University Press

    Résumé

    Information theory and the brain deals with a new and expanding area of neuroscience which provides a framework for understanding neuronal processing. It is derived from a conference held in Newquay, UK, where a handful of scientists from around the world met to discuss the topic. This book begins with an introduction to the basic concepts of information theory and then illustrates these concepts with examples from research over the last 40 years. Throughout the book, the contributors highlight current research from four different areas: (1) biological networks, including a review of information theory based on models of the retina, understanding the operation of the insect retina in terms of energy efficiency, and the relationship of image statistics and image coding; (2) information theory and artificial networks, including independent component-based networks and models of the emergence of orientation and ocular dominance maps; (3) information theory and psychology, including clarity of speech models, information theory and connectionist models, and models of information theory and resource allocation; (4) formal analysis, including chapters on modelling the hippocampus, stochastic resonance, and measuring information density. Each part includes an introduction and glossary covering basic concepts. This book will appeal to graduate students and researchers in neuroscience as well as computer scientists and cognitive scientists. Neuroscientists interested in any aspect of neural networks or information processing will find this a very useful addition to the current literature in this rapidly growing field.
    Information theory and the brain deals with a new and expanding area of neuroscience which provides a framework for understanding neuronal processing. It is derived from a conference held in Newquay, UK, where a handful of scientists from around the world met to discuss the topic. This book begins with an introduction to the basic concepts of information theory and then illustrates these concepts with examples from research over the last 40 years. Throughout the book, the contributors highlight current research from four different areas: (1) biological networks, including a review of information theory based on models of the retina, understanding the operation of the insect retina in terms of energy efficiency, and the relationship of image statistics and image coding; (2) information theory and artificial networks, including independent component-based networks and models of the emergence of orientation and ocular dominance maps; (3) information theory and psychology, including clarity of speech models, information theory and connectionist models, and models of information theory and resource allocation; (4) formal analysis, including chapters on modelling the hippocampus, stochastic resonance, and measuring information density. Each part includes an introduction and glossary covering basic concepts. This book will appeal to graduate students and researchers in neuroscience as well as computer scientists and cognitive scientists. Neuroscientists interested in any aspect of neural networks or information processing will find this a very useful addition to the current literature in this rapidly growing field.