Overview

Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. How do groups of neurons interact to enable the organism to see, decide, and move appropriately? What are the principles whereby networks of neurons represent and compute? These are the central questions probed by The Computational Brain. Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework. Computer models constrained by neurobiological data can help reveal how—networks of neurons subserve perception and behavior—bow their physical interactions can yield global results in perception and behavior, and how their physical properties are used to code information and compute solutions. The Computational Brain focuses mainly on three domains: visual perception, learning and memory, and sensorimotor integration. Examples of recent computer models in these domains are discussed in detail, highlighting strengths and weaknesses, and extracting principles applicable to other domains. Churchland and Sejnowski show how both abstract models and neurobiologically realistic models can have useful roles in computational neuroscience, and they predict the coevolution of models and experiments at many levels of organization, from the neuron to the system. The Computational Brain addresses a broad audience: neuroscientists, computer scientists, cognitive scientists, and philosophers. It is written for both the expert and novice. A basic overview of neuroscience and computational theory is provided, followed by a study of some of the most recent and sophisticated modeling work in the context of relevant neurobiological research. Technical terms are clearly explained in the text, and definitions are provided in an extensive glossary. The appendix contains a précis of neurobiological techniques. The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework. Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field. A Bradford Book Computational Neuroscience series

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This attractive and well-illustrated volume falls somewhere between a trade book and a textbook, with a style well suited for the Scientific American reader, as well as the active scientist, who may know something of either computer science or neuroscience but welcomes a crisp narrative that includes the necessary background from each discipline.... The reader will be well rewarded who seeks to understand, from well-chosen examples, how to merge the analysis of neuroscientific data with the developments of computational principles. --Michael A. Arbib, Science

Author Information

Patricia S. Churchland is President's Professor of Philosophy Emerita at the University of California, San Diego, and Adjunct Professor at the Salk Institute for Biological Sciences. She is the author of many books, including Neurophilosophy and Brain-Wise (both published by the MIT Press). Terrence J. Sejnowski holds the Francis Crick Chair at the Salk Institute for Biological Studies and is a Distinguished Professor at the University of California, San Diego. He was a member of the advisory committee for the Obama administration's BRAIN initiative and is President of the Neural Information Processing (NIPS) Foundation. He is the author of The Deep Learning Revolution (MIT Press) and other books.

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