The computational brain

An anniversary edition of the classic work that influenced a generation of neuroscientists and cognitive neuroscientists.Before The Computational Brain was published in 1992, conceptual frameworks for brain function were based on the behavior of single neurons, applied globally. In The Computational...

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Bibliographic Details
Main Authors: Churchland, Patricia Smith, Sejnowski, Terrence J. (Author)
Format: eBook
Language:English
Published: Cambridge, MA The MIT Press 2017
Edition:25th Anniversary edition
Series:Computational neuroscience series
Subjects:
Online Access:
Collection: MIT Press eBook Archive - Collection details see MPG.ReNa
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520 |a An anniversary edition of the classic work that influenced a generation of neuroscientists and cognitive neuroscientists.Before The Computational Brain was published in 1992, conceptual frameworks for brain function were based on the behavior of single neurons, applied globally. In The Computational Brain, Patricia Churchland and Terrence Sejnowski developed a different conceptual framework, based on large populations of neurons. They did this by showing that patterns of activities among the units in trained artificial neural network models had properties that resembled those recorded from populations of neurons recorded one at a time. It is one of the first books to bring together computational concepts and behavioral data within a neurobiological framework. Aimed at a broad audience of neuroscientists, computer scientists, cognitive scientists, and philosophers, The Computational Brain is written for both expert and novice. This anniversary edition offers a new preface by the authors that puts the book in the context of current research.This approach influenced a generation of researchers. Even today, when neuroscientists can routinely record from hundreds of neurons using optics rather than electricity, and the 2013 White House BRAIN initiative heralded a new era in innovative neurotechnologies, the main message of The Computational Brain is still relevant