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From Neuron to Cognition Via Computational Neuroscience

PUBLISHER MIT Press (11/11/2016)
PRODUCT TYPE Hardcover (Hardcover)

Description
A comprehensive, integrated, and accessible textbook presenting core neuroscientific topics from a computational perspective, tracing a path from cells and circuits to behavior and cognition.

This textbook presents a wide range of subjects in neuroscience from a computational perspective. It offers a comprehensive, integrated introduction to core topics, using computational tools to trace a path from neurons and circuits to behavior and cognition. Moreover, the chapters show how computational neuroscience--methods for modeling the causal interactions underlying neural systems--complements empirical research in advancing the understanding of brain and behavior.

The chapters--all by leaders in the field, and carefully integrated by the editors--cover such subjects as action and motor control; neuroplasticity, neuromodulation, and reinforcement learning; vision; and language--the core of human cognition.

The book can be used for advanced undergraduate or graduate level courses. It presents all necessary background in neuroscience beyond basic facts about neurons and synapses and general ideas about the structure and function of the human brain. Students should be familiar with differential equations and probability theory, and be able to pick up the basics of programming in MATLAB and/or Python. Slides, exercises, and other ancillary materials are freely available online, and many of the models described in the chapters are documented in the brain operation database, BODB (which is also described in a book chapter).

Contributors
Michael A. Arbib, Joseph Ayers, James Bednar, Andrej Bicanski, James J. Bonaiuto, Nicolas Brunel, Jean-Marie Cabelguen, Carmen Canavier, Angelo Cangelosi, Richard P. Cooper, Carlos R. Cortes, Nathaniel Daw, Paul Dean, Peter Ford Dominey, Pierre Enel, Jean-Marc Fellous, Stefano Fusi, Wulfram Gerstner, Frank Grasso, Jacqueline A. Griego, Ziad M. Hafed, Michael E. Hasselmo, Auke Ijspeert, Stephanie Jones, Daniel Kersten, Jeremie Knuesel, Owen Lewis, William W. Lytton, Tomaso Poggio, John Porrill, Tony J. Prescott, John Rinzel, Edmund Rolls, Jonathan Rubin, Nicolas Schweighofer, Mohamed A. Sherif, Malle A. Tagamets, Paul F. M. J. Verschure, Nathan Vierling-Claasen, Xiao-Jing Wang, Christopher Williams, Ransom Winder, Alan L. Yuille

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Product Format
Product Details
ISBN-13: 9780262034968
ISBN-10: 0262034964
Binding: Hardback or Cased Book (Sewn)
Content Language: English
More Product Details
Page Count: 808
Carton Quantity: 8
Product Dimensions: 8.70 x 1.30 x 11.00 inches
Weight: 4.10 pound(s)
Feature Codes: Bibliography, Index, Price on Product, Illustrated
Country of Origin: US
Subject Information
BISAC Categories
Science | Life Sciences - Neuroscience
Science | Computer Science
Science | Neuroscience
Grade Level: College Freshman and up
Dewey Decimal: 612.823
Library of Congress Control Number: 2016013116
Descriptions, Reviews, Etc.
publisher marketing
A comprehensive, integrated, and accessible textbook presenting core neuroscientific topics from a computational perspective, tracing a path from cells and circuits to behavior and cognition.

This textbook presents a wide range of subjects in neuroscience from a computational perspective. It offers a comprehensive, integrated introduction to core topics, using computational tools to trace a path from neurons and circuits to behavior and cognition. Moreover, the chapters show how computational neuroscience--methods for modeling the causal interactions underlying neural systems--complements empirical research in advancing the understanding of brain and behavior.

The chapters--all by leaders in the field, and carefully integrated by the editors--cover such subjects as action and motor control; neuroplasticity, neuromodulation, and reinforcement learning; vision; and language--the core of human cognition.

The book can be used for advanced undergraduate or graduate level courses. It presents all necessary background in neuroscience beyond basic facts about neurons and synapses and general ideas about the structure and function of the human brain. Students should be familiar with differential equations and probability theory, and be able to pick up the basics of programming in MATLAB and/or Python. Slides, exercises, and other ancillary materials are freely available online, and many of the models described in the chapters are documented in the brain operation database, BODB (which is also described in a book chapter).

Contributors
Michael A. Arbib, Joseph Ayers, James Bednar, Andrej Bicanski, James J. Bonaiuto, Nicolas Brunel, Jean-Marie Cabelguen, Carmen Canavier, Angelo Cangelosi, Richard P. Cooper, Carlos R. Cortes, Nathaniel Daw, Paul Dean, Peter Ford Dominey, Pierre Enel, Jean-Marc Fellous, Stefano Fusi, Wulfram Gerstner, Frank Grasso, Jacqueline A. Griego, Ziad M. Hafed, Michael E. Hasselmo, Auke Ijspeert, Stephanie Jones, Daniel Kersten, Jeremie Knuesel, Owen Lewis, William W. Lytton, Tomaso Poggio, John Porrill, Tony J. Prescott, John Rinzel, Edmund Rolls, Jonathan Rubin, Nicolas Schweighofer, Mohamed A. Sherif, Malle A. Tagamets, Paul F. M. J. Verschure, Nathan Vierling-Claasen, Xiao-Jing Wang, Christopher Williams, Ransom Winder, Alan L. Yuille

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Editor: Arbib, Michael A.
Michael A. Arbib is University Professor, Fletcher Jones Professor of Computer Science, and Professor of Biological Sciences, Biomedical Engineering, Electrical Engineering, Neuroscience, and Psychology at the University of Southern California. He is the author or editor of many books, including "The Handbook of Brain Theory and Neural Networks" (MIT Press, second edition 2002).
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Your Price  $113.85
Hardcover