An edition of Theoretical neuroscience
(2001)
Theoretical neuroscience
computational and mathematical modeling of neural systems
by Peter Dayan, Peter Dayan, and L. F. Abbott
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"Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate. This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory."--BOOK JACKET.
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Previews available in: English
Subjects
Computer simulation, Computational neuroscience, Human information processing, Neural networks (Neurobiology), Computer modelling & simulation, Neurosciences, Medical, Medical / Nursing, Neuroscience, Medical / Neuroscience, Computational neuroscience, Computer simulation, Human information processing, Neural networks (Neurobiology), Neural networks (neurobiology), Computer Neural Networks, Computer Simulation, Neurological Models, Neurosciences informatiques, Réseaux neuronaux (Neurobiologie), Simulation par ordinateur, Traitement de l'information chez l'homme, SOCIAL SCIENCE, Anthropology, Physical, Neurale netwerken, Cognitieve processen, Computersimulaties, Réseau neuronal (Biologie), Traitement de l'information par le cerveau, Neurone, Plasticité neuronale, Apprentissage, Modèle mathématique, Neuroscience informatique, Nerve Net, Medical Informatics ComputingShowing 2 featured editions. View all 2 editions?
| Edition | Availability |
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1
Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems
September 1, 2005, The MIT Press
Paperback
in English
0262541858 9780262541855
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2
Theoretical neuroscience: computational and mathematical modeling of neural systems
2001, Massachusetts Institute of Technology Press, The MIT Press
in English
0262041995 9780262041997
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Book Details
Published in
Cambridge, Mass
Table of Contents
Neural encoding I: firing rates and spike statistics
Neural encoding II: reverse correlation and visual receptive fields
Neural decoding
Information theory
Model neurons I: neuroelectronics
Model neurons II: conductances and morphology
Network models
Plasticity and learning
Classical conditioning and reinforcement learning
Representational learning
Mathematical appendix.
Edition Notes
Includes bibliographical references (p. [419]-438) and index.
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| November 14, 2023 | Edited by MARC Bot | import existing book |
| January 7, 2023 | Edited by MARC Bot | import existing book |
| July 31, 2020 | Edited by ImportBot | import existing book |
| July 30, 2019 | Edited by MARC Bot | associate edition with work OL11652198W |
| December 11, 2009 | Created by WorkBot | add works page |