Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition

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9781107060838: Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition

What happens in our brain when we make a decision? What triggers a neuron to send out a signal? What is the neural code? This textbook for advanced undergraduate and beginning graduate students provides a thorough and up-to-date introduction to the fields of computational and theoretical neuroscience. It covers classical topics, including the Hodgkin-Huxley equations and Hopfield model, as well as modern developments in the field such as generalized linear models and decision theory. Concepts are introduced using clear step-by-step explanations suitable for readers with only a basic knowledge of differential equations and probabilities, and are richly illustrated by figures and worked-out examples. End-of-chapter summaries and classroom-tested exercises make the book ideal for courses or for self-study. The authors also give pointers to the literature and an extensive bibliography, which will prove invaluable to readers interested in further study.

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Book Description:

Exploring neuron models, the neural code, decision making and learning, this textbook provides a thorough and up-to-date introduction to computational neuroscience for advanced undergraduate and beginning graduate students. With step-by-step explanations, end-of-chapter summaries and classroom-tested exercises, it is ideal for courses or for self-study.

About the Author:

Wulfram Gerstner is Director of the Laboratory of Computational Neuroscience and a Professor of Life Sciences and Computer Science at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. He studied physics in Tubingen and Munich and holds a PhD from the Technical University of Munich. His research in computational neuroscience concentrates on models of spiking neurons and synaptic plasticity. He teaches computational neuroscience to physicists, computer scientists, mathematicians, and life scientists. He is a co-author of Spiking Neuron Models (Cambridge, 2002).

Werner M. Kistler received a Master's and PhD in physics from the Technical University of Munich. He previously worked as Assistant Professor in Rotterdam for computational neuroscience and he is the co-author of Spiking Neuron Models (Cambridge, 2002). He is now working in Munich as a patent attorney. His scientific contributions are related to spiking neuron models, synaptic plasticity, and network models of the cerebellum and the inferior olive.

Richard Naud holds a PhD in computational neuroscience from the EPFL in Switzerland and a Bachelor's degree in physics from McGill University, Canada. He has published several scientific articles and book chapters on the dynamics of neurons. He is now a postdoctoral researcher.

Liam Paninski is a Professor in the Department of Statistics at Columbia University and co-director of the Grossman Center for the Statistics of Mind. He is also a member of the Center for Theoretical Neuroscience, the Kavli Institute for Brain Science and the doctoral program in neurobiology and behavior. He holds a PhD in neuroscience from New York University and a Bachelor's from Brown University. His work focuses on neuron models, estimation methods, neural coding and neural decoding. He teaches courses on computational statistics, inference, and statistical analysis of neural data.

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Wulfram Gerstner, Werner M. Kistler, Richard Naud
Editorial: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2014)
ISBN 10: 1107060834 ISBN 13: 9781107060838
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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2014. Hardback. Estado de conservación: New. Language: English . Brand New Book. What happens in our brain when we make a decision? What triggers a neuron to send out a signal? What is the neural code? This textbook for advanced undergraduate and beginning graduate students provides a thorough and up-to-date introduction to the fields of computational and theoretical neuroscience. It covers classical topics, including the Hodgkin-Huxley equations and Hopfield model, as well as modern developments in the field such as generalized linear models and decision theory. Concepts are introduced using clear step-by-step explanations suitable for readers with only a basic knowledge of differential equations and probabilities, and are richly illustrated by figures and worked-out examples. End-of-chapter summaries and classroom-tested exercises make the book ideal for courses or for self-study. The authors also give pointers to the literature and an extensive bibliography, which will prove invaluable to readers interested in further study. Nº de ref. de la librería AAU9781107060838

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Wulfram Gerstner, Werner M. Kistler, Richard Naud, Liam Paninski
Editorial: Cambridge University Press 2014-07-24, Cambridge (2014)
ISBN 10: 1107060834 ISBN 13: 9781107060838
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Descripción Cambridge University Press 2014-07-24, Cambridge, 2014. hardback. Estado de conservación: New. Nº de ref. de la librería 9781107060838

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Gerstner, Wulfram, Kistler, Werner M., Naud, Richard, Paninski, Liam
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ISBN 10: 1107060834 ISBN 13: 9781107060838
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Descripción Cambridge University Press, 2014. Estado de conservación: New. This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience. Num Pages: 590 pages, 280 b/w illus. 6 tables 80 exercises. BIC Classification: UYQN. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 253 x 181 x 30. Weight in Grams: 1286. . 2014. 1st Edition. Hardcover. . . . . . Nº de ref. de la librería V9781107060838

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Descripción Cambridge University Press, 2014. HRD. Estado de conservación: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Nº de ref. de la librería BB-9781107060838

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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2014. Hardback. Estado de conservación: New. Language: English . Brand New Book. What happens in our brain when we make a decision? What triggers a neuron to send out a signal? What is the neural code? This textbook for advanced undergraduate and beginning graduate students provides a thorough and up-to-date introduction to the fields of computational and theoretical neuroscience. It covers classical topics, including the Hodgkin-Huxley equations and Hopfield model, as well as modern developments in the field such as generalized linear models and decision theory. Concepts are introduced using clear step-by-step explanations suitable for readers with only a basic knowledge of differential equations and probabilities, and are richly illustrated by figures and worked-out examples. End-of-chapter summaries and classroom-tested exercises make the book ideal for courses or for self-study. The authors also give pointers to the literature and an extensive bibliography, which will prove invaluable to readers interested in further study. Nº de ref. de la librería AAU9781107060838

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Descripción Cambridge University Press, 2014. Estado de conservación: New. book. Nº de ref. de la librería ria9781107060838_rkm

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Descripción Cambridge University Press. Estado de conservación: New. This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience. Num Pages: 590 pages, 280 b/w illus. 6 tables 80 exercises. BIC Classification: UYQN. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 253 x 181 x 30. Weight in Grams: 1286. . 2014. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland. Nº de ref. de la librería V9781107060838

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Descripción Cambridge University Press, 2015. Estado de conservación: New. Nº de ref. de la librería EH9781107060838

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