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

Autor Wulfram Gerstner, Werner M. Kistler, Richard Naud, Liam Paninski
en Limba Engleză Paperback – 23 iul 2014
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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Specificații

ISBN-13: 9781107635197
ISBN-10: 1107635195
Pagini: 578
Ilustrații: 280 b/w illus. 6 tables 80 exercises
Dimensiuni: 174 x 246 x 26 mm
Greutate: 0.93 kg
Ediția:New.
Editura: Cambridge University Press
Colecția Cambridge University Press
Locul publicării:New York, United States

Cuprins

Preface; Part I. Foundations of Neuronal Dynamics: 1. Introduction; 2. The Hodgkin–Huxley model; 3. Dendrites and synapses; 4. Dimensionality reduction and phase plane analysis; Part II. Generalized Integrate-and-Fire Neurons: 5. Nonlinear integrate-and-fire models; 6. Adaptation and firing patterns; 7. Variability of spike trains and neural codes; 8. Noisy input models: barrage of spike arrivals; 9. Noisy output: escape rate and soft threshold; 10. Estimating models; 11. Encoding and decoding with stochastic neuron models; Part III. Networks of Neurons and Population Activity: 12. Neuronal populations; 13. Continuity equation and the Fokker–Planck approach; 14. The integral-equation approach; 15. Fast transients and rate models; Part IV. Dynamics of Cognition: 16. Competing populations and decision making; 17. Memory and attractor dynamics; 18. Cortical field models for perception; 19. Synaptic plasticity and learning; 20. Outlook: dynamics in plastic networks; Bibliography; Index.

Notă biografică


Descriere

This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.