Neuronal Dynamics

From single neurons to networks and models of cognition

Wulfram Gerstner, Werner M. Kistler, Richard Naud and Liam Paninski

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.

Neuronal Dynamics was published with Cambridge University Press in July 2014.

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Wulfram Gerstner
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 Tübingen 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 co-author of Spiking Neuron Models (Cambridge University Press, 2002).
Werner M. Kistler
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 co-author of Spiking Neuron Models (Cambridge University Press, 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
Richard Naud holds a PhD in computational neuroscience from the École Polytechnique Fédérale de Lausanne (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 post-doctoral researcher.
Liam Paninski
Liam Paninski is a Professor in the statistics department 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.

Neuronal Dynamics is the true Everything you've always wanted to know about spiking models but were afraid to ask guide for those of us who care about action potentials, the computations they perform in the brain, and the information they represent and communicate to fellow neurons.

Christof Koch, Chief Scientific Officer, Allen Institute for Brain Science

... this book not only gives the mathematical underpinnings of theoretical neuroscience, but is also a very useful how to demonstration of the methods that have been used to solve specific neuronal modeling problems. I expect that, over the next few years, we will see many computational neuroscience papers inspired by the exemplars so well presented in this book.

Leonard Maler, University of Ottawa

This comprehensive book sets a new standard for modeling single neurons and networks. Students of the field can read it as a practical guide to computational neuroscience and will enjoy the hands-on examples, while researchers will appreciate its thorough analysis and up-to-date content.

Mark van Rossum, The University of Edinburgh

It will be a landmark for researchers in neuroscience wanting to learn, teach or deepen their understanding of the dynamical mechanisms underlying brain functions ... . I really enjoyed reading it and I will certainly use it for my own lectures (introductory and advanced). It is a book for your must-read list!

Gustavo Deco, Universitat Pompeu Fabra, Barcelona

You can order the book directly from Cambridge University Press or from Amazon.

The book is also available as an e-book in pdf format directly from Cambridge University Press.

Please see the table of contents of the online version of the book.