Computational Modeling Methods for Neuroscientists (Computational Neuroscience Series)
| Author | : | |
| Rating | : | 4.91 (644 Votes) |
| Asin | : | 0262013274 |
| Format Type | : | paperback |
| Number of Pages | : | 432 Pages |
| Publish Date | : | 2016-12-22 |
| Language | : | English |
DESCRIPTION:
"An indispensable reference" according to TB. It sometimes seems to me that books on computational neuroscience are split into two categories: Books for people who want to understand the theory behind the models, and books for people who want to build and run models. This book is useful for the former, but indispensable for the latter. The coverage ranges from low-level topics (calcium dynamics, synapses) to high-level modeling of networks. The focus of the book is primarily on providing much of the information necessary to sit down in fr
(Mathematical Reviews)Neuroscientists with a computational background will benefit most from this book, and will find it a comprehensive source of information on how to build and critically assess neuron models at many levels of description. Successfully integrated data-driven modeling with experimental work…all of the material is accessible to experimentalists. (Giancarlo La Camera The Quarterly Review of Biology)
This book offers an introduction to current methods in computational modeling in neuroscience. The book describes realistic modeling methods at levels of complexity ranging from molecular interactions to large neural networks. van Rossum, Stefan Wils. Huguenard, William R. W. The chapters offer comprehensive coverage with little overlap and extensive cross-references, moving from basic building blocks to more complex applications.ContributorsPablo Achard, Haroon Anwar, Upinder S. It is intended for experimental neuroscientists and graduate students who have little formal training in mathematical methods, but it will also be useful for scientists with theoretical backgrounds who want to start using data-driven modeling methods. Prinz, Imad Riachi, John Rinzel, Arnd Roth, Felix Schürmann, Werner Van Geit, Mark C. Bhalla, Michiel Berends, Nicolas Brunel, Ronald L. A "how to" book rather than an analytical account, it focuses on the presentation of methodological approaches, including the selec
Erik De Schutter is Principal Investigator and Head of the Computational Neuroscience Unit at the Okinawa Institute of Science and Technology, Japan, and Head of the Theoretical Neurobiology Laboratory in the Department of Biomedical Sciences at the University of Antwerp, Belgium.