Computational Neuroscience: Realistic Modeling for Experimentalists

by Erik De Schutter (editor)

Designed primarily as an introduction to realistic modeling methods, Computational Realistic Modeling for Experimentalists focuses on methodological approaches, selecting appropriate methods, and identifying potential pitfalls. The author addresses varying levels of complexity, from molecular interactions within single neurons to the processing of information by neural networks. He avoids theoretical mathematics and provides just enough of the basic math used by experimentalists.

What makes this resource unique is the inclusion of downloadable resources that furnish interactive modeling examples. It contains tutorials and demos, movies and images, and the simulation scripts necessary to run the full simulation described in the chapter examples. Each chapter the theoretical foundation; parameters needed; appropriate software descriptions; evaluation of the model; future directions expected; examples in text boxes linked to the downloadable resources; and references.

The first book to bring you cutting-edge developments in neuronal modeling. It provides an introduction to realistic modeling methods at levels of complexity varying from molecular interactions to neural networks. The book and downloadable resources combine to make Computational Realistic Modeling for Experimentalists the complete package for understanding modeling techniques.

368 pages, Hardcover

First published January 1, 2000

About the author

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.