1st Edition
Computational Neuroscience Realistic Modeling for Experimentalists
Edited By Erik De Schutter
Copyright 2001
368 Pages
by
CRC Press
368 Pages
by
CRC Press
Also available as eBook on:
Designed primarily as an introduction to realistic modeling methods, Computational Neuroscience: 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... Read more
Foreword
Introduction
Introduction to Equation Solving and Parameter Fitting
Modeling Networks of Signaling Pathways
Modeling Local and Global Calcium Signals Using Reaction-Diffusion Systems
Monte Carlo methods for Simulating Realistic Synaptic Microphysiology Using Mcell
Which Formalism to Use for Modeling Voltage-Dependent Conductances
Accurate Reconstruction of Neuronal Morphology
Modeling Dendritic Geometry and the Development of Nerve Connections
Passive Cable Modeling - a Practical Introduction
Modeling Simple and Complex Active Neurons
Realistic Modeling of Small Neuronal Circuits
Modeling of Large Networks
Modeling of Interactions Between Neural Networks and Musculoskeletal Systems
Introduction
Introduction to Equation Solving and Parameter Fitting
Modeling Networks of Signaling Pathways
Modeling Local and Global Calcium Signals Using Reaction-Diffusion Systems
Monte Carlo methods for Simulating Realistic Synaptic Microphysiology Using Mcell
Which Formalism to Use for Modeling Voltage-Dependent Conductances
Accurate Reconstruction of Neuronal Morphology
Modeling Dendritic Geometry and the Development of Nerve Connections
Passive Cable Modeling - a Practical Introduction
Modeling Simple and Complex Active Neurons
Realistic Modeling of Small Neuronal Circuits
Modeling of Large Networks
Modeling of Interactions Between Neural Networks and Musculoskeletal Systems
Biography
Erik De Schutter
"This book is a refreshing exception to [the dour expectations of multiauthored books]. Instead of merely repackaging their own scientific findings, the authors focused on the methodology of creating computational implementations of conceptual models of biological neurons and networks."
- N.T. Carnevale, Psychology, Yale University, in The Quarterly Review of Biology, Vol. 77, No. 2
