Computational Modeling Methods for Neuroscientists (Computational Neuroscience)

✍ Scribed by Erik De Schutter

Publisher: The MIT Press
Year: 2009
Tongue: English
Leaves: 433
Series: Computational Neuroscience
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

A guide to computational modeling methods in neuroscience, covering a range of modeling scales from molecular reactions to large neural networks.

✦ Table of Contents

Contents......Page 6
Series Foreword......Page 8
Introduction......Page 10
1 Differential Equations......Page 14
2 Parameter Searching......Page 44
3 Reaction-Diffusion Modeling......Page 74
4 Modeling Intracellular Calcium Dynamics......Page 106
5 Modeling Voltage-Dependent Channels......Page 120
6 Modeling Synapses......Page 152
7 Modeling Point Neurons......Page 174
8 Reconstruction of Neuronal Morphology......Page 200
9 An Approach to Capturing Neuron Morphological Diversity......Page 224
10 Passive Cable Modeling......Page 246
11 Modeling Complex Neurons......Page 272
12 Realistic Modeling of Small Neuronal Networks......Page 298
13 Large-Scale Network Simulations in Systems Neuroscience......Page 330
Software Appendix......Page 368
References......Page 380
Contributors......Page 418
Index......Page 422

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