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Computational Modeling Methods for Neuroscientists$
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Computational Modeling Methods for Neuroscientists

Erik De Schutter

Print publication date: 2009

Print ISBN-13: 9780262013277

Published to MIT Press Scholarship Online: August 2013

DOI: 10.7551/mitpress/9780262013277.001.0001

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PRINTED FROM MIT PRESS SCHOLARSHIP ONLINE (www.mitpress.universitypressscholarship.com). (c) Copyright The MIT Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in MITSO for personal use.date: 28 November 2021

Introduction

Introduction

Chapter:
(p.ix) Introduction
Source:
Computational Modeling Methods for Neuroscientists
Author(s):

Erik De Schutter

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262013277.003.0001

This book concentrates on data-driven modeling, i.e., the use of fairly standardized modeling methods to replicate the behavior of neural systems at different levels of detail. The chapters are structured in intuitive order and try to cover all aspects of neural modeling, from molecules to networks. Each addresses the equations needed to simulate these models, sources of data for the model parameters, approaches to validate the models, and a short review of relevant models. This chapter provides an overview of those that follow.

Keywords:   data-driven modeling, neural systems, neural modeling, molecules, networks

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