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Computational Modeling Methods for Neuroscientists$
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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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Large-Scale Network Simulations in Systems Neuroscience

Large-Scale Network Simulations in Systems Neuroscience

Chapter:
(p.317) 13 Large-Scale Network Simulations in Systems Neuroscience
Source:
Computational Modeling Methods for Neuroscientists
Author(s):

Reinoud Maex

Michiel Berends

Hugo Cornelis

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262013277.003.0014

This chapter deals with the large networks in systems neuroscience. It presents examples of scientific questions that warranted the simulation of large-scale networks, along with a summary of alternative solution strategies which avoid large-scale simulations. The chapter reports the most important and time-consuming part of the modeling process—network design—and analyzes the large-scale datasets and the epistemological question of how much physiological inference can be made from incompletely constrained models. It shows that nonlinear systems can display complex interactions among processes with different time courses.

Keywords:   systems neuroscience, large-scale networks, simulations, network design, nonlinear systems, large-scale datasets

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