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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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Parameter Searching

Parameter Searching

Chapter:
(p.31) 2 Parameter Searching
Source:
Computational Modeling Methods for Neuroscientists
Author(s):

Pablo Achard

Werner Van Geit

Gwendal LeMasson

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262013277.003.0003

This chapter discusses the automated parameter-fitting methods and describes how to tune parameters in an efficient way. It tries to minimize the fitness values. Fitness functions are introduced for two concrete and common examples in the field of neuroscience“activation curves and electrophysiological traces“and the most traditional algorithms for current problems are addressed. The chapter then considers more complex problems and how they are handled, without entering into detailed descriptions of the machinery, and shows that an algorithm which is optimal for one problem will be poor for others.

Keywords:   parameter-fitting methods, fitness values, fitness functions, activation curves, electrophysiological traces, algorithms, neuroscience

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