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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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PRINTED FROM MIT PRESS SCHOLARSHIP ONLINE (www.mitpress.universitypressscholarship.com). (c) Copyright The MIT Press, 2022. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in MITSO for personal use.date: 02 July 2022

Passive Cable Modeling

Passive Cable Modeling

(p.233) 10 Passive Cable Modeling
Computational Modeling Methods for Neuroscientists

William R. Holmes

The MIT Press

This chapter examines the basic passive cable theory, evaluates the properties of passive systems important for experimentalists, and presents some insights from cable theory. It also describes how to estimate electrotonic parameter values from experimental data, along with problems associated with these older techniques. Modern methods for estimating parameter values from data for passive systems and guidelines for constructing passive models are explained, along with potential pitfalls that one should be aware of. The chapter suggests that passive electrotonic parameters in the model should be fit to match multiple voltage traces from the experimental cell, to make the modeled cell electrotonically similar to the experimental cell.

Keywords:   passive cable theory, passive systems, electrotonic parameter, passive models, multiple voltage

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