A state-mutating genetic algorithm to design ion-channel models

Vilas Menon, Nelson Spruston, William L. Kath

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Realistic computational models of single neurons require component ion channels that reproduce experimental findings. Here, a topology-mutating genetic algorithm that searches for the best state diagram and transition-rate parameters to model macroscopic ion-channel behavior is described. Important features of the algorithm include a topology-altering strategy, automatic satisfaction of equilibrium constraints (microscopic reversibility), and multiple-protocol fitting using sequential goal programming rather than explicit weighting. Application of this genetic algorithm to design a sodium-channel model exhibiting both fast and prolonged inactivation yields a six-state model that produces realistic activity-dependent attenuation of action-potential backpropagation in current-clamp simulations of a CA1 pyramidal neuron.

Original languageEnglish (US)
Pages (from-to)16829-16834
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume106
Issue number39
DOIs
StatePublished - Sep 29 2009

ASJC Scopus subject areas

  • General

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