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

Edited by Nancy J. Kopell, Boston University, Boston, MA, and approved July 21, 2009
September 29, 2009
106 (39) 16829-16834


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.

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We thank A. Korngreen for helpful discussions concerning genetic algorithms. This work was supported by National Institutes of Health Grant NS-046064.

Supporting Information

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Supporting Information


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Published in

Go to Proceedings of the National Academy of Sciences
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Proceedings of the National Academy of Sciences
Vol. 106 | No. 39
September 29, 2009
PubMed: 19805381


Submission history

Received: April 5, 2009
Published online: September 29, 2009
Published in issue: September 29, 2009


We thank A. Korngreen for helpful discussions concerning genetic algorithms. This work was supported by National Institutes of Health Grant NS-046064.


This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/cgi/content/full/0807786105/DCSupplemental.
This formulation is the transpose of standard notation (3); this is done so that the incidence matrices in the graph-theoretic formulation to follow can be used in their standard forms.



Vilas Menon
Engineering Sciences and Applied Mathematics, McCormick School of Engineering;
Nelson Spruston
Neurobiology and Physiology, Weinberg College of Arts and Sciences; and
William L. Kath1 [email protected]
Engineering Sciences and Applied Mathematics, McCormick School of Engineering;
Neurobiology and Physiology, Weinberg College of Arts and Sciences; and
Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208


To whom correspondence should be addressed. E-mail: [email protected]
Author contributions: V.M., N.S., and W.L.K. designed research; V.M. and W.L.K. performed research; V.M. analyzed data; and V.M., N.S., and W.L.K. wrote the paper.

Competing Interests

The authors declare no conflict of interest.

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    A state-mutating genetic algorithm to design ion-channel models
    Proceedings of the National Academy of Sciences
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