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Prog Biophys Mol Biol. 2004 Jun-Jul;85(2-3):407-31.

Parameter estimation in cardiac ionic models.

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  • 1Graduate School of Biomedical Engineering, University of New South Wales, Sydney 2052, NSW, Australia. s.dokos@unsw.edu.au

Abstract

We examine the problem of parameter estimation in mathematical models of excitable cell cardiac electrical activity using the well-known Beeler-Reuter (1977) ionic equations for the ventricular action potential. The estimation problem can be regarded as equivalent to the accurate reconstruction of ionic current kinetics and amplitudes in an excitable cell model, given only action potential experimental data. We show that in the Beeler-Reuter case, all ionic currents may be reasonably reconstructed using an experimental design consisting of action potential recordings perturbed by pseudo-random injection currents. The Beeler-Reuter model was parameterised into 63 parameters completely defining all membrane current amplitudes and kinetics. Total membrane current was fitted to model-generated experimental data using a 'data-clamp' protocol. The experimental data consisted of a default action-potential waveform and an optional series of perturbed waveforms generated by current injections. Local parameter identifiability was ascertained from the reciprocal condition value (1/lambda) of the Hessian at the known solution. When fitting to a single action potential waveform, the model was found to be over-determined, having a 1/lambda value of approximately 3.6e-14. This value improved slightly to approximately 1.4e-10 when an additional 2 perturbed waveforms were included in the fitting process, suggesting that the additional data did not overly improve the identifiability problem. The additional data, however, did allow the accurate reconstruction of all ionic currents. This indicates that by appropriate experimental design, it may be possible to infer the properties of underlying membrane currents from observation of transmembrane potential waveforms perturbed by pseudo-random currents.

Copyright 2004 Elsevier Ltd.

PMID:
15142755
[PubMed - indexed for MEDLINE]
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