Literature DB >> 16563440

Hodgkin-Huxley type ion channel characterization: an improved method of voltage clamp experiment parameter estimation.

Jack Lee1, Bruce Smaill, Nicolas Smith.   

Abstract

The Hodgkin-Huxley formalism for quantitative characterization of ionic channels is widely used in cellular electrophysiological models. Model parameters for these individual channels are determined from voltage clamp experiments and usually involve the assumption that inactivation process occurs on a time scale which is infinitely slow compared to the activation process. This work shows that such an assumption may lead to appreciable errors under certain physiological conditions and proposes a new numerical approach to interpret voltage clamp experiment results. In simulated experimental protocols the new method was shown to exhibit superior accuracy compared to the traditional least squares fitting methods. With noiseless input data the error in gating variables and time constants was less than 1%, whereas the traditional methods generated upwards of 10% error and predicted incorrect gating kinetics. A sensitivity analysis showed that the new method could tolerate up to approximately 15% perturbation in the input data without unstably amplifying error in the solution. This method could also assist in designing more efficient experimental protocols, since all channel parameters (gating variables, time constants and maximum conductance) could be determined from a single voltage step.

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Year:  2006        PMID: 16563440     DOI: 10.1016/j.jtbi.2006.02.006

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  8 in total

1.  Extending the conditions of application of an inversion of the Hodgkin-Huxley gating model.

Authors:  Ashley E Raba; Jonathan M Cordeiro; Charles Antzelevitch; Jacques Beaumont
Journal:  Bull Math Biol       Date:  2013-04-18       Impact factor: 1.758

2.  Estimability Analysis and Optimal Design in Dynamic Multi-scale Models of Cardiac Electrophysiology.

Authors:  Matthew S Shotwell; Richard A Gray
Journal:  J Agric Biol Environ Stat       Date:  2016-01-21       Impact factor: 1.524

Review 3.  Improving cardiomyocyte model fidelity and utility via dynamic electrophysiology protocols and optimization algorithms.

Authors:  Trine Krogh-Madsen; Eric A Sobie; David J Christini
Journal:  J Physiol       Date:  2016-02-04       Impact factor: 5.182

Review 4.  Calibration of ionic and cellular cardiac electrophysiology models.

Authors:  Dominic G Whittaker; Michael Clerx; Chon Lok Lei; David J Christini; Gary R Mirams
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2020-02-21

5.  Hodgkin-Huxley revisited: reparametrization and identifiability analysis of the classic action potential model with approximate Bayesian methods.

Authors:  Aidan C Daly; David J Gavaghan; Chris Holmes; Jonathan Cooper
Journal:  R Soc Open Sci       Date:  2015-12-23       Impact factor: 2.963

Review 6.  Validation and Trustworthiness of Multiscale Models of Cardiac Electrophysiology.

Authors:  Pras Pathmanathan; Richard A Gray
Journal:  Front Physiol       Date:  2018-02-15       Impact factor: 4.566

7.  Reproducible model development in the cardiac electrophysiology Web Lab.

Authors:  Aidan C Daly; Michael Clerx; Kylie A Beattie; Jonathan Cooper; David J Gavaghan; Gary R Mirams
Journal:  Prog Biophys Mol Biol       Date:  2018-05-26       Impact factor: 3.667

8.  Four Ways to Fit an Ion Channel Model.

Authors:  Michael Clerx; Kylie A Beattie; David J Gavaghan; Gary R Mirams
Journal:  Biophys J       Date:  2019-08-06       Impact factor: 4.033

  8 in total

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