Literature DB >> 12935171

Comparison of asymptotics of heart and nerve excitability.

Rebecca Suckley1, Vadim N Biktashev.   

Abstract

We analyze the asymptotic structure of two classical models of mathematical biology, the models of electrical action by Hodgkin-Huxley (1952) for a giant squid axon and by Noble (1962) for mammalian Purkinje fibres. We use the procedure of parametric embedding to formally introduce small parameters in these experiment-based models. Although one of the models was designed as a modification of the other, their structure with respect to the small parameters appears to be entirely different: the Hodgkin-Huxley model has two slow and two fast variables, while Noble's model has one slow variable, two fast variables, and one superfast variable. The singular perturbation theory of these models adequately reproduces some features of the accurate numeric solutions, such as excitability and the shape of the voltage upstroke, but fails to reproduce other features, such as the relatively slow return from the excited state, compared to the speed of the upstroke. We present arguments towards the viewpoint that contrary to the conjecture proposed by Zeeman (1972), for these two models this failure is an inevitable consequence of the Tikhonov-style appearance of the small parameters, and a more adequate asymptotic description may only be achieved with small parameters entering the equations in a significantly different way.

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Year:  2003        PMID: 12935171     DOI: 10.1103/PhysRevE.68.011902

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  6 in total

1.  Conditions for propagation and block of excitation in an asymptotic model of atrial tissue.

Authors:  Radostin D Simitev; Vadim N Biktashev
Journal:  Biophys J       Date:  2006-01-13       Impact factor: 4.033

2.  Reconstructing parameters of the FitzHugh-Nagumo system from boundary potential measurements.

Authors:  Yuan He; David E Keyes
Journal:  J Comput Neurosci       Date:  2007-05-10       Impact factor: 1.621

3.  Reduction of stochastic conductance-based neuron models with time-scales separation.

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Journal:  J Comput Neurosci       Date:  2011-08-13       Impact factor: 1.621

4.  Nonlinear model-based cardiac arrhythmia diagnosis using the optimization-based inverse problem solution.

Authors:  Maryam Gholami; Mahsa Maleki; Saeed Amirkhani; Ali Chaibakhsh
Journal:  Biomed Eng Lett       Date:  2022-03-07

5.  Quantitative Decomposition of Dynamics of Mathematical Cell Models: Method and Application to Ventricular Myocyte Models.

Authors:  Takao Shimayoshi; Chae Young Cha; Akira Amano
Journal:  PLoS One       Date:  2015-06-19       Impact factor: 3.240

6.  A method of ‘speed coefficients’ for biochemical model reduction applied to the NF-κB system.

Authors:  Simon West; Lloyd J Bridge; Michael R H White; Pawel Paszek; Vadim N Biktashev
Journal:  J Math Biol       Date:  2015-02       Impact factor: 2.259

  6 in total

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