Literature DB >> 19152030

Evaluation of stochastic differential equation approximation of ion channel gating models.

Ian C Bruce1.   

Abstract

Fox and Lu derived an algorithm based on stochastic differential equations for approximating the kinetics of ion channel gating that is simpler and faster than "exact" algorithms for simulating Markov process models of channel gating. However, the approximation may not be sufficiently accurate to predict statistics of action potential generation in some cases. The objective of this study was to develop a framework for analyzing the inaccuracies and determining their origin. Simulations of a patch of membrane with voltage-gated sodium and potassium channels were performed using an exact algorithm for the kinetics of channel gating and the approximate algorithm of Fox & Lu. The Fox & Lu algorithm assumes that channel gating particle dynamics have a stochastic term that is uncorrelated, zero-mean Gaussian noise, whereas the results of this study demonstrate that in many cases the stochastic term in the Fox & Lu algorithm should be correlated and non-Gaussian noise with a non-zero mean. The results indicate that: (i) the source of the inaccuracy is that the Fox & Lu algorithm does not adequately describe the combined behavior of the multiple activation particles in each sodium and potassium channel, and (ii) the accuracy does not improve with increasing numbers of channels.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19152030     DOI: 10.1007/s10439-009-9635-z

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  8 in total

1.  Persistent membranous cross correlations due to the multiplicity of gates in ion channels.

Authors:  Marifi Güler
Journal:  J Comput Neurosci       Date:  2011-05-17       Impact factor: 1.621

2.  Stochastic amplification of calcium-activated potassium currents in Ca2+ microdomains.

Authors:  David Arthur Stanley; Berj L Bardakjian; Mark L Spano; William L Ditto
Journal:  J Comput Neurosci       Date:  2011-05-03       Impact factor: 1.621

3.  Stochastic differential equation models for ion channel noise in Hodgkin-Huxley neurons.

Authors:  Joshua H Goldwyn; Nikita S Imennov; Michael Famulare; Eric Shea-Brown
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2011-04-11

4.  Simple, fast and accurate implementation of the diffusion approximation algorithm for stochastic ion channels with multiple states.

Authors:  Patricio Orio; Daniel Soudry
Journal:  PLoS One       Date:  2012-05-22       Impact factor: 3.240

5.  Accurate and fast simulation of channel noise in conductance-based model neurons by diffusion approximation.

Authors:  Daniele Linaro; Marco Storace; Michele Giugliano
Journal:  PLoS Comput Biol       Date:  2011-03-10       Impact factor: 4.475

Review 6.  The what and where of adding channel noise to the Hodgkin-Huxley equations.

Authors:  Joshua H Goldwyn; Eric Shea-Brown
Journal:  PLoS Comput Biol       Date:  2011-11-17       Impact factor: 4.475

7.  Diffusion approximation-based simulation of stochastic ion channels: which method to use?

Authors:  Danilo Pezo; Daniel Soudry; Patricio Orio
Journal:  Front Comput Neurosci       Date:  2014-11-03       Impact factor: 2.380

8.  The ISI distribution of the stochastic Hodgkin-Huxley neuron.

Authors:  Peter F Rowat; Priscilla E Greenwood
Journal:  Front Comput Neurosci       Date:  2014-10-08       Impact factor: 2.380

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.