Annals of Biomedical Engineering

, Volume 35, Issue 2, pp 315–318 | Cite as

Implementation Issues in Approximate Methods for Stochastic Hodgkin–Huxley Models

  • Ian C. BruceEmail author
Letter to the editor


The article by Mino et al.7 compares four different algorithms for implementing Hodgkin–Huxley models6 with stochastic sodium channels: Strassberg and DeFelice (1993),9 Rubinstein (1995),8 Chow and White (1996),3 and Fox (1997).4 The first three algorithms utilize exact methods for describing channel kinetics with finite-state Markov process models. In contrast, the algorithm of Fox uses stochastic differential equations (SDEs) to approximate the Markov process models. In addition to being simpler, the approximate method of Fox is around 7 times faster than the Chow & White algorithm, the fastest of the exact methods.7 However, for simulations of a patch of membrane with 1,000 sodium channels, Mino et al.7reported that the approximate method of Fox produced quite different action potential (AP) statistics than the other methods. They consequently argued that, in spite of its computational advantage, the Fox algorithm may be too inaccurate in some circumstances to use...


Current Amplitude Stimulus Current Relative Spread Show Simulation Result Huxley Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The author thanks Hiroyuki Mino for providing model code and corrected parameter values and Faheem Dinath for computer programming assistance.


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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringMcMaster UniversityHamiltonCanada

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