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International Conference on Nonlinear Dynamics of Electronic Systems

NDES 2014: Nonlinear Dynamics of Electronic Systems pp 325–332Cite as

Stochastic Modeling of Excitable Dynamics: Improved Langevin Model for Mesoscopic Channel Noise

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 438))

Abstract

Influence of mesoscopic channel noise on excitable dynamics of living cells became a hot subject within the last decade, and the traditional biophysical models of neuronal dynamics such as Hodgkin-Huxley model have been generalized to incorporate such effects. There still exists but a controversy on how to do it in a proper and computationally efficient way. Here we introduce an improved Langevin description of stochastic Hodgkin-Huxley dynamics with natural boundary conditions for gating variables. It consistently describes the channel noise variance in a good agreement with discrete state model. Moreover, we show by comparison with our improved Langevin model that two earlier Langevin models by Fox and Lu also work excellently starting from several hundreds of ion channels upon imposing numerically reflecting boundary conditions for gating variables.

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Author information

Authors and Affiliations

  1. Institute for Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24/25, 14476, Potsdam-Golm, Germany

    Igor Goychuk

Authors
  1. Igor Goychuk
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Editor information

Editors and Affiliations

  1. Technical University of Sofia, 8 St. Kl. Ohridski Blvd., 1000, Sofia, Bulgaria

    Valeri M. Mladenov

  2. Physics Department, Boston University, 590 Commonwealth Avenue, 02215, Boston, MA, USA

    Plamen Ch. Ivanov

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© 2014 Springer International Publishing Switzerland

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Goychuk, I. (2014). Stochastic Modeling of Excitable Dynamics: Improved Langevin Model for Mesoscopic Channel Noise. In: Mladenov, V.M., Ivanov, P.C. (eds) Nonlinear Dynamics of Electronic Systems. NDES 2014. Communications in Computer and Information Science, vol 438. Springer, Cham. https://doi.org/10.1007/978-3-319-08672-9_38

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  • DOI: https://doi.org/10.1007/978-3-319-08672-9_38

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08671-2

  • Online ISBN: 978-3-319-08672-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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