Asymptotic model of electrical stimulation of nerve fibers.

We present a novel theory and computational algorithm for modeling electrical stimulation of nerve fibers in three dimensions. Our approach uses singular perturbation to separate the full 3D boundary value problem into a set of 2D "transverse" problems coupled with a 1D "longitudinal" problem. The r...

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Publicado en:Medical & Biological Engineering & Computing Vol. 50; no. 3; pp. 243 - 252
Autores principales: Cranford JP, Kim BJ, Krassowska Neu W, Cranford, Jonathan P, Kim, Brian J, Neu, Wanda Krassowska
Formato: Journal Article
Publicado: Springer Nature Mar2012
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2012
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      pub: Springer Nature
      place: New York, New York
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          Cranford JP
          Kim BJ
          Krassowska Neu W
          Cranford, Jonathan P
          Kim, Brian J
          Neu, Wanda Krassowska
        affil: Department of Biomedical Engineering, Duke University, Box 90281, Durham, NC 27708-0281, USA
      sug:
        subj:
          Electric Stimulation Methods
          Models, Biological
          Nerve Fibers Physiology
          Algorithms
          Membrane Potentials Physiology
      ab: We present a novel theory and computational algorithm for modeling electrical stimulation of nerve fibers in three dimensions. Our approach uses singular perturbation to separate the full 3D boundary value problem into a set of 2D "transverse" problems coupled with a 1D "longitudinal" problem. The resulting asymptotic model contains not one but two activating functions (AF): the longitudinal AF that drives the slow development of the mean transmembrane potential and the transverse AF that drives the rapid polarization of the fiber in the transverse direction. The asymptotic model is implemented for a prototype 3D cylindrical fiber with a passive membrane in an isotropic extracellular region. The validity of this approach is tested by comparing the numerical solution of the asymptotic model to the analytical solutions. The results show that the asymptotic model predicts steady-state transmembrane potential directly under the electrodes with the root mean square error of 0.539 mV, i.e., 1.04% of the maximum transmembrane potential. Thus, this work has created a computationally efficient algorithm that facilitates studies of the complete spatiotemporal dynamics of nerve fibers in three dimensions.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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