A spectral element method with adaptive segmentation for accurately simulating extracellular electrical stimulation of neurons.

The capacity to quickly and accurately simulate extracellular stimulation of neurons is essential to the design of next-generation neural prostheses. Existing platforms for simulating neurons are largely based on finite-difference techniques; due to the complex geometries involved, the more powerful...

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Publicado en:Medical & Biological Engineering & Computing Vol. 55; no. 5; pp. 823 - 832
Autores principales: Eiber, Calvin, Dokos, Socrates, Lovell, Nigel, Suaning, Gregg, Eiber, Calvin D, Lovell, Nigel H, Suaning, Gregg J
Formato: Journal Article
Publicado: Springer Nature May2017
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
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        atl: A spectral element method with adaptive segmentation for accurately simulating extracellular electrical stimulation of neurons.
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        au:
          Eiber, Calvin
          Dokos, Socrates
          Lovell, Nigel
          Suaning, Gregg
          Eiber, Calvin D
          Lovell, Nigel H
          Suaning, Gregg J
        affil: Graduate School of Biomedical Engineering , University of New South Wales , Sydney 2052 Australia
      sug:
        subj:
          Neurons Physiology
          Finite Element Analysis
          Action Potentials Physiology
          Nerve Fibers Physiology
          Electric Stimulation Methods
          Electrodes, Implanted
          Models, Biological
          Computer Simulation
      ab: The capacity to quickly and accurately simulate extracellular stimulation of neurons is essential to the design of next-generation neural prostheses. Existing platforms for simulating neurons are largely based on finite-difference techniques; due to the complex geometries involved, the more powerful spectral or differential quadrature techniques cannot be applied directly. This paper presents a mathematical basis for the application of a spectral element method to the problem of simulating the extracellular stimulation of retinal neurons, which is readily extensible to neural fibers of any kind. The activating function formalism is extended to arbitrary neuron geometries, and a segmentation method to guarantee an appropriate choice of collocation points is presented. Differential quadrature may then be applied to efficiently solve the resulting cable equations. The capacity for this model to simulate action potentials propagating through branching structures and to predict minimum extracellular stimulation thresholds for individual neurons is demonstrated. The presented model is validated against published values for extracellular stimulation threshold and conduction velocity for realistic physiological parameter values. This model suggests that convoluted axon geometries are more readily activated by extracellular stimulation than linear axon geometries, which may have ramifications for the design of neural prostheses.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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