4.6 Article

Modeling extracellular electrical stimulation: I. Derivation and interpretation of neurite equations

期刊

JOURNAL OF NEURAL ENGINEERING
卷 9, 期 6, 页码 -

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IOP PUBLISHING LTD
DOI: 10.1088/1741-2560/9/6/065005

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资金

  1. Australian Research Council (ARC) through its Special Research Initiative (SRI) in Bionic Vision Science and Technology
  2. Victorian Government through its Operational Infrastructure Support Program
  3. Victorian Life Sciences Computation Initiative (VLSCI) on its Peak Computing Facility at the University of Melbourne, an initiative of the Victorian Government [VR0138]

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Neuroprosthetic devices, such as cochlear and retinal implants, work by directly stimulating neurons with extracellular electrodes. This is commonly modeled using the cable equation with an applied extracellular voltage. In this paper a framework for modeling extracellular electrical stimulation is presented. To this end, a cylindrical neurite with confined extracellular space in the subthreshold regime is modeled in three-dimensional space. Through cylindrical harmonic expansion of Laplace's equation, we derive the spatio-temporal equations governing different modes of stimulation, referred to as longitudinal and transverse modes, under types of boundary conditions. The longitudinal mode is described by the well-known cable equation, however, the transverse modes are described by a novel ordinary differential equation. For the longitudinal mode, we find that different electrotonic length constants apply under the two different boundary conditions. Equations connecting current density to voltage boundary conditions are derived that are used to calculate the trans-impedance of the neurite-plus-thin-extracellular-sheath. A detailed explanation on depolarization mechanisms and the dominant current pathway under different modes of stimulation is provided. The analytic results derived here enable the estimation of a neurite's membrane potential under extracellular stimulation, hence bypassing the heavy computational cost of using numerical methods.

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