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Modified cable equation incorporating transverse polarization of neuronal membranes for accurate coupling of electric fields.

Publication ,  Journal Article
Wang, B; Aberra, AS; Grill, WM; Peterchev, AV
Published in: J Neural Eng
April 2018

OBJECTIVE: We present a theory and computational methods to incorporate transverse polarization of neuronal membranes into the cable equation to account for the secondary electric field generated by the membrane in response to transverse electric fields. The effect of transverse polarization on nonlinear neuronal activation thresholds is quantified and discussed in the context of previous studies using linear membrane models. APPROACH: The response of neuronal membranes to applied electric fields is derived under two time scales and a unified solution of transverse polarization is given for spherical and cylindrical cell geometries. The solution is incorporated into the cable equation re-derived using an asymptotic model that separates the longitudinal and transverse dimensions. Two numerical methods are proposed to implement the modified cable equation. Several common neural stimulation scenarios are tested using two nonlinear membrane models to compare thresholds of the conventional and modified cable equations. MAIN RESULTS: The implementations of the modified cable equation incorporating transverse polarization are validated against previous results in the literature. The test cases show that transverse polarization has limited effect on activation thresholds. The transverse field only affects thresholds of unmyelinated axons for short pulses and in low-gradient field distributions, whereas myelinated axons are mostly unaffected. SIGNIFICANCE: The modified cable equation captures the membrane's behavior on different time scales and models more accurately the coupling between electric fields and neurons. It addresses the limitations of the conventional cable equation and allows sound theoretical interpretations. The implementation provides simple methods that are compatible with current simulation approaches to study the effect of transverse polarization on nonlinear membranes. The minimal influence by transverse polarization on axonal activation thresholds for the nonlinear membrane models indicates that predictions of stronger effects in linear membrane models with a fixed activation threshold are inaccurate. Thus, the conventional cable equation works well for most neuroengineering applications, and the presented modeling approach is well suited to address the exceptions.

Duke Scholars

Published In

J Neural Eng

DOI

EISSN

1741-2552

Publication Date

April 2018

Volume

15

Issue

2

Start / End Page

026003

Location

England

Related Subject Headings

  • Nonlinear Dynamics
  • Neurons
  • Models, Neurological
  • Membrane Potentials
  • Humans
  • Cell Membrane
  • Biomedical Engineering
  • 4003 Biomedical engineering
  • 3209 Neurosciences
  • 1109 Neurosciences
 

Citation

APA
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ICMJE
MLA
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Wang, B., Aberra, A. S., Grill, W. M., & Peterchev, A. V. (2018). Modified cable equation incorporating transverse polarization of neuronal membranes for accurate coupling of electric fields. J Neural Eng, 15(2), 026003. https://doi.org/10.1088/1741-2552/aa8b7c
Wang, Boshuo, Aman S. Aberra, Warren M. Grill, and Angel V. Peterchev. “Modified cable equation incorporating transverse polarization of neuronal membranes for accurate coupling of electric fields.J Neural Eng 15, no. 2 (April 2018): 026003. https://doi.org/10.1088/1741-2552/aa8b7c.
Wang, Boshuo, et al. “Modified cable equation incorporating transverse polarization of neuronal membranes for accurate coupling of electric fields.J Neural Eng, vol. 15, no. 2, Apr. 2018, p. 026003. Pubmed, doi:10.1088/1741-2552/aa8b7c.
Journal cover image

Published In

J Neural Eng

DOI

EISSN

1741-2552

Publication Date

April 2018

Volume

15

Issue

2

Start / End Page

026003

Location

England

Related Subject Headings

  • Nonlinear Dynamics
  • Neurons
  • Models, Neurological
  • Membrane Potentials
  • Humans
  • Cell Membrane
  • Biomedical Engineering
  • 4003 Biomedical engineering
  • 3209 Neurosciences
  • 1109 Neurosciences