English

Multiscale modeling via split-step methods in neural firing

Neurons and Cognition 2018-10-26 v2

Abstract

Neuronal models based on the Hodgkin-Huxley equation form a fundamental framework in the field of computational neuroscience. While the neuronal state is often modeled deterministically, experimental recordings show stochastic fluctuations, presumably driven by molecular noise from the underlying microphysical conditions. In turn, the firing of individual neurons gives rise to an electric field n extracellular space, also thought to affect the firing pattern of nearby neurons. We develop a multiscale model which combines a stochastic ion channel gating process taking place on the neuronal membrane, together with the propagation of an action potential along the neuronal structure. We also devise a numerical method relying on a split-step strategy which effectively couples these two processes and we experimentally test the feasibility of this approach. We finally also explain how the approach can be extended with Maxwell's equations to allow the potential to be propagated in extracellular space.

Keywords

Cite

@article{arxiv.1611.00509,
  title  = {Multiscale modeling via split-step methods in neural firing},
  author = {Pavol Bauer and Stefan Engblom and Sanja Mikulovic and Aleksandar Senek},
  journal= {arXiv preprint arXiv:1611.00509},
  year   = {2018}
}

Comments

23 pages, 10 figures

R2 v1 2026-06-22T16:39:29.004Z