Literature DB >> 23503026

Computationally efficient simulation of electrical activity at cell membranes interacting with self-generated and externally imposed electric fields.

Andres Agudelo-Toro1, Andreas Neef.   

Abstract

OBJECTIVE: We present a computational method that implements a reduced set of Maxwell's equations to allow simulation of cells under realistic conditions: sub-micron cell morphology, a conductive non-homogeneous space and various ion channel properties and distributions. APPROACH: While a reduced set of Maxwell's equations can be used to couple membrane currents to extra- and intracellular potentials, this approach is rarely taken, most likely because adequate computational tools are missing. By using these equations, and introducing an implicit solver, numerical stability is attained even with large time steps. The time steps are limited only by the time development of the membrane potentials. MAIN
RESULTS: This method allows simulation times of tens of minutes instead of weeks, even for complex problems. The extracellular fields are accurately represented, including secondary fields, which originate at inhomogeneities of the extracellular space and can reach several millivolts. We present a set of instructive examples that show how this method can be used to obtain reference solutions for problems, which might not be accurately captured by the traditional approaches. This includes the simulation of realistic magnitudes of extracellular action potential signals in restricted extracellular space. SIGNIFICANCE: The electric activity of neurons creates extracellular potentials. Recent findings show that these endogenous fields act back onto the neurons, contributing to the synchronization of population activity. The influence of endogenous fields is also relevant for understanding therapeutic approaches such as transcranial direct current, transcranial magnetic and deep brain stimulation. The mutual interaction between fields and membrane currents is not captured by today's concepts of cellular electrophysiology, including the commonly used activation function, as those concepts are based on isolated membranes in an infinite, isopotential extracellular space. The presented tool makes simulations with detailed morphology and implicit interactions of currents and fields available to the electrophysiology community.

Mesh:

Year:  2013        PMID: 23503026     DOI: 10.1088/1741-2560/10/2/026019

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  17 in total

1.  Cortical neuron activation induced by electromagnetic stimulation: a quantitative analysis via modelling and simulation.

Authors:  Tiecheng Wu; Jie Fan; Kim Seng Lee; Xiaoping Li
Journal:  J Comput Neurosci       Date:  2015-12-30       Impact factor: 1.621

2.  Neuronal coupling by endogenous electric fields: cable theory and applications to coincidence detector neurons in the auditory brain stem.

Authors:  Joshua H Goldwyn; John Rinzel
Journal:  J Neurophysiol       Date:  2016-01-28       Impact factor: 2.714

Review 3.  The development and modelling of devices and paradigms for transcranial magnetic stimulation.

Authors:  Stefan M Goetz; Zhi-De Deng
Journal:  Int Rev Psychiatry       Date:  2017-04-26

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

Authors:  Boshuo Wang; Aman S Aberra; Warren M Grill; Angel V Peterchev
Journal:  J Neural Eng       Date:  2018-04       Impact factor: 5.379

5.  Multiscale coupling of transcranial direct current stimulation to neuron electrodynamics: modeling the influence of the transcranial electric field on neuronal depolarization.

Authors:  Edward T Dougherty; James C Turner; Frank Vogel
Journal:  Comput Math Methods Med       Date:  2014-10-23       Impact factor: 2.238

6.  Modelling and Analysis of Electrical Potentials Recorded in Microelectrode Arrays (MEAs).

Authors:  Torbjørn V Ness; Chaitanya Chintaluri; Jan Potworowski; Szymon Łęski; Helena Głąbska; Daniel K Wójcik; Gaute T Einevoll
Journal:  Neuroinformatics       Date:  2015-10

7.  An Evaluation of the Accuracy of Classical Models for Computing the Membrane Potential and Extracellular Potential for Neurons.

Authors:  Aslak Tveito; Karoline H Jæger; Glenn T Lines; Łukasz Paszkowski; Joakim Sundnes; Andrew G Edwards; Tuomo Māki-Marttunen; Geir Halnes; Gaute T Einevoll
Journal:  Front Comput Neurosci       Date:  2017-04-24       Impact factor: 2.380

8.  Properties of cardiac conduction in a cell-based computational model.

Authors:  Karoline Horgmo Jæger; Andrew G Edwards; Andrew McCulloch; Aslak Tveito
Journal:  PLoS Comput Biol       Date:  2019-05-31       Impact factor: 4.475

9.  Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue.

Authors:  Geir Halnes; Tuomo Mäki-Marttunen; Daniel Keller; Klas H Pettersen; Ole A Andreassen; Gaute T Einevoll
Journal:  PLoS Comput Biol       Date:  2016-11-07       Impact factor: 4.475

10.  A Kirchhoff-Nernst-Planck framework for modeling large scale extracellular electrodiffusion surrounding morphologically detailed neurons.

Authors:  Andreas Solbrå; Aslak Wigdahl Bergersen; Jonas van den Brink; Anders Malthe-Sørenssen; Gaute T Einevoll; Geir Halnes
Journal:  PLoS Comput Biol       Date:  2018-10-04       Impact factor: 4.475

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