Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue.

Recorded potentials in the extracellular space (ECS) of the brain is a standard measure of population activity in neural tissue. Computational models that simulate the relationship between the ECS potential and its underlying neurophysiological processes are commonly used in the interpretation of su...

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Main Authors: Geir Halnes, Tuomo Mäki-Marttunen, Daniel Keller, Klas H Pettersen, Ole A Andreassen, Gaute T Einevoll
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-11-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC5098741?pdf=render
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spelling doaj-1483af5fea1b43ee965c59e4b26504222020-11-24T21:58:58ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582016-11-011211e100519310.1371/journal.pcbi.1005193Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue.Geir HalnesTuomo Mäki-MarttunenDaniel KellerKlas H PettersenOle A AndreassenGaute T EinevollRecorded potentials in the extracellular space (ECS) of the brain is a standard measure of population activity in neural tissue. Computational models that simulate the relationship between the ECS potential and its underlying neurophysiological processes are commonly used in the interpretation of such measurements. Standard methods, such as volume-conductor theory and current-source density theory, assume that diffusion has a negligible effect on the ECS potential, at least in the range of frequencies picked up by most recording systems. This assumption remains to be verified. We here present a hybrid simulation framework that accounts for diffusive effects on the ECS potential. The framework uses (1) the NEURON simulator to compute the activity and ionic output currents from multicompartmental neuron models, and (2) the electrodiffusive Kirchhoff-Nernst-Planck framework to simulate the resulting dynamics of the potential and ion concentrations in the ECS, accounting for the effect of electrical migration as well as diffusion. Using this framework, we explore the effect that ECS diffusion has on the electrical potential surrounding a small population of 10 pyramidal neurons. The neural model was tuned so that simulations over ∼100 seconds of biological time led to shifts in ECS concentrations by a few millimolars, similar to what has been seen in experiments. By comparing simulations where ECS diffusion was absent with simulations where ECS diffusion was included, we made the following key findings: (i) ECS diffusion shifted the local potential by up to ∼0.2 mV. (ii) The power spectral density (PSD) of the diffusion-evoked potential shifts followed a 1/f2 power law. (iii) Diffusion effects dominated the PSD of the ECS potential for frequencies up to several hertz. In scenarios with large, but physiologically realistic ECS concentration gradients, diffusion was thus found to affect the ECS potential well within the frequency range picked up in experimental recordings.http://europepmc.org/articles/PMC5098741?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Geir Halnes
Tuomo Mäki-Marttunen
Daniel Keller
Klas H Pettersen
Ole A Andreassen
Gaute T Einevoll
spellingShingle Geir Halnes
Tuomo Mäki-Marttunen
Daniel Keller
Klas H Pettersen
Ole A Andreassen
Gaute T Einevoll
Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue.
PLoS Computational Biology
author_facet Geir Halnes
Tuomo Mäki-Marttunen
Daniel Keller
Klas H Pettersen
Ole A Andreassen
Gaute T Einevoll
author_sort Geir Halnes
title Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue.
title_short Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue.
title_full Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue.
title_fullStr Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue.
title_full_unstemmed Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue.
title_sort effect of ionic diffusion on extracellular potentials in neural tissue.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2016-11-01
description Recorded potentials in the extracellular space (ECS) of the brain is a standard measure of population activity in neural tissue. Computational models that simulate the relationship between the ECS potential and its underlying neurophysiological processes are commonly used in the interpretation of such measurements. Standard methods, such as volume-conductor theory and current-source density theory, assume that diffusion has a negligible effect on the ECS potential, at least in the range of frequencies picked up by most recording systems. This assumption remains to be verified. We here present a hybrid simulation framework that accounts for diffusive effects on the ECS potential. The framework uses (1) the NEURON simulator to compute the activity and ionic output currents from multicompartmental neuron models, and (2) the electrodiffusive Kirchhoff-Nernst-Planck framework to simulate the resulting dynamics of the potential and ion concentrations in the ECS, accounting for the effect of electrical migration as well as diffusion. Using this framework, we explore the effect that ECS diffusion has on the electrical potential surrounding a small population of 10 pyramidal neurons. The neural model was tuned so that simulations over ∼100 seconds of biological time led to shifts in ECS concentrations by a few millimolars, similar to what has been seen in experiments. By comparing simulations where ECS diffusion was absent with simulations where ECS diffusion was included, we made the following key findings: (i) ECS diffusion shifted the local potential by up to ∼0.2 mV. (ii) The power spectral density (PSD) of the diffusion-evoked potential shifts followed a 1/f2 power law. (iii) Diffusion effects dominated the PSD of the ECS potential for frequencies up to several hertz. In scenarios with large, but physiologically realistic ECS concentration gradients, diffusion was thus found to affect the ECS potential well within the frequency range picked up in experimental recordings.
url http://europepmc.org/articles/PMC5098741?pdf=render
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