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  Action potential propagation and synchronisation in myelinated axons

Schmidt, H., & Knösche, T. R. (2019). Action potential propagation and synchronisation in myelinated axons. PLoS Computational Biology, 15(10): e1007004. doi:10.1371/journal.pcbi.1007004.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0004-CF4E-D Version Permalink: http://hdl.handle.net/21.11116/0000-0005-18ED-6
Genre: Journal Article

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 Creators:
Schmidt, Helmut1, Author              
Knösche, Thomas R.1, Author              
Affiliations:
1Methods and Development Unit - MEG and Cortical Networks, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205650              

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 Abstract: With the advent of advanced MRI techniques it has become possible to study axonal white matter non-invasively and in great detail. Measuring the various parameters of the long-range connections of the brain opens up the possibility to build and refine detailed models of large-scale neuronal activity. One particular challenge is to find a mathematical description of action potential propagation that is sufficiently simple, yet still biologically plausible to model signal transmission across entire axonal fibre bundles. We develop a mathematical framework in which we replace the Hodgkin-Huxley dynamics by a spike-diffuse-spike model with passive sub-threshold dynamics and explicit, threshold-activated ion channel currents. This allows us to study in detail the influence of the various model parameters on the action potential velocity and on the entrainment of action potentials between ephaptically coupled fibres without having to recur to numerical simulations. Specifically, we recover known results regarding the influence of axon diameter, node of Ranvier length and internode length on the velocity of action potentials. Additionally, we find that the velocity depends more strongly on the thickness of the myelin sheath than was suggested by previous theoretical studies. We further explain the slowing down and synchronisation of action potentials in ephaptically coupled fibres by their dynamic interaction. In summary, this study presents a solution to incorporate detailed axonal parameters into a whole-brain modelling framework.

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Language(s): eng - English
 Dates: 2019-04-012019-09-272019-10-17
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1007004
PMID: 31622338
Other: Epub ahead of print
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Project name : Computational Connectomics / SPP 2041
Grant ID : 588/7-1
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Funding organization : German Research Foundation (DFG)

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Title: PLoS Computational Biology
Source Genre: Journal
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Pages: - Volume / Issue: 15 (10) Sequence Number: e1007004 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1