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A multi-scale computational model of the effects of TMS on motor cortex
The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS) activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different pyramidal cell types in motor cortex due to TMS....
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000Research
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5373428/ https://www.ncbi.nlm.nih.gov/pubmed/28408973 http://dx.doi.org/10.12688/f1000research.9277.3 |
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author | Seo, Hyeon Schaworonkow, Natalie Jun, Sung Chan Triesch, Jochen |
author_facet | Seo, Hyeon Schaworonkow, Natalie Jun, Sung Chan Triesch, Jochen |
author_sort | Seo, Hyeon |
collection | PubMed |
description | The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS) activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different pyramidal cell types in motor cortex due to TMS. Our model determines precise electric fields based on an individual head model derived from magnetic resonance imaging and calculates how these electric fields activate morphologically detailed models of different neuron types. We predict neural activation patterns for different coil orientations consistent with experimental findings. Beyond this, our model allows us to calculate activation thresholds for individual neurons and precise initiation sites of individual action potentials on the neurons’ complex morphologies. Specifically, our model predicts that cortical layer 3 pyramidal neurons are generally easier to stimulate than layer 5 pyramidal neurons, thereby explaining the lower stimulation thresholds observed for I-waves compared to D-waves. It also shows differences in the regions of activated cortical layer 5 and layer 3 pyramidal cells depending on coil orientation. Finally, it predicts that under standard stimulation conditions, action potentials are mostly generated at the axon initial segment of cortical pyramidal cells, with a much less important activation site being the part of a layer 5 pyramidal cell axon where it crosses the boundary between grey matter and white matter. In conclusion, our computational model offers a detailed account of the mechanisms through which TMS activates different cortical pyramidal cell types, paving the way for more targeted application of TMS based on individual brain morphology in clinical and basic research settings. |
format | Online Article Text |
id | pubmed-5373428 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | F1000Research |
record_format | MEDLINE/PubMed |
spelling | pubmed-53734282017-04-12 A multi-scale computational model of the effects of TMS on motor cortex Seo, Hyeon Schaworonkow, Natalie Jun, Sung Chan Triesch, Jochen F1000Res Research Article The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS) activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different pyramidal cell types in motor cortex due to TMS. Our model determines precise electric fields based on an individual head model derived from magnetic resonance imaging and calculates how these electric fields activate morphologically detailed models of different neuron types. We predict neural activation patterns for different coil orientations consistent with experimental findings. Beyond this, our model allows us to calculate activation thresholds for individual neurons and precise initiation sites of individual action potentials on the neurons’ complex morphologies. Specifically, our model predicts that cortical layer 3 pyramidal neurons are generally easier to stimulate than layer 5 pyramidal neurons, thereby explaining the lower stimulation thresholds observed for I-waves compared to D-waves. It also shows differences in the regions of activated cortical layer 5 and layer 3 pyramidal cells depending on coil orientation. Finally, it predicts that under standard stimulation conditions, action potentials are mostly generated at the axon initial segment of cortical pyramidal cells, with a much less important activation site being the part of a layer 5 pyramidal cell axon where it crosses the boundary between grey matter and white matter. In conclusion, our computational model offers a detailed account of the mechanisms through which TMS activates different cortical pyramidal cell types, paving the way for more targeted application of TMS based on individual brain morphology in clinical and basic research settings. F1000Research 2017-05-12 /pmc/articles/PMC5373428/ /pubmed/28408973 http://dx.doi.org/10.12688/f1000research.9277.3 Text en Copyright: © 2017 Seo H et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Seo, Hyeon Schaworonkow, Natalie Jun, Sung Chan Triesch, Jochen A multi-scale computational model of the effects of TMS on motor cortex |
title | A multi-scale computational model of the effects of TMS on motor cortex |
title_full | A multi-scale computational model of the effects of TMS on motor cortex |
title_fullStr | A multi-scale computational model of the effects of TMS on motor cortex |
title_full_unstemmed | A multi-scale computational model of the effects of TMS on motor cortex |
title_short | A multi-scale computational model of the effects of TMS on motor cortex |
title_sort | multi-scale computational model of the effects of tms on motor cortex |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5373428/ https://www.ncbi.nlm.nih.gov/pubmed/28408973 http://dx.doi.org/10.12688/f1000research.9277.3 |
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