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Dissecting whole-brain conduction delays through MRI microstructural measures

Network models based on structural connectivity have been increasingly used as the blueprint for large-scale simulations of the human brain. As the nodes of this network are distributed through the cortex and interconnected by white matter pathways with different characteristics, modeling the associ...

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Autores principales: Mancini, Matteo, Tian, Qiyuan, Fan, Qiuyun, Cercignani, Mara, Huang, Susie Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8448685/
https://www.ncbi.nlm.nih.gov/pubmed/34390416
http://dx.doi.org/10.1007/s00429-021-02358-w
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author Mancini, Matteo
Tian, Qiyuan
Fan, Qiuyun
Cercignani, Mara
Huang, Susie Y.
author_facet Mancini, Matteo
Tian, Qiyuan
Fan, Qiuyun
Cercignani, Mara
Huang, Susie Y.
author_sort Mancini, Matteo
collection PubMed
description Network models based on structural connectivity have been increasingly used as the blueprint for large-scale simulations of the human brain. As the nodes of this network are distributed through the cortex and interconnected by white matter pathways with different characteristics, modeling the associated conduction delays becomes important. The goal of this study is to estimate and characterize these delays directly from the brain structure. To achieve this, we leveraged microstructural measures from a combination of advanced magnetic resonance imaging acquisitions and computed the main determinants of conduction velocity, namely axonal diameter and myelin content. Using the model proposed by Rushton, we used these measures to calculate the conduction velocity and estimated the associated delays using tractography. We observed that both the axonal diameter and conduction velocity distributions presented a rather constant trend across different connection lengths, with resulting delays that scale linearly with the connection length. Relying on insights from graph theory and Kuramoto simulations, our results support the approximation of constant conduction velocity but also show path- and region-specific differences. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00429-021-02358-w.
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spelling pubmed-84486852021-10-01 Dissecting whole-brain conduction delays through MRI microstructural measures Mancini, Matteo Tian, Qiyuan Fan, Qiuyun Cercignani, Mara Huang, Susie Y. Brain Struct Funct Original Article Network models based on structural connectivity have been increasingly used as the blueprint for large-scale simulations of the human brain. As the nodes of this network are distributed through the cortex and interconnected by white matter pathways with different characteristics, modeling the associated conduction delays becomes important. The goal of this study is to estimate and characterize these delays directly from the brain structure. To achieve this, we leveraged microstructural measures from a combination of advanced magnetic resonance imaging acquisitions and computed the main determinants of conduction velocity, namely axonal diameter and myelin content. Using the model proposed by Rushton, we used these measures to calculate the conduction velocity and estimated the associated delays using tractography. We observed that both the axonal diameter and conduction velocity distributions presented a rather constant trend across different connection lengths, with resulting delays that scale linearly with the connection length. Relying on insights from graph theory and Kuramoto simulations, our results support the approximation of constant conduction velocity but also show path- and region-specific differences. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00429-021-02358-w. Springer Berlin Heidelberg 2021-08-14 2021 /pmc/articles/PMC8448685/ /pubmed/34390416 http://dx.doi.org/10.1007/s00429-021-02358-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Mancini, Matteo
Tian, Qiyuan
Fan, Qiuyun
Cercignani, Mara
Huang, Susie Y.
Dissecting whole-brain conduction delays through MRI microstructural measures
title Dissecting whole-brain conduction delays through MRI microstructural measures
title_full Dissecting whole-brain conduction delays through MRI microstructural measures
title_fullStr Dissecting whole-brain conduction delays through MRI microstructural measures
title_full_unstemmed Dissecting whole-brain conduction delays through MRI microstructural measures
title_short Dissecting whole-brain conduction delays through MRI microstructural measures
title_sort dissecting whole-brain conduction delays through mri microstructural measures
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8448685/
https://www.ncbi.nlm.nih.gov/pubmed/34390416
http://dx.doi.org/10.1007/s00429-021-02358-w
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