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Functionnectome as a framework to analyse the contribution of brain circuits to fMRI
In recent years, the field of functional neuroimaging has moved away from a pure localisationist approach of isolated functional brain regions to a more integrated view of these regions within functional networks. However, the methods used to investigate functional networks rely on local signals in...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413369/ https://www.ncbi.nlm.nih.gov/pubmed/34475518 http://dx.doi.org/10.1038/s42003-021-02530-2 |
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author | Nozais, Victor Forkel, Stephanie J. Foulon, Chris Petit, Laurent Thiebaut de Schotten, Michel |
author_facet | Nozais, Victor Forkel, Stephanie J. Foulon, Chris Petit, Laurent Thiebaut de Schotten, Michel |
author_sort | Nozais, Victor |
collection | PubMed |
description | In recent years, the field of functional neuroimaging has moved away from a pure localisationist approach of isolated functional brain regions to a more integrated view of these regions within functional networks. However, the methods used to investigate functional networks rely on local signals in grey matter and are limited in identifying anatomical circuitries supporting the interaction between brain regions. Mapping the brain circuits mediating the functional signal between brain regions would propel our understanding of the brain’s functional signatures and dysfunctions. We developed a method to unravel the relationship between brain circuits and functions: The Functionnectome. The Functionnectome combines the functional signal from fMRI with white matter circuits’ anatomy to unlock and chart the first maps of functional white matter. To showcase this method’s versatility, we provide the first functional white matter maps revealing the joint contribution of connected areas to motor, working memory, and language functions. The Functionnectome comes with an open-source companion software and opens new avenues into studying functional networks by applying the method to already existing datasets and beyond task fMRI. |
format | Online Article Text |
id | pubmed-8413369 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-84133692021-09-22 Functionnectome as a framework to analyse the contribution of brain circuits to fMRI Nozais, Victor Forkel, Stephanie J. Foulon, Chris Petit, Laurent Thiebaut de Schotten, Michel Commun Biol Article In recent years, the field of functional neuroimaging has moved away from a pure localisationist approach of isolated functional brain regions to a more integrated view of these regions within functional networks. However, the methods used to investigate functional networks rely on local signals in grey matter and are limited in identifying anatomical circuitries supporting the interaction between brain regions. Mapping the brain circuits mediating the functional signal between brain regions would propel our understanding of the brain’s functional signatures and dysfunctions. We developed a method to unravel the relationship between brain circuits and functions: The Functionnectome. The Functionnectome combines the functional signal from fMRI with white matter circuits’ anatomy to unlock and chart the first maps of functional white matter. To showcase this method’s versatility, we provide the first functional white matter maps revealing the joint contribution of connected areas to motor, working memory, and language functions. The Functionnectome comes with an open-source companion software and opens new avenues into studying functional networks by applying the method to already existing datasets and beyond task fMRI. Nature Publishing Group UK 2021-09-02 /pmc/articles/PMC8413369/ /pubmed/34475518 http://dx.doi.org/10.1038/s42003-021-02530-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Nozais, Victor Forkel, Stephanie J. Foulon, Chris Petit, Laurent Thiebaut de Schotten, Michel Functionnectome as a framework to analyse the contribution of brain circuits to fMRI |
title | Functionnectome as a framework to analyse the contribution of brain circuits to fMRI |
title_full | Functionnectome as a framework to analyse the contribution of brain circuits to fMRI |
title_fullStr | Functionnectome as a framework to analyse the contribution of brain circuits to fMRI |
title_full_unstemmed | Functionnectome as a framework to analyse the contribution of brain circuits to fMRI |
title_short | Functionnectome as a framework to analyse the contribution of brain circuits to fMRI |
title_sort | functionnectome as a framework to analyse the contribution of brain circuits to fmri |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413369/ https://www.ncbi.nlm.nih.gov/pubmed/34475518 http://dx.doi.org/10.1038/s42003-021-02530-2 |
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