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Spectral mapping of brain functional connectivity from diffusion imaging
Understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain is a central question in neuroscience. On the one hand, modern neuroimaging technologies, such as diffusion tensor imaging, can be used to construct structural graphs representing the ar...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5780460/ https://www.ncbi.nlm.nih.gov/pubmed/29362436 http://dx.doi.org/10.1038/s41598-017-18769-x |
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author | Becker, Cassiano O. Pequito, Sérgio Pappas, George J. Miller, Michael B. Grafton, Scott T. Bassett, Danielle S. Preciado, Victor M. |
author_facet | Becker, Cassiano O. Pequito, Sérgio Pappas, George J. Miller, Michael B. Grafton, Scott T. Bassett, Danielle S. Preciado, Victor M. |
author_sort | Becker, Cassiano O. |
collection | PubMed |
description | Understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain is a central question in neuroscience. On the one hand, modern neuroimaging technologies, such as diffusion tensor imaging, can be used to construct structural graphs representing the architecture of white matter streamlines linking cortical and subcortical structures. On the other hand, temporal patterns of neural activity can be used to construct functional graphs representing temporal correlations between brain regions. Although some studies provide evidence that whole-brain functional connectivity is shaped by the underlying anatomy, the observed relationship between function and structure is weak, and the rules by which anatomy constrains brain dynamics remain elusive. In this article, we introduce a methodology to map the functional connectivity of a subject at rest from his or her structural graph. Using our methodology, we are able to systematically account for the role of structural walks in the formation of functional correlations. Furthermore, in our empirical evaluations, we observe that the eigenmodes of the mapped functional connectivity are associated with activity patterns associated with different cognitive systems. |
format | Online Article Text |
id | pubmed-5780460 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57804602018-02-06 Spectral mapping of brain functional connectivity from diffusion imaging Becker, Cassiano O. Pequito, Sérgio Pappas, George J. Miller, Michael B. Grafton, Scott T. Bassett, Danielle S. Preciado, Victor M. Sci Rep Article Understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain is a central question in neuroscience. On the one hand, modern neuroimaging technologies, such as diffusion tensor imaging, can be used to construct structural graphs representing the architecture of white matter streamlines linking cortical and subcortical structures. On the other hand, temporal patterns of neural activity can be used to construct functional graphs representing temporal correlations between brain regions. Although some studies provide evidence that whole-brain functional connectivity is shaped by the underlying anatomy, the observed relationship between function and structure is weak, and the rules by which anatomy constrains brain dynamics remain elusive. In this article, we introduce a methodology to map the functional connectivity of a subject at rest from his or her structural graph. Using our methodology, we are able to systematically account for the role of structural walks in the formation of functional correlations. Furthermore, in our empirical evaluations, we observe that the eigenmodes of the mapped functional connectivity are associated with activity patterns associated with different cognitive systems. Nature Publishing Group UK 2018-01-23 /pmc/articles/PMC5780460/ /pubmed/29362436 http://dx.doi.org/10.1038/s41598-017-18769-x Text en © The Author(s) 2018 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/. |
spellingShingle | Article Becker, Cassiano O. Pequito, Sérgio Pappas, George J. Miller, Michael B. Grafton, Scott T. Bassett, Danielle S. Preciado, Victor M. Spectral mapping of brain functional connectivity from diffusion imaging |
title | Spectral mapping of brain functional connectivity from diffusion imaging |
title_full | Spectral mapping of brain functional connectivity from diffusion imaging |
title_fullStr | Spectral mapping of brain functional connectivity from diffusion imaging |
title_full_unstemmed | Spectral mapping of brain functional connectivity from diffusion imaging |
title_short | Spectral mapping of brain functional connectivity from diffusion imaging |
title_sort | spectral mapping of brain functional connectivity from diffusion imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5780460/ https://www.ncbi.nlm.nih.gov/pubmed/29362436 http://dx.doi.org/10.1038/s41598-017-18769-x |
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