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Within brain area tractography suggests local modularity using high resolution connectomics
Previous structural brain connectivity studies have mainly focussed on the macroscopic scale of around 1,000 or fewer brain areas (network nodes). However, it has recently been demonstrated that high resolution structural connectomes of around 50,000 nodes can be generated reproducibly. In this stud...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5213837/ https://www.ncbi.nlm.nih.gov/pubmed/28054634 http://dx.doi.org/10.1038/srep39859 |
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author | Taylor, Peter N. Wang, Yujiang Kaiser, Marcus |
author_facet | Taylor, Peter N. Wang, Yujiang Kaiser, Marcus |
author_sort | Taylor, Peter N. |
collection | PubMed |
description | Previous structural brain connectivity studies have mainly focussed on the macroscopic scale of around 1,000 or fewer brain areas (network nodes). However, it has recently been demonstrated that high resolution structural connectomes of around 50,000 nodes can be generated reproducibly. In this study, we infer high resolution brain connectivity matrices using diffusion imaging data from the Human Connectome Project. With such high resolution we are able to analyse networks within brain areas in a single subject. We show that the global network has a scale invariant topological organisation, which means there is a hierarchical organisation of the modular architecture. Specifically, modules within brain areas are spatially localised. We find that long range connections terminate between specific modules, whilst short range connections via highly curved association fibers terminate within modules. We suggest that spatial locations of white matter modules overlap with cytoarchitecturally distinct grey matter areas and may serve as the structural basis for function specialisation within brain areas. Future studies might elucidate how brain diseases change this modular architecture within brain areas. |
format | Online Article Text |
id | pubmed-5213837 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-52138372017-01-09 Within brain area tractography suggests local modularity using high resolution connectomics Taylor, Peter N. Wang, Yujiang Kaiser, Marcus Sci Rep Article Previous structural brain connectivity studies have mainly focussed on the macroscopic scale of around 1,000 or fewer brain areas (network nodes). However, it has recently been demonstrated that high resolution structural connectomes of around 50,000 nodes can be generated reproducibly. In this study, we infer high resolution brain connectivity matrices using diffusion imaging data from the Human Connectome Project. With such high resolution we are able to analyse networks within brain areas in a single subject. We show that the global network has a scale invariant topological organisation, which means there is a hierarchical organisation of the modular architecture. Specifically, modules within brain areas are spatially localised. We find that long range connections terminate between specific modules, whilst short range connections via highly curved association fibers terminate within modules. We suggest that spatial locations of white matter modules overlap with cytoarchitecturally distinct grey matter areas and may serve as the structural basis for function specialisation within brain areas. Future studies might elucidate how brain diseases change this modular architecture within brain areas. Nature Publishing Group 2017-01-05 /pmc/articles/PMC5213837/ /pubmed/28054634 http://dx.doi.org/10.1038/srep39859 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Taylor, Peter N. Wang, Yujiang Kaiser, Marcus Within brain area tractography suggests local modularity using high resolution connectomics |
title | Within brain area tractography suggests local modularity using high resolution connectomics |
title_full | Within brain area tractography suggests local modularity using high resolution connectomics |
title_fullStr | Within brain area tractography suggests local modularity using high resolution connectomics |
title_full_unstemmed | Within brain area tractography suggests local modularity using high resolution connectomics |
title_short | Within brain area tractography suggests local modularity using high resolution connectomics |
title_sort | within brain area tractography suggests local modularity using high resolution connectomics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5213837/ https://www.ncbi.nlm.nih.gov/pubmed/28054634 http://dx.doi.org/10.1038/srep39859 |
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