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Mapping Human Whole-Brain Structural Networks with Diffusion MRI
Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and in...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1895920/ https://www.ncbi.nlm.nih.gov/pubmed/17611629 http://dx.doi.org/10.1371/journal.pone.0000597 |
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author | Hagmann, Patric Kurant, Maciej Gigandet, Xavier Thiran, Patrick Wedeen, Van J. Meuli, Reto Thiran, Jean-Philippe |
author_facet | Hagmann, Patric Kurant, Maciej Gigandet, Xavier Thiran, Patrick Wedeen, Van J. Meuli, Reto Thiran, Jean-Philippe |
author_sort | Hagmann, Patric |
collection | PubMed |
description | Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world. |
format | Text |
id | pubmed-1895920 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-18959202007-07-04 Mapping Human Whole-Brain Structural Networks with Diffusion MRI Hagmann, Patric Kurant, Maciej Gigandet, Xavier Thiran, Patrick Wedeen, Van J. Meuli, Reto Thiran, Jean-Philippe PLoS One Research Article Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world. Public Library of Science 2007-07-04 /pmc/articles/PMC1895920/ /pubmed/17611629 http://dx.doi.org/10.1371/journal.pone.0000597 Text en Hagmann et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Hagmann, Patric Kurant, Maciej Gigandet, Xavier Thiran, Patrick Wedeen, Van J. Meuli, Reto Thiran, Jean-Philippe Mapping Human Whole-Brain Structural Networks with Diffusion MRI |
title | Mapping Human Whole-Brain Structural Networks with Diffusion MRI |
title_full | Mapping Human Whole-Brain Structural Networks with Diffusion MRI |
title_fullStr | Mapping Human Whole-Brain Structural Networks with Diffusion MRI |
title_full_unstemmed | Mapping Human Whole-Brain Structural Networks with Diffusion MRI |
title_short | Mapping Human Whole-Brain Structural Networks with Diffusion MRI |
title_sort | mapping human whole-brain structural networks with diffusion mri |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1895920/ https://www.ncbi.nlm.nih.gov/pubmed/17611629 http://dx.doi.org/10.1371/journal.pone.0000597 |
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