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High-resolution directed human connectomes and the Consensus Connectome Dynamics

Here we show a method of directing the edges of the connectomes, prepared from HARDI datasets from the human brain. Before the present work, no high-definition directed braingraphs were published, because the tractography methods in use are not capable of assigning directions to the neural tracts di...

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Autores principales: Szalkai, Balázs, Kerepesi, Csaba, Varga, Bálint, Grolmusz, Vince
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467387/
https://www.ncbi.nlm.nih.gov/pubmed/30990832
http://dx.doi.org/10.1371/journal.pone.0215473
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author Szalkai, Balázs
Kerepesi, Csaba
Varga, Bálint
Grolmusz, Vince
author_facet Szalkai, Balázs
Kerepesi, Csaba
Varga, Bálint
Grolmusz, Vince
author_sort Szalkai, Balázs
collection PubMed
description Here we show a method of directing the edges of the connectomes, prepared from HARDI datasets from the human brain. Before the present work, no high-definition directed braingraphs were published, because the tractography methods in use are not capable of assigning directions to the neural tracts discovered. Previous work on the functional connectomes applied low-resolution functional MRI-detected statistical causality for the assignment of directions of connectomes of typically several dozens of vertices. Our method is based on the phenomenon of the “Consensus Connectome Dynamics”, described earlier by our research group. In this contribution, we apply the method to the 423 braingraphs, each with 1015 vertices, computed from the public release of the Human Connectome Project, and we also made the directed connectomes publicly available at the site http://braingraph.org. We also show the robustness of our edge directing method in four independently chosen connectome datasets: we have found that 86% of the edges, which were present in all four datasets, get the same directions in all datasets; therefore the direction method is robust. While our new edge-directing method still needs more empirical validation, we think that our present contribution opens up new possibilities in the analysis of the high-definition human connectome.
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spelling pubmed-64673872019-05-03 High-resolution directed human connectomes and the Consensus Connectome Dynamics Szalkai, Balázs Kerepesi, Csaba Varga, Bálint Grolmusz, Vince PLoS One Research Article Here we show a method of directing the edges of the connectomes, prepared from HARDI datasets from the human brain. Before the present work, no high-definition directed braingraphs were published, because the tractography methods in use are not capable of assigning directions to the neural tracts discovered. Previous work on the functional connectomes applied low-resolution functional MRI-detected statistical causality for the assignment of directions of connectomes of typically several dozens of vertices. Our method is based on the phenomenon of the “Consensus Connectome Dynamics”, described earlier by our research group. In this contribution, we apply the method to the 423 braingraphs, each with 1015 vertices, computed from the public release of the Human Connectome Project, and we also made the directed connectomes publicly available at the site http://braingraph.org. We also show the robustness of our edge directing method in four independently chosen connectome datasets: we have found that 86% of the edges, which were present in all four datasets, get the same directions in all datasets; therefore the direction method is robust. While our new edge-directing method still needs more empirical validation, we think that our present contribution opens up new possibilities in the analysis of the high-definition human connectome. Public Library of Science 2019-04-16 /pmc/articles/PMC6467387/ /pubmed/30990832 http://dx.doi.org/10.1371/journal.pone.0215473 Text en © 2019 Szalkai 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Szalkai, Balázs
Kerepesi, Csaba
Varga, Bálint
Grolmusz, Vince
High-resolution directed human connectomes and the Consensus Connectome Dynamics
title High-resolution directed human connectomes and the Consensus Connectome Dynamics
title_full High-resolution directed human connectomes and the Consensus Connectome Dynamics
title_fullStr High-resolution directed human connectomes and the Consensus Connectome Dynamics
title_full_unstemmed High-resolution directed human connectomes and the Consensus Connectome Dynamics
title_short High-resolution directed human connectomes and the Consensus Connectome Dynamics
title_sort high-resolution directed human connectomes and the consensus connectome dynamics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467387/
https://www.ncbi.nlm.nih.gov/pubmed/30990832
http://dx.doi.org/10.1371/journal.pone.0215473
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