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Effects of parcellation and threshold on brainconnectivity measures

It is shown that the statistical properties of connections between regions of the brain and their dependence on coarse-graining and thresholding in published data can be reproduced by a simple distance-based physical connectivity model. This allows studies with differing parcellation and thresholdin...

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Detalles Bibliográficos
Autores principales: Lacy, T. C., Robinson, P. A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7529295/
https://www.ncbi.nlm.nih.gov/pubmed/33002019
http://dx.doi.org/10.1371/journal.pone.0239717
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author Lacy, T. C.
Robinson, P. A.
author_facet Lacy, T. C.
Robinson, P. A.
author_sort Lacy, T. C.
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description It is shown that the statistical properties of connections between regions of the brain and their dependence on coarse-graining and thresholding in published data can be reproduced by a simple distance-based physical connectivity model. This allows studies with differing parcellation and thresholding to be interrelated objectively, and for the results of future studies on more finely grained or differently thresholded networks to be predicted. As examples of the implications, it is shown that the dependences of network measures on thresholding and parcellation imply that chosen brain regions can appear to form a small world network, even though the network at finer scales, or ultimately of individual neurons, may not be small world networks themselves.
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spelling pubmed-75292952020-10-08 Effects of parcellation and threshold on brainconnectivity measures Lacy, T. C. Robinson, P. A. PLoS One Research Article It is shown that the statistical properties of connections between regions of the brain and their dependence on coarse-graining and thresholding in published data can be reproduced by a simple distance-based physical connectivity model. This allows studies with differing parcellation and thresholding to be interrelated objectively, and for the results of future studies on more finely grained or differently thresholded networks to be predicted. As examples of the implications, it is shown that the dependences of network measures on thresholding and parcellation imply that chosen brain regions can appear to form a small world network, even though the network at finer scales, or ultimately of individual neurons, may not be small world networks themselves. Public Library of Science 2020-10-01 /pmc/articles/PMC7529295/ /pubmed/33002019 http://dx.doi.org/10.1371/journal.pone.0239717 Text en © 2020 Lacy, Robinson 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
Lacy, T. C.
Robinson, P. A.
Effects of parcellation and threshold on brainconnectivity measures
title Effects of parcellation and threshold on brainconnectivity measures
title_full Effects of parcellation and threshold on brainconnectivity measures
title_fullStr Effects of parcellation and threshold on brainconnectivity measures
title_full_unstemmed Effects of parcellation and threshold on brainconnectivity measures
title_short Effects of parcellation and threshold on brainconnectivity measures
title_sort effects of parcellation and threshold on brainconnectivity measures
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7529295/
https://www.ncbi.nlm.nih.gov/pubmed/33002019
http://dx.doi.org/10.1371/journal.pone.0239717
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