Robust dynamic community detection with applications to human brain functional networks

Understanding how brain networks evolve in time remains a challenge, with the potential for significant impact to human health and disease. Here, the authors introduce a new methodology to track dynamic functional networks that is robust to edge noise, and yields well-defined spatiotemporal communit...

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Autores principales:	L.-E. Martinet, M. A. Kramer, W. Viles, L. N. Perkins, E. Spencer, C. J. Chu, S. S. Cash, E. D. Kolaczyk
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/8f7cd92cb2444562a9abbe7affa09f59
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spelling	oai:doaj.org-article:8f7cd92cb2444562a9abbe7affa09f592021-12-02T17:51:04ZRobust dynamic community detection with applications to human brain functional networks10.1038/s41467-020-16285-72041-1723https://doaj.org/article/8f7cd92cb2444562a9abbe7affa09f592020-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-16285-7https://doaj.org/toc/2041-1723Understanding how brain networks evolve in time remains a challenge, with the potential for significant impact to human health and disease. Here, the authors introduce a new methodology to track dynamic functional networks that is robust to edge noise, and yields well-defined spatiotemporal communities that span forward and backwards in time.L.-E. MartinetM. A. KramerW. VilesL. N. PerkinsE. SpencerC. J. ChuS. S. CashE. D. KolaczykNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-13 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q L.-E. Martinet M. A. Kramer W. Viles L. N. Perkins E. Spencer C. J. Chu S. S. Cash E. D. Kolaczyk Robust dynamic community detection with applications to human brain functional networks
description	Understanding how brain networks evolve in time remains a challenge, with the potential for significant impact to human health and disease. Here, the authors introduce a new methodology to track dynamic functional networks that is robust to edge noise, and yields well-defined spatiotemporal communities that span forward and backwards in time.
format	article
author	L.-E. Martinet M. A. Kramer W. Viles L. N. Perkins E. Spencer C. J. Chu S. S. Cash E. D. Kolaczyk
author_facet	L.-E. Martinet M. A. Kramer W. Viles L. N. Perkins E. Spencer C. J. Chu S. S. Cash E. D. Kolaczyk
author_sort	L.-E. Martinet
title	Robust dynamic community detection with applications to human brain functional networks
title_short	Robust dynamic community detection with applications to human brain functional networks
title_full	Robust dynamic community detection with applications to human brain functional networks
title_fullStr	Robust dynamic community detection with applications to human brain functional networks
title_full_unstemmed	Robust dynamic community detection with applications to human brain functional networks
title_sort	robust dynamic community detection with applications to human brain functional networks
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/8f7cd92cb2444562a9abbe7affa09f59
work_keys_str_mv	AT lemartinet robustdynamiccommunitydetectionwithapplicationstohumanbrainfunctionalnetworks AT makramer robustdynamiccommunitydetectionwithapplicationstohumanbrainfunctionalnetworks AT wviles robustdynamiccommunitydetectionwithapplicationstohumanbrainfunctionalnetworks AT lnperkins robustdynamiccommunitydetectionwithapplicationstohumanbrainfunctionalnetworks AT espencer robustdynamiccommunitydetectionwithapplicationstohumanbrainfunctionalnetworks AT cjchu robustdynamiccommunitydetectionwithapplicationstohumanbrainfunctionalnetworks AT sscash robustdynamiccommunitydetectionwithapplicationstohumanbrainfunctionalnetworks AT edkolaczyk robustdynamiccommunitydetectionwithapplicationstohumanbrainfunctionalnetworks
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Robust dynamic community detection with applications to human brain functional networks

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