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Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity

The brain is organized into large scale spatial networks that can be detected during periods of rest using fMRI. The brain is also a dynamic organ with activity that changes over time. We developed a method and investigated properties where the connections as a function of time are derived and quant...

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Detalles Bibliográficos
Autores principales: Thompson, William Hedley, Fransson, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5171789/
https://www.ncbi.nlm.nih.gov/pubmed/27991540
http://dx.doi.org/10.1038/srep39156
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author Thompson, William Hedley
Fransson, Peter
author_facet Thompson, William Hedley
Fransson, Peter
author_sort Thompson, William Hedley
collection PubMed
description The brain is organized into large scale spatial networks that can be detected during periods of rest using fMRI. The brain is also a dynamic organ with activity that changes over time. We developed a method and investigated properties where the connections as a function of time are derived and quantified. The point based method (PBM) presented here derives covariance matrices after clustering individual time points based upon their global spatial pattern. This method achieved increased temporal sensitivity, together with temporal network theory, allowed us to study functional integration between resting-state networks. Our results show that functional integrations between two resting-state networks predominately occurs in bursts of activity. This is followed by varying intermittent periods of less connectivity. The described point-based method of dynamic resting-state functional connectivity allows for a detailed and expanded view on the temporal dynamics of resting-state connectivity that provides novel insights into how neuronal information processing is integrated in the human brain at the level of large-scale networks.
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spelling pubmed-51717892016-12-28 Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity Thompson, William Hedley Fransson, Peter Sci Rep Article The brain is organized into large scale spatial networks that can be detected during periods of rest using fMRI. The brain is also a dynamic organ with activity that changes over time. We developed a method and investigated properties where the connections as a function of time are derived and quantified. The point based method (PBM) presented here derives covariance matrices after clustering individual time points based upon their global spatial pattern. This method achieved increased temporal sensitivity, together with temporal network theory, allowed us to study functional integration between resting-state networks. Our results show that functional integrations between two resting-state networks predominately occurs in bursts of activity. This is followed by varying intermittent periods of less connectivity. The described point-based method of dynamic resting-state functional connectivity allows for a detailed and expanded view on the temporal dynamics of resting-state connectivity that provides novel insights into how neuronal information processing is integrated in the human brain at the level of large-scale networks. Nature Publishing Group 2016-12-19 /pmc/articles/PMC5171789/ /pubmed/27991540 http://dx.doi.org/10.1038/srep39156 Text en Copyright © 2016, 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
Thompson, William Hedley
Fransson, Peter
Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity
title Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity
title_full Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity
title_fullStr Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity
title_full_unstemmed Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity
title_short Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity
title_sort bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5171789/
https://www.ncbi.nlm.nih.gov/pubmed/27991540
http://dx.doi.org/10.1038/srep39156
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