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Dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle

Sex steroid hormones have been shown to alter regional brain activity, but the extent to which they modulate connectivity within and between large-scale functional brain networks over time has yet to be characterized. Here, we applied dynamic community detection techniques to data from a highly samp...

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Autores principales: Mueller, Joshua M., Pritschet, Laura, Santander, Tyler, Taylor, Caitlin M., Grafton, Scott T., Jacobs, Emily Goard, Carlson, Jean M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MIT Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935041/
https://www.ncbi.nlm.nih.gov/pubmed/33688609
http://dx.doi.org/10.1162/netn_a_00169
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author Mueller, Joshua M.
Pritschet, Laura
Santander, Tyler
Taylor, Caitlin M.
Grafton, Scott T.
Jacobs, Emily Goard
Carlson, Jean M.
author_facet Mueller, Joshua M.
Pritschet, Laura
Santander, Tyler
Taylor, Caitlin M.
Grafton, Scott T.
Jacobs, Emily Goard
Carlson, Jean M.
author_sort Mueller, Joshua M.
collection PubMed
description Sex steroid hormones have been shown to alter regional brain activity, but the extent to which they modulate connectivity within and between large-scale functional brain networks over time has yet to be characterized. Here, we applied dynamic community detection techniques to data from a highly sampled female with 30 consecutive days of brain imaging and venipuncture measurements to characterize changes in resting-state community structure across the menstrual cycle. Four stable functional communities were identified, consisting of nodes from visual, default mode, frontal control, and somatomotor networks. Limbic, subcortical, and attention networks exhibited higher than expected levels of nodal flexibility, a hallmark of between-network integration and transient functional reorganization. The most striking reorganization occurred in a default mode subnetwork localized to regions of the prefrontal cortex, coincident with peaks in serum levels of estradiol, luteinizing hormone, and follicle stimulating hormone. Nodes from these regions exhibited strong intranetwork increases in functional connectivity, leading to a split in the stable default mode core community and the transient formation of a new functional community. Probing the spatiotemporal basis of human brain–hormone interactions with dynamic community detection suggests that hormonal changes during the menstrual cycle result in temporary, localized patterns of brain network reorganization.
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spelling pubmed-79350412021-03-08 Dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle Mueller, Joshua M. Pritschet, Laura Santander, Tyler Taylor, Caitlin M. Grafton, Scott T. Jacobs, Emily Goard Carlson, Jean M. Netw Neurosci Research Article Sex steroid hormones have been shown to alter regional brain activity, but the extent to which they modulate connectivity within and between large-scale functional brain networks over time has yet to be characterized. Here, we applied dynamic community detection techniques to data from a highly sampled female with 30 consecutive days of brain imaging and venipuncture measurements to characterize changes in resting-state community structure across the menstrual cycle. Four stable functional communities were identified, consisting of nodes from visual, default mode, frontal control, and somatomotor networks. Limbic, subcortical, and attention networks exhibited higher than expected levels of nodal flexibility, a hallmark of between-network integration and transient functional reorganization. The most striking reorganization occurred in a default mode subnetwork localized to regions of the prefrontal cortex, coincident with peaks in serum levels of estradiol, luteinizing hormone, and follicle stimulating hormone. Nodes from these regions exhibited strong intranetwork increases in functional connectivity, leading to a split in the stable default mode core community and the transient formation of a new functional community. Probing the spatiotemporal basis of human brain–hormone interactions with dynamic community detection suggests that hormonal changes during the menstrual cycle result in temporary, localized patterns of brain network reorganization. MIT Press 2021-02-01 /pmc/articles/PMC7935041/ /pubmed/33688609 http://dx.doi.org/10.1162/netn_a_00169 Text en © 2020 Massachusetts Institute of Technology This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode.
spellingShingle Research Article
Mueller, Joshua M.
Pritschet, Laura
Santander, Tyler
Taylor, Caitlin M.
Grafton, Scott T.
Jacobs, Emily Goard
Carlson, Jean M.
Dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle
title Dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle
title_full Dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle
title_fullStr Dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle
title_full_unstemmed Dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle
title_short Dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle
title_sort dynamic community detection reveals transient reorganization of functional brain networks across a female menstrual cycle
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935041/
https://www.ncbi.nlm.nih.gov/pubmed/33688609
http://dx.doi.org/10.1162/netn_a_00169
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