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Intrinsic Brain Network Abnormalities in Migraines without Aura Revealed in Resting-State fMRI
BACKGROUND: Previous studies have defined low-frequency, spatially consistent intrinsic connectivity networks (ICN) in resting functional magnetic resonance imaging (fMRI) data which reflect functional interactions among distinct brain areas. We sought to explore whether and how repeated migraine at...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3532057/ https://www.ncbi.nlm.nih.gov/pubmed/23285228 http://dx.doi.org/10.1371/journal.pone.0052927 |
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author | Xue, Ting Yuan, Kai Zhao, Ling Yu, Dahua Zhao, Limei Dong, Tao Cheng, Ping von Deneen, Karen M. Qin, Wei Tian, Jie |
author_facet | Xue, Ting Yuan, Kai Zhao, Ling Yu, Dahua Zhao, Limei Dong, Tao Cheng, Ping von Deneen, Karen M. Qin, Wei Tian, Jie |
author_sort | Xue, Ting |
collection | PubMed |
description | BACKGROUND: Previous studies have defined low-frequency, spatially consistent intrinsic connectivity networks (ICN) in resting functional magnetic resonance imaging (fMRI) data which reflect functional interactions among distinct brain areas. We sought to explore whether and how repeated migraine attacks influence intrinsic brain connectivity, as well as how activity in these networks correlates with clinical indicators of migraine. METHODS/PRINCIPAL FINDINGS: Resting-state fMRI data in twenty-three patients with migraines without aura (MwoA) and 23 age- and gender-matched healthy controls (HC) were analyzed using independent component analysis (ICA), in combination with a “dual-regression” technique to identify the group differences of three important pain-related networks [default mode network (DMN), bilateral central executive network (CEN), salience network (SN)] between the MwoA patients and HC. Compared with the HC, MwoA patients showed aberrant intrinsic connectivity within the bilateral CEN and SN, and greater connectivity between both the DMN and right CEN (rCEN) and the insula cortex - a critical region involving in pain processing. Furthermore, greater connectivity between both the DMN and rCEN and the insula correlated with duration of migraine. CONCLUSIONS: Our findings may provide new insights into the characterization of migraine as a condition affecting brain activity in intrinsic connectivity networks. Moreover, the abnormalities may be the consequence of a persistent central neural system dysfunction, reflecting cumulative brain insults due to frequent ongoing migraine attacks. |
format | Online Article Text |
id | pubmed-3532057 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-35320572013-01-02 Intrinsic Brain Network Abnormalities in Migraines without Aura Revealed in Resting-State fMRI Xue, Ting Yuan, Kai Zhao, Ling Yu, Dahua Zhao, Limei Dong, Tao Cheng, Ping von Deneen, Karen M. Qin, Wei Tian, Jie PLoS One Research Article BACKGROUND: Previous studies have defined low-frequency, spatially consistent intrinsic connectivity networks (ICN) in resting functional magnetic resonance imaging (fMRI) data which reflect functional interactions among distinct brain areas. We sought to explore whether and how repeated migraine attacks influence intrinsic brain connectivity, as well as how activity in these networks correlates with clinical indicators of migraine. METHODS/PRINCIPAL FINDINGS: Resting-state fMRI data in twenty-three patients with migraines without aura (MwoA) and 23 age- and gender-matched healthy controls (HC) were analyzed using independent component analysis (ICA), in combination with a “dual-regression” technique to identify the group differences of three important pain-related networks [default mode network (DMN), bilateral central executive network (CEN), salience network (SN)] between the MwoA patients and HC. Compared with the HC, MwoA patients showed aberrant intrinsic connectivity within the bilateral CEN and SN, and greater connectivity between both the DMN and right CEN (rCEN) and the insula cortex - a critical region involving in pain processing. Furthermore, greater connectivity between both the DMN and rCEN and the insula correlated with duration of migraine. CONCLUSIONS: Our findings may provide new insights into the characterization of migraine as a condition affecting brain activity in intrinsic connectivity networks. Moreover, the abnormalities may be the consequence of a persistent central neural system dysfunction, reflecting cumulative brain insults due to frequent ongoing migraine attacks. Public Library of Science 2012-12-28 /pmc/articles/PMC3532057/ /pubmed/23285228 http://dx.doi.org/10.1371/journal.pone.0052927 Text en © 2012 Xue 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Xue, Ting Yuan, Kai Zhao, Ling Yu, Dahua Zhao, Limei Dong, Tao Cheng, Ping von Deneen, Karen M. Qin, Wei Tian, Jie Intrinsic Brain Network Abnormalities in Migraines without Aura Revealed in Resting-State fMRI |
title | Intrinsic Brain Network Abnormalities in Migraines without Aura Revealed in Resting-State fMRI |
title_full | Intrinsic Brain Network Abnormalities in Migraines without Aura Revealed in Resting-State fMRI |
title_fullStr | Intrinsic Brain Network Abnormalities in Migraines without Aura Revealed in Resting-State fMRI |
title_full_unstemmed | Intrinsic Brain Network Abnormalities in Migraines without Aura Revealed in Resting-State fMRI |
title_short | Intrinsic Brain Network Abnormalities in Migraines without Aura Revealed in Resting-State fMRI |
title_sort | intrinsic brain network abnormalities in migraines without aura revealed in resting-state fmri |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3532057/ https://www.ncbi.nlm.nih.gov/pubmed/23285228 http://dx.doi.org/10.1371/journal.pone.0052927 |
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