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Lifespan anxiety is reflected in human amygdala cortical connectivity

The amygdala plays a pivotal role in processing anxiety and connects to large‐scale brain networks. However, intrinsic functional connectivity (iFC) between amygdala and these networks has rarely been examined in relation to anxiety, especially across the lifespan. We employed resting‐state function...

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Autores principales: He, Ye, Xu, Ting, Zhang, Wei, Zuo, Xi‐Nian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5064618/
https://www.ncbi.nlm.nih.gov/pubmed/26859312
http://dx.doi.org/10.1002/hbm.23094
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author He, Ye
Xu, Ting
Zhang, Wei
Zuo, Xi‐Nian
author_facet He, Ye
Xu, Ting
Zhang, Wei
Zuo, Xi‐Nian
author_sort He, Ye
collection PubMed
description The amygdala plays a pivotal role in processing anxiety and connects to large‐scale brain networks. However, intrinsic functional connectivity (iFC) between amygdala and these networks has rarely been examined in relation to anxiety, especially across the lifespan. We employed resting‐state functional MRI data from 280 healthy adults (18–83.5 yrs) to elucidate the relationship between anxiety and amygdala iFC with common cortical networks including the visual network, somatomotor network, dorsal attention network, ventral attention network, limbic network, frontoparietal network, and default network. Global and network‐specific iFC were separately computed as mean iFC of amygdala with the entire cerebral cortex and each cortical network. We detected negative correlation between global positive amygdala iFC and trait anxiety. Network‐specific associations between amygdala iFC and anxiety were also detectable. Specifically, the higher iFC strength between the left amygdala and the limbic network predicted lower state anxiety. For the trait anxiety, left amygdala anxiety–connectivity correlation was observed in both somatomotor and dorsal attention networks, whereas the right amygdala anxiety–connectivity correlation was primarily distributed in the frontoparietal and ventral attention networks. Ventral attention network exhibited significant anxiety–gender interactions on its iFC with amygdala. Together with findings from additional vertex‐wise analysis, these data clearly indicated that both low‐level sensory networks and high‐level associative networks could contribute to detectable predictions of anxiety behaviors by their iFC profiles with the amygdala. This set of systems neuroscience findings could lead to novel functional network models on neural correlates of human anxiety and provide targets for novel treatment strategies on anxiety disorders. Hum Brain Mapp 37:1178–1193, 2016. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
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spelling pubmed-50646182016-10-19 Lifespan anxiety is reflected in human amygdala cortical connectivity He, Ye Xu, Ting Zhang, Wei Zuo, Xi‐Nian Hum Brain Mapp Research Articles The amygdala plays a pivotal role in processing anxiety and connects to large‐scale brain networks. However, intrinsic functional connectivity (iFC) between amygdala and these networks has rarely been examined in relation to anxiety, especially across the lifespan. We employed resting‐state functional MRI data from 280 healthy adults (18–83.5 yrs) to elucidate the relationship between anxiety and amygdala iFC with common cortical networks including the visual network, somatomotor network, dorsal attention network, ventral attention network, limbic network, frontoparietal network, and default network. Global and network‐specific iFC were separately computed as mean iFC of amygdala with the entire cerebral cortex and each cortical network. We detected negative correlation between global positive amygdala iFC and trait anxiety. Network‐specific associations between amygdala iFC and anxiety were also detectable. Specifically, the higher iFC strength between the left amygdala and the limbic network predicted lower state anxiety. For the trait anxiety, left amygdala anxiety–connectivity correlation was observed in both somatomotor and dorsal attention networks, whereas the right amygdala anxiety–connectivity correlation was primarily distributed in the frontoparietal and ventral attention networks. Ventral attention network exhibited significant anxiety–gender interactions on its iFC with amygdala. Together with findings from additional vertex‐wise analysis, these data clearly indicated that both low‐level sensory networks and high‐level associative networks could contribute to detectable predictions of anxiety behaviors by their iFC profiles with the amygdala. This set of systems neuroscience findings could lead to novel functional network models on neural correlates of human anxiety and provide targets for novel treatment strategies on anxiety disorders. Hum Brain Mapp 37:1178–1193, 2016. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. John Wiley and Sons Inc. 2015-12-21 /pmc/articles/PMC5064618/ /pubmed/26859312 http://dx.doi.org/10.1002/hbm.23094 Text en © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Articles
He, Ye
Xu, Ting
Zhang, Wei
Zuo, Xi‐Nian
Lifespan anxiety is reflected in human amygdala cortical connectivity
title Lifespan anxiety is reflected in human amygdala cortical connectivity
title_full Lifespan anxiety is reflected in human amygdala cortical connectivity
title_fullStr Lifespan anxiety is reflected in human amygdala cortical connectivity
title_full_unstemmed Lifespan anxiety is reflected in human amygdala cortical connectivity
title_short Lifespan anxiety is reflected in human amygdala cortical connectivity
title_sort lifespan anxiety is reflected in human amygdala cortical connectivity
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5064618/
https://www.ncbi.nlm.nih.gov/pubmed/26859312
http://dx.doi.org/10.1002/hbm.23094
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