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Age-Associated Differences of Modules and Hubs in Brain Functional Networks

Healthy aging is usually accompanied by changes in the functional modular organization of the human brain, which may result in the decline of cognition and underlying brain dysfunction. However, the relationship between age-related brain functional modular structure differences and cognition remain...

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Autores principales: Zhang, Yinghui, Wang, Yin, Chen, Nan, Guo, Man, Wang, Xiuzhen, Chen, Guangcai, Li, Yongchao, Yang, Lin, Li, Shan, Yao, Zhijun, Hu, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7848126/
https://www.ncbi.nlm.nih.gov/pubmed/33536893
http://dx.doi.org/10.3389/fnagi.2020.607445
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author Zhang, Yinghui
Wang, Yin
Chen, Nan
Guo, Man
Wang, Xiuzhen
Chen, Guangcai
Li, Yongchao
Yang, Lin
Li, Shan
Yao, Zhijun
Hu, Bin
author_facet Zhang, Yinghui
Wang, Yin
Chen, Nan
Guo, Man
Wang, Xiuzhen
Chen, Guangcai
Li, Yongchao
Yang, Lin
Li, Shan
Yao, Zhijun
Hu, Bin
author_sort Zhang, Yinghui
collection PubMed
description Healthy aging is usually accompanied by changes in the functional modular organization of the human brain, which may result in the decline of cognition and underlying brain dysfunction. However, the relationship between age-related brain functional modular structure differences and cognition remain debatable. In this study, we investigated the age-associated differences of modules and hubs from young, middle and old age groups, using resting-state fMRI data from a large cross-sectional adulthood sample. We first divided the subjects into three age groups and constructed an individual-level network for each subject. Subsequently, a module-guided group-level network construction method was applied to form a weighted network for each group from which functional modules were detected. The intra- and inter-modular connectivities were observed negatively correlated with age. According to the detected modules, we found the number of connector hubs in the young group was more than middle-age and old group, while the quantity of provincial hubs in middle-age group was discovered more than other two groups. Further ROI-wise analysis shows that different hubs have distinct age-associated trajectories of intra- and inter-modular connections, which suggests the different types of topological role transitions in functional networks across age groups. Our results indicated an inverse association between functional segregation/integration with age, which demonstrated age-associated differences in communication effeciency. This study provides a new perspective and useful information to better understand the normal aging of brain networks.
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spelling pubmed-78481262021-02-02 Age-Associated Differences of Modules and Hubs in Brain Functional Networks Zhang, Yinghui Wang, Yin Chen, Nan Guo, Man Wang, Xiuzhen Chen, Guangcai Li, Yongchao Yang, Lin Li, Shan Yao, Zhijun Hu, Bin Front Aging Neurosci Neuroscience Healthy aging is usually accompanied by changes in the functional modular organization of the human brain, which may result in the decline of cognition and underlying brain dysfunction. However, the relationship between age-related brain functional modular structure differences and cognition remain debatable. In this study, we investigated the age-associated differences of modules and hubs from young, middle and old age groups, using resting-state fMRI data from a large cross-sectional adulthood sample. We first divided the subjects into three age groups and constructed an individual-level network for each subject. Subsequently, a module-guided group-level network construction method was applied to form a weighted network for each group from which functional modules were detected. The intra- and inter-modular connectivities were observed negatively correlated with age. According to the detected modules, we found the number of connector hubs in the young group was more than middle-age and old group, while the quantity of provincial hubs in middle-age group was discovered more than other two groups. Further ROI-wise analysis shows that different hubs have distinct age-associated trajectories of intra- and inter-modular connections, which suggests the different types of topological role transitions in functional networks across age groups. Our results indicated an inverse association between functional segregation/integration with age, which demonstrated age-associated differences in communication effeciency. This study provides a new perspective and useful information to better understand the normal aging of brain networks. Frontiers Media S.A. 2021-01-18 /pmc/articles/PMC7848126/ /pubmed/33536893 http://dx.doi.org/10.3389/fnagi.2020.607445 Text en Copyright © 2021 Zhang, Wang, Chen, Guo, Wang, Chen, Li, Yang, Li, Yao and Hu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Zhang, Yinghui
Wang, Yin
Chen, Nan
Guo, Man
Wang, Xiuzhen
Chen, Guangcai
Li, Yongchao
Yang, Lin
Li, Shan
Yao, Zhijun
Hu, Bin
Age-Associated Differences of Modules and Hubs in Brain Functional Networks
title Age-Associated Differences of Modules and Hubs in Brain Functional Networks
title_full Age-Associated Differences of Modules and Hubs in Brain Functional Networks
title_fullStr Age-Associated Differences of Modules and Hubs in Brain Functional Networks
title_full_unstemmed Age-Associated Differences of Modules and Hubs in Brain Functional Networks
title_short Age-Associated Differences of Modules and Hubs in Brain Functional Networks
title_sort age-associated differences of modules and hubs in brain functional networks
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7848126/
https://www.ncbi.nlm.nih.gov/pubmed/33536893
http://dx.doi.org/10.3389/fnagi.2020.607445
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