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Structural Brain Network Changes across the Adult Lifespan
A number of magnetic resonance imaging (MRI) studies have shown age-related alterations in brain structural networks in different age groups. However, the specific age-associated changes in brain structural networks across the adult lifespan is underexplored. In the current study, we performed a mul...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5562685/ https://www.ncbi.nlm.nih.gov/pubmed/28860988 http://dx.doi.org/10.3389/fnagi.2017.00275 |
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author | Liu, Ke Yao, Shixiu Chen, Kewei Zhang, Jiacai Yao, Li Li, Ke Jin, Zhen Guo, Xiaojuan |
author_facet | Liu, Ke Yao, Shixiu Chen, Kewei Zhang, Jiacai Yao, Li Li, Ke Jin, Zhen Guo, Xiaojuan |
author_sort | Liu, Ke |
collection | PubMed |
description | A number of magnetic resonance imaging (MRI) studies have shown age-related alterations in brain structural networks in different age groups. However, the specific age-associated changes in brain structural networks across the adult lifespan is underexplored. In the current study, we performed a multivariate independent component analysis (ICA) to identify structural brain networks based on covariant gray matter volume and then investigated the age-related trajectories of structural networks over the adult lifespan in 536 healthy subjects aged 20–86 years. Twenty independent components (ICs) were extracted in the ICA, and statistical analyses between age and ICA weights revealed 16 age-related ICs across the adult lifespan. Most of the trajectories of ICA weights demonstrated significant linear decline tendencies, and the corresponding structural networks primarily included the anterior and posterior dorsal attention networks, the ventral and posterior default mode networks, the auditory network, five cerebellum networks and the hippocampus-related network with the most significant decreased tendency among all ICs (p of age = 1.11E-77). Only the temporal lobe-related network showed a significant quadratic tendency with age (p of age(2) = 5.66E-06). Our findings not only provide insight into the patterns of the age-related changes of structural networks but also provide a foundation for understanding abnormal aging. |
format | Online Article Text |
id | pubmed-5562685 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-55626852017-08-31 Structural Brain Network Changes across the Adult Lifespan Liu, Ke Yao, Shixiu Chen, Kewei Zhang, Jiacai Yao, Li Li, Ke Jin, Zhen Guo, Xiaojuan Front Aging Neurosci Neuroscience A number of magnetic resonance imaging (MRI) studies have shown age-related alterations in brain structural networks in different age groups. However, the specific age-associated changes in brain structural networks across the adult lifespan is underexplored. In the current study, we performed a multivariate independent component analysis (ICA) to identify structural brain networks based on covariant gray matter volume and then investigated the age-related trajectories of structural networks over the adult lifespan in 536 healthy subjects aged 20–86 years. Twenty independent components (ICs) were extracted in the ICA, and statistical analyses between age and ICA weights revealed 16 age-related ICs across the adult lifespan. Most of the trajectories of ICA weights demonstrated significant linear decline tendencies, and the corresponding structural networks primarily included the anterior and posterior dorsal attention networks, the ventral and posterior default mode networks, the auditory network, five cerebellum networks and the hippocampus-related network with the most significant decreased tendency among all ICs (p of age = 1.11E-77). Only the temporal lobe-related network showed a significant quadratic tendency with age (p of age(2) = 5.66E-06). Our findings not only provide insight into the patterns of the age-related changes of structural networks but also provide a foundation for understanding abnormal aging. Frontiers Media S.A. 2017-08-17 /pmc/articles/PMC5562685/ /pubmed/28860988 http://dx.doi.org/10.3389/fnagi.2017.00275 Text en Copyright © 2017 Liu, Yao, Chen, Zhang, Yao, Li, Jin and Guo. 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) or licensor 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 Liu, Ke Yao, Shixiu Chen, Kewei Zhang, Jiacai Yao, Li Li, Ke Jin, Zhen Guo, Xiaojuan Structural Brain Network Changes across the Adult Lifespan |
title | Structural Brain Network Changes across the Adult Lifespan |
title_full | Structural Brain Network Changes across the Adult Lifespan |
title_fullStr | Structural Brain Network Changes across the Adult Lifespan |
title_full_unstemmed | Structural Brain Network Changes across the Adult Lifespan |
title_short | Structural Brain Network Changes across the Adult Lifespan |
title_sort | structural brain network changes across the adult lifespan |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5562685/ https://www.ncbi.nlm.nih.gov/pubmed/28860988 http://dx.doi.org/10.3389/fnagi.2017.00275 |
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