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A longitudinal study of structural brain network changes with normal aging

The aim of this study was to investigate age-related changes in the topological organization of structural brain networks by applying a longitudinal design over 6 years. Structural brain networks were derived from measurements of regional gray matter volume and were constructed in age-specific group...

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Autores principales: Wu, Kai, Taki, Yasuyuki, Sato, Kazunori, Qi, Haochen, Kawashima, Ryuta, Fukuda, Hiroshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3615182/
https://www.ncbi.nlm.nih.gov/pubmed/23565087
http://dx.doi.org/10.3389/fnhum.2013.00113
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author Wu, Kai
Taki, Yasuyuki
Sato, Kazunori
Qi, Haochen
Kawashima, Ryuta
Fukuda, Hiroshi
author_facet Wu, Kai
Taki, Yasuyuki
Sato, Kazunori
Qi, Haochen
Kawashima, Ryuta
Fukuda, Hiroshi
author_sort Wu, Kai
collection PubMed
description The aim of this study was to investigate age-related changes in the topological organization of structural brain networks by applying a longitudinal design over 6 years. Structural brain networks were derived from measurements of regional gray matter volume and were constructed in age-specific groups from baseline and follow-up scans. The structural brain networks showed economical small-world properties, providing high global and local efficiency for parallel information processing at low connection costs. In the analysis of the global network properties, the local and global efficiency of the baseline scan were significantly lower compared to the follow-up scan. Moreover, the annual rate of change in local and global efficiency showed a positive and negative quadratic correlation with the baseline age, respectively; both curvilinear correlations peaked at approximately the age of 50. In the analysis of the regional nodal properties, significant negative correlations between the annual rate of change in nodal strength and the baseline age were found in the brain regions primarily involved in the visual and motor/control systems, whereas significant positive quadratic correlations were found in the brain regions predominately associated with the default-mode, attention, and memory systems. The results of the longitudinal study are consistent with the findings of our previous cross-sectional study: the structural brain networks develop into a fast distribution from young to middle age (approximately 50 years old) and eventually became a fast localization in the old age. Our findings elucidate the network topology of structural brain networks and its longitudinal changes, thus enhancing the understanding of the underlying physiology of normal aging in the human brain.
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spelling pubmed-36151822013-04-05 A longitudinal study of structural brain network changes with normal aging Wu, Kai Taki, Yasuyuki Sato, Kazunori Qi, Haochen Kawashima, Ryuta Fukuda, Hiroshi Front Hum Neurosci Neuroscience The aim of this study was to investigate age-related changes in the topological organization of structural brain networks by applying a longitudinal design over 6 years. Structural brain networks were derived from measurements of regional gray matter volume and were constructed in age-specific groups from baseline and follow-up scans. The structural brain networks showed economical small-world properties, providing high global and local efficiency for parallel information processing at low connection costs. In the analysis of the global network properties, the local and global efficiency of the baseline scan were significantly lower compared to the follow-up scan. Moreover, the annual rate of change in local and global efficiency showed a positive and negative quadratic correlation with the baseline age, respectively; both curvilinear correlations peaked at approximately the age of 50. In the analysis of the regional nodal properties, significant negative correlations between the annual rate of change in nodal strength and the baseline age were found in the brain regions primarily involved in the visual and motor/control systems, whereas significant positive quadratic correlations were found in the brain regions predominately associated with the default-mode, attention, and memory systems. The results of the longitudinal study are consistent with the findings of our previous cross-sectional study: the structural brain networks develop into a fast distribution from young to middle age (approximately 50 years old) and eventually became a fast localization in the old age. Our findings elucidate the network topology of structural brain networks and its longitudinal changes, thus enhancing the understanding of the underlying physiology of normal aging in the human brain. Frontiers Media S.A. 2013-04-03 /pmc/articles/PMC3615182/ /pubmed/23565087 http://dx.doi.org/10.3389/fnhum.2013.00113 Text en Copyright © 2013 Wu, Taki, Sato, Qi, Kawashima and Fukuda. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
spellingShingle Neuroscience
Wu, Kai
Taki, Yasuyuki
Sato, Kazunori
Qi, Haochen
Kawashima, Ryuta
Fukuda, Hiroshi
A longitudinal study of structural brain network changes with normal aging
title A longitudinal study of structural brain network changes with normal aging
title_full A longitudinal study of structural brain network changes with normal aging
title_fullStr A longitudinal study of structural brain network changes with normal aging
title_full_unstemmed A longitudinal study of structural brain network changes with normal aging
title_short A longitudinal study of structural brain network changes with normal aging
title_sort longitudinal study of structural brain network changes with normal aging
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3615182/
https://www.ncbi.nlm.nih.gov/pubmed/23565087
http://dx.doi.org/10.3389/fnhum.2013.00113
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