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Alterations via inter-regional connective relationships in Alzheimer’s disease

Disruptions in the inter-regional connective correlation within the brain are believed to contribute to memory impairment. To detect these corresponding correlation networks in Alzheimer’s disease (AD), we conducted three types of inter-regional correlation analysis, including structural covariance,...

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Autores principales: Ren, Xiaomei, Huang, Yunzhi, Dong, Bowen, Luan, Ying, Wu, Ye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672243/
https://www.ncbi.nlm.nih.gov/pubmed/38021241
http://dx.doi.org/10.3389/fnhum.2023.1276994
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author Ren, Xiaomei
Huang, Yunzhi
Dong, Bowen
Luan, Ying
Wu, Ye
author_facet Ren, Xiaomei
Huang, Yunzhi
Dong, Bowen
Luan, Ying
Wu, Ye
author_sort Ren, Xiaomei
collection PubMed
description Disruptions in the inter-regional connective correlation within the brain are believed to contribute to memory impairment. To detect these corresponding correlation networks in Alzheimer’s disease (AD), we conducted three types of inter-regional correlation analysis, including structural covariance, functional connectivity and group-level independent component analysis (group-ICA). The analyzed data were obtained from the Alzheimer’s Disease Neuroimaging Initiative, comprising 52 cognitively normal (CN) participants without subjective memory concerns, 52 individuals with late mild cognitive impairment (LMCI) and 52 patients with AD. We firstly performed vertex-wise cortical thickness analysis to identify brain regions with cortical thinning in AD and LMCI patients using structural MRI data. These regions served as seeds to construct both structural covariance networks and functional connectivity networks for each subject. Additionally, group-ICA was performed on the functional data to identify intrinsic brain networks at the cohort level. Through a comparison of the structural covariance and functional connectivity networks with ICA networks, we identified several inter-regional correlation networks that consistently exhibited abnormal connectivity patterns among AD and LMCI patients. Our findings suggest that reduced inter-regional connectivity is predominantly observed within a subnetwork of the default mode network, which includes the posterior cingulate and precuneus regions, in both AD and LMCI patients. This disruption of connectivity between key nodes within the default mode network provides evidence supporting the hypothesis that impairments in brain networks may contribute to memory deficits in AD and LMCI.
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spelling pubmed-106722432023-01-01 Alterations via inter-regional connective relationships in Alzheimer’s disease Ren, Xiaomei Huang, Yunzhi Dong, Bowen Luan, Ying Wu, Ye Front Hum Neurosci Human Neuroscience Disruptions in the inter-regional connective correlation within the brain are believed to contribute to memory impairment. To detect these corresponding correlation networks in Alzheimer’s disease (AD), we conducted three types of inter-regional correlation analysis, including structural covariance, functional connectivity and group-level independent component analysis (group-ICA). The analyzed data were obtained from the Alzheimer’s Disease Neuroimaging Initiative, comprising 52 cognitively normal (CN) participants without subjective memory concerns, 52 individuals with late mild cognitive impairment (LMCI) and 52 patients with AD. We firstly performed vertex-wise cortical thickness analysis to identify brain regions with cortical thinning in AD and LMCI patients using structural MRI data. These regions served as seeds to construct both structural covariance networks and functional connectivity networks for each subject. Additionally, group-ICA was performed on the functional data to identify intrinsic brain networks at the cohort level. Through a comparison of the structural covariance and functional connectivity networks with ICA networks, we identified several inter-regional correlation networks that consistently exhibited abnormal connectivity patterns among AD and LMCI patients. Our findings suggest that reduced inter-regional connectivity is predominantly observed within a subnetwork of the default mode network, which includes the posterior cingulate and precuneus regions, in both AD and LMCI patients. This disruption of connectivity between key nodes within the default mode network provides evidence supporting the hypothesis that impairments in brain networks may contribute to memory deficits in AD and LMCI. Frontiers Media S.A. 2023-11-09 /pmc/articles/PMC10672243/ /pubmed/38021241 http://dx.doi.org/10.3389/fnhum.2023.1276994 Text en Copyright © 2023 Ren, Huang, Dong, Luan, Wu and for the Alzheimer's Disease Neuroimaging Initiative. https://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 Human Neuroscience
Ren, Xiaomei
Huang, Yunzhi
Dong, Bowen
Luan, Ying
Wu, Ye
Alterations via inter-regional connective relationships in Alzheimer’s disease
title Alterations via inter-regional connective relationships in Alzheimer’s disease
title_full Alterations via inter-regional connective relationships in Alzheimer’s disease
title_fullStr Alterations via inter-regional connective relationships in Alzheimer’s disease
title_full_unstemmed Alterations via inter-regional connective relationships in Alzheimer’s disease
title_short Alterations via inter-regional connective relationships in Alzheimer’s disease
title_sort alterations via inter-regional connective relationships in alzheimer’s disease
topic Human Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10672243/
https://www.ncbi.nlm.nih.gov/pubmed/38021241
http://dx.doi.org/10.3389/fnhum.2023.1276994
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