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Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease

Subjective cognitive decline (SCD) is considered to be the preclinical stage of Alzheimer's disease (AD) and has the potential for the early diagnosis and intervention of AD. It was implicated that CSF-tau, which increases very early in the disease process in AD, has a high sensitivity and spec...

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Autores principales: Wang, Jue, Wang, Kexin, Liu, Tiantian, Wang, Li, Suo, Dingjie, Xie, Yunyan, Funahashi, Shintaro, Wu, Jinglong, Pei, Guangying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9108158/
https://www.ncbi.nlm.nih.gov/pubmed/35586480
http://dx.doi.org/10.3389/fncom.2022.885126
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author Wang, Jue
Wang, Kexin
Liu, Tiantian
Wang, Li
Suo, Dingjie
Xie, Yunyan
Funahashi, Shintaro
Wu, Jinglong
Pei, Guangying
author_facet Wang, Jue
Wang, Kexin
Liu, Tiantian
Wang, Li
Suo, Dingjie
Xie, Yunyan
Funahashi, Shintaro
Wu, Jinglong
Pei, Guangying
author_sort Wang, Jue
collection PubMed
description Subjective cognitive decline (SCD) is considered to be the preclinical stage of Alzheimer's disease (AD) and has the potential for the early diagnosis and intervention of AD. It was implicated that CSF-tau, which increases very early in the disease process in AD, has a high sensitivity and specificity to differentiate AD from normal aging, and the highly connected brain regions behaved more tau burden in patients with AD. Thus, a highly connected state measured by dynamic functional connectivity may serve as the early changes of AD. In this study, forty-five normal controls (NC), thirty-six individuals with SCD, and thirty-five patients with AD were enrolled to obtain the resting-state functional magnetic resonance imaging scanning. Sliding windows, Pearson correlation, and clustering analysis were combined to investigate the different levels of information transformation states. Three states, namely, the low state, the middle state, and the high state, were characterized based on the strength of functional connectivity between each pair of brain regions. For the global dynamic functional connectivity analysis, statistically significant differences were found among groups in the three states, and the functional connectivity in the middle state was positively correlated with cognitive scales. Furthermore, the whole brain was parcellated into four networks, namely, default mode network (DMN), cognitive control network (CCN), sensorimotor network (SMN), and occipital-cerebellum network (OCN). For the local network analysis, statistically significant differences in CCN for low state and SMN for middle state and high state were found in normal controls and patients with AD. Meanwhile, the differences were also found in normal controls and individuals with SCD. In addition, the functional connectivity in SMN for high state was positively correlated with cognitive scales. Converging results showed the changes in dynamic functional states in individuals with SCD and patients with AD. In addition, the changes were mainly in the high strength of the functional connectivity state.
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spelling pubmed-91081582022-05-17 Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease Wang, Jue Wang, Kexin Liu, Tiantian Wang, Li Suo, Dingjie Xie, Yunyan Funahashi, Shintaro Wu, Jinglong Pei, Guangying Front Comput Neurosci Neuroscience Subjective cognitive decline (SCD) is considered to be the preclinical stage of Alzheimer's disease (AD) and has the potential for the early diagnosis and intervention of AD. It was implicated that CSF-tau, which increases very early in the disease process in AD, has a high sensitivity and specificity to differentiate AD from normal aging, and the highly connected brain regions behaved more tau burden in patients with AD. Thus, a highly connected state measured by dynamic functional connectivity may serve as the early changes of AD. In this study, forty-five normal controls (NC), thirty-six individuals with SCD, and thirty-five patients with AD were enrolled to obtain the resting-state functional magnetic resonance imaging scanning. Sliding windows, Pearson correlation, and clustering analysis were combined to investigate the different levels of information transformation states. Three states, namely, the low state, the middle state, and the high state, were characterized based on the strength of functional connectivity between each pair of brain regions. For the global dynamic functional connectivity analysis, statistically significant differences were found among groups in the three states, and the functional connectivity in the middle state was positively correlated with cognitive scales. Furthermore, the whole brain was parcellated into four networks, namely, default mode network (DMN), cognitive control network (CCN), sensorimotor network (SMN), and occipital-cerebellum network (OCN). For the local network analysis, statistically significant differences in CCN for low state and SMN for middle state and high state were found in normal controls and patients with AD. Meanwhile, the differences were also found in normal controls and individuals with SCD. In addition, the functional connectivity in SMN for high state was positively correlated with cognitive scales. Converging results showed the changes in dynamic functional states in individuals with SCD and patients with AD. In addition, the changes were mainly in the high strength of the functional connectivity state. Frontiers Media S.A. 2022-05-02 /pmc/articles/PMC9108158/ /pubmed/35586480 http://dx.doi.org/10.3389/fncom.2022.885126 Text en Copyright © 2022 Wang, Wang, Liu, Wang, Suo, Xie, Funahashi, Wu and Pei. 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 Neuroscience
Wang, Jue
Wang, Kexin
Liu, Tiantian
Wang, Li
Suo, Dingjie
Xie, Yunyan
Funahashi, Shintaro
Wu, Jinglong
Pei, Guangying
Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease
title Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease
title_full Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease
title_fullStr Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease
title_full_unstemmed Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease
title_short Abnormal Dynamic Functional Networks in Subjective Cognitive Decline and Alzheimer's Disease
title_sort abnormal dynamic functional networks in subjective cognitive decline and alzheimer's disease
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9108158/
https://www.ncbi.nlm.nih.gov/pubmed/35586480
http://dx.doi.org/10.3389/fncom.2022.885126
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