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Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study

Recent fMRI studies have demonstrated that resting-state functional connectivity (FC) is of nonstationarity. Temporal variability of FC reflects the dynamic nature of brain activity. Exploring temporal variability of FC offers a new approach to investigate reorganization and integration of brain net...

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Autores principales: Hu, Jianping, Du, Juan, Xu, Qiang, Yang, Fang, Zeng, Fanyong, Weng, Yifei, Dai, Xi-jian, Qi, Rongfeng, Liu, Xiaoxue, Lu, Guangming, Zhang, Zhiqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5907391/
https://www.ncbi.nlm.nih.gov/pubmed/29849574
http://dx.doi.org/10.1155/2018/9394156
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author Hu, Jianping
Du, Juan
Xu, Qiang
Yang, Fang
Zeng, Fanyong
Weng, Yifei
Dai, Xi-jian
Qi, Rongfeng
Liu, Xiaoxue
Lu, Guangming
Zhang, Zhiqiang
author_facet Hu, Jianping
Du, Juan
Xu, Qiang
Yang, Fang
Zeng, Fanyong
Weng, Yifei
Dai, Xi-jian
Qi, Rongfeng
Liu, Xiaoxue
Lu, Guangming
Zhang, Zhiqiang
author_sort Hu, Jianping
collection PubMed
description Recent fMRI studies have demonstrated that resting-state functional connectivity (FC) is of nonstationarity. Temporal variability of FC reflects the dynamic nature of brain activity. Exploring temporal variability of FC offers a new approach to investigate reorganization and integration of brain networks after stroke. Here, we examined longitudinal alterations of FC temporal variability in brain networks after stroke. Nineteen stroke patients underwent resting fMRI scans across the acute stage (within-one-week after stroke), subacute stage (within-two-weeks after stroke), and early chronic stage (3-4 months after stroke). Nineteen age- and sex-matched healthy individuals were enrolled. Compared with the controls, stroke patients exhibited reduced regional temporal variability during the acute stages, which was recovered at the following two stages. Compared with the acute stage, the subacute stage exhibited increased temporal variability in the primary motor, auditory, and visual cortices. Across the three stages, the temporal variability in the ipsilesional precentral gyrus (PreCG) was increased first and then reduced. Increased temporal variability in the ipsilesional PreCG from the acute stage to the subacute stage was correlated with motor recovery from the acute stage to the early chronic stage. Our results demonstrated that temporal variability of brain network might be a potential tool for evaluating and predicting motor recovery after stroke.
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spelling pubmed-59073912018-05-30 Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study Hu, Jianping Du, Juan Xu, Qiang Yang, Fang Zeng, Fanyong Weng, Yifei Dai, Xi-jian Qi, Rongfeng Liu, Xiaoxue Lu, Guangming Zhang, Zhiqiang Neural Plast Research Article Recent fMRI studies have demonstrated that resting-state functional connectivity (FC) is of nonstationarity. Temporal variability of FC reflects the dynamic nature of brain activity. Exploring temporal variability of FC offers a new approach to investigate reorganization and integration of brain networks after stroke. Here, we examined longitudinal alterations of FC temporal variability in brain networks after stroke. Nineteen stroke patients underwent resting fMRI scans across the acute stage (within-one-week after stroke), subacute stage (within-two-weeks after stroke), and early chronic stage (3-4 months after stroke). Nineteen age- and sex-matched healthy individuals were enrolled. Compared with the controls, stroke patients exhibited reduced regional temporal variability during the acute stages, which was recovered at the following two stages. Compared with the acute stage, the subacute stage exhibited increased temporal variability in the primary motor, auditory, and visual cortices. Across the three stages, the temporal variability in the ipsilesional precentral gyrus (PreCG) was increased first and then reduced. Increased temporal variability in the ipsilesional PreCG from the acute stage to the subacute stage was correlated with motor recovery from the acute stage to the early chronic stage. Our results demonstrated that temporal variability of brain network might be a potential tool for evaluating and predicting motor recovery after stroke. Hindawi 2018-04-05 /pmc/articles/PMC5907391/ /pubmed/29849574 http://dx.doi.org/10.1155/2018/9394156 Text en Copyright © 2018 Jianping Hu et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Hu, Jianping
Du, Juan
Xu, Qiang
Yang, Fang
Zeng, Fanyong
Weng, Yifei
Dai, Xi-jian
Qi, Rongfeng
Liu, Xiaoxue
Lu, Guangming
Zhang, Zhiqiang
Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study
title Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study
title_full Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study
title_fullStr Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study
title_full_unstemmed Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study
title_short Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study
title_sort dynamic network analysis reveals altered temporal variability in brain regions after stroke: a longitudinal resting-state fmri study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5907391/
https://www.ncbi.nlm.nih.gov/pubmed/29849574
http://dx.doi.org/10.1155/2018/9394156
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