Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study
Joint Authors
Xu, Qiang
Zhang, Zhiqiang
Dai, Xi-jian
Du, Juan
Yang, Fang
Hu, Jianping
Zeng, Fanyong
Weng, Yifei
Qi, Rongfeng
Liu, Xiaoxue
Lu, Guang Ming
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-05
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Hu, Jianping& Du, Juan& Xu, Qiang& Yang, Fang& Zeng, Fanyong& Weng, Yifei…[et al.]. 2018. Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study. Neural Plasticity،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1210539
Modern Language Association (MLA)
Hu, Jianping…[et al.]. Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study. Neural Plasticity No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1210539
American Medical Association (AMA)
Hu, Jianping& Du, Juan& Xu, Qiang& Yang, Fang& Zeng, Fanyong& Weng, Yifei…[et al.]. Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal Resting-State fMRI Study. Neural Plasticity. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1210539
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1210539