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Dynamic Network Analysis Reveals Altered Temporal Variability in Brain Regions after Stroke: A Longitudinal
Jianping Hu1,2, Juan Du3, Qiang Xu4
1Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Neural Plasticity
|June 1, 2018
Summary
Brain network temporal variability changes after stroke, with reduced connectivity in acute stages recovering over time. This variability, especially in the motor cortex, may predict motor function recovery.
Area of Science:
- Neuroscience
- Medical Imaging
- Systems Biology
Background:
- Resting-state functional connectivity (FC) exhibits non-stationarity, reflecting dynamic brain activity.
- Temporal variability of FC offers insights into brain network reorganization post-stroke.
- Understanding these dynamics is crucial for stroke recovery assessment.
Purpose of the Study:
- To investigate longitudinal changes in FC temporal variability in stroke patients.
- To explore the relationship between FC temporal variability and motor recovery.
- To identify potential biomarkers for stroke rehabilitation.
Main Methods:
- Utilized resting-state functional magnetic resonance imaging (fMRI) in 19 stroke patients and 19 healthy controls.
- Scanned patients during acute, subacute, and early chronic stages post-stroke.
- Analyzed temporal variability of FC within and across brain networks.
Main Results:
- Stroke patients showed reduced regional temporal variability in acute stages compared to controls, with recovery observed later.
- Increased temporal variability was noted in motor, auditory, and visual cortices during the subacute stage.
- Temporal variability in the ipsilesional precentral gyrus (PreCG) initially increased then decreased, correlating with motor recovery.
Conclusions:
- Temporal variability of brain networks is altered following stroke.
- Dynamic changes in FC temporal variability may serve as a biomarker for motor recovery.
- This approach could aid in evaluating and predicting stroke patient outcomes.
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