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Updated: Mar 31, 2026
Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke
Published on: October 10, 2025
Functional reorganization and prediction of motor recovery after a stroke: A graph theoretical analysis of functional
Jungsoo Lee1, Minji Lee2, Dae-Shik Kim1
1Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea.
Purpose:
This study investigated the changes in the network topological configuration of the ipsilesional and contralesional hemispheres after a stroke and the indicators for the prediction of motor recovery using a graph theoretical approach in networks obtained from functional magnetic resonance imaging (fMRI).
Methods:
A longitudinal observational experiments (2 weeks and 1, 3, and 6 months after onset) were conducted on 12 patients after a stroke. We investigated the network reorganization during recovery in the ipsilesional and contralesional hemispheres by examining changes of graph indices related to network randomization. We predicted the recovery of motor function by examining the relationship between specific network measures and improved motor function scores.
Results:
The ipsilesional hemispheric network showed active reorganization during recovery after a stroke. The randomness of the network significantly increased for 3 months post-stroke. We described an indicator for the prediction of the recovery of motor function from graph indices: the characteristic path length. As the path length of the ipsilesional network was lower immediately after onset, the better recovery could be expected after 3 months.
Conclusions:
This approach were helpful for understanding dynamic reorganizations of both hemispheric networks after a stroke and finding the implication for recovery.
