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Updated: Jul 25, 2025

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
Published on: September 1, 2023
Neuroimaging prognostic factors for treatment response to motor imagery training after stroke
Kexu Zhang1, Hewei Wang2, Xu Wang1
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Abstract:
The efficacy of motor imagery training for motor recovery is well acknowledged, but with substantial inter-individual variability in stroke patients. To help optimize motor imagery training therapy plans and screen suitable patients, this study aimed to explore neuroimaging biomarkers explaining variability in treatment response. Thirty-nine stroke patients were randomized to a motor imagery training group (n = 22, received a combination of conventional rehabilitation therapy and motor imagery training) and a control group (n = 17, received conventional rehabilitation therapy and health education) for 4 weeks of interventions. Their demography and clinical information, brain lesion from structural MRI, spontaneous brain activity and connectivity from rest fMRI, and sensorimotor brain activation from passive motor task fMRI were acquired to identify prognostic factors. We found that the variability of outcomes from sole conventional rehabilitation therapy could be explained by the reserved sensorimotor neural function, whereas the variability of outcomes from motor imagery training + conventional rehabilitation therapy was related to the spontaneous activity in the ipsilesional inferior parietal lobule and the local connectivity in the contralesional supplementary motor area. The results suggest that additional motor imagery training treatment is also efficient for severe patients with damaged sensorimotor neural function, but might be more effective for patients with impaired motor planning and reserved motor imagery.
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