Modulation of Functional Connectivity and Low-Frequency Fluctuations After Brain-Computer Interface-Guided Robot Hand...

Area of Science:

• Neuroscience
• Rehabilitation Medicine
• Biomedical Engineering

Background:

• Chronic stroke survivors often experience plateaued hand function recovery by six months post-stroke.
• Brain-computer interface (BCI)-guided robot-assisted training shows promise for upper-limb motor function recovery in chronic stroke.
• The neuroplasticity mechanisms underlying BCI-guided training effectiveness remain incompletely understood.

Purpose of the Study:

• To investigate whole-brain neuroplasticity changes following BCI-guided robot hand training in chronic stroke survivors.
• To determine if these neuroplasticity changes are maintained at a 6-month follow-up.
• To correlate neurological changes with clinical improvements in upper-limb motor function.

Main Methods:

• 14 chronic stroke subjects underwent 20 sessions of BCI-guided robot hand training.
• Clinical assessments included the Action Research Arm Test (ARAT) and Fugl-Meyer Assessment for Upper-Limb (FMA).
• Neuroimaging utilized resting-state functional magnetic resonance imaging (fMRI) for functional connectivity (FC) and fractional amplitude of low-frequency fluctuations (fALFF) analysis.

Main Results:

• Significant long-term motor function improvements were observed in both FMA and ARAT scores post-training.
• Seed-based FC analysis revealed sustained modulations between ipsilesional motor regions and contralesional areas.
• fALFF analysis demonstrated sustained increases in local neuronal activity in central, frontal, and parietal regions.

Conclusions:

• BCI-guided robot hand training induces sustained neuroplastic changes in chronic stroke survivors.
• These changes involve enhanced functional connectivity and local neuronal activity in sensorimotor and fronto-parietal networks.
• The findings support BCI-guided training as a viable strategy for long-term motor recovery in chronic stroke.