Brain-Machine Interface-Driven Post-Stroke Upper-Limb Functional Recovery Correlates With Beta-Band Mediated Cortical...

Area of Science:

• Neuroscience
• Robotics
• Rehabilitation Medicine

Background:

• Brain-machine interface (BMI)-driven robot-assisted neurorehabilitation shows promise for upper-limb (UL) motor function recovery in post-stroke hemiparetic patients.
• Understanding the underlying neurophysiological changes during such interventions is crucial for optimizing treatment.
• Existing research has not fully elucidated the longitudinal changes in functional connectivity networks associated with this type of rehabilitation.

Purpose of the Study:

• To investigate the longitudinal changes in band-limited resting-state (RS) functional connectivity (FC) networks.
• To associate these FC network changes with upper-limb (UL) functional recovery in post-stroke patients undergoing a multimodal intervention.
• To identify neurophysiological patterns linked to motor recovery through a combination of motor attempt (MA)-based BMI and robotic hand-exoskeleton therapy.

Main Methods:

• A multimodal intervention combining motor attempt (MA)-based brain-machine interface (BMI) and a robotic hand-exoskeleton was administered to four adult participants.
• Rehabilitation lasted up to six weeks, with resting-state magnetoencephalography (RS-MEG) signals, Action Research Arm Test (ARAT), and grip strength (GS) recorded at five sessions.
• Cluster-based statistical tests correlated beta-band (15-26 Hz) RS-MEG FCs with UL functional recovery metrics (ARAT and GS).

Main Results:

• Significant average post-interventional increases of 100.0% (p=0.00028) in ARAT scores and 88.0% in grip strength were observed.
• Positively correlated beta-band RS-MEG FC sub-networks were identified in both contralesional and ipsilesional motor cortices.
• Frontoparietal FC exhibited hemispheric lateralization, with more positive correlations in the contralesional hemisphere and negative correlations in the ipsilesional hemisphere.

Conclusions:

• The findings support the theory of bilateral motor cortical involvement in upper-limb recovery after stroke.
• Novel functional connectivity patterns associated with motor recovery were identified, potentially serving as biomarkers for treatment efficacy.
• These neurophysiological insights can inform the development of more effective brain-machine interface and robotic-assisted neurorehabilitation strategies.