Post-stroke upper limb recovery is correlated with dynamic resting-state network connectivity

Area of Science:

• Neuroscience
• Biomedical Engineering
• Rehabilitation Medicine

Background:

• Motor recovery after stroke remains a significant challenge, particularly for individuals with severe functional impairments.
• Understanding the neural mechanisms of recovery is crucial for developing effective interventions.
• Resting-state electrophysiology offers a promising, blood flow-independent method to study neural activity, but behaviorally relevant network dynamics post-stroke are not well-defined.

Purpose of the Study:

• To identify behaviorally relevant features of resting-state sensorimotor network dynamics in individuals with subcortical stroke and hand paresis.
• To investigate the longitudinal changes in these network dynamics and their correlation with motor function recovery.
• To explore the potential of resting-state network metrics as biomarkers for motor recovery.

Main Methods:

• Longitudinal study of 37 individuals with subcortical ischemic stroke and unilateral hand paresis at 3 and 12 weeks post-stroke, compared to matched controls.
• Resting-state magnetoencephalography (MEG) recordings.
• Data-driven hidden Markov model (HMM) analysis to decompose MEG data into time-varying resting-state networks (RSNs).
• Assessment of motor function using the Action Research Arm Test (ARAT) and Fugl-Meyer upper extremity (FM-UE) scores.

Main Results:

• Individuals with stroke showed significant motor function improvement between 3 and 12 weeks post-stroke (ARAT and FM-UE, P < 0.001).
• An alpha-band ipsilesional resting-state sensorimotor network exhibited significantly increased lifetime and fractional occupancy at 3 weeks post-stroke compared to controls.
• The increased lifetime of this ipsilesional sensorimotor network positively correlated with concurrent motor scores in individuals with incomplete recovery, and this association was specific to the ipsilesional sensorimotor network.

Conclusions:

• Increased recruitment of the alpha-band ipsilesional resting-state sensorimotor network in the early subacute phase post-stroke serves as a functionally relevant biomarker.
• These findings are specific to individuals with incomplete hand paresis and may reflect ongoing motor recovery processes.
• The identified neural network dynamics provide insights into the physiological mechanisms of motor recovery after stroke.