Distinct Disconnection Patterns Explain Task-Specific Motor Impairment and Outcome After Stroke.

Area of Science:

• Neuroscience
• Neurology
• Brain Connectivity

Background:

• Stroke is increasingly viewed as a network disorder affecting white matter connectivity.
• Previous studies show post-stroke motor deficits linked to sensorimotor and nonsensorimotor network damage.
• The distinct disconnection patterns underlying initial impairment versus long-term outcome remain unclear.

Purpose of the Study:

• To investigate if task-specific initial motor impairment and long-term outcome after stroke arise from distinct brain disconnection patterns.
• To identify specific structural connectivity disruptions associated with upper limb motor deficits in subacute stroke patients.
• To explore the predictive power of connectome-based lesion-symptom mapping for motor recovery.

Main Methods:

• Included 113 subacute stroke patients with lesion data and upper limb motor assessments.
• Employed connectome-based lesion-symptom mapping using a normative structural connectome.
• Utilized machine learning to predict individual motor impairment and >3-month outcomes.

Main Results:

• Identified task-specific disconnection patterns predicting initial motor impairment and outcome.
• A task-general reach-to-grasp network involved both sensorimotor and nonsensorimotor areas.
• Disconnections for basal motor control prediction differed significantly between initial impairment and chronic-stage outcome, with time- and task-dependent interhemispheric changes.

Conclusions:

• Distinct disconnection patterns predict specific aspects of motor impairment and outcome post-stroke.
• The contralesional hemisphere plays a time- and task-dependent role in recovery, with nonsensorimotor temporal areas potentially aiding compensation.
• Differences in predictive disconnection patterns suggest basal motor control relies on brain structural reserve during recovery, supporting connectome mapping's clinical potential.