Resting State Connectivity Is Modulated by Motor Learning in Individuals After Stroke. (June 2021)

• Record Type: Journal Article
• Authors: Kraeutner, Sarah N.; Rubino, Cristina; Rinat, Shie; Lakhani, Bimal; Borich, Michael R.; Wadden, Katie P.; Boyd, Lara A.
• Is Part Of: Neurorehabilitation & neural repair. Volume 35:Number 6(2021)
• Page Start: 513
• Page End: 524
• Publication Date: 2021-06
• Subjects: motor learning -- stroke -- rs-fMRI -- graph theory -- functional connectivity; Nervous system -- Diseases -- Patients -- Rehabilitation -- Periodicals; Brain damage -- Patients -- Rehabilitation -- Periodicals; Spinal cord -- Wounds and injuries -- Patients -- Rehabilitation -- Periodicals; Nervous system -- Regeneration -- Periodicals; Neuroplasticity -- Periodicals; 616.804305
• DOI: 10.1177/15459683211006713
• Languages: English
• ISSNs: 1545-9683

Abstract

Objective: Activity patterns across brain regions that can be characterized at rest (ie, resting-state functional connectivity [rsFC]) are disrupted after stroke and linked to impairments in motor function. While changes in rsFC are associated with motor recovery, it is not clear how rsFC is modulated by skilled motor practice used to promote recovery. The current study examined how rsFC is modulated by skilled motor practice after stroke and how changes in rsFC are linked to motor learning. Methods: Two groups of participants (individuals with stroke and age-matched controls) engaged in 4 weeks of skilled motor practice of a complex, gamified reaching task. Clinical assessments of motor function and impairment, and brain activity (via functional magnetic resonance imaging) were obtained before and after training. Results: While no differences in rsFC were observed in the control group, increased connectivity was observed in the sensorimotor network, linked to learning in the stroke group. Relative to healthy controls, a decrease in network efficiency was observed in the stroke group following training. Conclusions: Findings indicate that rsFC patterns related to learning observed after stroke reflect a shift toward a compensatory network configuration characterized by decreased network efficiency.