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White Matter Biomarkers Associated with Motor Change in Individuals with Stroke: A Continuous Theta Burst Stimulation
K P Wadden1, S Peters2, M R Borich3
1Faculty of Medicine, Memorial University of Newfoundland, St. John's, Canada.
Abstract:
Continuous theta burst stimulation (cTBS) is a form of noninvasive repetitive brain stimulation that, when delivered over the contralesional hemisphere, can influence the excitability of the ipsilesional hemisphere in individuals with stroke. cTBS applied prior to skilled motor practice interventions may augment motor learning; however, there is a high degree of variability in individual response to this intervention. The main objective of the present study was to assess white matter biomarkers of response to cTBS paired with skilled motor practice in individuals with chronic stroke. We tested the effects of stimulation of the contralesional hemisphere at the site of the primary motor cortex (M1c) or primary somatosensory cortex (S1c) and a third group who received sham stimulation. Within each stimulation group, individuals were categorized into responders or nonresponders based on their capacity for motor skill change. Baseline diffusion tensor imaging (DTI) indexed the underlying white matter microstructure of a previously known motor learning network, named the constrained motor connectome (CMC), as well as the corticospinal tract (CST) of lesioned and nonlesioned hemispheres. Across practice, there were no differential group effects. However, when categorized as responders vs. nonresponders using change in motor behaviour, we demonstrated a significant difference in CMC microstructural properties (as measured by fractional anisotropy (FA)) for individuals in M1c and S1c groups. There were no significant differences between responders and nonresponders in clinical baseline measures or microstructural properties (FA) in the CST. The present study identifies a white matter biomarker, which extends beyond the CST, advancing our understanding of the importance of white matter networks for motor after stroke.
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