Learning in Stroke

After a stroke, plasticity occurs in the brain from microscopic to network level with positive but also negative consequences for functional recovery. Why post-stroke plasticity takes a beneficial or a maladaptive direction is still incompletely understood. Because the biological mechanisms underlying sensorimotor learning parallel those observed during recovery, learning mechanisms could be potential modifiers of post-stroke neuroplasticity and have a discrete mal-/adaptive impact on the recovery of sensorimotor function. This project seeks to further the understanding of the link between brain circuits that control the integration of new information during procedural learning in the injured brain and those circuits that are involved in adaptive plastic changes during recovery of sensorimotor function post-stroke. The project's methodological approach will allow the characterization of procedural learning-related neural network dynamics based on functional magnetic resonance imaging (MRI) in human volunteers with and without neurologically impairment post-stroke. Through multivariate integration of behavioral and biological descriptors of sensorimotor recovery, the project will investigate the association between motor learning-related network dynamics and descriptors of recovery.