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.

Participants undergo functional magnetic resonance imaging during the performance of the visuomotor learning task. The visuomotor learning task involves holding a device in the hand that measures the strength of the grip when squeezing the 'gripper'.

1. Isometric whole-hand grip force is captured continuously with grip-force transducers (at 1000Hz) and adjusted relative to the individual maximum voluntary contraction. Precision of force adjustment is based on the recorded muscle force monitored during task performance and defined as the actual force exerted by the participant relative to the target force (measurement unit: precision in %), with positive values indicating over- and negative values indicating undershoot. Learning rate from before to after learning will be defined as the difference in precision between before as compared to after one single learning session.

Learning-related change of brain activation is defined based on changes in multi-voxel patterns of BOLD-signal-derived brain activation.

INCLUSION CRITERIA For all participants: adult volunteers (age ≥18 years) right-hand dominance as defined by the Edinburgh Handedness Inventory Stroke-specific inclusion criteria: ischemic or hemorrhagic lesion subcortical or cortical tissue involvement chronic phase (>6 months) after their index lesion voluntary whole-hand grip force (MRC, Medical Research Council scale for muscle force ≥2) repeated release (standardized as a reduction of 50% of maximum voluntary contraction measured with a dynamometer) EXCLUSION CRITERIA For all participants: Presence of any MRI risk factors substance use disorder psychotic disorders Stroke-group specific exclusion criteria: Primary intracerebral hematoma subarachnoid hemorrhage bi-hemispheric or cerebellar strokes other concomitant neurological disorders affecting upper extremity motor function documented history of dementia before or after stroke severe aphasia, particularly of receptive nature (NIHSS Language subsection ≥2), affecting their ability to understand the purpose of the study and give informed consent uncontrolled hypertension despite treatment intake of tricyclic anti-depressants or neuroleptic medication.