Stroke is the leading cause of disability in the United States. Stroke frequently devastates movement, limiting the ability to feed, bathe, dress, and care for oneself. Although the brain is capable of some reorganization after stroke, recovery is generally incomplete and inadequate. We believe that neurorehabilitation can--and should--do better.
Our central mission is to restore motor function after stroke by harnessing the brain's neuroplastic potential. We focus on developing methods to accelerate motor learning and recovery, and on understanding the mechanisms that underlie this acceleration. We study individuals who are healthy and who have had a stroke. Our research seeks to hone neurorehabilitation strategies, guided by our understanding of neuroplasticity and learning.
One major area of research is developing a tool to objectively quantify therapy dose (i.e., the number of functional movements trained) in individuals undergoing upper limb stroke rehabilitation. An optimal early rehabilitation dose to maximize recovery has never been established. This gap in knowledge stems from a lack of pragmatic tools that can precisely quantify what and how much patients are doing in an actual rehabilitation setting. We are using a combination of wireless sensors and machine learning algorithms to identify and count functional movement repetitions. We aim to use this tool in quantitative dose-response rehabilitation trials in the future.
Another major area of research is understanding the neural mechanisms of motor skill learning and recovery. We use noninvasive brain stimulation, such as transcranial electrical stimulation (TES) and transcranial magnetic stimulation (TMS), to accelerate and probe learning. We have previously shown that applying TES during training improves motor skill learning in individuals with and without stroke. We thus use TES to induce a "gain of function" effect to better understand cortical and subcortical networks involved in learning and recovery. Using TMS and movement kinematics, we additionally probe changes in neural circuitry and motor control that are associated with motor learning and recovery. This collective methodological approach enables us to identify the drivers of motor skill learning and recovery. Using insights gained from healthy individuals, we aim to develop strategies to elicit maximal learning effects in individuals with stroke, and to understand mechanisms of learning in this population.