Research Focus
We possess a remarkable ability to learn new motor skills and retain memories for those skills throughout life, such as riding a bicycle. The ease with which we perform these skills belies their overwhelming computational complexity. Our research focuses on unraveling the different computational processes involved in solving this motor control problem. A primary area of our research aims at understanding how explicit, cognitive strategies interact with implicit motor adaptation during skill acquisition. Specifically, how do novel movement strategies arise, what are the functional consequences of their interaction with learning, and what are their respective neural systems? Ultimately, we hope that this work can lead to the development of optimal training protocols that can guide learning towards different, but still functioning learning mechanisms following stroke or disease.
Recent Work
Al-Fawakhiri N., et al. (2023). On the money and right on the target: How robust are reward and task success for implicit motor adaptation. bioRxiv.
Annes, C.K., et al. (2023). The effect of workspace tidiness on schoolwork performance of high school students. Journal of Emerging Investigators, 6:1-5.
Poh, E., et al. (2022). Top-down effects in motor generalization, bioRxiv.
Avraham, G., et al. (2022). Contextual effects in sensorimotor adaptation adhere to associative learning rules. eLife, 11:e75801.
Kim, O. A., et al. (2022). Motor learning without movement. Proceedings of the National Academy of Sciences, 119(30):e2204379119.
McDougle, S.D., et al. (2022). Continuous manipulation of mental representations is compromised in cerebellar degeneration. Brain, 145(12):4246-4263.
Mushtaq, F., et al. (2022). Distinct neural signatures of outcome monitoring after selection and execution errors. Journal of Cognitive Neuroscience, 34(5):748-765.
McDougle, S.D, et al. (2022). Revisiting the role of the medial temporal lobe in motor learning. Journal of Cognitive Neuroscience, 34(3):532-549.