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
Velázquez-Vargas, Carlos A., and Jordan A. Taylor (2024). Learning to Move and Plan Like the Knight: Sequential Decision Making With a Novel Motor Mapping. BioRxiv.
Falcone, Sara, and Jordan A. Taylor. “The Impact of Spatiotemporal Calibration on Sense of Embodiment and Task Performance in Teleoperation.” Proceedings of the 46th Annual Conference of the Cognitive Science Society. (2024): 2226–2232.
Tsay, Jonathan Sanching et al. “Fundamental Processes in Sensorimotor Learning: Reasoning, Refinement, and Retrieval.” eLife (2024): 1–25.
Velázquez-Vargas, Carlos A., Nathaniel D. Daw, and Jordan A. Taylor. “The Role of Training Variability for Model-Based and Model-Free Learning of an Arbitrary Visuomotor Mapping.” PLoS Computational Biology (2024)
Velázquez-Vargas, Carlos A., and Jordan A. Taylor. “Working Memory Constraints for Visuomotor Retrieval Strategies.” Journal of Neurophysiology 132.2 (2024): 347–361.
Velázquez-Vargas, Carlos A. et al. “Learning to Abstract Visuomotor Mappings Using Meta-Reinforcement Learning.” Proceedings of the Annual Meeting of the Cognitive Science Society 46 (2024): 2240–2246.