He received a bachelor’s degree in Mathematics and Applied Mathematics from Beijing Normal University and PHD in Kinesiology from University of Maryland, College Park. His research was focused on how children and adults learn motor sequences differently.
Yue’s long-term goal is to use behavioral studies, computational modeling, and functional neuroimaging, to unravel how cognitive processes interact with different aspects of motor actions (i.e., action selection, motor planning, and movement execution). He is also interested in the multiplicity of motor learning processes: How distinct learning processes are interactively implemented in the brain and what are their functional roles in learning and memory that operate across different timescales (i.e., consolidation, retention, generalization, habit formation).
ydu27 [at] jhu.edu
550 N Wolfe Street
Dissociable habits of response preparation versus response initiation. Yue Du, Adrian M. Haith (2023). PsyArXiv preprint.
Evidence for a common mechanism supporting invigoration of action selection and action execution. Kahori Kita, Yue Du, Adrian M. Haith (2023). Journal of Neurophysiology.
Comparing the speed of action initiation and action inhibition (2022). Yue Du, Alexander D Forrence, Delaney M Metcalf, Adrian M Haith bioRxiv preprint.
Dissociable habits of response preparation and response initiation. Du, Y. & Haith, A. M.. (2021). In Proc. Advances in Motor Learning and Motor Control.
Sequence structure has a differential effect on underlying motor learning processes. Prashad, S., Du, Y., & Clark, J. E. (2021). Journal of Motor Learning and Development, 9, 38–57.
When going can be faster than stopping: Rethinking response inhibition as a flexible decision about whether or not to act. Du, Y., Forrence, A. D., Metcalf, D. M., Haith, A. M.. (2020) Proc. Advances in Motor Learning and Motor Control.
Beyond the Mean Reaction Time: Trial-by-Trial Reaction Time Reveals the Distraction Effect on Perceptual-Motor Sequence Learning. Du, Y., and Clark, J. E. (2020). Cognition 202:104287. https://doi.org/10.1016/j.cognition.2020.104287
The” motor” in implicit motor sequence learning: A foot-stepping serial reaction time task. Du, Y., & Clark, J. E. (2018). Journal of Visualized Experiments: JoVE.
Timing at peak force may be the hidden target controlled in continuation and synchronization tapping. Du, Y., Clark, J. E., & Whitall, J. (2017). Experimental Brain Research, 235, 1541–1554. https://doi.org/10.1007/s00221-017-4918-3
Children and adults both learn motor sequences quickly, but do so differently. Du, Y., Valentini, N. C., Kim, M. J., Whitall, J., & Clark, J. E. (2017). Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.00158
New insights into statistical learning and chunk learning in implicit sequence acquisition. Du, Y., & Clark, J. E. (2016). Psychonomic Bulletin & Review, 1–9. https://doi.org/10.3758/s13423-016-1193-4
Probabilistic motor sequence yields greater offline and less online learning than fixed sequence. Du, Y., Prashad, S., Schoenbrun, I., & Clark, J. E. (2016). Frontiers in Human Neuroscience, 10. https://doi.org/10.3389/fnhum.2016.00087
A clinically relevant method of analyzing continuous change in robotic upper extremity chronic stroke rehabilitation. Massie, C. L., Du, Y., Conroy, S. S., Krebs, H. I., Wittenberg, G. F., Bever, C. T., & Whitall, J. (2016). Neurorehabilitation and Neural Repair, 30, 703–712. https://doi.org/10.1177/1545968315620301