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).
Du, Y., Clark, J. E., & Whitall, J. (2017). Timing at peak force may be the hidden target controlled in continuation and synchronization tapping. Experimental Brain Research, 235, 1541–1554. https://doi.org/10.1007/s00221-017-4918-3
Du, Y., Valentini, N. C., Kim, M. J., Whitall, J., & Clark, J. E. (2017). Children and adults both learn motor sequences quickly, but do so differently. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.00158
Du, Y., & Clark, J. E. (2016). New insights into statistical learning and chunk learning in implicit sequence acquisition. Psychonomic Bulletin & Review, 1–9. https://doi.org/10.3758/s13423-016-1193-4
Du, Y., Prashad, S., Schoenbrun, I., & Clark, J. E. (2016). Probabilistic motor sequence yields greater offline and less online learning than fixed sequence. Frontiers in Human Neuroscience, 10. https://doi.org/10.3389/fnhum.2016.00087
Massie, C. L., Du, Y., Conroy, S. S., Krebs, H. I., Wittenberg, G. F., Bever, C. T., & Whitall, J. (2016). A clinically relevant method of analyzing continuous change in robotic upper extremity chronic stroke rehabilitation. Neurorehabilitation and Neural Repair, 30, 703–712. https://doi.org/10.1177/1545968315620301