Current advisor: ShiNung Ching, PhD
Undergraduate university: Peking University, 2021
Enrollment year: 2021
Statistical, dynamical and theoretical modeling of human brain activity at rest and during cognitive control
I am interested in human brain dynamics and how they support cognitive control functions (inhibitory control, attention, working memory, etc.). I approach these questions using neuroimaging data analysis and computational modeling.
Currently I am collaborating with Michael Freund and Dr. Todd Braver to investigate the test-retest reliability of the neural correlates of cognitive control effects with hierarchical Bayesian modeling. We found that fMRI multivariate pattern analysis generated much more robust cognitive control index than traditional univariate methods, which may provide an explanation and solution to the reproducible crisis in the current literature. We plan to publish the results soon.
Under the supervision of Dr. ShiNung Ching and Dr. Todd Braver, I am now developing a functional brain model to investigate the computational mechanisms and individual differences of brain dynamics in cognitive control. We expect this model to provide unique insights into the relationship between intrinsic brain dynamics and task-evoked computation, and guide translational studies such as brain stimulation therapies.
Besides, I collaborated with Ty Easley and Dr. Janine Bijsterbosch in a project to predict subject’s fluid intelligence and neuroticism from resting state fMRI network connectivity. I found that “pseudo-resting state” signal extracted from task fMRI contained shared information about these individual traits with “real” resting state fMRI signal. Along with other techniques, including “pseudo-resting state” data significantly improved the prediction of intelligence and neuroticism. Our result was published on bioRxiv and is now under peer review.