I am Yaxin (pronounced as Yak-sin). I am currently a postdoc fellow in the Bach Lab at the University of Bonn, where I study perception-action in virtual reality. I did my PhD in cognition and development in the Lourenco Lab at Emory University.
My research focuses broadly on the perceptual basis and decision-making of spatial cognition.
PhD in Psychology, 2023
BSc in Psychology & Cognitive Science, 2017
University of Toronto
Affective factors such as anxiety, confidence, and motivation can impair and enhance task performance. Here, we used drift diffusion modeling (DDM) to examine how these variables affect visualization, manipulation, and decision making on a mental rotation task (MRT). The effects of affective factors on visuospatial reasoning are largely unknown, perhaps in part because analyses are generally concerned with overall accuracy and reaction time (RT), without decomposing the stages of processing. With DDM, we decompose performance on a MRT into separate processing components, particularly the speed of information update (drift rate) and the amount of evidence accumulation (decision threshold). 106 adult participants performed a two-alternative forced-choice (2- AFC) MRT, and throughout, they rated their levels of anxiety, confidence, and motivation. We found that although anxiety, confidence, and motivation all impacted drift rate, only confidence affected the decision threshold. Moreover, we observed a unique role for confidence in mediating the links between gender and model parameters, as well as a unique moderating role of motivation in this mediation. Altogether, these findings shed light on the interrelations between affective factors in accounting for mental rotation performance in men and women, including the unique combination of confidence and motivation in explaining the gender difference in mental rotation performance.
Apparent motion is a robust perceptual phenomenon in which observers perceive a stimulus traversing the vacant visual space between two flashed stimuli. Although it is known that the “filling-in” of appa- rent motion favors the simplest and most economical path, the interpolative computations remain poorly understood. Here, we tested whether the perception of apparent motion is best characterized by Newtonian physics or kinematic geometry. Participants completed a target detection task while Pacmen- shaped objects were presented in succession to create the perception of apparent motion. We found that target detection was impaired when apparent motion, as predicted by kinematic geometry, not Newtonian physics, obstructed the target’s location. Our findings shed light on the computations employed by the visual system, suggesting specifically that the “filling-in” perception of apparent motion may be dominated by kinematic geometry, not Newtonian physics.
Instructor of Record
Scholarly Inquiry and Research (Fall 2022)
Sex and Cognition (Summer 2022)
Probability and Statistics (Fall 2021)
Laboratory in Experimental Methods (Spring 2019, Spring 2022)
Statistics with SPSS (Spring 2021)
Cognitive Development (Fall 2020)
Introduction to Psychobiology and Cognition (Fall 2018, 2019)
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