The Yau Lab at the Baylor College of Medicine aims to identify perceptual and neural processing principles that unify the senses and characterize the complex interactions between the sensory systems.
My research aims to understand how the brain uses sensory context to shape the flexible perceptual outcomes that we experience in the world. We use human time perception as a system for understanding how the brain flexibly interprets sensory stimuli. In a duration discrimination task, we describe novel ways in which attractive and repulsive interactions occur in multisensory time perception.
Furthermore, we develop a Conditioned Bayesian Interaction (CBI) model that provides a new theoretical framework for understanding the computations that yield a flexible range of perceptual outcomes. Critically, our model conditions perceptual outcomes on an initial decision to bind or separate cues. We validate our model experimentally by showing that increased sensory uncertainty shifts repulsive biases toward attraction. Our findings provide a general framework that governs flexible multisensory interactions, explain human perception quantitatively in a series of empirical studies, and predict conditions under which the same sensory inputs can be interpreted differentially.
I recently defended my undergraduate thesis “Multisensory Context Warps Time Perception” as a part of the Rice Undergraduate Scholars Program. A manuscript is in preparation.
- RURS 2015, 2016: Rice Undergraduate Research Symposium, Houston, TX.
- Society for Neuroscience 2016: San Diego, CA. | [Poster]
- International Multisensory Research Forum, 2017: Vanderbilt University, Nashville, TN. | [Poster]
- Cognitive Computational Neuroscience 2017: Columbia University, New York City, NY. | [Poster] [Conference Paper]
I spent Summer 2016 learning Bayesian computational methods under Dr. Mehrdad Jazayeri at MIT as a Center for Sensorimotor Neural Engineering (CSNE) NSF-REU Fellow. The Jaz Lab studies timing in neural dynamics and human behavior.
My research focused on the understanding how timing represented in memory and how that representation aids sensorimotor tasks. Using human psychophysics and computational modeling, we derived a Bayesian inference model to explain how the memory recall and inference processes contribute to the variability underlying motor responses in a simple interval production task.
- Center for Sensorimotor Neural Engineering REU Symposium 2016: University of Washington, Seattle, WA. |[Poster]
I spent Summer 2017 learning to record from neurons under Dr. Joshua Dudman at Janelia Research Campus as a Janelia Undergraduate Scholar. The DudLab studies the neural circuits underlying purposive actions in the basal ganglia.
My research probed the neural representations underlying action choice in the dorsal striatum. Previous work has argued that the striatum encodes action value–that is, a combination of action choice and reward magnitude. However, because movement vigor correlates tightly with action value, we have reason to suspect that striatum might encode action kinematics. By simultaneously recording from the motor cortex and striatum of mice performing a free-choice reaching task, we seek to understand how action selection is carried out in the neural signatures of cortical and striatal neurons.
- Janelia Undergraduate Scholar Symposium 2017: Janelia Research Campus, Ashburn, VA. |[Poster]