My research aims to better understand subjective perceptual experience
As a Post-Doctoral Researcher at the University of California-Los Angeles, and as a visiting researcher at the
Advanced Telecommunications Research Institute Interational (ATR) in Kyoto, Japan, my research focuses on
using an array of techniques to better understand the neural and computational processes underlying how we
perceive the world around us. To that end, I have conducted studies using behavior measures, psychophysics,
computational modeling, machine learning, and neurophysiology. Over the last several years,
my research interests have centered on a few main themes, described below.
Decoding Perceptual Confidence from Different Brain Areas
You can read about our most recent results from a study on the superior colliculus
We will be presenting additional experiments on perceptual confidence in 2018.
Investigating the Role of Prefrontal Cortex in Conscious Perception
Does the activity of prefrontal cortex (PFC) facilitate subjective perceptual experience? This interesting question has
re-emerged in the literature in recent years, and holds promise to arbitrate among several theories about consciousness.
Recently, together with
Dr. Robert T. Knight and my post-doc advisor, Hakwan Lau, I published
a debate piece, arguing that PFC activity plays a critical role in facilitating conscious experience.
You can read a dissenting viewpoint from Boly et al.
Recently, I have launched experiments to probe this question empirically,
and I will be presenting this work at conferences starting in late 2017, continuing through 2018.
Multisensory Integration: Insights from Computational Modeling
At any given moment, as we look out at our surrounding environment, we are bombarded by an array of sensory inforation from
our eyes, ears, nose, and other sensory orgrans, and our brains must integrate this information to form a coherent whole.
My published graduate work focused on applying
this Bayesian modeling framework with
these additional methods to use it as a tool to better understand certain principles underlying multisensory processing.
For example, previous work using this model indicates that how we perceive our multisensory world is based on not only
the reliability of unisensory encoding, but also upon a Bayesian prior which influences the tendency to integrate our senses
(what we call the "binding tendency"). Part of my work aimed to answer questions about characteristics of this prior:
Is this prior stable across time? Does it generalize across tasks?
Psychological Science, 2016
Evidence indicates the answers are "yes," and "no," respectively
Can this prior change with sensory experience?
Yes. In a spatial task, it increases when repeated presentation of spatially discrepant, temporally related
Does this prior correlate with sensory abnormalities in the general population which are related to schizophrenia?
Clinical Psychological Science, 2017,
Supplemental Material Hmmm. Possibly? Some data from the spatial task in this paper is worthy of a raised eyebrow and a
replication effort, to see if there's further evidence to support this hypothesis.
Other aspects of this work focused on how attention influences computational elements in this framework, and how to account
for interesting biases that seem to be present in spatial localization data.
How does attention influence multisensory perception in this framework in spatial and temporal tasks?
Neuroscience Letters, 2017,
Supplemental Material Primarily by influencing the precision in sensory representations, not by changing priors.
Spatial localization behavior shows interesting biases. How can this framework account for this?
PLOS Computational Biology, 2015
Model comparisons in this paper provide an answer.
Over five years as a Ph.D. student at UCLA, I had the privilege of working as a teaching assistant, teaching fellow,
and instructor for many courses in the psychology department. Working with such diverse, enthusiastic, capable students
every day was one of the top highlights and joys of my graduate career. My didactic pursuits included the following
Introduction to Research Methods
Fundamentals of Behavioral Neuroscience
Behavioral Neuroscience Laboratory Course
Introduction to Psychobiology
Sensation & Perception
Interdisciplinary Programs ("Cluster" Courses)
Moreover, during my final two years in the Ph.D. program, I had a chance to work in a new, year-long
neuroscience cluster course for incoming freshmen students, which aimed to teach students about the human
mind from historical, philosophical, and neuroscientific perspectives. All teaching fellows in this course
held study sections, developed and administered neuroscientific laboratory exercises, and created assessments
to test students on their critical thinking, quantitative, and reasoning skills in relation to course material.
You can read more about this course, which was featured in a press release by UCLA,
My colleagues and I also wrote an article about this course's content and student outcomes, for other
universities looking to establish similar interdisciplinary programs, which can be found
Finally, as part of my work in the Cluster Course, I developed a new seminar called, "Sex, Drugs, and Rock & Roll:
How Romance, Psychoactive Substances, and Music Change the Brain." Beyond the catchy name, though, the course
focused on helping students develop a skeptical, critical eye for evaluating neuroscientific evidence for interesting
mental phenomena, all while cultivating general skills through writing exercises, in-class debates, and discussions with
experts on each topic. I tailored course material for students from different backgrounds and interests; a typical unit
would begin by exposing students to ideas and anecdotal stories relevant for certain topics, such as content from the following:
Radio programs like This American Life (e.g., the episode on
testosterone and the episode on
love), as well as RadioLab
Videos of informative (and inspiring) patients, such as
After "warming up" with this content to cultivate interest and ideas, students then read scientific articles
and heard talks by faculty and post-docs doing research in these areas to learn how knowledge is actually built from
studies on these topics. Students also engaged in discussions with each speaker to ask for their opinions and insight
on recent scientific papers, as well as how unanswered questions in each field could be addressed by new experiments.
My syllabus for this seminar can be found
and my reading list for the seminar can be found
During my time in two different labs at UCLA, I've been able to mentor 27 fantastic students and volunteers as
they worked on various projects. It was (and is) amazing getting to work with such motivated, responsible,
intelligent people on a daily basis. I'm proud to say that many of them are continuing to pursue academia or
medicine after their undergraduate careers, including the following:
Eden Sayed, Harvard University, Joint Ph.D. Program in Neuroscience & Philosophy
Jason Carpenter, University of San Francisco, M.S. in Analytics Program, USF Data Institute
Fangfang Hong, NYU, Ph.D. Program in Psychology (Supervisor: Michael Landy)
Yasamine Bolourian, UC-Riverside, Ph.D. Program, Dept. of Education
Musen Li, Tsinghua University, China, Ph.D. Program, Department of Industrial Engineering
Seong Hah Cho, Hong Kong University, Ph.D. Program, Department of Psychology
Sanne Kellij, Vrije Universiteit Amsterdam (VU), Research Masters in Cognitive Neuropsychology
Andrew Marin, UCLA, Research Coordinator, Jeste EEG Lab, UCLA Center for Autism Research and Treatment
Yechan Lew, UCLA, Research Coordinator, Lau and Kaiser Labs
Sivananda Rajananda, UCLA, Research Associate
Shannon Gordon, Concordia University, RN Program
Sy Clark, UC-Davis, MD Program
Rahul Iyengar, University of Miami (FL), MD Program
Jing Liu, Zhejiang University (China),MD Program
In addition to these former colleagues now in academia, it's been great seeing what other former lab volunteers
have accomplished in industry and other areas outside the university setting. Many thanks to everyone listed below!
The research we've done over the years would not have been possible without your contributions and hard work.