» Current Research

+ - Driving Simulator Project

Researcher monitoring activity of a subject utilizing the Driving Simulator.

We have created a driving simulator with 3DoF (pitch, roll, yaw), and integrated it with Virtual Reality Headset (Oculus CV1). Simulators are useful tools with which we can set up an experiment with less noise and hazard, in the case of driving. We aim to use this driving simulator in various experiments such as moral dilemma, microdose, and more. We are planning to integrate the driving simulator with electroencephalogram (EEG) and motion capture system to further its usage.

+ - E-Bike Project

E-bike with pedal assist compared to passive commuting via car or public transit. While the health benefits of standard bicycles are well known they have not been established to the same degree for e-bikes.

+ - Free Will Survey

Our survey project investigates two commonalities of experiments in the neuroscience of free will. First, the actions undertaken in these experiments are devoid of both consequences and meaning/reasoning. Second, the experiments often conflate freedom and free will. It is unclear how much these constructs overlap in the lay-perspective. Using Qualtrics and MTurk, we conduct an experimental philosophy study to answer these questions.

+ - Human random sequence generation

While it is known that humans are generally bad at creating random sequences, our project on human random sequence generation looks at the question of when humans can learn to be more random. We ask participants to generate sequences of rock, paper and scissors in neutral, and competitive situations, with different levels of awareness of the competition, and assess any corresponding changes in randomness. We are interested in determining how random people can act, to observe a theoretical upper bound of how freely people do in fact act when faced with clearly defined choices and decision criteria.

+ - Metacognition in Deliberate and Arbitrary choices

This project explores how the timing of people’s judgment of their own actions and intentions change across types of decisions. Based on Libet’s work in 1983 and 1985, we aim to explore whether neural activities can be decoded and used to predict when people make deliberate choices (such as choosing between appealing and unappealing drinks), as well as which choice will be made.

+ - Neurofeedback

Researcher and subject monitoring EEG results on a computer screen.

Our neurofeedback project teaches participants to self-regulate their brain activity from sad or neutral states to happy states. This involves recording brain activity while participants are in these various moods and teaching a machine learning algorithm to distinguish the moods in real time. The ultimate goals of this study are 1) to validate personalized EEG neurofeedback as a treatment for depression; and 2) to identify brain regions as potential targets for Deep Brain Stimulation, an option for treatment-resistant depression.

+ - Self-Driving Vehicle Survey

We are using a 3D reconstruction of the environment recognized by sensors of a self-driving vehicle (SDV) in real life driving. The arrival of self-driving vehicle technology is inevitable, but it is questionable how people will react and interact with the new technology. We address this question by showing the clips of this video to examine how people perceive SDVs and if their perceptions change after watching the video.

+ - TMS Agency Project

Research subject in chair with TMS wand near head.

We are in collaboration with Caltech to use Transcranial Magnetic Stimulation (TMS) to investigate the sense of agency - the sense of ownership or authorship of our actions. TMS is used to artificially activate cortical regions of the brain, and when it is applied to motor cortex participants will move their arms, legs, or other muscles involuntarily. Wittgenstein famously asked “what is left over if I subtract the fact that my arm goes up from that fact that I raise my arm?” We aim to answer this interesting question.