Neural Correlates of Emotion as an Arbitrator to Reconcile the Conflicts within Dual Processing in the Context of Decision Making under Risk

We are performing behavioral and fMRI experiments to probe the role of emotion when people face a dual‑process induced cognitive conflict under a risky condition. I am currently engaged in the analysis of fMRI data. I am also involved in developing an estimation method for the parameters in the utility function.

Analysis of Cognitive Structures Underlying Financial Behavior

project grew out of an industry-academia collaboration with Alliance Bernstein. For this project, we investigated possible factors that caused biases in investment and finance. To this end, we used a survey to collect data on biases in financial behaviors. I applied exploratory factor analysis to uncover the latent structure/factors of financial biases, aiming to design a game in which the subjects’ behaviors in the game will be related to the factors.

From Mind Reading to Mind Sharing: A Study on Neural Correlates of Cognitive and Affective Theory of Mind and Their Applications to Salesforce Enhancement

This project aimed to explore the underlying mechanisms of the theory of mind in gambling. For this project, we used magnetoencephalography (MEG) to measure the changing processes in gambling and model possible strategies formed in participants’ brains.

Coalition without Trust: The Intra‑Brain Connectivity and Inter‑Brain Synchronization of Herd Behaviors in an Economic Bubble Game

This project aimed to explore humans’ decision processes in stock markets. For that project, we simulated a stock market and asked subjects to compete (recorded using hyperscanning fMRI). The goal was to construct a computational model to explain the behavioral and neural data of participants. In the project, I analyzed the behavioral and fMRI data. Because subjects might apply different strategies in the game, I used the k-mean clustering method to group subjects to figure out different response patterns.