Recording
Speaker
Shen Xu
Bio
Shen Xu is a third-year Ph.D. student from the School of Psychological and Cognitive Sciences at Peking University. He studies Basic Psychology under the supervision of Professor Dr. Xiaolin Zhou, and he is mainly keen on millisecond tactile information integration and computational social cognition. For the former, Shen focuses on how different tactile information is integrated and its temporal dynamics in the human brain. For the latter, he focuses on the computational and neural mechanisms of advantageous and disadvantageous unfair decision-making in Parkinson’s patients.
Abstract
In recent years, the use of high-precision computational models in social science, cognitive science, and affective neuroscience has increased dramatically. These models can be matched with empirical data to facilitate quantitative studies of the cognitive neural mechanisms underlying behavior. Yet most psychological researchers lack hands-on experience with computational modeling. In this tutorial, I will talk about decision-making tasks in social learning, and data-fitting using hierarchical Bayesian reinforcement learning (hBRL) models within a more comprehensive computational modeling framework. We collected behavioral data from 82 participants using the classic four-armed bandit task and explored the cognitive effects associated with each model parameter. Our tutorial provides more detailed theoretical and practical guidance to help novices to implement their own computational models and avoid common pitfalls.