Department of Psychology and Cognitive Sciences · THU Minds Club · Academic Lecture
Cracking the Neurocomputational Mechanisms of Flexible (Social) Behaviour in Health and Disease
TIME: 2025-03-17, 14:00
LOCATION: Lv Dalong Building 1100
SPEAKER: Lei Zhang
INVITRT: Zhen Wu
Speaker Profile:
ZHANG-Lei is an associate professor at the School of Psychology, University of Birmingham, UK. He graduated from the School of Psychology (now the Department of Psychology) at Beijing Normal University in 2011, obtained a master's degree from the Basque Institute of Cognition, Language, and Brain in Spain in 2013, and earned a PhD from the Institute of Systems Neuroscience at the Medical Center of the University of Hamburg in Germany (with highest honors; 2018). He subsequently engaged in research and teaching at the Department of Psychology, University of Vienna, Austria. His research focuses on elucidating the cognitive neural foundations of human flexibility and adaptive behavior in complex social contexts, as well as the corresponding cognitive neural deficits observed in mental disorders. He employs a combination of functional magnetic resonance imaging (fMRI) and computational modeling, particularly reinforcement learning models, to study human social decision-making, social interaction, and social learning. His work has been published in journals such as Science Advances, PLOS Biology, eLife, and Psychological Methods. He serves on the editorial boards of Communications Biology and PLOS Computational Biology, and is a reviewer for research funding agencies including the European Research Council (ERC), the UK Research and Innovation (UKRI), and the Swiss National Science Foundation (SNSF). In 2022, he received the APS Rising Star Award from the Association for Psychological Science.
Report Summary:
Flexible (learning) behaviour refers to the adaptive change of behaviour in response to changing environmental contingencies. Although flexible learning behaviour has been studied extensively in the past, very little is known about its neurocomputational mechanism. In this talk, I will first illustrate how to assess flexible learning behaviour through the lens of computational modelling, then I will showcase two studies, one (MRI study) focusing on flexible learning in a social context, and the other (behavioural study with large sample) focusing on flexible learning in individuals with autism. These studies are expected to motivate new research avenues in social neuroscience and computational psychiatry.
