Distinguished Lectures in Humanities: Neuroscience in the Wild: The Neurocognitive Computation of Naturalistic Conversation

Abstract

The human brain is a hierarchical prediction system capable of processing complex social and linguistic information in everyday life. However, little is known about how we infer others' semantic meaning and communicative intentions during naturalistic conversation, and how we utilize such inferences to facilitate teaching and learning in the real classroom. Our results revealed an active inference process to generate candidate utterances and then select the optimal one by integrating pragmatic predictions with prediction errors, thereby enhancing the activation of the target utterance. Hyperscanning data supported this model, revealing a hierarchical neural architecture processing both predictions about the partner and prediction errors. Furthermore, we demonstrated how this social interaction mechanism supports observational learning in children at home and facilitates knowledge construction among students in the real classroom.

About the speaker

Chunming LU is a Professor and Principal Investigator at the State Key Laboratory of Cognitive Neuroscience and Learning and the IDG/McGovern Institute for Brain Research, Beijing Normal University. His research focuses on the neurocognitive mechanisms of social interaction and language communication in naturalistic contexts. His group has developed state-of-the-art approaches to study real-time social interaction in naturalistic settings, proposed original theoretical models to understand these interactions, and conducted pioneering work in the field of educational neuroscience. He has published over 70 papers in journals such as Nature Communications, PNAS, Advanced Science, and Psychological Science. His research is supported by multiple research grants, including the Major Program of the National Natural Science Foundation of China (NSFC) and NSFC for Excellent Young Scholars.