Professor Guorong Wu from the University of North Carolina at Chapel Hill was specially invited to give an academic report

Report title: Adaptive Sensorimotor Intelligence Through Cortical Oscillatory Synchrony (Adaptive Sensorimotor Intelligence Through Cortical Oscillatory Synchrony)

Speaker: Professor Guorong Wu

Unit: University of North Carolina at Chapel Hill, USA

Reporting time: July 15, 2026 9:00-11:00

Zoom meeting number: 968 3766 1980 Password: 412314

Moderator: Xu Jun, Nanjing University of Information Science & Technology

Report Summary

Human cognition arises from coordinated spiking dynamics in distributed cortical columns, where perceptual representations are shaped by experience-dependent plasticity in the vertical connections across cortical layers. Inspired by this notion, our central premise is a two-layer computational model of sensorimotor learning: upper-layer neurons encode sensory input while indexing a spatial reference frame anchored in the lower layer. Upon movement, the lower layer transitions to a new location, generating a prediction of the next sensory input in the upper layer. To that end, we develop a brain-inspired learning primitive in which cognition-level neural synchrony emerges through iterative bottom-up and top-down interactions between micro-scale dynamics of spiking neurons and a macro-scale mechanism of oscillatory synchronization. This research opens a new window into advanced learning-enabled intelligence by addressing fundamental questions about neural information representation and the mechanisms of cognition.

Human cognition arises from coordinated neuronal spike firing dynamics among distributed cortical columns, where perceptual representations are shaped by experience-dependent plasticity in vertical connections across cortical hierarchies. Inspired by this point of view, we propose a two-layer computational model of sensory-motor learning: while encoding sensory input, the upper layer neurons index the spatial reference frame anchored by the lower layer; when movement occurs, the lower layer will migrate to a new spatial position and generate a prediction of the upper layer’s sensory input at the next moment accordingly. To this end, we construct a brain-inspired learning primitive in which neural synchronization at the cognitive level emerges through iterative bottom-up and top-down interactions between the microscale dynamics of spiking neurons and the macroscopic mechanisms of oscillatory synchronization. This research opens up a new research window towards more advanced learning-empowered intelligence by exploring basic issues of neural information representation and the mechanism of cognitive formation.

Brief introduction of the reporter

Professor Guorong Wu currently works at the University of North Carolina at Chapel Hill, USA. He received a PhD in computer science and engineering from Shanghai Jiao Tong University in 2006 and has been engaged in research on medical image analysis and machine learning for a long time. Its research focuses on using advanced computational models and data-driven methods to understand human brain mechanisms and discover highly sensitive and specific biomarkers for neurological diseases such as Alzheimer’s disease. He has published more than 360 papers in top international journals and conferences such as Nature Communications, PNAS, IEEE PAMI, IEEE TMI, NeurIPS, ICML, ICLR, and AAAI. He is also actively involved in international academic services and serves as/has served as an editor, editorial board member or review expert for international journals such as IEEE TMI. In addition, Professor Wu is cooperating with top international scholars such as Professor Pohl from Stanford University and Professor Prince from Johns Hopkins University to jointly organize a special summer camp on life sciences and health technology (AI4Science) with the theme of “Application of Autonomous Multimodal Agents in Medical Imaging”. This summer camp will focus on intelligent analysis of medical images, multi-modal large models, autonomous agents and their cutting-edge applications in the field of life and health. Students in related fields are sincerely welcome to consult and participate.

Translated from the original Chinese source.