Guorong (Rudy) Wu, U North Carolina
YouTube Stream: https://youtube.com/live/BEMWNkw4M-o
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Abstract:
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 for advanced learning-enabled intelligence by addressing fundamental questions of neural information representation and mechanisms of cognition.
Bio:
Dr. Guorong (Rudy) Wu is an Associate Professor in the Department of Psychiatry at the University of North Carolina at Chapel Hill, where he also holds appointments in the Departments of Computer Science, Statistics and Operations Research, and the UNC Neuroscience Center. He earned his PhD in Computer Science from Shanghai Jiao Tong University in 2007. Dr. Wu's interdisciplinary research program focuses on biomedical image analysis, machine learning, and computational neuroscience. Supported by multiple National Institutes of Health (NIH) grants, his laboratory develops cutting-edge computational tools and mathematical frameworks to discover biomarkers and tracking neurodegeneration trajectories in Alzheimer's disease and other neurodegenerative and neurodevelopmental disorders.