Inferring and Characterizing Neuronal Connectivity with Deep Geometry and Topology

Explore innovative methods for decoding neural connectivity rules in embryonic development through a 50-minute lecture by Yale University's Smita Krishaswamy. Delve into the application of deep geometry and topology to analyze the C. elegans nerve ring, focusing on diffusion condensation and persistent homology techniques. Discover how these approaches reveal the adaptation of nervous system architecture during allometric growth. Learn about the RITINI deep learning technique for inferring neuronal networks using graph ODEs. Gain insights into the hypothesis that persistent area contacts between neurons precede stable chemical synapse formation in developing neural circuits.