Informational and Topological Signatures of Individuality in Network Neuroscience

Explore cutting-edge research in network neuroscience through this 45-minute lecture presented by Giovanni Petri of Northeastern University at IPAM's Mathematical Approaches for Connectome Analysis Workshop. Delve into the limitations of Functional Connectivity (FC) in understanding brain function and discover how topological data analysis tools can provide deeper insights. Learn about the application of algebraic-topological features extracted from resting fMRI data to improve brain fingerprinting and age discrimination. Examine the effectiveness of persistent homology and topological scaffolds in outperforming traditional FC methods for individual identification across different recording sessions. Investigate the characteristic patterns of information redundancy and synergy in topologically important brain regions, establishing a novel connection between topology and information theory in neuroscience. Gain valuable knowledge about advanced mathematical approaches for analyzing brain connectivity and their potential implications for understanding individual differences in brain function.