Centrality and Hubs

This lecture covers the concepts of centrality and hubs in network neuroscience, focusing on the three cardinal axes of centrality: degree, betweenness, and closeness. It explores the importance of nodes in network function, the small-world network phenomenon, and the structural connectome of the brain. The instructor discusses network failures, clustering coefficients, and percolation theory in brain networks, emphasizing the emergence of the giant component. Various centrality measures such as eigenvector centrality and PageRank are explained, along with examples of disconnected nodes and phase transitions in random graphs.