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This lecture covers the concepts of centrality and hubs in network neuroscience, exploring the three cardinal axes of centrality: degree, betweenness, and closeness. It delves into the importance of eigenvectors, clustering coefficients, small-world networks, and network failures. The instructor discusses the significance of hubs in the brain's structural connectome, the connectedness of networks, and the emergence of the giant component in random graphs. Percolation theory and its application in brain networks are also addressed, highlighting the movement and filtering of fluids through porous materials.