This lecture covers the concepts of node degree and strength in network neuroscience, focusing on brain connectomics, measures of node connectivity, Erdős-Rényi graphs, degree distribution, real networks, scale-free networks, the Barabàsi-Albert model, and weight distribution in the brain. It discusses the construction of random networks, the difference between random and real networks, and the challenges of fitting power laws to real data.