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This lecture covers the measurement of brain node connectivity, focusing on node degree and strength in network neuroscience. It discusses brain connectomics, diffusion weighted imaging, and the Erdős-Rényi model for random networks. The lecture also delves into the Barabàsi-Albert model, power law distributions, and the weight distribution in the brain, emphasizing the complexity of real networks and the caution needed when testing for power laws.