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This lecture by the instructor covers the dynamics of neuronal populations in computational neuroscience, focusing on random networks. Topics include balanced states, mean-field arguments for random connectivity, and simulations of model networks. The lecture also discusses integrate-and-fire neurons, connectivity schemes, and the prediction of population activity. References to classic studies and modeling approaches in neuronal populations are provided.