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This lecture covers the likelihood of a spike train in computational neuroscience, focusing on generative models and log-likelihood calculations based on observed spike trains. The instructor discusses the stochastic generation of spikes and the escape rate model, emphasizing the calculation of the likelihood that an experimental spike train could have been produced by a given model.