Dear Students,
this week we apply the notions of 'noisy neurons' and 'stochasticity' to the question of how to extract parameters of neuron models from data.
The lecture covers a modern and elegant approach of parameter estimation in the context of Generalized Linear Models that is used in many neuroscience labs world wide. At the same time, you can also view the lecture as a review of material that we have seen before: single-neuron models, phase planes, stochasticity, interval distributions, point processes.
I hope you will enjoy this series of lectures,
Wulfram Gerstner
