Simplified Neuron Models: Analytical Approachability

This lecture discusses simplified neuron models and their analytical approachability, focusing on the random walk model and its implications on spiking activity. The instructor explains how random walks behave, the impact of trajectories on reaching the threshold, and the correction for decay in membrane potential. The lecture delves into the importance of understanding neural modeling, the assumptions made in Gaussian distribution approaches, and the evolution of models to explain motor neurons. Additionally, the discussion covers the concept of time average versus population average, the challenges in modeling individual neurons within a network, and the limitations of the integrated and fire neuron model in reproducing certain neural behaviors.