Non-Gaussian modeling of EEG data

It is common when modeling EEG data to employ an assumption of normality. While this assumption usually provides a modest approximation for random variables, its use for EEG data is limited. In this paper we examine why general modeling of EEG data as normal is inadequate and provide an example of approximating various stages of a seizure with non-normal distributions.