Visualizing and quantifying EEG complexity on the base of ordinal pattern distributions

Ordinal time series analysis which is based on analyzing distributions of ordinal patterns is a new promising approach to the exploration of long and complex time series. This paper reviews applications of this approach to EEG analysis and discusses and illustrates some ideas for visualizing and quantifying EEG complexity. Moreover, the central concept of permutation entropy is considered from the modeling viewpoint.