Chapter 7

Application of the change-point analysis to the investigation of the brain's electrical activity

A.Ya.Kaplan, S.L.Shishkin

This chapter is devoted to one of the most interesting applications of non-parametric statistical diagnosis, namely, to the analysis of the human brain's electrical activity (the electroencephalogram, or EEG). The meaning and the features of the EEG, as well as the problems arising from the high non-stationarity of the EEG signal, are reviewed. We present experimental results demonstrating the application of the statistical diagnosis methods described in this book to the EEG, and discuss the prospects for further development of the change-point detection methodology with the emphasis on the estimation of coupling between different signal channels.

7.1 Introduction
7.2 General description of the approaches to quantitative feature extraction from an EEG signal
7.3 Non-stationarities in EEG. Methods of segmentations of the EEG signal 7.3.1 Segmentation of the EEG using fixed intervals
7.3.2 Parametric segmentation of the EEG
7.3.3 Nonparametric approaches to the description of piecewise stationary structure of EEG 7.4 Experimental results 7.4.1 Change-point detection algorithm performance with real EEG data
7.4.2 Change-points in EEG components with different pattern
7.4.3 Detection of change-points at different levels of the hierarchy of EEG segmental descriptions
7.4.4 Change-points in multi-channel EEG
7.4.5 The approach to the analysis of change-point synchronization in multi-channel EEG
7.4.6 Change-point synchronization in pairs of EEG channels
7.4.7 Multichannel analysis of spatial synchronization of the change-points 7.5 Some general theoretical considerations 7.5.1 Unsolved problems and new prospects
7.5.2 Change-point based analysis of the synchronization between signals or signal components 7.6 Other prospects of the change-point based analysis
7.7 Conclusion
Bibliography

This book chapter (final draft, adapted for web) is published at MSU Brain Research Group web site with permission of Kluwer Academic Publishers.