Autoregressive and bispectral analysis techniques: EEG applications

1 March 1990

journal article
Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Engineering in Medicine and Biology Magazine

Vol. 9 (1) , 47-50
https://doi.org/10.1109/51.62905

Abstract

Some basic properties of autoregressive (AR) modeling and bispectral analysis are reviewed, and examples of their application in electroencephalography (EEG) research are provided. A second-order AR model was used to score cortical EEGs in order. In tests performed on five adult rats to distinguish between different vigilance states such a quiet-waking (QW), rapid-eye-movement (REM), and slow-wave sleep (SWS), SWS activity was correctly identified over 96% of the time, and a 95% agreement rate was achieved in recognizing the REM sleep stage. In a bispectral analysis of the rat EEG, third-order cumulant (TOC) sequences of 32 epochs belonging to the same vigilance state were estimated and then averaged. Preliminary results have shown that bispectra of hippocampal EEGs during REM Sleep exhibit significant quadratic phase couplings between frequencies in the 6-8-Hz range, associated with the theta rhythm.<>

Keywords

This publication has 8 references indexed in Scilit:

Bispectral analysis of the rat EEG during various vigilance states
IEEE Transactions on Biomedical Engineering, 1989
Bispectrum estimation: A digital signal processing framework
Proceedings of the IEEE, 1987
Piecewise analysis of EEGs using AR-modeling and clustering
Computers and Biomedical Research, 1981
Computer analysis of EEG signals with parametric models
Proceedings of the IEEE, 1981
On the stationarity and normality of the electroencephalographic data during sleep stages
Computer Programs in Biomedicine, 1978
Analysis of the interrelations between frequency bands of the EEG by means of the bispectrum a preliminary study
Electroencephalography and Clinical Neurophysiology, 1971
Bispectrum Analysis of Electroencephalogram Signals during Waking and Sleeping
Science, 1971
Statistical methods for investigating phase relations in stationary stochastic processes
IEEE Transactions on Audio and Electroacoustics, 1971