Bicoherence of intracranial EEG in sleep, wakefulness and seizures

The hypothesis that the intracranial EEG has local structure and short-term non-stationarity is tested with a little-studied measure of non-linear phase coupling, the bicoherence in human subdural and deep temporal lobe probe data from 11 subjects during sleeping, waking and seizure states. This measure of cooperativity estimates the proportion of energy in every possible pair of frequency components, F1, F2 (from 1 to 50 Hz in this study), that satisfies the definition of quadratic phase coupling (phase of component at F3, which is F1 + F2, equals phase of F1 + phase of F2). Derived from the bispectrum, which segregates the non-Gaussian energy, auto-bicoherence uses the frequency components in one channel; cross-bicoherence uses one channel for F1 and F2 and another for F3. These higher order spectra are used in physical systems for detection of episodes of non-linearity and transients, for pattern recognition and robust classification, relatively immune to Gaussian components and low signal to noise ratios. Bicoherence is found not to be a fixed character of the EEG but quite local and unstable, in agreement with the hypothesis. Bicoherence can be quite different in adjacent segments as brief as 1.6 s as well as adjacent intracranial electrodes as close as 6.5 mm, even when the EEG looks similar. It can rise or fall steeply within millimeters. It is virtually absent in many analysis epochs of 17s duration. Other epochs show significant bicoherence with diverse form and distribution over the bifrequency plane. Isolated peaks, periodic peaks or rounded mountain ranges are either widely scattered or confined to one or a few parts of the plane. Bicoherence is generally an invisible feature: one cannot usually recognize the responsible form of non-linearity or any obvious correlate in the raw EEG. During stage II/III sleep overall mean bicoherence is generally higher than in the waking state. During seizures the diverse EEG patterns average a significant elevation in bicoherence but have a wide variance. Maximum bispectrum, maximum power spectrum, maximum and mean bicoherence, skewness and asymmetry all vary independently of each other. Cross-bicoherence is often intermediate between the two auto-bicoherence spectra but commonly resembles one of the two. Of the known factors that contribute to bicoherence, transient as distinct from ongoing wave forms can be more important in our data sets. This measure of non-linear higher moments is very sensitive to weak quadratic phase coupling; this can come from several kinds of waveforms. New methods are needed to evaluate their respective contributions. Utility of this descriptor cannot be claimed before more carefully defined and repeatable brain states are studied.