During stage II/III sleep overall mean bicoherence is generally higher than in the waking state. Bicoherence is generally an invisible feature: one cannot usually recognize the responsible form of non-linearity or any obvious correlate in the raw EEG. Isolated peaks, periodic peaks or rounded mountain ranges are either widely scattered or confined to one or a few parts of the plane. Other epochs show significant bicoherence with diverse form and distribution over the bifrequency plane. It is virtually absent in many analysis epochs of 17s duration. It can rise or fall steeply within millimeters. 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. Bicoherence is found not to be a fixed character of the EEG but quite local and unstable, in agreement with the hypothesis. 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. 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 F 1 and F 2 and another for F 3. This measure of cooperativity estimates the proportion of energy in every possible pair of frequency components, F 1, F 2 (from 1 to 50 Hz in this study), that satisfies the definition of quadratic phase coupling (phase of component at F 3, which is F 1 + F 2, equals phase of F 1 + phase of F 2). The hypothesis that the intracranial EEG has local structure and short-term non-stationarity is tested with a little-studied measure of nonlinear phase coupling, the bicoherence in human subdural and deep temporal lobe probe data from 11 subjects during sleeping, waking and seizure states. La cohérence de l'activité bêta harmonique dépend grosso modo de la qualité de l'activité fondamentale.ĭans l'analyse des bêta harmoniques ou complexes, l'analyse de bi-cohérence peut donner des informations supplémentaires. L'activité bêta de la catégorie 3 se montre non-cohérente dans la grande majorité des observations. Une cohérence significative peut être observée dans les catégories 1 et 2 où elle apparaît surtout dans les combinaisons intra-hémisphériques, tandis qu'une cohérence inter-hémisphérique significative est peu fréquente. L'application des diverses techniques de l'analyse spectrale à l'activité EEG rapide ou bêta augmente fortement la résolution des fréquences et de l'amplitude, en comparaison avec la résolution pauvre de ces phénomènes dans le domaine du temps.ĭans le domaine des fréquences, on peut distinguer entre plusieurs catégories d'activité rapide: activité bêta de bande de fréquence étroite (1), moyenne (2) et large (3) de plus, des activités bêta harmoniques (4), où les composantes spectrales bêta sont couplées de manière harmonique avec une activité de base plus lente en outre, on peut distinguer une activité bêta complexe (5), composée de deux ou plusieurs catégories spectrales, et, finalement, une catégorie non-définie (6) où l'augmentation de la puissance bêta relative manque de caractères particuliers. Coherence of harmonic beta depends largely on the features of the underlying component.īi-coherence analysis may be of help to further analysis of harmonic or complex beta activity. If observed, significant coherence occurs most frequently between antero-posterior leads in activities of types 1 and 2, whereas coherence between hemispheres is generally low Broad-band beta seems to be essentially non-coherent. In the frequency domain several different types of beta activity may be distinguished, i.e., (1) narrow (2) medium (3) broad-band beta (4) harmonic beta where the beta component shows a harmonic relationship to a lower frequency component (5) complex beta as a mixture of 2 or more of the foregoing types and (6) undefined beta, where the relative increase of beta power is the only assessable feature. This is in contrast to the generally poor resolution of fast activity in the time domain, an effect which may be compared with that of a magnifying glass applied to beta activity. Spectral analysis techniques provide high resolution of the beta frequency range and, if a logarithmic transformation is used, also of lower level intensity.
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