The bispectrum and its relationship to phase-amplitude coupling

NeuroImage
Christopher K KovachHiroto Kawasaki

Abstract

Most biological signals are non-Gaussian, reflecting their origins in highly nonlinear physiological systems. A versatile set of techniques for studying non-Gaussian signals relies on the spectral representations of higher moments, known as polyspectra, which describe forms of cross-frequency dependence that do not arise in time-invariant Gaussian signals. The most commonly used of these employ the bispectrum. Recently, other measures of cross-frequency dependence have drawn interest in EEG literature, in particular those which address phase-amplitude coupling (PAC). Here we demonstrate a close relationship between the bispectrum and popular measures of PAC, which we relate to smoothings of the signal bispectrum, making them fundamentally bispectral estimators. Viewed this way, however, conventional PAC measures exhibit some unfavorable qualities, including poor bias properties, lack of correct symmetry and artificial constraints on the spectral range and resolution of the estimate. Moreover, information obscured by smoothing in measures of PAC, but preserved in standard bispectral estimators, may be critical for distinguishing nested oscillations from transient signal features and other non-oscillatory causes of "spurious" PAC...Continue Reading

Citations

Dec 6, 2018·Journal of Neurophysiology·A SheremetA P Maurer
Jun 13, 2019·Journal of Neural Engineering·Stefania CoelliAnna Maria Bianchi
Jan 22, 2019·Frontiers in Systems Neuroscience·Alex SheremetAndrew P Maurer
Dec 29, 2020·Journal of Neuroscience Methods·Coen S Zandvoort, Guido Nolte
Aug 17, 2021·Journal of Neural Engineering·Kyle Q LepageSujith Vijayan

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