Decomposing the alpha rhythms: comparative performance evaluation of parametric bispectral algorithms for EEG

Abstract

The alpha wave is often harmonically related or coupled to frequencies in other EEG bands. Several autoregressive and eigenstructure-based bispectral algorithms have proven to be effective in the detection and estimation of alpha coupling. The authors extend the triple Kronecker product method of Swindlehurst and Kailath (1989) to estimation of biphases through a generalized eigenvalue approach. As a major concentration of significant bispectral peaks lie in the alpha-alpha coupling region, low model order can be used for accurate results with these methods.<>