et al., 2004), maximum likelihood estimation (Jaskowski and Verleger, 1999), parametric modeling (von Spreckelsen and Bromm, 1988), multivariate matching pursuit algorithms (Sieluzycki et al., 2009), general linear model analyses (Pernet et al., 2011), and decomposing data using ICA (Jung et al., 2001). ICA provides an elegant solution to the problems associated with spatial mixing of EEG, and facilitates analysis of single-trials by decomposing EEG data into separate informational components of brain dynamics that closely reflect activity associated with specific cognitive or sensory processes, thus removing the need for time-locked averaging (e.g., see Jung et al., 2001).
