Information-based modeling of event-related brain dynamics.

By Julie Anne Onton, Scott Makeig. Progress in Brain Research, 2006

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Imaging human EEG dynamics using independent component analysis. (2006, neutral): “5, Onton and Makeig, 2006).”
CLASSIFICATION OF SCHIZOPHRENIA AND BIPOLAR PATIENTS USING STATIC AND DYNAMIC RESTING-STATE FMRI BRAIN CONNECTIVITY (2016, background): “Static FNC analysis overlooks the fact that individual subjects are likely to engage in slightly different mental activities at different instances in time (Arieli et al., 1996; Makeig et al., 2004; Onton and Makeig, 2006).”
The Harvard Automated Processing Pipeline for Electroencephalography (HAPPE): Standardized Processing Software for Developmental and High-Artifact Data (2018, background): “It should be noted, though, that the PCA approach introduces nonlinearities into the data (a slight corruption of the signal), and through selecting a PCA component subset, some amount of brain-origin signal is discarded with the rejected components (Onton and Makeig, 2006).”
Decoding the tradeoff between encoding and retrieval to predict memory for overlapping events (2018, positive): “We used an automatic artifact correction algorithm based on (Nolan et al., 2010) using Independent Components Analysis (ICA; Bell and Sejnowski, 1995; Onton and Makeig, 2006) to detect and correct for eye blinks and saccades.”