Removal of FMRI environment artifacts from EEG data using optimal basis sets

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Don't fear ‘fear conditioning’: Methodological considerations for the design and analysis of studies on human fear acquisition, extinction, and return of fear (2017, unknown): “For EEG/EMG/startle data (e.g. Lindner et al., 2015), imaging rtefact removal is indispensable and can be achieved through umerous methods and software (Allen et al., 1998, 2000; Garreffa t al., 2003; Mantini et al., 2007; Niazy et al., 2005; Ritter et al., 007; Ullsperger and Debener, 2010).”
Trial-by-Trial Coupling of Concurrent Electroencephalogram and Functional Magnetic Resonance Imaging Identifies the Dynamics of Performance Monitoring (2005, methodology): “0 (Niazy et al., 2005) (FMRIB EEGLAB plug-in for removal of fMRI-related artifacts, Center for functional MRI of the Brain, Oxford, UK; http://www.”
EEG correlates of time-varying BOLD functional connectivity (2013, unknown): “Gradient and ballistocardiogram artifacts in the EEG data were treated using EGI's NetStation software, which implements methods based on template subtraction (Allen et al., 2000) and principal component analysis (Niazy et al., 2005), respectively.”