Methods for pulse artefact reduction: Experiences with EEG data recorded at 9.4T static magnetic field

Time-frequency analysis of resting state and evoked EEG data recorded at higher magnetic fields up to 9.4T

“…For this, independent component analysis and mutual information was applied in a combined fashion and its performance was investigated with special focus on time-frequency analysis of EEG data. Based on our previous study (Arrubla et al, 2014), we introduced additional steps for the rejection workflow, which are of particular importance when EEG signals are recorded at higher magnetic field strengths. We present an artefact rejection scheme based on the combination of the following concepts: ICA transformation combined with mutual information and a component selection method based on Gaussian variates (cf.…”

“…Moreover, the averaged signals acquired at different magnetic field strengths (s 2 ) from EXP2 were compared after artefact rejection with signal recordings outside the scanner (s 1 ) using the difference parameter (d) as reported in Mantini et al (2008), Vanderperren et al (2010) and Arrubla et al (2014). The measure accounts for signal changes after artefact rejection and different field strengths and is computed using the following expression:…”

“…The combination of the two techniques is based on the notion that both measures are complementary and that the measured signals are produced by the same or closely related brain structures. The feasibility of this approach has been demonstrated in a number of studies at 3 T (Kruggel et al, 2000;Mulert et al, 2005;Thaerig et al, 2008;Mayhew et al, 2010) as well as at 7 T Brookes et al, 2009;Jorge et al, 2015), and 9.4 T (Arrubla et al, , 2014Neuner et al, 2013aNeuner et al, , 2013b.…”

“…Independent component analysis (ICA) has been shown to be a powerful tool for the decomposition of signal mixtures separating electrophysiological activity from noise and artefacts (Arrubla et al, 2014). Recently, Arrubla et al (2014) investigated the efficiency of different cardio-ballistic artefact rejection methods including four ICA based methods with different strategies for the identification of artefactual components.…”

“…Recently, Arrubla et al (2014) investigated the efficiency of different cardio-ballistic artefact rejection methods including four ICA based methods with different strategies for the identification of artefactual components. In this study, ICA was applied and combined with: (i) visual inspection, (ii) blind source separation (BSS) (Jung et al, 2000), (iii) cross-trial phase statistics (CTPS) (Dammers and Schiek, 2011;Dammers et al, 2008), and (iv) optimal basis set (OBS) (Delorme and Makeig, 2004) combined with BSS.…”