A novel approach for the removal of tACS artifacts from high-density EEG recordings

Abstract

Event Abstract Back to Event A novel approach for the removal of tACS artifacts from high-density EEG recordings Thiago Santos Monteiro1, Kirstin F. Heise1*, Stephan P. Swinnen1 and Dante Mantini1, 2 1 KU Leuven, Faculty of Kinesiology and Rehabilitation Science, Belgium 2 ETH Zurich, Department of Health Sciences and Technology, Switzerland Concurrent application of electroencephalography (EEG) and non-invasive brain stimulation with alternating electrical current (tACS) holds great potential for retrieving information about causal relationships between neural activity and behaviour (1). Principal component analysis (PCA) is the method currently used to separate neural activity and stimulation artifacts that are mixed in EEG recordings PCA (2). Importantly, the use of PCA may alter phase relationships between target areas. Furthermore, the approach has been developed for and applied to few EEG electrodes, and has not been implemented for high-density (hd-) EEG recordings. Based on a validation procedure using real resting-state hd-EEG data and a simulated tACS artefact we compared the performance of PCA with a novel combination of advanced filtering methods (Hampel filtering based on windowed version of autoregressive modelled artefact, wAR/HF) (3). While the wAR/HF approach is more precise in removing the excessive tACS artefact from the hd-EEG signal thereby retaining the frequencies of interest (figure 1A depicts deviation from original signal after artefact removal averaged across all channels, figure 1B indicates deviation in relative power distribution), the PCA is more stable for retaining the interregional phase relationships. This work constitutes a critical methodological step to allow for the application of concurrent tACS in hd-EEG, which may permit the study of causal relationship between oscillatory activity in the brain and behaviour. Figure 1