Reduction of TMS Induced Artifacts in EEG Using Principal Component Analysis

Abstract

Co-registration of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) is a new, promising method for assessing cortical excitability and connectivity. Using this technique, a TMS evoked potential (TEP) can be induced and registered with the EEG. However, the TEP contains an early, short lasting artifact due to the magnetic pulse, and a second artifact, which depends on the location of stimulation and can last up to 40 ms. Different causes for this second artifact have been suggested in literature. In this study, we used principal component analysis (PCA) to suppress both the first and second artifact in TMS-EEG data. Single pulse TMS was applied at the motor and visual cortex in 18 healthy subjects. PCA using singular value decomposition was applied on single trials to suppress the artifactual components. A large artifact suppression was realized after the removal of the first five PCA components, thereby revealing early TEP peaks, with only a small suppression of later TEP components. The spatial distribution of the second artifact suggests that it is caused by electrode movement due to activation of the temporal musculature. In conclusion, we showed that PCA can be used to reduce TMS-induced artifacts in EEG, thereby revealing components of the TMS evoked potential.

N100 as a generic cortical electrophysiological marker based on decomposition of TMS-evoked potentials across five anatomic locations

“…Furthermore, subthreshold TMS pulses induced larger N100 than sham TMS despite the fact that sham TMS had louder sound. Previous studies also showed that earplug or other sound-attenuating methods sharply reduced TMS-evoked N100 (Ter Braack et al 2015), and the TMS-evoked N100 and P200 were also presented when subject was completely deaf (Ter Braack et al 2013). …”

“…2b) when single-pulse TMS was delivered over the superior parietal lobule. Also, TMS-evoked N100 was obtained with single vertex stimulation after removing auditory confounds (Ter Braack et al 2013). However, those N100 evoked by single-pulse TMS over different brain areas were demonstrated separately, and hence, there was no direct comparison between those N100s.…”

Intermittent theta-burst stimulation induces correlated changes in cortical and corticospinal excitability in healthy older subjects

“…The P60 component is believed to reflect somatosensory return (Paus et al, 2001), and the N100 has been associated with the activation of GABA-B receptors (Bonnard et al, 2009; Nikulin et al, 2003; Premoli et al, 2014). The P60, N100 and P180 components are also thought to be contaminated with an auditory evoked potential originated from the TMS pulse click (ter Braack et al, 2013). …”

Noise removal in electroencephalogram signals using an artificial neural network based on the simultaneous perturbation method

“…Another technique implemented in the comparison was PCA. PCA [25][26][27] is a well-established multivariate data technique which finds the direction in the data with most variation. It is expected that the direction with most variation contains the noise signals, because of the large amplitude difference between noise and EEG signals.…”

“…One of the common approaches is the adaptive filtering (AF) architecture which has been used for interference cancellation of EEG [15][16][17][18][19] and wavelet [20][21][22][23]. In this context, principal component analysis (PCA) [24][25][26][27] and independent component analysis (ICA) [23,[28][29][30][31][32][33][34] have become popular for analysing biomedical data (e.g., EEG and EMG). One of the main advantages of these approaches relates to their applicability to multisensory observations of mixed signals.…”