The impact of artifact removal approaches on TMS–EEG signal

Abstract

AbstractTranscranial magnetic stimulation (TMS)-evoked potentials (TEPs) allow one to assess cortical excitability and effective connectivity in clinical and basic research. However, obtaining clean TEPs is challenging due to the various TMS-related artifacts that contaminate the electroencephalographic (EEG) signal when the TMS pulse is delivered. Different preprocessing approaches have been employed to remove the artifacts, but the degree of artifact reduction or signal distortion introduced in this phase of analysis is still unknown. Knowing and controlling this potential source of uncertainty will increase the inter-rater reliability of TEPs and improve the comparability between TMS–EEG studies. The goal of this study was to assess the variability in TEP waveforms due to of the use of different preprocessing pipelines. To accomplish this aim, we preprocessed the same TMS–EEG data with four different pipelines and compared the results. The dataset was obtained from 16 subjects in two identical recording sessions, each session consisting of both left dorsolateral prefrontal cortex and left inferior parietal lobule stimulation at 100% of the resting motor threshold. Considerable differences in TEP amplitudes were found between the preprocessing pipelines. Topographies of TEPs from the different pipelines were all highly correlated (ρ>0.8) at latencies over 100 ms. By contrast, waveforms at latencies under 100 ms showed a variable level of correlation, with ρ ranging between 0.2 and 0.9. Moreover, the test–retest reliability of TEPs depended on the preprocessing pipeline. Taken together, these results take us to suggest that the choice of the preprocessing approach has a marked impact on the final TEP, and that caution should be taken when comparing TMS–EEG studies that used different approaches. Finally, we propose strategies to control this source of variability.