A TMS-EEG Pre-processing Parameters Tuning Study

The integration of transcranial magnetic stimulation and electroencephalography (TMS-EEG) has been sought to explore connectivity and cortical excitability in healthy and pathological subjects. Although the number of studies in this field is continuously increasing, there is still no consensus on the pre-processing pipeline. The goal of this work is to study the effect of two pre-processing parameters, (i) the interpolation window size and (ii) the regularization parameter of the source-estimate-utilizing noise-discarding (SOUND) algorithm, on the resulting TMS-evoked potentials (TEPs) and five peaks of interest. The comparison of four combinations of parameters showed the effect of the parameters on the TMS residual artifacts, which resulted in major differences between TEPs in the early windows after the TMS pulses. The work showed how the interpolation window size and the regularization parameter influence the TEPs results and proposed a combination of parameters that retrieve information of interest, decreasing the amount of noise in data.