EEG signal processing and feature extraction
The EEG data analysed here correspond to the 2-min resting state EEG in eyes closed condition recorded before the start of tDCS stimulation in each T3 to T6 trial for each participant. Data were first band pass filtered using a 1000 coefficients FIR filter with cut-off frequencies at 2Hz and 45 Hz, demeaned and detrended. Frontal channels AF4, Fp2, Fp1 and AF3 were removed from further processing and analysis due to the presence of numerous eye-movement related artifacts. High amplitude artifacts were removed using an amplitude threshold of 100 μV. Finally, the data were re-referenced to electrode Cz, which was then excluded from further processing. The relative band power was computed in 4-s time-windows epochs with 50% overlap in bands delta (2–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz) and gamma (30–45 Hz). The final relative band power values for each subject and session were taken as the median of the epochs. The EEG data pre-processing was done in Python 3.9 using custom scripts and Python packages (i.e. MNE).