## 2 Materials and Methods
### Electrophysiological Data  
#### 2.4.1 General Pre-Processing of Electrophysiological Data  
Using the 64-channel Biosemi ActiveTwo EEG system (BioSemi, Amsterdam, The Netherlands), continuous EEG data were recorded through a quickcap adhering to the 10/10 system at a sampling rate of 2048 Hz. Flat-type electrodes were positioned 1 cmfrom the outer canth of both eyes to capture horizontal electrooculograms (HEOGs). For vertical electrooculograms (VEOGs) and blinks, electrodes were placed above and below the right eye. Additionally, two electrodes were attached to each earlobe. Pin-type electrodes were secured with an elastic cap after applying electrode gel. Unlike other EEG systems, ActiveTwo allows for reference-free EEG signal recording. Instead, the ground reference is managed by two electrodes (DRL/CMS), creating a feedback loop to regulate the current from the participant to the analog-digital (AD) box. EEG data pre-processing was conducted with BrainVision Analyzer 2.3 software (Brain Products GmbH, Munich, Germany). First, three channels that did not contain data for further analysis were disabled (EXG7, EXG8, and Status). Next, a linear derivation function was applied to compute the bipolar HEOG channel from the outer canth electrodes of both eyes (i.e., HEOGL and HEOGR) and the VEOG channel using the two electrodes and one electrode placed above and below the right eye (i.e., VEOGU and VEOGL). Next, raw EEG data were band-pass-filtered between 0.3 and 46 Hz with 8 th-order rolloffs, with a 50 Hz notch employing zero-phase-shift Butterworth (IIR) filters. Next, automatic raw data inspection was conducted, excluding frontal electrodes that were contaminated by eye movements and blinks (i.e., Fp1, AF7, AF3, F7, F5, F3, F1, FPz, AFz, Fz, FP2, AF8, AF4, F8, F6, F4, F2). The EEG events are marked as bad from 200 ms before to 200 ms after the event by applying the following exclusion criteria: (1) check the gradient if the maximal allowed voltage step exceeds 50 \(\mu\)V/ms; (2) check the difference (max-min) if the values in 200 ms intervals exceed 200 \(\mu\)V; (3) check the amplitude if the minimal and maximal allowed amplitudes exceed \(\pm\)200 \(\mu\)V; (4) check for low activity if the values in 100 ms intervals are lower than 0.5 \(\mu\)V). Next, if EEG channels contained intervals with obvious non-ocular artifacts (i.e., muscular contractions and electrode artifacts) over prolonged periods (i.e., \(>\)100 s), these were removed. Next, after the exclusion of bad channels, the automatic raw data inspection procedure was re-conducted on the remaining \"good\" channels to reduce the amount of EEG intervals marked as bad and, therefore, maximize the amount of EEG signals to use in subsequent pre-processing stages. Next, as a pre-processing step for ICA ocular artifact reduction procedures, high-pass filtering at 1 Hz (8 th-order rolloffs) with a zero-phase-shift Butterworth (IIR) filter was applied to compute the ICA weights, and this produced good results in terms of the signal-to-noise ratio (SNR) [52]. Next, ocular artifacts were reduced by employing the ICA function within the BrainVision Analyzer software using VEOG/HEOG channels. This function searches for an ocular artifact template in VEOG/HEOG channels and then finds ICA-derived components that account for a user-specified amount of variance (70%) in the template-matched portion of the signal from VEOG/HEOG. Data used for ICA were 328 s long, and the ICA algorithm used was Infomax-restricted. Next, ICA weights for less high-pass-filtered data (i.e., 0.3 Hz, 8 th-order rolloffs) were applied using a linear derivation function. So, the ICA components containing artifacts were removed from the EEG signal, which was then reconstructed for further processing. Next, bad EEG channels that were previously removed were topographically spline-interpolated with order 4, degree 10, and lambda 1 \(\times\) 10\({}^{-5}\). Next, the original order of the 64 electrodes plus A1, A2, HEOG, and VEOG was re-established.