## 3 Materials and Methods  
### GIGAScience Dataset for MI-EEG and Signal Preprocessing  
**DB-I--GiGaScience**[26] ([[http://ggagdb.org/dataset/100295](http://ggagdb.org/dataset/100295)]([http://ggagdb.org/dataset/100295](http://ggagdb.org/dataset/100295)), accessed on 23 October 2024). It consists of 52 subjects, 50 of whom have their EEG data available for evaluation. Each subject is asked to perform a single session of MI, comprising five to six runs with 100 to 120 trials per class. Each trial lasts seven seconds, starting with a blank screen and followed by a cue within two seconds. When the cue appears onscreen, the subject imagines moving their left or right hand. The trial ends with two more seconds of a blank screen and an inter-trial break of 0.1 to 0.8 s. The EEG data were collected using 64 electrodes placed according to the international 10-10 system, as seen in Figure 1, sampled at 512 Hz. Actual movement and six types of non-task-related data (blinking eyes, eyeball movement up/down, eyeball movement left/right, head movement, jaw clenching, and resting state) were also collected. Figure 1: GIGAScience database experiment for MI-EEG classification (left vs. right hand). **(Left)** Trial timing: A marker appears onscreen; after two seconds, an instruction is shown to the patient, asking them to imagine moving either their left or right hand. The instruction stays onscreen for three seconds before disappearing. **(Right)** Spatial EEG montage: electrodes are placed starting at the left frontal nodes and continuing through a serpent pattern until they reach the back, at which point they go back to the front and down the center until they reach the CPZ node (10-10 system). **Preprocessing:** Signals were preprocessed before training. An average reference was utilized. Notably, we re-referenced the average after including the initial reference, ensuring the data's full rank [60]. Then, a fifth-order Butterworth bandpass filter (4-40 Hz) was applied. As the database focuses on motor imagery, rather than higher mental activity like multisensory information integration, most of the information can be found throughout three frequency bands: Theta (4-8 Hz), Alpha (8-13 Hz), and Beta (13-32 Hz) [61; 62], while the Gamma rhythm (40 Hz and above) is usually omitted [63]. Afterward, signals are downsampled from 512 Hz to 128 Hz for consistent results between DL models [38; 39]. Lastly, only the motor imagery time window is used, as denoted in Figure 1. A summarized version of this preprocess can be seen in Figure 2.  
Additionally, subjects were asked to complete a physiological questionnaire during the MI experiment. Before beginning the MI experiment, subjects answered 15 personal questions concerning, for example, age, sex, BCI experience, or any recent consumption of coffee, alcohol, or cigarettes. After every run, subjects answered another ten questions about their mood and expected performance. Finally, after the MI experiment, subjects had to answer four questions regarding their thoughts on the experiment and overall personal performance. In total, each subject answered 69 questions. Questions relating to how the patient felt were answered on a scale from one to five, while open questions such as age or expected performance were answered numerically without decimals. However, not all questions were utilized in this study. [PERSON]'s entropy, as presented in Equation (1),  
\[H(\mathbf{\xi}_{q})=-\mathbb{E}\{\log(p(\xi_{rq})):\forall r\in R\}, \tag{1}\]  
was measured for each of the \(Q\) questions, \(\xi_{rq}\in\mathbf{\xi}_{q}\), and \(q\in Q\), correctly encoded and normalized between \([0,1]\), along with the \(R\) subjects to find the ones who provided the most expected information, with the response histogram giving an estimate of \(p(\xi_{rq})\). This enabled us to remove cases in which answers had a probability density with low variance (and, by proxy, little discriminant information), such as handedness.