Krzysztof Wrobel, Grzegorz M. Wojcik · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28427 · open-access PDF
ونحن نستعرض ما إذا كان شبكة عصبية 2D Convolutional (CNN) التي تم تدريبها على إشارات EEG المحددة على الأقل يمكن أن تخصيص حساسية التهاب الكبد في مختلف مناطق الدماغ المختلفة. 62 المشاركين الرجال (32 التحكم، 30 صورة تدريبية / مجموعة Hipno) قاموا بتسجيل EEG لمدة 20 دقيقة باستخدام قفل EGI 256 قناة.
Machine translation (Meta M2M100); the English original follows.
We investigate whether a 2D Convolutional Neural Network (CNN) trained on minimally preprocessed EEG signals can classify hypnotic susceptibility across distinct brain regions. Sixty-two male participants (32 Control, 30 Guided Imagery / Hipno group) underwent a 20-minute EEG recording using a 256-channel EGI cap. A sliding-window approach evaluates all 10-second windows within the recording for each of seven predefined brain regions (prefrontal, frontal, temporal, central, parietal, occipital, and facial), yielding up to 868 independently trained models. Initial screening with a segment-level
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