Neuroticism and Frontal EEG Asymmetry Correlated With Dynamic Facial Emotional Processing in Adolescents
Bibliographic record
Abstract
The aim of this research was to investigate the link between resting frontal EEG asymmetry, neuroticism and the valence of emotional face processing in adolescents. Fifty right-handed adolescents (50 % male; mean age = 14.20, SD = 1.97) were selected from schools in Mashhad. In order to investigate variables, we used BFQ-C, ADFES-BIV, and EEG. All data were analyzed using SPSS 22. The results showed that neuroticism correlates with the valences of fear, disgust, sadness, and surprise, but not with happiness, anger, and neutral faces. Furthermore, it was found that N was significantly positively correlated with mid-frontal asymmetry (F3–F4), and the lateral-frontal (F7-F8), whereas no correlation was found between N and frontal pole (Fp1-Fp2). We found significant negative correlations between the valence of fear, Fp1-Fp2, F3-F4, and F7-F8. The interaction findings revealed that neuroticism*mid-frontal asymmetry can significantly affect the valence of fear. Therefore, neuroticism and mid-frontal EEG asymmetry may serve as a risk indicator for psychopathology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".