Fearful, surprised, happy, and angry facial expressions modulate gaze-oriented attention: Behavioral and ERP evidence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The impact of emotions on gaze-oriented attention was investigated in non-anxious participants. A neutral face cue with straight gaze was presented, which then averted its gaze to the side while remaining neutral or expressing an emotion (fear/surprise in Exp.1 and anger/happiness in Exp.2). Localization of a subsequent target was faster at the gazed-at location (congruent condition) than at the non-gazed-at location (incongruent condition). This Gaze-Orienting Effect (GOE) was enhanced for fear, surprise, and anger, compared to neutral expressions which did not differ from happy expressions. In addition, Event Related Potentials (ERPs) to the target showed a congruency effect on P1 for fear and surprise and a left lateralized congruency effect on P1 for happy faces, suggesting that target visual processing was also influenced by attention to gaze and emotions. Finally, at cue presentation, early postero-lateral (Early Directing Attention Negativity (EDAN)) and later antero-lateral (Anterior Directing Attention Negativity (ADAN)) attention-related ERP components were observed, reflecting, respectively, the shift of attention and its holding at gazed-at locations. These two components were not modulated by emotions. Together, these findings show that the processing of social signals such as gaze and facial expression interact rather late and in a complex manner to modulate spatial attention.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it