Spontaneous eye-movements in neutral and emotional gaze-cuing: An eye-tracking investigation
Bibliographic record
Abstract
Our attention is spontaneously oriented in the direction where others are looking. This attention shift manifests as faster responses to peripheral targets when they are gazed at by a central face instead of gazed away from, and this effect is even more pronounced when the face expresses an emotion. This so called gaze-cuing effect, and its enhancement by emotion, is thought to reflect covert attention orienting. However, eye movements are typically not monitored in gaze-cuing paradigms, yet free viewing and saccadic reaction time research suggests individuals commonly and quickly look at gazed-at locations. Furthermore, in dynamic gaze-cuing studies, emotional faces differ from neutral faces in their affective content but also in their apparent facial motion, both of which could affect participants' eye-movements. We investigated the contribution of overt orienting to the gaze-cuing effect by monitoring eye-movements during emotional and neutral gaze-cuing trials. We found that eye-movements were infrequent, and when they occurred, they were directed toward the target, not toward the gazed-at location. Removing trials with eye-movements did not affect gaze-cuing much, confirming it reflects a covert attention process. However, participants were more likely to move their eyes during neutral trials, which lacked perceived face movement, than during emotion trials or neutral movement trials. Including these eye-movement contaminated trials in our analysis resulted in an impaired ability to detect the gaze-cuing variations with emotion. In contrast, removing trials with eye-movements, or including a neutral movement control such as a neutral tongue protrusion, revealed more subtle emotional modulation of gaze-cuing.
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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 | 0.000 | 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 | 0.000 |
| 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 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".