Alexithymia Moderates Salience Effects in Emotional Facial Expression Perception and Recognition
Bibliographic record
Abstract
Alexithymia is a multi-faceted personality trait associated with particularities in emotion processing and regulation. While alexithymia total scores have frequently been used to explain these particularities, recent models suggest a differentiated role of specific alexithymia facets at specific emotion processing stages. In this study, we investigated whether alexithymia total scores and facets moderate the effect of emotional salience on valence ratings, arousal ratings and correct emotion recognition. Ninety-four non-clinical participants provided valence and arousal ratings as well as discrete emotion labels for 160 pictures of emotional facial expressions varying in morphing intensity (40%, 60%, 80% and 100% emotion intensity) and discrete emotion type (happy, angry, disgusted, sad, fearful). Alexithymia levels were measured with the Toronto Alexithymia Scale (TAS-20). Our results show that alexithymia total scores moderate arousal and emotion recognition at lower salience levels. Higher alexithymia total scores were associated with higher arousal ratings and higher emotion recognition probability, but only at 40% morphing intensity, which partially supports the over-responding model of alexithymia. In addition, we found contrasted effects of alexithymia facets. Taken together, these results highlight the importance of focusing on emotional salience perception in alexithymia.
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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".