Effects of diazepam on facial emotion recognition
Bibliographic record
Abstract
OBJECTIVE: There have been few studies of the pharmacologic modulation of facial emotion recognition. The present study aimed to replicate and extend the finding that recognition of facial anger was selectively impaired by diazepam. The hypothesis was that, in comparison with placebo, diazepam would impair the recognition of facial anger in healthy volunteers, but not the recognition of 5 other basic emotions: happiness, surprise, fear, sadness and disgust. DESIGN: A randomized, counterbalanced, double-blind, placebo-controlled, within-subjects comparison of diazepam with placebo. SETTING: A university psychopharmacology research unit. PARTICIPANTS: Healthy male (n = 6) and female (n = 22) volunteers, aged 18-45 years. PROCEDURES: Subjects were tested on 2 tasks following the administration of diazepam, 15 mg, and placebo on separate occasions. In the first "multimorph" task, images of facial expressions were morphed to produce continua between the neutral and full expressions of 6 basic emotions. Accuracy and identification thresholds were assessed for stimuli in which the intensity of expression gradually increased. In the second "emotional hexagon" task, facial expressions were morphed between pairs of emotions. Single images were presented, and accuracy and speed of response were assessed. RESULTS: Diazepam produced broad impairments in response accuracy, recognition thresholds and response speed on the facial emotion tasks that were not limited to angry expressions. CONCLUSIONS: The present study found that diazepam, 15 mg, impaired facial emotion recognition, but not selectively. In the emotional hexagon task, a reaction-time analysis suggested that the identification of facial anger might be differentially sensitive to variations in stimulus duration, complicating the interpretation of this paradigm.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".