Do fearful eyes activate empathy-related brain regions in individuals with callous traits?
Bibliographic record
Abstract
Psychopathy, a developmental disorder characterized by profound social disturbance, is associated with impaired recognition of distress cues. Since distress processing and moral socialization are closely linked, uncovering techniques to improve distress recognition could have positive treatment implications for developmental disorders that feature empathy impairments. Previous studies demonstrate that fear-recognition deficits can be remedied by redirecting attention to critical cues (the eyes for fearful faces). However, it remains unclear whether this manipulation increases activity in empathy-related brain regions, or has an alternate compensatory effect that may not promote prosocial behaviours. In this fMRI study, a community sample of individuals with high vs low callous traits completed an emotion recognition task that varied whether the most or least socially meaningful facial features were visible (the eyes were isolated or occluded). For fearful faces, individuals with high callous traits showed significantly less amygdala and medial prefrontal cortex activity than those with low callous traits when the eyes were occluded, but not when they were isolated. Consistent with recent models of the amygdala that emphasize orientation to disambiguate stimuli rather than represent distress, individuals with low trait empathy showed greater amygdala activity to the least vs most socially meaningful features of fearful faces.
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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) | 0.002 | 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".