Empathic responsiveness in amygdala and anterior cingulate cortex in youths with psychopathic traits
Bibliographic record
Abstract
BACKGROUND: Psychopathic traits are associated with increases in antisocial behaviors such as aggression and are characterized by reduced empathy for others' distress. This suggests that psychopathic traits may also impair empathic pain sensitivity. However, whether psychopathic traits affect responses to the pain of others versus the self has not been previously assessed. METHOD: We used whole-brain functional magnetic resonance imaging to measure neural activation in 14 adolescents with oppositional defiant disorder or conduct disorder and psychopathic traits, as well as 21 healthy controls matched on age, gender, and intelligence. Activation in structures associated with empathic pain perception was assessed as adolescents viewed photographs of pain-inducing injuries. Adolescents imagined either that the body in each photograph was their own or that it belonged to another person. Behavioral and neuroimaging data were analyzed using random-effects analysis of variance. RESULTS: Youths with psychopathic traits showed reduced activity within regions associated with empathic pain as the depicted pain increased. These regions included rostral anterior cingulate cortex, ventral striatum (putamen), and amygdala. Reductions in amygdala activity particularly occurred when the injury was perceived as occurring to another. Empathic pain responses within both amygdala and rostral anterior cingulate cortex were negatively correlated with the severity of psychopathic traits as indexed by PCL:YV scores. CONCLUSIONS: Youths with psychopathic traits show less responsiveness in regions implicated in the affective response to another's pain as the perceived intensity of this pain increases. Moreover, this reduced responsiveness appears to predict symptom severity.
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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".