Brain Responses During Face Processing in Conduct Disorder: Considering Sex and Callous-Unemotional Traits
Bibliographic record
Abstract
BACKGROUND: Functional magnetic resonance imaging studies of conduct disorder (CD) have mostly been limited to males. Here, we examined whether male and female youths with CD showed similar or distinct alterations in brain responses to emotional faces, using a large sample of male and female youths with CD. We also investigated the influence of callous-unemotional (CU) traits. METHODS: Brain responses to angry, fearful, and neutral faces were assessed in 161 youths with CD (74 female) and 241 typically developing (TD) youths (139 female) ages 9 to 18 years. Categorical analyses tested for diagnosis effects (CD vs. TD and CD with high levels of CU traits [CD/HCU] vs. low levels of CU traits [CD/LCU] vs. TD) and sex × diagnosis interactions. RESULTS: When processing faces in general (all faces vs. baseline), youths with CD exhibited lower amygdala responses compared with TD youths, which seemed to be driven by the CD/HCU subgroup. Sex × CU subgroup interactions were identified in the amygdala (CD/LCU females < TD females; CD/LCU males > TD males) and anterior insula (CD/HCU females > CD/LCU females; CD/HCU males < CD/LCU males). CONCLUSIONS: The findings for males support an influential neurocognitive model of CD. However, the association between CU traits and brain response to facial expressions differed in females and males with CD, suggesting distinct pathophysiological processes.
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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 | 0.000 |
| 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) | 0.001 | 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".