Hippocampal and parahippocampal volumes vary by sex and traumatic life events in children
Bibliographic record
Abstract
Background: Childhood trauma is reliably associated with smaller hippocampal volume in adults; however, this finding has not been shown in children, and even less is known about how sex and trauma interact to affect limbic structural development in children. Methods: Typically developing children aged 9 to 15 years who completed a trauma history questionnaire and structural T1-weighted MRI were included in this study (n = 172; 85 female, 87 male). All children who reported 4 or more traumas (n = 36) composed the high trauma group, and all children who reported 3 or fewer traumas (n = 136) composed the low trauma group. Using multivariate analysis of covariance, we compared FreeSurfer-derived structural MRI volumes (normalized by total intracranial volume) of the amygdalar, hippocampal and parahippocampal regions by sex and trauma level, controlling for age and study site. Results: We found a significant sex × trauma interaction, such that girls with high trauma had greater volumes than boys with high trauma. Follow-up analyses indicated significantly increased volumes for girls and generally decreased volumes for boys, specifically in the hippocampal and parahippocampalregions for the high trauma group; we observed no sex differences in the low trauma group. We noted no interaction effect for the amygdalae. Limitations: We assessed a community sample and did not include a clinical sample. We did not collect data about the ages at which children experienced trauma. Conclusion: Results revealed that psychological trauma affects brain development differently in girls and boys. These findings need to be followed longitudinally to elucidate how structural differences progress and contribute to well-known sex disparities in psychopathology.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".