Anxious arousal predicts within-person changes in hippocampal volume in adults with a history of childhood maltreatment: A CAN-BIND4 report.
Bibliographic record
Abstract
Childhood maltreatment (CM) is a strong transdiagnostic risk factor for future psychopathology. This risk is theorized to emerge partly because of glucocorticoid-mediated atrophy in the hippocampus, which leaves this area sensitive to further volume loss even through adulthood in the face of future stress and the emergence of psychopathology. This proof-of-principle study examines which specific dimensions of internalizing psychopathology in the context of a CM history are associated with decreases in hippocampal volume over a 6-month period. This study included 80 community-recruited adults (ages 18-66 years, 61.3% women) oversampled for a lifetime history of internalizing psychopathology. At baseline and a naturalistic 6-month follow-up, the symptom dimensions of the tripartite model (anxious arousal, anhedonic depression, and general distress) were assessed by self-report. Hippocampal volume was derived through T1-weighted magnetic resonance imaging scanning segmented via the volBrain HIPS pipeline. CM severity was determined via a semistructured, contextual interview with independent ratings. We found that higher levels of anxious arousal predicted decreases in hippocampal volume over time in those with greater severity of CM but were associated at a trend with increases in hippocampal volume over time in those with lower severity of maltreatment. Findings were specific to anxious arousal and the CA1 subregion of the hippocampus. These novel results suggest that for individuals with a history of CM, transdiagnostic interventions that target and reduce psychological and physiological arousal may result in the preservation of hippocampal structure and, thus, improvements in cognitive and emotional regulation in the face of stress. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".