Whole‐brain morphometry in Canadian soldiers with posttraumatic stress disorder
Bibliographic record
Abstract
Patients with posttraumatic stress disorder (PTSD) display several structural brain differences when compared with healthy individuals. However, findings are particularly inconsistent for soldiers with PTSD. Here, we characterized the brain morphometry of 37 soldiers from the Canadian Armed Forces with adulthood war-related PTSD using structural magnetic resonance imaging. We assessed time since trauma, as well as PTSD, depressive, and anxiety symptoms with the Modified PTSD Symptoms Scale, Beck Depression Inventory, and Beck Anxiety Inventory, respectively. Whole-brain morphometry was extracted with FreeSurfer and compared with a validated normative database of more than 2700 healthy individuals. Volume and thickness from several regions differed from the norms. Frontal regions were smaller and thinner, particularly the superior and rostral middle frontal gyri. Furthermore, smaller left rostral middle frontal gyrus, left pericalcarine cortex, and right fusiform gyrus were associated with more recent trauma. All subcortical structures were bigger, except the hippocampus. These findings suggest a particular brain morphometric signature of PTSD in soldiers. Smaller and thinner frontal and larger subcortical regions support impaired top-down and/or downregulation of emotional response in PTSD. Finally, the correlation of smaller frontal, temporal, and occipital regions with more recent trauma might inform future therapeutic approaches.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".