Structural brain aberrations associated with the dissociative subtype of post‐traumatic stress disorder
Bibliographic record
Abstract
OBJECTIVE: One factor potentially contributing to the heterogeneity of previous results on structural grey matter alterations in adult participants suffering from post-traumatic stress disorder (PTSD) is the varying levels of dissociative symptomatology. The aim of this study was therefore to test whether the recently defined dissociative subtype of PTSD characterized by symptoms of depersonalization and derealization is characterized by specific differences in volumetric brain morphology. METHOD: Whole-brain MRI data were acquired for 59 patients with PTSD. Voxel-based morphometry was carried out to test for group differences between patients classified as belonging (n = 15) vs. not belonging (n = 44) to the dissociative subtype of PTSD. The correlation between dissociation (depersonalization/derealization) severity and grey matter volume was computed. RESULTS: Patients with PTSD classified as belonging to the dissociative subtype exhibited greater grey matter volume in the right precentral and fusiform gyri as well as less volume in the right inferior temporal gyrus. Greater dissociation severity was associated with greater volume in the right middle frontal gyrus. CONCLUSION: The results of this first whole-brain investigation of specific grey matter volume in dissociative subtype PTSD indentified structural aberrations in regions subserving the processing and regulation of emotional arousal. These might constitute characteristic biomarkers for the dissociative subtype PTSD.
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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 | 0.001 | 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) | 0.002 | 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".