<scp>fMRI</scp>functional connectivity of the periaqueductal gray in<scp>PTSD</scp>and its dissociative subtype
Bibliographic record
Abstract
Abstract Background Posttraumatic stress disorder (PTSD) is associated with hyperarousal and active fight or flight defensive responses. By contrast, the dissociative subtype ofPTSD, characterized by depersonalization and derealization symptoms, is frequently accompanied by additional passive or submissive defensive responses associated with autonomic blunting. Here, the periaqueductal gray (PAG) plays a central role in defensive responses, where the dorsolateral (DL‐PAG) and ventrolateralPAG(VL‐PAG) are thought to mediate active and passive defensive responses, respectively. Methods We examinedPAGsubregion (dorsolateral and ventrolateral) resting‐state functional connectivity in three groups:PTSDpatients without the dissociative subtype (n = 60);PTSDpatients with the dissociative subtype (n = 37); and healthy controls (n = 40) using a seed‐based approach via PickAtlas andSPM12. Results AllPTSDpatients showed extensiveDL‐ andVL‐PAGfunctional connectivity at rest with areas associated with emotional reactivity and defensive action as compared to controls (n = 40). Although allPTSDpatients demonstratedDL‐PAGfunctional connectivity with areas associated with initiation of active coping strategies and hyperarousal (e.g., dorsal anterior cingulate; anterior insula), only dissociativePTSDpatients exhibited greaterVL‐PAGfunctional connectivity with brain regions linked to passive coping strategies and increased levels of depersonalization (e.g., temporoparietal junction; rolandic operculum). Conclusions These findings suggest greater defensive posturing inPTSDpatients even at rest and demonstrate that those with the dissociative subtype show unique patterns ofPAGfunctional connectivity when compared to those without the subtype. Taken together, these findings represent an important first step toward identifying neural and behavioral targets for therapeutic interventions that address defensive strategies in trauma‐related disorders.
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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) | 0.002 | 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".