Resting‐state pulvinar‐posterior parietal decoupling in PTSD and its dissociative subtype
Bibliographic record
Abstract
Key evidence points toward alterations in the neurocircuitry of large-scale networks among patients with posttraumatic stress disorder (PTSD). The pulvinar is a thalamic region displaying reciprocal connectivity with the cortex and has been shown to modulate alpha synchrony to facilitate network communication. During rest, the pulvinar displays functional connectivity with the posterior parietal cortex (PPC), a heteromodal network of brain areas underlying multisensory integration and socioaffective functions that are shown at deficit in PTSD. Accordingly, this study seeks to reveal the resting-state functional connectivity (rsFC) patterns of individuals with PTSD, its dissociative subtype (PTSD + DS) and healthy controls. A whole-brain rsFC analysis was conducted using SPM12 and PickAtlas. Connectivity was analyzed for the left and right pulvinar across groups of individuals with PTSD (n = 81), PTSD + DS (n = 49), and controls (n = 51). As compared to PTSD, controls displayed significantly greater pulvinar rsFC with the superior parietal lobule and precuneus. Moreover, as compared to PTSD + DS, controls showed increased pulvinar connectivity with the superior parietal lobule, inferior parietal lobule and the precuneus. PTSD groups did not display stronger connectivity with any region as compared to controls. Last, PTSD had greater rsFC in the supramarginal gyrus relative to PTSD + DS. Reduced connectivity between the pulvinar and PPC may explain impairments to autobiographical memory, self-referential processing, and socioaffective domains in PTSD and PTSD + DS even at "rest." Critically, these alterations appear to be exacerbated in individuals with PTSD + DS, which may have important implications for treatment.
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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) | 0.003 | 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".