Disrupted intrathalamic and thalamocortical structural covariance networks in posttraumatic stress disorder
Bibliographic record
Abstract
Abstract The thalamus is a heterogeneous structure crucial for corticocortical communication, affective–perceptual integration, motor preparation, and memory-related functions. Posttraumatic stress disorder (PTSD) is characterized by various symptoms that likely relate to thalamic functions. Group-level and individual differential structural covariance (SC) analyses were conducted on intrathalamic, thalamocortical, and thalamosubcortical volumetric networks by segmenting structural MRI data from 2,784 subjects (PTSD n = 1,306; controls n = 1,478) into 25 thalamic nuclei per hemisphere. We found that PTSD was associated with stronger intrathalamic and thalamocortical network strength and stronger SC between the limbic thalamus and the somatomotor and auditory thalamus. PTSD severity was related to specific regional alterations in the intrathalamic network involving the lateral pulvinar. Comorbid depression severity positively correlated with global intrathalamic alterations, while avoidance symptoms positively correlated with global thalamosubcortical alterations. Hyperarousal symptoms related to altered SC in the thalamocortical network between the reuniens, central medial, paratenial, centromedian, and limitans-suprageniculate nuclei and lateral cortical regions spanning the occipital, temporal, and orbitofrontal cortices. Differential associations between avoidance, hyperarousal, and comorbid depression symptoms and thalamic SC in PTSD suggest that specific thalamic covariance patterns may be involved in unique facets of PTSD symptomatology.
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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) | 0.001 | 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".