White‐matter correlates of anxiety: The contribution of the corpus‐callosum to the study of anxiety and stress‐related disorders
Bibliographic record
Abstract
OBJECTIVES: Traumatic stress has been associated with increased risk for brain alterations and development of anxiety disorders. Studies conducted in posttraumatic patients have shown white-mater volume and diffusion alterations in the corpus-callosum. Decreased cognitive performance has been demonstrated in acute stress disorder and posttraumatic patients. However, whether cognitive alterations result from stress related neuropathology or reflect a predisposition is not known. In the current study, we examined in healthy controls, whether individual differences in anxiety are associated with those cognitive and brain alterations reported in stress related pathologies. METHODS: Twenty healthy volunteers were evaluated for anxiety using the state-trait inventory (STAI), and were tested for memory performance. Brain imaging was employed to extract volumetric and diffusion characteristics of the corpus-callosum. RESULTS: Significant correlations were found between trait anxiety and all three diffusion parameters (fractional-anisotropy, mean and radial-diffusivity). Associative-memory performance and corpus-callosum volume were also significantly correlated. CONCLUSION: We suggest that cognitive and brain alterations, as tested in the current work and reported in stress related pathologies, are present early and possibly persist throughout life. Our findings support the hypothesis that individual differences in trait anxiety predispose individuals towards negative cognitive outcomes and brain alterations, and potentially to stress 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".