Links between white matter microstructure and cortisol reactivity to stress in early childhood: Evidence for moderation by parenting
Bibliographic record
Abstract
Activity of the hypothalamic-pituitary-adrenal axis (measured via cortisol reactivity) may be a biological marker of risk for depression and anxiety, possibly even early in development. However, the structural neural correlates of early cortisol reactivity are not well known, although these would potentially inform broader models of mechanisms of risk, especially if the early environment further shapes these relationships. Therefore, we examined links between white matter architecture and young girls' cortisol reactivity and whether early caregiving moderated these links. We recruited 45 6-year-old girls based on whether they had previously shown high or low cortisol reactivity to a stress task at age 3. White matter integrity was assessed by calculating fractional anisotropy (FA) of diffusion-weighted magnetic resonance imaging scans. Parenting styles were measured via a standardized parent-child interaction task. Significant associations were found between FA in white matter regions adjacent to the left thalamus, the right anterior cingulate cortex, and the right superior frontal gyrus (all ps < .001). Further, positive early caregiving moderated the effect of high cortisol reactivity on white matter FA (all ps ≤ .05), with high stress reactive girls who received greater parent positive affect showing white matter structure more similar to that of low stress reactive girls. Results show associations between white matter integrity of various limbic regions of the brain and early cortisol reactivity to stress and provide preliminary support for the notion that parenting may moderate associations.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".