Testosterone-Related Cortical Maturation Across Childhood and Adolescence
Bibliographic record
Abstract
Neuroendocrine theories of brain development hold testosterone as the predominant factor mediating sex-specific cortical growth and the ensuing lateralization of hemispheric function. However, studies to date have focussed on prenatal testosterone rather than pubertal changes in testosterone. Yet, animal studies have shown a high density of androgen-sensitive receptors in multiple key cortical areas, and puberty is known to coincide with both a significant rise in testosterone and the emergence of behavioral sex differences, suggesting peripubertal influences of testosterone on brain development. Here, we used linear mixed models to examine sex-specific cortical maturation associated with changes in testosterone levels in a longitudinal sample of developmentally healthy children and adolescents. A significant "sex by age by testosterone" interaction on cortical thickness (CTh) involving widespread areas of the developing brain was found. Testosterone levels were associated with CTh changes in regions of the left hemisphere in males and of the right hemisphere in females. In both sexes, the relationship between testosterone and CTh varied across the age span. These findings show the association between testosterone and CTh to be complex, highly dynamic, and to vary, depending on sex and age; they also suggest sex-related hemispheric lateralization effects of testosterone in humans.
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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 | 0.001 |
| 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".