Few sex differences in regional gray matter volume growth trajectories across early childhood
Bibliographic record
Abstract
Abstract Sex-specific developmental differences in brain structure have been documented in older children and adolescents, with females generally showing smaller overall brain volumes and earlier peak ages than males. However, sex differences in gray matter structural development in early childhood are less studied. We characterized sex-specific trajectories of gray matter volume development in children aged 2–8 years. We acquired anatomical magnetic resonance imaging (MRI) of the brain at the Alberta Children's Hospital in 123 typically developing children. Most children were scanned multiple times, for a total of 393 scans (mean = 3.2 scans/subject). We segmented T1-weighted structural MRI with MaCRUISE to define 116 regions and measured both absolute volumes (mm3) and proportional volumes (percent of intracranial volume). We characterized growth trajectories of gray matter volume for these brain regions between 2 and 8 years using mixed-effects models, showing volume increases, with most posterior and temporo-parietal regions peaking before 8 years. We found widespread main effects of sex, with males having larger volumes in 86% of brain regions. However, there were no significant sex differences in trajectories (age or age2 terms) for absolute volume. Proportional volumes of the right occipital fusiform gyrus and left medial postcentral gyrus showed significant age-by-sex interactions where females had steeper volume decreases than males. This study also confirms regional patterns observed in previous studies of older children, such as posterior-to-anterior timing of brain maturation. These results provide a comprehensive picture of gray matter volume development across early childhood, and suggest that sex differences do not emerge until later in development.
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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 | 0.001 |
| 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) | 0.002 | 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".