Trajectories of brain white matter development in young children with prenatal alcohol exposure
Bibliographic record
Abstract
Prenatal alcohol exposure (PAE) is associated with alterations to brain white matter microstructure. Previous studies of PAE have demonstrated different findings in young children compared to older children and adolescents, suggesting altered developmental trajectories and highlighting the need for longitudinal research. 122 datasets in 54 children with PAE (27 males) and 196 datasets in 89 children without PAE (45 males) were included in this analysis. Children underwent diffusion tensor imaging between 2 and 8 years of age, returning approximately every 6 months. Mean fractional anisotropy (FA) and mean diffusivity (MD) were obtained for 10 major brain white matter tracts and examined for age-related changes using linear mixed effects models with age, sex, group (PAE vs. control) and an age-by-group interaction. Children with PAE had slower decreases of MD over time in the genu of the corpus callosum, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus. No significant age-by-group interactions were noted for FA. These findings show slower white matter development in young children with PAE than in unexposed controls. This connects previous cross-sectional findings of lower MD in young children with PAE to findings of higher MD in older children and adolescents with PAE, and further helps to understand brain development in children with PAE. This deviation from typical development trajectories may reflect altered brain plasticity, which has implications for cognitive and behavioral learning in children with PAE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 teacher head, 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".