Sex-specific relationships between gray matter volume and executive function in young children with and without prenatal alcohol exposure
Bibliographic record
Abstract
Sex differences in brain volume are well established across ages however, limited research has investigated if sex differences in brain structure associate with early cognitive outcomes. Moreover, associations among sex, brain structure, and cognition in individuals with prenatal alcohol exposure (PAE), the most common known cause of developmental delay in North America, are unclear. Here, we investigated associations between executive function (measured by the BRIEF or BRIEF-P Global Executive Composite (GEC) and the Statue subtest of the NEPSY-II) and volumes of 36 gray matter regions in a longitudinal MRI sample of 169 young children (N PAE =37; 534 total scans) aged 2-8 years. We found significant three-way interactions between sex, alcohol exposure, and executive function in 22 regions for GEC and 6 regions for Statue. Unexposed males showed negative executive function-volume associations, whereas males with PAE showed opposite associations. Unexposed females showed strong positive executive function-volume associations whereas females with PAE showed weak positive associations. We also evaluated reduced models in regions without significant 3-way interactions and found significant two-way interactions of sex and executive function for the GEC in three regions, and for the Statue in 22 regions. Males showed a negative executive function-volume relationship whereas females showed a positive relationship, regardless of exposure status. Our results suggest that males with PAE and unexposed females show relatively more mature volume-executive function relationships than females with PAE and unexposed males. This study highlights the importance of considering sex in investigations of brain and cognition, especially in populations with PAE.
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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 | 0.001 | 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) | 0.001 | 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".