Volume changes and brain‐behavior relationships in white matter and subcortical gray matter in children with prenatal alcohol exposure
Bibliographic record
Abstract
Children with prenatal alcohol exposure (PAE) may have cognitive, behavioral and brain abnormalities. Here, we compare rates of white matter and subcortical gray matter volume change in PAE and control children, and examine relationships between annual volume change and arithmetic ability, behavior, and executive function. Participants (n = 75 PAE/64 control; age: 7.1-15.9 years) each received two structural magnetic resonance scans, ~2 years apart. Assessments included Wechsler Intelligence Scale for Children (WISC-IV), the Child Behavior Checklist and the Behavior Rating Inventory of Executive Function. Subcortical white and gray volumes were extracted for each hemisphere. Group volume differences were tested using false discovery rate (q < 0.05). Analyses examined group-by-age interactions and group-score interactions for correlations between change in volume and raw behavioral scores. Results showed that subjects with PAE had smaller volumes than control subjects across the brain. Significant group-score interactions were found in temporal and parietal regions for WISC arithmetic scores and in frontal and parietal regions for behavioral measures. Poorer cognitive/ behavioral outcomes were associated with larger volume increases in PAE, while control subjects generally showed no significant correlations. In contrast with previous results demonstrating different trajectories of cortical volume change in PAE, our results show similar rates of subcortical volume growth in subjects with PAE and control subjects. We also demonstrate abnormal brain-behavior relationships in subjects with PAE, suggesting different use of brain resources. Our results are encouraging in that, due to the stable volume differences, there may be an extended window of opportunity for intervention in children with PAE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".