Effects of prenatal alcohol exposure on hippocampal volume, verbal learning, and verbal and spatial recall in late childhood
Bibliographic record
Abstract
Children with prenatal alcohol exposure (PAE) show deficits in verbal learning and spatial memory, as well as abnormal hippocampal development. The relationship between their memory and neuroanatomic impairments, however, has not been directly explored. Given that the hippocampus is integral for the synthesis and retrieval of learned information and is particularly vulnerable to the teratogenic effects of alcohol, we assessed whether reduced learning and recall abilities in children with fetal alcohol spectrum disorders (FASDs) are associated with abnormal hippocampal volumes. Nineteen children with FASDs and 18 typically developing controls aged 9 to 15 years were assessed for verbal learning and verbal and spatial recall and underwent structural magnetic resonance imaging. Images were analyzed for total intracranial volume and for right and left hippocampal volumes. Results revealed smaller left hippocampi and poorer verbal learning and verbal and spatial recall performance in children with FASDs than controls, as well as positive correlations between selective memory indices and hippocampal volumes only in the FASD group. Additionally, hippocampal volumes increased significantly with age in controls only, suggesting that PAE may be associated with long-term abnormalities in hippocampal development that may contribute to impaired verbal learning and verbal and spatial recall.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".