Effects of prenatal alcohol exposure on neurobehavioural development and volume of rostral cingulate cortex subregions
Bibliographic record
Abstract
BACKGROUND: Maternal alcohol consumption during pregnancy can have widespread and long-lasting effects on children's cognition, behaviour, brain function and structure. The pregenual anterior cingulate cortex (ACC) and the anterior midcingulate cortex (MCC) mediate emotional and cognitive behaviours that are affected by prenatal alcohol exposure. However, the neurobehavioural development of the pregenual ACC and anterior MCC has not been examined in people with prenatal alcohol exposure. METHODS: We recruited 30 children and adolescents with prenatal alcohol exposure and 50 age- and gender-matched unexposed controls. We acquired structural MRI data sets on a 3 T scanner. We manually delineated 2 areas of the rostral cingulate cortex - the pregenual ACC and the anterior MCC - and compared them between groups. We measured behavioural and emotional problems using the Behaviour Assessment System for Children, 2nd Edition, Parent Rating Scale, and then explored their associations with rostral cingulate cortex volumes. RESULTS: Intracranial-normalized volumes of the right pregenual ACC and the right total rostral cingulate cortex were significantly smaller in individuals with prenatal alcohol exposure than in unexposed controls. The volume of the right anterior MCC had a significant positive association with scores on the Internalizing Problems scale in individuals with prenatal alcohol exposure. LIMITATIONS: This study was cross-sectional, and detailed information about the timing and amount of exposure was not always available. CONCLUSION: Prenatal alcohol exposure is associated with lower volumes in the right pregenual ACC. This finding may underlie some of the emotional and behavioural problems experienced by individuals with prenatal alcohol exposure.
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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 | 0.000 | 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 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".