Brain Diffusion Abnormalities in Children With Fetal Alcohol Spectrum Disorder
Bibliographic record
Abstract
BACKGROUND: Children with fetal alcohol spectrum disorder (FASD) have a variety of cognitive, behavioral, and neurological impairments, including structural brain damage. Despite the importance of white matter connections for proper brain function, little is known about how these connections, and the deep gray matter structures that act as relay stations, are affected in children with FASD. The purpose of this study was to use diffusion tensor imaging, an advanced magnetic resonance imaging technique, to examine microstructural differences of white and deep gray matter in children with FASD. METHODS: Subjects were 24 children aged 5-13 years previously diagnosed with FASD and 95 healthy children over the same age range. Diffusion tractography was used to delineate 10 major white matter tracts in each individual, and region-of-interest analysis was used to assess 4 deep gray matter structures. Fractional anisotropy, an indicator of white matter integrity, and mean diffusivity, a measure of the average water diffusion, were assessed in all 14 brain structures. RESULTS: Diffusion tensor imaging revealed significant differences of diffusion parameters in several areas of the brain, including the genu and splenium of the corpus callosum, cingulum, corticospinal tracts, inferior fronto-occipital fasciculus, inferior and superior longitudinal fasciculi, globus pallidus, putamen, and thalamus. Reduced white and gray matter volumes, as well as total brain volume, were observed in the FASD group. CONCLUSIONS: These results demonstrate diffusion abnormalities in FASD beyond the corpus callosum and suggest that several specific white matter regions, particularly commissural and temporal connections, and deep gray matter areas of the brain are sensitive to 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 | 0.002 | 0.001 |
| 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".