White matter microstructure in school-age children with down syndrome
Bibliographic record
Abstract
Down syndrome (DS) is the most common genetic cause of intellectual disability, but our understanding of white matter microstructure in children with DS remains limited. Previous studies have reported reductions in white matter integrity, but nearly all studies to date have been conducted in adults or relied solely on diffusion tensor imaging (DTI), which lacks the ability to disentangle underlying properties of white matter organization. This study examined white matter microstructural differences in 7- to 12-year-old children with DS (n=23), autism (n=27), and typical development (n=50) using DTI as well as High Angular Resolution Diffusion Imaging, and Neurite Orientation and Dispersion Imaging. There was a spatially specific pattern of results that showed a dissociation between intra- and inter-hemispheric pathways. Intra-hemispheric pathways (e.g., inferior fronto-occipital fasciculus, superior longitudinal fasciculus) exhibited reduced organization and structural integrity. Inter-hemispheric pathways (e.g., corpus callosum projections) and motor pathways (e.g., corticospinal tract) showed denser neurite packing and lower neurite dispersion. The current findings provide early insight into white matter development in school-aged children with DS and have the potential to further elucidate microstructural differences and inform more targeted clinical trials than what has previously been observed through DTI models alone. • First study to examine white matter in school-aged children with Down syndrome • Structural disassociation observed for intra- and inter-hemispheric fiber pathways • Intra-hemispheric pathways observed to have lower integrity and organization • Inter-hemispheric and motor pathways characterized by lower neurite dispersion
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".