Common White Matter Microstructure Alterations in Pediatric Motor and Attention Disorders
Bibliographic record
Abstract
OBJECTIVE: To characterize white matter alterations in children with isolated or concurrent developmental coordination disorder and/or attention-deficit/hyperactivity disorder (ADHD) compared with typically-developing controls, and to determine whether group differences on motor and attention tasks could be explained by differences in diffusion tensor imaging (DTI) measures. STUDY DESIGN: In a cohort of children (n = 85) with developmental coordination disorder, ADHD, or combined developmental coordination disorder+ADHD, we examined 3 major white matter tracts involved in attention and motor processes. Using DTI, the corpus callosum, superior longitudinal fasciculus, and cingulum were analyzed with respect to measures of white matter integrity. Differences in fractional anisotropy (FA), mean diffusivity, radial diffusivity, and axial diffusivity were analyzed using ANOVA. Motor and attentional functioning was assessed using standardized tests, and correlated to DTI measures. RESULTS: FA reductions were noted in the frontal regions of the corpus callosum for children with ADHD (P = .039), whereas children with developmental coordination disorder displayed similar reductions in regions of the corpus callosum underlying parietal brain regions (P = .040), as well as the left superior longitudinal fasciculus (P = .026). White matter integrity was impacted in both frontal and parietal regions for children with comorbid developmental coordination disorder+ADHD (P = .029; .046). FA was positively correlated with scores on both motor and attentional assessments in a region-specific manner. CONCLUSION: Our findings suggest that alterations in the corpus callosum underlie difficulties in motor and attention functioning. These changes are functionally and regionally distinct and could reflect a neurobiological basis for motor and attention disorders in children.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".