Brain activation associated with motor skill practice in children with developmental coordination disorder: an fMRI study
Bibliographic record
Abstract
Children with developmental coordination disorder (DCD) have difficulty in learning new motor skills. At present, it is not known whether these children employ a different set of brain regions than typically developing (TD) children during skilled motor practice. Using functional magnetic resonance imaging, we mapped brain activity associated with skilled motor practice of a trail-tracing task in 7 children with DCD and 7 age-matched controls (aged 8-12 years). We indexed change in motor performance as a reduction in tracing error from early practice to retention. Children with DCD showed less blood-oxygen-level-dependent signal as compared to TD children in a network of brain regions associated with skilled motor practice: bilateral inferior parietal lobules (Brodmann Area (BA) 40), right lingual gyrus (BA 18), right middle frontal gyrus (BA 9), left fusiform gyrus (BA 37), right cerebellar crus I, left cerebellar lobule VI, and left cerebellar lobule IX. While no statistically significant differences were detected, effect size testing revealed that children with DCD demonstrated poorer tracing accuracy than TD children at retention (d=0.48). Our results suggest that, compared to TD peers, children with DCD demonstrate under-activation in cerebellar-parietal and cerebellar-prefrontal networks and in brain regions associated with visual-spatial learning. These data suggest a neurobiological correlation with impaired learning of motor skills in children with DCD, which will need to be confirmed with a larger sample.
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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 | 0.000 |
| 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".