Brain Activation of Children With Developmental Coordination Disorder is Different Than Peers
Bibliographic record
Abstract
OBJECTIVES: Children with developmental coordination disorder (DCD) struggle to learn new motor skills, demonstrating more variable performance than typically developing (TD) children. The purpose of this study was to determine whether patterns of brain activity differed between children with and without DCD while performing a motor task. METHODS: Using functional MRI, we measured brain activation patterns in 7 children with DCD and 7 age-matched peers (aged 8-12 years) during a fine-motor, trail-tracing task. RESULTS: Despite similar levels of behavioral motor performance, different patterns of brain activity were noted between the 2 groups. The group with DCD showed significantly more activation than control subjects in left inferior parietal lobule, right middle frontal gyrus, right supramarginal gyrus, right lingual gyrus, right parahippocampal gyrus, right posterior cingulate gyrus, right precentral gyrus, right superior temporal gyrus, and right cerebellar lobule VI. These results suggest that the group with DCD relied on visuospatial processing to complete the task. The TD group demonstrated significantly more activation than the group with DCD in left precuneus, left superior frontal gyrus, right superior temporal gyrus/insula, left inferior frontal gyrus, and left postcentral gyrus; these regions have been associated with spatial processing, motor control and learning, and error processing. CONCLUSIONS: Children with DCD activate different brain regions from typical children when performing the same trail-tracing task. Despite the small sample size, our results contribute to a growing body of literature suggesting that children with DCD exhibit differences in neural networks and patterns of brain activation relative to same-age peers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".