Defining the neuroanatomic basis of motor coordination in children and its relationship with symptoms of attention-deficit/hyperactivity disorder
Bibliographic record
Abstract
BACKGROUND: When children have marked problems with motor coordination, they often have problems with attention and impulse control. Here, we map the neuroanatomic substrate of motor coordination in childhood and ask whether this substrate differs in the presence of concurrent symptoms of attention-deficit/hyperactivity disorder (ADHD). METHOD: Participants were 226 children. All completed Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5)-based assessment of ADHD symptoms and standardized tests of motor coordination skills assessing aiming/catching, manual dexterity and balance. Symptoms of developmental coordination disorder (DCD) were determined using parental questionnaires. Using 3 Tesla magnetic resonance data, four latent neuroanatomic variables (for the cerebral cortex, cerebellum, basal ganglia and thalamus) were extracted and mapped onto each motor coordination skill using partial least squares pathway modeling. RESULTS: The motor coordination skill of aiming/catching was significantly linked to latent variables for both the cerebral cortex (t = 4.31, p < 0.0001) and the cerebellum (t = 2.31, p = 0.02). This effect was driven by the premotor/motor cortical regions and the superior cerebellar lobules. These links were not moderated by the severity of symptoms of inattention, hyperactivity and impulsivity. In categorical analyses, the DCD group showed atypical reduction in the volumes of these regions. However, the group with DCD alone did not differ significantly from those with DCD and co-morbid ADHD. CONCLUSIONS: The superior cerebellar lobules and the premotor/motor cortex emerged as pivotal neural substrates of motor coordination in children. The dimensions of these motor coordination regions did not differ significantly between those who had DCD, with or without co-morbid ADHD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".