Feedforward control in children with cerebral palsy and association with white matter integrity
Bibliographic record
Abstract
Background: Precise upper limb movements required for daily activities rely on feedback and feedforward control mechanisms. In children with cerebral palsy (CP), damage to white matter tracts impairs motor execution and sensorimotor control. Most studies in CP have focused on motor execution deficits, whereas the relationship between feedforward control alterations and white matter microstructure features has received less attention. Method: This study compared feedforward control during a grasp and lift task in 9 children with CP (diagnosis of hemiplegic CP with mild to moderate upper limb deficits) to 40 typically developing (TD) children aged 8 to 17 years. A secondary objective was to examine associations between feedforward control and the microstructural measures of corticocerebellar and other motor-planning related tracts. All participants completed 13 trials of the grasp and lift task. The CP group also underwent diffusion magnetic resonance imaging (MRI) using a 3-Tesla system to acquire anatomical and diffusion MRI. Results: Results showed feedforward control deficits in the non-dominant hand of children with CP, reflected by reduced peak force rates before sensory feedback was available and a lack of adaptation across trials. Strong correlations were observed between feedforward control and microstructural measures of the corticospinal tract and superior longitudinal fasciculus, but not with the corticocerebellar tracts. Conclusion: These findings suggest that broader sensorimotor processes, beyond feedforward control alone, contribute to force control deficits observed in children with CP.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".