Neuromuscular activation and motor-unit firing characteristics in cerebral palsy
Bibliographic record
Abstract
Muscle strength, neuromuscular activation, and motor-unit firing characteristics (firing rate, recruitment, and short-term synchronization) were assessed during voluntary contractions of the medial gastrocnemius (GAS) and tibialis anterior (TA) muscles of 10 participants with spastic diplegic or hemiplegic cerebral palsy (CP). The participants (six females, four males; age range 6 to 37y) walked with equinus gait at Gross Motor Function Classification System levels II to III. These were compared with 10 age-matched controls (five females; age range 7 to 35y). Neuromuscular activation was estimated by the ratio of surface electromyogram amplitude to M-wave amplitude elicited by supramaximal electrical nerve stimulation. Participants with CP produced significantly less torque (normalized by leg length) compared with controls (TA: mean 2.3, SD 1.6 vs mean 8.9, SD 3.4N m/m; GAS mean 13.7, SD 7.1 vs mean 28.6, SD 5.1Nm/m, p<0.001). Neuromuscular activation during maximum voluntary contraction was significantly reduced in the participants with CP compared with controls (mean 2.4, SD 1.5 vs mean 9.7, SD 2.7Nm/m for TA; mean 1.04, SD 0.41 vs mean 3.1, SD 1.2Nm/m for GAS, p<0.001). When compared at the same submaximal level of neuromuscular activation, motor-unit recruitment and firing rates were not different between the groups, although short-term synchronization in TA was reduced in the participants with CP. These data indicate that weakness, known to be an important component of the motor deficit in CP, has a strong central component. Although the relation between recruitment and firing rate remained substantially intact at the low and moderate force contractions tested, results suggest that the participants with CP were unable to recruit higher threshold motor units or to drive lower threshold motor units to higher firing rates.
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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 | 0.000 |
| 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".