Motor units in the human medial gastrocnemius muscle are not spatially localized or functionally grouped
Bibliographic record
Abstract
KEY POINTS: Human medial gastrocnemius (MG) motor units (MUs) are thought to occupy small muscle territories or regions, with low-threshold units preferentially located distally. We used intramuscular recordings to measure the territory of muscle fibres from MG MUs and determine whether these MUs are grouped by recruitment threshold or joint action (ankle plantar flexion and knee flexion). The territory of MUs from the MG muscle varied from somewhat localized to highly distributed, with approximately half the MUs spanning at least half the length and width of the muscle. There was also no evidence of regional muscle activity based on MU recruitment thresholds or joint action. The CNS does not have the means to selectively activate regions of the MG muscle based on task requirements. ABSTRACT: Human medial gastrocnemius (MG) motor units (MUs) are thought to occupy small muscle territories, with low-threshold units preferentially located distally. In this study, subjects (n = 8) performed ramped and sustained isometric contractions (ankle plantar flexion and knee flexion; range: ∼1-40% maximal voluntary contraction) and we measured MU territory size with spike-triggered averages from fine-wire electrodes inserted along the length (seven electrodes) or across the width (five electrodes) of the MG muscle. Of 69 MUs identified along the length of the muscle, 32 spanned at least half the muscle length (≥ 6.9 cm), 11 of which spanned all recording sites (13.6-17.9 cm). Distal fibres had smaller pennation angles (P < 0.05), which were accompanied by larger territories in MUs with fibres located distally (P < 0.05). There was no distal-to-proximal pattern of muscle activation in ramp contraction (P = 0.93). Of 36 MUs identified across the width of the muscle, 24 spanned at least half the muscle width (≥ 4.0 cm), 13 of which spanned all recording sites (8.0-10.8 cm). MUs were not localized (length or width) based on recruitment threshold or contraction type, nor was there a relationship between MU territory size and recruitment threshold (Spearman's rho = -0.20 and 0.13, P > 0.18). MUs in the human MG have larger territories than previously reported and are not localized based on recruitment threshold or joint action. This indicates that the CNS does not have the means to selectively activate regions of the MG muscle based on task requirements.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".