Selective motor unit recruitment via intrafascicular multielectrode stimulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recruitment of force via independent asynchronous firing of large numbers of motor units produces the grace and endurance of physiological motion. We have investigated the possibility of reproducing this physiological recruitment strategy by determining the selectivity of access to large numbers of independent motor units through intrafascicular multielectrode stimulation (IFMS) of the peripheral nerve. A Utah Slanted Electrode Array containing 100, 0.5-1.5 mm-long penetrating electrodes was inserted into the sciatic nerve of a cat, and forces generated by the 3 heads of triceps surea in response to electrical stimulation of the nerve were monitored via force transducers attached to their tendons. We found a mean of 17.4 +/- 4.9 (mean +/- SEM) electrodes selectively excited maximal forces in medial gastrocnemius before exciting another muscle. Among electrodes demonstrating selectivity at threshold, a mean of 7.3 +/- 2.7 electrodes were shown to recruit independent populations of motor units innervating medial gastrocnemius (overlap < 20%). Corresponding numbers of electrodes were reported for lateral gastrocnemius and soleus, as well. We used these stimulation data to emulate physiological recruitment strategies, and found that independent motor unit pool recruitment approximates physiological activation more closely than does intensity-based recruitment or frequency-based recruitment.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it