Robotic-assisted stepping modulates monosynaptic reflexes in forearm muscles in the human
Bibliographic record
Abstract
Although the amplitude of the Hoffmann (H)-reflex in the forelimb muscles is known to be suppressed during rhythmic leg movement, it is unknown which factor plays a more important role in generating this suppression-movement-related afferent feedback or feedback related to body loading. To specifically explore the movement- and load-related afferent feedback, we investigated the modulation of the H-reflex in the flexor carpi radialis (FCR) muscle during robotic-assisted passive leg stepping. Passive stepping and standing were performed using a robotic gait-trainer system (Lokomat). The H-reflex in the FCR, elicited by electrical stimulation to the median nerve, was recorded at 10 different phases of the stepping cycle, as well as during quiet standing. We confirmed that the magnitude of the FCR H-reflex was suppressed significantly during passive stepping compared with during standing. The suppressive effect on the FCR H-reflex amplitude was seen at all phases of stepping, irrespective of whether the stepping was conducted with body weight loaded or unloaded. These results suggest that movement-related afferent feedback, rather than load-related afferent feedback, plays an important role in suppressing the FCR H-reflex amplitude.
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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".