Neural control of rhythmic, cyclical human arm movement: task dependency, nerve specificity and phase modulation of cutaneous reflexes
Bibliographic record
Abstract
1. The organization and pattern of cutaneous reflex modulation during rhythmic cyclical movements of the human upper limbs has received much less attention than that afforded the lower limb. Our working hypothesis is that control mechanisms underlying the modulation of cutaneous reflex amplitude during rhythmic arm movement are similar to those that control reflex modulation in the leg. Thus, we hypothesized that cutaneous reflexes would show task dependency and nerve specificity in the upper limb during rhythmic cyclical arm movement as has been demonstrated in the human lower limb. 2. EMG was recorded from 10 muscles crossing the human shoulder, elbow and wrist joints while bilateral whole arm rhythmic cyclical movements were performed on a custom-made, hydraulic apparatus. 3. Cutaneous reflexes were evoked with trains (5 x 1.0 ms pulses at 300 Hz) of electrical stimulation delivered at non-noxious intensities (approximately 2 x threshold for radiating parasthesia) to the superficial radial, median and ulnar nerves innervating the hand. 4. Cutaneous reflexes were typically modulated with the movement cycle (i.e. phase dependency was observed). There was evidence for nerve specificity of cutaneous reflexes during rhythmic movement of the upper limbs. Task-dependent modulation was also seen as cutaneous reflexes were of larger amplitude or inhibitory (reflex reversal) during arm cycling as compared to static contraction. 5. While there are some differences in the patterns of cutaneous reflex modulation seen between the arms and legs, it is concluded that cutaneous reflexes are modulated similarly in the upper and lower limbs implicating similar motor control mechanisms.
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.
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 | 0.001 |
| 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".