Anatomically remote muscle contraction facilitates patellar tendon reflex reinforcement while mental activity does not: a within-participants experimental trial
Bibliographic record
Abstract
BACKGROUND: The Jendrassik maneuver (JM) is a remote facilitation muscular contraction shown to affect amplitude and temporal components of the human stretch reflex. Conflicting theoretical models exist regarding the neurological mechanism related to its ability to reinforce reflex parameters. One mechanism involves the gamma motoneurons of the fusimotor system, which are subject to both physical and mental activity. A second mechanism describes reduced alpha motoneuron presynaptic inhibition, which is not subject to mental activity. In the current study, we determined if mental activity could be used to create a reflex facilitation comparable to a remote muscle contraction. METHOD: Using a within-participants design, we investigated the relative effect of the JM and a successfully employed mental task (Stroop task) on the amplitude and temporal components of the patellar tendon reflex. RESULTS: We found that the addition of mental activity had no influence on the patellar tendon reflex parameters measured, while the JM provided facilitation (increased reflex amplitude, decreased total reflex time). CONCLUSION: The findings from this study support the view that the mechanism for the JM is a reduction in presynaptic inhibition of alpha motoneurons as it is influenced by physical and not mental activity.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".