The role of the γ-motor system in increasing muscle tone and muscle pain syndromes: A review of the Johansson/Sojka hypothesis
Bibliographic record
Abstract
OBJECTIVES: To review literature that pertained to the Johansson/Sojka hypothesis that positive feedback loops in the gamma-motor system are responsible for chronic muscle pain and increases in muscle tone. DATA SOURCES: Articles were selected from MEDLINE searches and from manual library searches. RESULTS: Normal, static, and ischemic muscle contractions and/or chemical mediators of inflammation excite intramuscular groups III and IV chemonociceptors. In groups III and IV, afferent firing stimulates gamma-motorneurons, which causes the firing of Ia and II muscle spindle afferents and increased extrafusal resistance to stretch (muscle tone). Some criticism of the involvement of the gamma-motor system in muscle tone was found to be dated or based on data from noncomparable research. Most of these studies (pro and con) were performed on prepared test animals, and the results may or may not translate to human subjects. CONCLUSIONS: There exists a sizable body of research that establishes a link between the activation of intramuscular chemonociceptors, increased gamma-motor activity, and increased Ia and II spindle output, as proposed by the hypothesis of Johansson and Sojka. However, because of the lack of sufficient data on human subjects, their hypothesis should not be considered proved. Further research into the effects of metabolites of muscle contraction and their effects on muscle tone is recommended. Research into subluxation/joint dysfunction in light of the Johansson/Sojka hypothesis is recommended.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".