Applicability of the theory of pain-sensorimotor interactions to orofacial pain and sensorimotor behavior, and implications for orofacial pain research and management
Bibliographic record
Abstract
The orofacial sensorimotor system encompasses a variety of orofacial tissues as well as several pathways and circuits in the central nervous system (CNS) that participate in orofacial sensorimotor behaviors such as chewing, facial expression, speech, and swallowing. Acute or chronic pain can severely affect these behaviors, but the relationships between sensorimotor behaviors and pain, and the factors influencing the interactions and underlying mechanisms have remained unclear. Several theories proposed to account for the interactions and mechanisms have not provided a comprehensive picture of pain-sensorimotor interactions, nor fully acknowledged the diversity of biopsychosocial factors that may affect pain-related sensorimotor behaviors and the musculoskeletal tissues involved in the behaviors, and that may also contribute to the inter-individual and sex differences in pain-sensorimotor interactions. Such considerations prompted, last year, a review that has provided new perspectives of pain-sensorimotor interactions, and identified the wide range of biological, psychological, and sociocultural factors that may influence the interactions and underlying mechanisms. It also resulted in a novel theory being proposed, the Theory of Pain-Sensorimotor Interactions (TOPSMI), which has provided a more comprehensive mechanistic framework to consider the interactions between sensorimotor behaviors and pain, and their complexity. Since the new perspectives leading to TOPSMI were derived mainly from findings in the spinal sensorimotor system, the present article aims to determine the particular applicability of TOPSMI to orofacial pain-sensorimotor interactions. It reviews orofacial pain-related sensorimotor behaviors and the nociceptive pathways, CNS circuits and their plasticity, and musculoskeletal tissues involved in these behaviors, as well as the influences of psychosocial, genetic, epigenetic, and environmental factors bearing specifically on orofacial pain-sensorimotor interactions. The article concludes that the basic tenets of TOPSMI are applicable to orofacial pain-sensorimotor interactions and that this has implications for the clinical management of orofacial pain and future research in this field.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".