Anatomical, biomechanical and behavioural characteristics of the human masseter muscle
Bibliographic record
Abstract
There is little information on the anatomical and functional organization of the human jaw muscles, despite their importance to the masticatory system and disorders which affect it. The current studies examined the anatomical, biomechanical and functional characteristics in the multipennate human masseter muscle as a model for understanding function in the human jaw. Masseter anatomy was investigated in fetuses, adult cadavers, and living subjects by histology, gross anatomical dissection and Magnetic-Resonance (MR) imaging. Nerve pathways and muscle-fibre arrangements suggested that both fetal and adult muscles could be divided into at least four neuromuscular compartments. Although some fetal specimens had developed peimation, internal aponeuroses were seldom present. Structural variations were also found in the cadaveric material and living subjects. As the number of aponeuroses increased with development, and their thickness varied between individuals, individualized contraction strategies are likely to occur during function. Movements of masseter insertion sites during jaw function were modelled in dry skulls. Muscle origins and insertions were measured three-dimensionally at different gapes and simulated masticatory positions. Their movements varied with craniofacial dimensions and their locations on the mandible. For some parts of the muscle, the balancing-side and the incisal-contact positions provided the most advantageous lines of muscle fibre action, while for others, the working-side task was most favourable. Separate portions of the muscle are thus uniquely placed to perform specific tasks. Movements of four insertion sites were also recorded in four living subjects. Insertion areas were identified on MR-derived reconstructions, and movements recorded with a jaw-tracking device. Ranges of insertion displacement were similar to these estimated for dry skulls, and varied between individuals. Interference electromyography, and single-motor-unit (MU) techniques were used to study physiological responses in eight subjects. The behaviour of low-threshold MUs was investigated relative to changes in bite side and experimental paradigm while subjects were biting on a force transducer. For each unit, the recruitment threshold, sustained-bite forces, the rate and regularity of sustained firing, and the coefficient of variation, were measured. Assessments were also made of the accuracy with which the target rates were attained, and of the contribution of each MU’s firing rate to bite force. These measures of behaviour frequently differed between tasks, but not reproducibly. The highest reproducibility and firing-rate accuracy were achieved when visual and auditory MU feedback was provided. A tendency for increased firing rate, and decreased discharge variability was found when subjects had no feedback. As approximately 50% of the units did not show reproducible behavioural characteristics, it seems that differences in intramuscular activation, differential activation of other muscles, and the inherent variability seen in low-threshold MU studies generally make quantitative comparisons of focal activity in the masseter implausible. Finally, a method was developed for locating the positions of moving needle electrodes relative to internal aponeuroses. It combined scanning electromyography, optical tracking of electrodes, MR imaging, and three-dimensional reconstruction. The territorial sizes of 162 MUs were then assessed in the muscles of four subjects. Their mean width was 3.7 ± 2.3 mm. Most MU territories were confined between tendons, although 10% of the units clearly extended across at least one tendon. This focal dispersion of most territories provides a firm anatomical basis for selective activation of the muscle. The findings collectively indicate an anatomical, biomechanical and physiological basis for differential motor control of at least four neuromuscular compartments in the human masseter muscle. The extent to which the central nervous system selectively activates these compartments, or coactivates them, remains to be demonstrated under functional conditions.
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 | 0.000 |
| 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".