Neuronal Activity Patterns in Primate Primary Motor Cortex Related to Trained or Semiautomatic Jaw and Tongue Movements
Bibliographic record
Abstract
The present study was undertaken to determine the firing patterns and the mechanoreceptive field (RF) properties of neurons within the face primary motor cortex (face-MI) in relation to chewing and other orofacial movements in the awake monkey. Of a total of 107 face-MI neurons recorded, 73 of 74 tested had activity related to chewing and 47 of 66 neurons tested showed activity related to a trained tongue task. Of the 73 chewing-related neurons, 52 (71.2%) showed clear rhythmic activity during rhythmic chewing. A total of 32 (43.8%) also showed significant alterations in activity in relation to the swallowing of a solid food (apple) bolus. Many of the chewing-related neurons (81.8% of 55 tested) had an orofacial RF, which for most was on the tongue dorsum. Tongue protrusion was evoked by intracortical microstimulation (ICMS) at most (63.6%) of the recording sites where neurons fired during the rhythmic jaw-opening phase, whereas tongue retraction was evoked by ICMS at most (66.7%) sites at which the neurons firing during the rhythmic jaw-closing phase were recorded. Of the 47 task-related neurons, 21 of 22 (95.5%) examined also showed chewing-related activity and 29 (61.7%) demonstrated significant alteration in activity in relation to the swallowing of a juice reward. There were no significant differences in the peak firing frequency among neuronal activities related to chewing, swallowing, or the task. These findings provide further evidence that face-MI may play an important role not only in trained orofacial movements but also in chewing as well as swallowing, including the control of tongue and jaw movements that occur during the masticatory sequence.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".