Jaw-Opening Reflex and Corticobulbar Motor Excitability Changes During Quiet Sleep in Non-Human Primates
Bibliographic record
Abstract
STUDY OBJECTIVE: To test the hypothesis that the reflex and corticobulbar motor excitability of jaw muscles is reduced during sleep. DESIGN: Polysomnographic recordings in the electrophysiological study. SETTING: University sleep research laboratories. PARTICIPANTS AND INTERVENTIONS: The reflex and corticobulbar motor excitability of jaw muscles was determined during the quiet awake state (QW) and quiet sleep (QS) in monkeys (n = 4). MEASUREMENTS AND RESULTS: During QS sleep, compared to QW periods, both tongue stimulation-evoked jaw-opening reflex peak and root mean square amplitudes were significantly decreased with stimulations at 2-3.5 × thresholds (P < 0.001). The jaw-opening reflex latency during sleep was also significantly longer than during QW. Intracortical microstimulation (ICMS) within the cortical masticatory area induced rhythmic jaw movements at a stable threshold (≤ 60 μA) during QW; but during QS, ICMS failed to induce any rhythmic jaw movements at the maximum ICMS intensity used, although sustained jaw-opening movements were evoked at significantly increased threshold (P < 0.001) in one of the monkeys. Similarly, during QW, ICMS within face primary motor cortex induced orofacial twitches at a stable threshold (≤ 35 μA), but the ICMS thresholds were elevated during QS. Soon after the animal awoke, rhythmic jaw movements and orofacial twitches could be evoked at thresholds similar to those before QS. CONCLUSIONS: The results suggest that the excitability of reflex and corticobulbar-evoked activity in the jaw motor system is depressed during QS.
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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 | 0.000 | 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 | 0.001 |
| 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".