5-HT<sub>1A</sub>Receptor-Responsive Pedunculopontine Tegmental Neurons Suppress REM Sleep and Respiratory Motor Activity
Bibliographic record
Abstract
Serotonin type 1A (5-HT(1A)) receptor-responsive neurons in the pedunculopontine tegmental nucleus (PPTn) become maximally active immediately before and during rapid eye movement (REM) sleep. A prevailing model of REM sleep generation indicates that activation of such neurons contributes significantly to the generation of REM sleep, and if correct then inactivation of such neurons ought to suppress REM sleep. We test this hypothesis using bilateral microperfusion of the 5-HT(1A) receptor agonist 8-hydroxy-2-(di-n-propylamino)tetralin (8-OH-DPAT, 10 μm) into the PPTn; this tool has been shown to selectively silence REM sleep-active PPTn neurons while the activity of wake/REM sleep-active PPTn neurons is unaffected. Contrary to the prevailing model, bilateral microperfusion of 8-OH-DPAT into the PPTn (n = 23 rats) significantly increased REM sleep both as a percentage of the total recording time and sleep time, compared with both within-animal vehicle controls and between-animal time-controls. This increased REM sleep resulted from an increased frequency of REM sleep bouts but not their duration, indicating an effect on mechanisms of REM sleep initiation but not maintenance. Furthermore, an increased proportion of the REM sleep bouts stemmed from periods of low REM sleep drive quantified electrographically. Targeted suppression of 5-HT(1A) receptor-responsive PPTn neurons also increased respiratory rate and respiratory-related genioglossus activity, and increased the frequency and amplitude of the sporadic genioglossus activations occurring during REM sleep. These data indicate that 5-HT(1A) receptor-responsive PPTn neurons normally function to restrain REM sleep by elevating the drive threshold for REM sleep induction, and restrain the expression of respiratory rate and motor activities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".