REM Sleep at its Core – Circuits, Neurotransmitters, and Pathophysiology
Bibliographic record
Abstract
Rapid eye movement (REM) sleep is generated and maintained by the interaction of a variety of neurotransmitter systems in the brainstem, forebrain, and hypothalamus. Within these circuits lies a core region that is active during REM sleep, known as the subcoeruleus nucleus (SubC) or sublaterodorsal nucleus. It is hypothesized that glutamatergic SubC neurons regulate REM sleep and its defining features such as muscle paralysis and cortical activation. REM sleep paralysis is initiated when glutamatergic SubC cells activate neurons in the ventral medial medulla, which causes release of GABA and glycine onto skeletal motoneurons. REM sleep timing is controlled by activity of GABAergic neurons in the ventrolateral periaqueductal gray and dorsal paragigantocellular reticular nucleus as well as melanin-concentrating hormone neurons in the hypothalamus and cholinergic cells in the laterodorsal and pedunculo-pontine tegmentum in the brainstem. Determining how these circuits interact with the SubC is important because breakdown in their communication is hypothesized to underlie narcolepsy/cataplexy and REM sleep behavior disorder (RBD). This review synthesizes our current understanding of mechanisms generating healthy REM sleep and how dysfunction of these circuits contributes to common REM sleep disorders such as cataplexy/narcolepsy and RBD.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".