Cannabinoids promote NREM sleep via inhibition of prefrontal cortico-hypothalamic projections
Bibliographic record
Abstract
Abstract Cannabinoids promote non-rapid eye movement (NREM) sleep, but its underlying mechanism is not known. Here we find that cannabinoid promotion of NREM sleep is inhibited by cannabinoid antagonist injection systemically or into the dorsomedial hypothalamus (DMH), where cannabinoids selectively inhibit glutamatergic inputs synapsing with glutamatergic but not GABAergic neurons. Photoactivation of DMH-projecting ventromedial prefrontal cortical (vmPFC) neurons, their terminals, or their postsynaptic DMH neurons rapidly switches NREM sleep to wakefulness, which is blocked by photoinhibition of DMH outputs. Chemoactivation of DMH glutamatergic but not GABAergic neurons innervated by vmPFCs promotes wakefulness and suppresses NREM sleep, whereas chemoinhibition of vmPFC projections in DMHs produces opposite effects by mimicking cannabinoid effects. DMH-projecting vmPFC neurons are inhibited during NREM sleep and activated during wakefulness. Chemoactivation of DMH-projecting vmPFC neurons blocks cannabinoid promotion of NREM sleep and suppression of wakefulness. Thus, vmPFC neurons innervating DMHs represent the first identified set of cerebral cortical neurons for promotion of physiological wakefulness and suppression of NREM sleep, while cannabinoid inhibition of vmPFC projections in DMHs promotes NREM sleep and suppresses wakefulness.
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) | 0.003 | 0.001 |
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".