Cannabinoids Elicit Antidepressant-Like Behavior and Activate Serotonergic Neurons through the Medial Prefrontal Cortex
Bibliographic record
Abstract
Preclinical and clinical studies show that cannabis modulates mood and possesses antidepressant-like properties, mediated by the agonistic activity of cannabinoids on central CB1 receptors (CB1Rs). The action of CB1R agonists on the serotonin (5-HT) system, the major transmitter system involved in mood control and implicated in the mechanism of action of antidepressants, remains however poorly understood. In this study, we demonstrated that, at low doses, the CB1R agonist WIN55,212-2 [R(+)-[2,3-dihydro-5-methyl-3-[(morpholinyl)]pyrrolo[1,2,3-de]-1,4-benzoxazinyl]-(1-naphthalenyl) methanone mesylate] exerts potent antidepressant-like properties in the rat forced-swim test (FST). This effect is CB1R dependent because it was blocked by the CB1R antagonist rimonabant and is 5-HT mediated because it was abolished by pretreatment with the 5-HT-depleting agent parachlorophenylalanine. Then, using in vivo electrophysiology, we showed that low doses of WIN55,212-2 dose dependently enhanced dorsal raphe nucleus 5-HT neuronal activity through a CB1R-dependent mechanism. Conversely, high doses of WIN55,212-2 were ineffective in the FST and decreased 5-HT neuronal activity through a CB1R-independent mechanism. The CB1R agonist-induced enhancement of 5-HT neuronal activity was abolished by total or medial prefrontocortical, but not by lateral prefrontocortical, transection. Furthermore, 5-HT neuronal activity was enhanced by the local microinjection of WIN55,212-2 into the ventromedial prefrontal cortex (mPFCv) but not by the local microinjection of WIN55,212-2 into the lateral prefrontal cortex. Similarly, the microinjection of WIN55,212-2 into the mPFCv produced a CB1R-dependent antidepressant-like effect in the FST. These results demonstrate that CB1R agonists possess antidepressant-like properties and modulate 5-HT neuronal activity via the mPFCv.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".