Differential effects of psilocybin and lisuride on serotonin and dopamine neuronal activity and behavior
Bibliographic record
Abstract
Psilocybin and lisuride are 5-HT 2A receptor agonists, but only psilocybin elicits the head twitch response (HTR) in rodents, a behavior commonly used as a proxy for hallucinogenic activity. This study aimed to compare their effects on serotonin (5-HT) and dopamine (DA) neuronal activity, as well as related behavioral outcomes, to elucidate the mechanisms underlying their divergent effects. Adult male C57BL/6 N mice were administered intraperitoneal injections of psilocybin (0.3–3 mg/kg), lisuride (0.1–0.5 mg/kg), or vehicle. In vivo electrophysiological recordings were performed in the dorsal raphe nucleus (DRN) and substantia nigra (SN) to monitor 5-HT and DA neuronal firing. MDL 100907 (0.2 mg/kg) pretreatment was used to determine 5-HT 2A receptor specificity. Behavioral assessments included HTR testing 10 min post-injection, followed by either the forced swim test (FST), open field test (OFT), or elevated plus maze (EPM) at 20 min post-injection. Psilocybin-induced inhibition, but not lisuride-induced inhibition, of 5-HT neuron firing was blocked by MDL 100907. Both drugs reduced DA neuron firing, however, lisuride's effect was more sensitive to 5-HT 2A receptor antagonism. Psilocybin elicited HTR, while lisuride did not. In the FST, only high-dose lisuride reduced immobility time. Both drugs reduced locomotor activity in the OFT and EPM. Principal Component Analysis (PCA) sufficiently separated the effects of each drug from each other, indicating distinct effect profiles. Although both drugs target 5-HT 2A receptors, they engage distinct neurobiological pathways. Psilocybin produces psychedelic-like, 5-HT–dominant effects, whereas lisuride displays DA-linked improvements in coping behavior, informing future development of serotonergic therapeutics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".