Classification of psychedelics and psychoactive drugs based on brain-wide imaging of cellular c-Fos expression.
bioRxiv : the preprint server for biology November 23, 2024 Farid Aboharb, Pasha A Davoudian, Ling-Xiao Shao et al. 3 citations preprint
A pipeline using light sheet fluorescence microscopy to measure immediate early gene expression in mouse brain tissues, combined with machine learning, can classify psychoactive drugs including psilocybin, ketamine, and MDMA. In one-versus-rest tests, the exact drug was identified with 67% accuracy, far above the 12.5% chance level. Psilocybin was discriminated from 5-MeO-DMT, ketamine, MDMA, or acute fluoxetine with over 95% accuracy in pairwise comparisons. Shapley additive explanation identified brain regions driving the predictions. The approach offers a novel way to characterize and validate psychedelic and related compounds.