Detection of acute 3,4-methylenedioxymethamphetamine (MDMA) effects across protocols using automated natural language processing
Neuropsychopharmacology January 24, 2020 Carla Agurto, Guillermo Cecchi, Raquel Norel et al. 33 citations
Computer-extracted speech features from acoustic, semantic, and psycholinguistic domains can detect mental states after controlled administration of MDMA and intranasal oxytocin. In a double-blind, placebo-controlled study with 31 healthy adults, speech tasks during peak drug effects yielded cross-validated accuracies up to 87% in the training/validation set and 92% in independent datasets for classifying drug conditions. Oxytocin-driven changes were mostly captured by acoustic features related to emotion and prosody, while MDMA-related mental states manifested across multiple speech domains. The experimental task—whether involving interaction with another individual—also affected speech responses. These results suggest speech analysis can provide objective markers of drug-induced mental states.