RATIONALE: Serotonergic psychedelics are being studied as novel treatments for mental health disorders and as facilitators of improved well-being, mental function, and creativity. Recent studies have found mixed results concerning the effects of low doses of psychedelics ("microdosing") on these domains. However, microdosing is generally investigated using instruments designed to assess larger doses of psychedelics, which might lack sensitivity and specificity for this purpose. OBJECTIVES: Determine whether unconstrained speech contains signatures capable of identifying the acute effects of psilocybin microdoses. METHODS: Natural speech under psilocybin microdoses (0.5 g of psilocybin mushrooms) was acquired from thirty-four healthy adult volunteers (11 females: 32.09 ± 3.53 years; 23 males: 30.87 ± 4.64 years) following a double-blind and placebo-controlled experimental design with two measurement weeks per participant. On Wednesdays and Fridays of each week, participants consumed either the active dose (psilocybin) or the placebo (edible mushrooms). Features of interest were defined based on variables known to be affected by higher doses: verbosity, semantic variability, and sentiment scores. Machine learning models were used to discriminate between conditions. Classifiers were trained and tested using stratified cross-validation to compute the AUC and p-values. RESULTS: Except for semantic variability, these metrics presented significant differences between a typical active microdose and the inactive placebo condition. Machine learning classifiers were capable of distinguishing between conditions with high accuracy (AUC [Formula: see text] 0.8). CONCLUSIONS: These results constitute first evidence that low doses of serotonergic psychedelics can be identified from unconstrained natural speech, with potential for widely applicable, affordable, and ecologically valid monitoring of microdosing schedules.

Applied Artificial Intelligence Lab CABA Buenos Aires Argentina

Cognitive Neuroscience Center Universidad de San Andrés Buenos Aires Argentina

Departamento de Física Universidad de Buenos Aires and Instituto de Física de Buenos Aires CABA Buenos Aires Argentina

Departamento de Lingüística Y Literatura Facultad de Humanidades Universidad de Santiago de Chile Santiago Chile

Department of Cognitive Science and Artificial Intelligence Tilburg University Tilburg the Netherlands

Department of Experimental Neurobiology National Institute of Mental Health Klecany Czech Republic

Forensic Laboratory of Biologically Active Substances Department of Chemistry of Natural Compounds University of Chemistry and Technology Prague Prague Czech Republic

Fundación Para La Lucha Contra Las Enfermedades Neurológicas de La Infancia Montañeses 2325 C1428 CABA Buenos Aires Argentina

Global Brain Health Institute Dublin Ireland

Global Brain Health Institute University of California San Francisco San Francisco CA USA

Institute of Cognitive and Translational Neuroscience INECO Foundation Favaloro University Buenos Aires Argentina

Latin American Brain Health Institute Universidad Adolfo Ibañez Santiago Chile

National Scientific and Technical Research Council Buenos Aires Argentina

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