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Natural language signatures of psilocybin microdosing

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dc.contributor.author Sanz, Camila
dc.contributor.author Cavanna, Federico
dc.contributor.author Muller, Stephanie
dc.contributor.author de la Fuente, Laura A.
dc.contributor.author Zamberlan, Federico
dc.contributor.author Palmucci, Matías
dc.contributor.author Janeckova, Lucie
dc.contributor.author Kuchar, Martin
dc.contributor.author Carrillo, Facundo
dc.contributor.author García, Adolfo M.
dc.contributor.author Pallavicini, Carla
dc.contributor.author Tagliazucchi, Enzo
dc.date.accessioned 2022-10-20T11:33:26Z
dc.date.available 2022-10-20T11:33:26Z
dc.date.issued 2022-09
dc.identifier.citation Sanz C, Cavanna F, Muller S, de la Fuente L, Zamberlan F, Palmucci M, Janeckova L, Kuchar M, Carrillo F, García AM, Pallavicini C, Tagliazucchi E. Natural language signatures of psilocybin microdosing. Psychopharmacology (Berl). 2022 Sep;239(9):2841-2852. doi: 10.1007/s00213-022-06170-0. Epub 2022 Jun 9. es_ES
dc.identifier.uri https://repositorio.fleni.org.ar/xmlui/handle/123456789/697
dc.identifier.uri https://doi.org/10.1007/s00213-022-06170-0
dc.description.abstract 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. es_ES
dc.language.iso eng es_ES
dc.publisher Springer-Verlag es_ES
dc.rights info:eu-repo/semantics/openAccess
dc.rights.uri https://creativecommons.org/licenses/by/2.5/ar/
dc.subject Psychopharmacology
dc.subject Psicofarmacología
dc.subject Alucinógenos es_ES
dc.subject Hallucinogens es_ES
dc.subject Speech es_ES
dc.subject Habla es_ES
dc.title Natural language signatures of psilocybin microdosing es_ES
dc.type info:eu-repo/semantics/article es_ES
dc.type info:eu-repo/semantics/publishedVersion
dc.relation.ispartofVOLUME 239
dc.relation.ispartofNUMBER 9
dc.relation.ispartofPAGINATION 2841-2852.
dc.relation.ispartofPAGINATION Fil: Cavanna, Federico. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Instituto de Física de Buenos Aires; Argentina. Fleni. Instituto de Neurociencias FLENI-CONICET; Argentina.
dc.relation.ispartofPAGINATION Fil: Pallavicini, Carla. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Instituto de Física de Buenos Aires; Argentina. Fleni. Instituto de Neurociencias FLENI-CONICET; Argentina.
dc.relation.ispartofPAGINATION Fil: Sanz, Camila. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Instituto de Física de Buenos Aires; Argentina.
dc.relation.ispartofPAGINATION Fil: Muller, Stephanie. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Instituto de Física de Buenos Aires; Argentina.
dc.relation.ispartofPAGINATION Fil: de la Fuente, Laura A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Instituto de Física de Buenos Aires; Argentina. Universidad Favaloro; Argentina. INECO Foundation. Institute of Cognitive and Translational Neuroscience; Argentina.
dc.relation.ispartofPAGINATION Fil: Zamberlan, Federico. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Instituto de Física de Buenos Aires; Argentina. Tilburg University. Department of Cognitive Science and Artificial Intelligence; Países Bajos.
dc.relation.ispartofPAGINATION Fil: Palmucci, Matías. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Instituto de Física de Buenos Aires; Argentina.
dc.relation.ispartofPAGINATION Fil: Janeckova, Lucie. University of Chemistry and Technology Prague. Department of Chemistry of Natural Compounds. Forensic Laboratory of Biologically Active Substances; República Checa.
dc.relation.ispartofPAGINATION Fil: Kuchar, Martin. University of Chemistry and Technology Prague. Department of Chemistry of Natural Compounds. Forensic Laboratory of Biologically Active Substances; República Checa. National Institute of Mental Health. Department of Experimental Neurobiology; República Checa.
dc.relation.ispartofPAGINATION Fil: Carrillo, Facundo. Applied Artificial Intelligence Lab; Argentina.
dc.relation.ispartofPAGINATION Fil: García, Adolfo M. Universidad de San Andrés. Cognitive Neuroscience Center; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Trinity College Dublin. Global Brain Health Institute ; Irlanda. Universidad de Santiago de Chile. Facultad de Humanidades. Departamento de Lingüística y Literatura; Chile.
dc.relation.ispartofPAGINATION Fil: Tagliazucchi, Enzo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Instituto de Física de Buenos Aires; Argentina. Fleni. Universidad Adolfo Ibañez. Latin American Brain Health Institute; Chile.
dc.relation.ispartofCOUNTRY Alemania
dc.relation.ispartofCITY Berlín
dc.relation.ispartofTITLE Psychopharmacology
dc.relation.ispartofISSN 1432-2072
dc.type.snrd info:ar-repo/semantics/artículo es_ES


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