Detection of acute 3,4-methylenedioxymethamphetamine (MDMA) effects across protocols using automated natural language processing.
Administration, Intranasal
Adult
Double-Blind Method
Female
Humans
Language
Male
N-Methyl-3,4-methylenedioxyamphetamine
/ administration & dosage
Neuropsychological Tests
Oxytocin
/ administration & dosage
Psycholinguistics
Psychotropic Drugs
/ administration & dosage
Semantics
Speech
/ drug effects
Young Adult
Journal
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
ISSN: 1740-634X
Titre abrégé: Neuropsychopharmacology
Pays: England
ID NLM: 8904907
Informations de publication
Date de publication:
04 2020
04 2020
Historique:
received:
23
08
2019
accepted:
08
01
2020
revised:
28
11
2019
pubmed:
25
1
2020
medline:
31
3
2021
entrez:
25
1
2020
Statut:
ppublish
Résumé
The detection of changes in mental states such as those caused by psychoactive drugs relies on clinical assessments that are inherently subjective. Automated speech analysis may represent a novel method to detect objective markers, which could help improve the characterization of these mental states. In this study, we employed computer-extracted speech features from multiple domains (acoustic, semantic, and psycholinguistic) to assess mental states after controlled administration of 3,4-methylenedioxymethamphetamine (MDMA) and intranasal oxytocin. The training/validation set comprised within-participants data from 31 healthy adults who, over four sessions, were administered MDMA (0.75, 1.5 mg/kg), oxytocin (20 IU), and placebo in randomized, double-blind fashion. Participants completed two 5-min speech tasks during peak drug effects. Analyses included group-level comparisons of drug conditions and estimation of classification at the individual level within this dataset and on two independent datasets. Promising classification results were obtained to detect drug conditions, achieving cross-validated accuracies of up to 87% in training/validation and 92% in the independent datasets, suggesting that the detected patterns of speech variability are associated with drug consumption. Specifically, we found that oxytocin seems to be mostly driven by changes in emotion and prosody, which are mainly captured by acoustic features. In contrast, mental states driven by MDMA consumption appear to manifest in multiple domains of speech. Furthermore, we find that the experimental task has an effect on the speech response within these mental states, which can be attributed to presence or absence of an interaction with another individual. These results represent a proof-of-concept application of the potential of speech to provide an objective measurement of mental states elicited during intoxication.
Identifiants
pubmed: 31978933
doi: 10.1038/s41386-020-0620-4
pii: 10.1038/s41386-020-0620-4
pmc: PMC7075895
doi:
Substances chimiques
Psychotropic Drugs
0
Oxytocin
50-56-6
N-Methyl-3,4-methylenedioxyamphetamine
KE1SEN21RM
Types de publication
Journal Article
Randomized Controlled Trial
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
823-832Subventions
Organisme : NIDA NIH HHS
ID : R01 DA002812
Pays : United States
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