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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 9 of 9 1 Identifying signals associated with psychiatric illness utilizing language and images posted to Facebook Birnbaum, Michael L.; Norel, Raquel; Van Meter, Anna... In: NPJ Schizophr (2020) BASE Show details 2 Language as a Biomarker for Psychosis: A Natural Language Processing Approach Corcoran, Cheryl M.; Mittal, Vijay A.; Bearden, Carrie E.... In: Schizophr Res (2020) BASE Show details 3 Detection of acute 3,4-methylenedioxymethamphetamine (MDMA) effects across protocols using automated natural language processing Agurto, Carla; Cecchi, Guillermo A.; Norel, Raquel. - : Springer International Publishing, 2020 BASE Show details 4 Differential 28-Days Cyclic Modulation of Affective Intensity in Female and Male Participants via Social Media Gallino, Lucila; Carrillo, Facundo; Cecchi, Guillermo A.. - : Frontiers Media S.A., 2019 BASE Show details 5 Prediction of psychosis across protocols and risk cohorts using automated language analysis Corcoran, Cheryl M.; Carrillo, Facundo; Fernández‐Slezak, Diego. - : John Wiley and Sons Inc., 2018 BASE Show details 6 Predicting natural language descriptions of mono-molecular odorants Gutiérrez, E. Darío; Dhurandhar, Amit; Keller, Andreas. - : Nature Publishing Group UK, 2018 BASE Show details 7 Fast Distributed Dynamics of Semantic Networks via Social Media Carrillo, Facundo; Cecchi, Guillermo A.; Sigman, Mariano. - : Hindawi Publishing Corporation, 2015 BASE Show details 8 A Window into the Intoxicated Mind? Speech as an Index of Psychoactive Drug Effects Bedi, Gillinder; Cecchi, Guillermo A; Slezak, Diego F; Carrillo, Facundo; Sigman, Mariano; de Wit, Harriet. - : Nature Publishing Group, 2014 Abstract: Abused drugs can profoundly alter mental states in ways that may motivate drug use. These effects are usually assessed with self-report, an approach that is vulnerable to biases. Analyzing speech during intoxication may present a more direct, objective measure, offering a unique ‘window' into the mind. Here, we employed computational analyses of speech semantic and topological structure after ±3,4-methylenedioxymethamphetamine (MDMA; ‘ecstasy') and methamphetamine in 13 ecstasy users. In 4 sessions, participants completed a 10-min speech task after MDMA (0.75 and 1.5 mg/kg), methamphetamine (20 mg), or placebo. Latent Semantic Analyses identified the semantic proximity between speech content and concepts relevant to drug effects. Graph-based analyses identified topological speech characteristics. Group-level drug effects on semantic distances and topology were assessed. Machine-learning analyses (with leave-one-out cross-validation) assessed whether speech characteristics could predict drug condition in the individual subject. Speech after MDMA (1.5 mg/kg) had greater semantic proximity than placebo to the concepts friend, support, intimacy, and rapport. Speech on MDMA (0.75 mg/kg) had greater proximity to empathy than placebo. Conversely, speech on methamphetamine was further from compassion than placebo. Classifiers discriminated between MDMA (1.5 mg/kg) and placebo with 88% accuracy, and MDMA (1.5 mg/kg) and methamphetamine with 84% accuracy. For the two MDMA doses, the classifier performed at chance. These data suggest that automated semantic speech analyses can capture subtle alterations in mental state, accurately discriminating between drugs. The findings also illustrate the potential for automated speech-based approaches to characterize clinically relevant alterations to mental state, including those occurring in psychiatric illness. Keyword: Original Article URL: https://doi.org/10.1038/npp.2014.80 http://www.ncbi.nlm.nih.gov/pubmed/24694926 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4138742/ BASE Hide details 9 Global organization of the Wordnet lexicon Sigman, Mariano; Cecchi, Guillermo A.. - : The National Academy of Sciences, 2002 BASE Show details

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