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dc.contributorVirginia Techen
dc.contributor.authorKoshelev, Mishaen
dc.contributor.authorLohrenz, Terryen
dc.contributor.authorVannucci, Marinaen
dc.contributor.authorMontague, P. Readen
dc.date.accessioned2017-09-26T13:07:51Zen
dc.date.available2017-09-26T13:07:51Zen
dc.date.issued2010-10-21en
dc.identifier.urihttp://hdl.handle.net/10919/79417en
dc.description.abstractWe used a multi-round, two-party exchange game in which a healthy subject played a subject diagnosed with a DSM-IV (Diagnostic and Statistics Manual-IV) disorder, and applied a Bayesian clustering approach to the behavior exhibited by the healthy subject. The goal was to characterize quantitatively the style of play elicited in the healthy subject (the proposer) by their DSM-diagnosed partner (the responder). The approach exploits the dynamics of the behavior elicited in the healthy proposer as a biosensor for cognitive features that characterize the psychopathology group at the other side of the interaction. Using a large cohort of subjects (n = 574), we found statistically significant clustering of proposers’ behavior overlapping with a range of DSM-IV disorders including autism spectrum disorder, borderline personality disorder, attention deficit hyperactivity disorder, and major depressive disorder. To further validate these results, we developed a computer agent to replace the human subject in the proposer role (the biosensor) and show that it can also detect these same four DSM-defined disorders. These results suggest that the highly developed social sensitivities that humans bring to a two-party social exchange can be exploited and automated to detect important psychopathologies, using an interpersonal behavioral probe not directly related to the defining diagnostic criteria.en
dc.language.isoen_USen
dc.publisherPLOSen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.titleBiosensor Approach to Psychopathology Classificationen
dc.typeArticle - Refereeden
dc.title.serialPLOS Computational Biologyen
dc.identifier.doihttps://doi.org/10.1371/journal.pcbi.1000966.g001en
dc.identifier.volume6en
dc.identifier.issue10en


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