biosensor approach to psychopathology classification生物传感器方法精神病理学分类.pdf

Biosensor Approach to Psychopathology Classification 1,2 3 2,4 1,2,3,4 Misha Koshelev , Terry Lohrenz , Marina Vannucci , P. Read Montague * 1 Program in Cell and Molecular Biology, Baylor College of Medicine, Houston, Texas, United States of America, 2 W. M. Keck Center for Interdisciplinary Bioscience Training, Houston, Texas, United States of America, 3 Department of Neuroscience, Computational Psychiatry Unit, Baylor College of Medicine, Houston, Texas, United States of America, 4 Department of Statistics, Rice University, Houston, Texas, United States of America Abstract We 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.