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Biosensor approach to psychopathology classification.

Koshelev M, Lohrenz T, Vannucci M, Montague PR - PLoS Comput. Biol. (2010)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Program in Cell and Molecular Biology, Baylor College of Medicine, Houston, Texas, USA.

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. 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.

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Interpersonal trust scale correlates with assignment of dyads with BPD trustees to cluster 3.For dyads with Borderline Personality Disorder, Medicated and Non-Medicated [6], assigned to cluster 3, in which they are over-represented, we analyzed the correlation of the (i) percent match of the dyad into cluster 3 from 30,000 draws from the posterior and (ii) the score on the Interpersonal Trust Scale [29] of the BPD individual playing in the trustee role (self-report, lower score implies less trust). We found a correlation with  and  ().
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pcbi-1000966-g004: Interpersonal trust scale correlates with assignment of dyads with BPD trustees to cluster 3.For dyads with Borderline Personality Disorder, Medicated and Non-Medicated [6], assigned to cluster 3, in which they are over-represented, we analyzed the correlation of the (i) percent match of the dyad into cluster 3 from 30,000 draws from the posterior and (ii) the score on the Interpersonal Trust Scale [29] of the BPD individual playing in the trustee role (self-report, lower score implies less trust). We found a correlation with and ().

Mentions: For two disorders, there are known scores describing its severity: for ASD, there is a score on the Autism Diagnostic Interview-Revised [28] Repetitive behavior subscale, and for BPD, there is a score on the Interpersonal Trust Scale [29]. In both cases, we found a statistically significant correlation between these scores and the probability of belonging to the corresponding cluster ( = percent match of the dyad in this cluster from 30,000 draws from the posterior): and for ASD (Figure 3) and and for BPD (Figure 4).


Biosensor approach to psychopathology classification.

Koshelev M, Lohrenz T, Vannucci M, Montague PR - PLoS Comput. Biol. (2010)

Interpersonal trust scale correlates with assignment of dyads with BPD trustees to cluster 3.For dyads with Borderline Personality Disorder, Medicated and Non-Medicated [6], assigned to cluster 3, in which they are over-represented, we analyzed the correlation of the (i) percent match of the dyad into cluster 3 from 30,000 draws from the posterior and (ii) the score on the Interpersonal Trust Scale [29] of the BPD individual playing in the trustee role (self-report, lower score implies less trust). We found a correlation with  and  ().
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2958801&req=5

pcbi-1000966-g004: Interpersonal trust scale correlates with assignment of dyads with BPD trustees to cluster 3.For dyads with Borderline Personality Disorder, Medicated and Non-Medicated [6], assigned to cluster 3, in which they are over-represented, we analyzed the correlation of the (i) percent match of the dyad into cluster 3 from 30,000 draws from the posterior and (ii) the score on the Interpersonal Trust Scale [29] of the BPD individual playing in the trustee role (self-report, lower score implies less trust). We found a correlation with and ().
Mentions: For two disorders, there are known scores describing its severity: for ASD, there is a score on the Autism Diagnostic Interview-Revised [28] Repetitive behavior subscale, and for BPD, there is a score on the Interpersonal Trust Scale [29]. In both cases, we found a statistically significant correlation between these scores and the probability of belonging to the corresponding cluster ( = percent match of the dyad in this cluster from 30,000 draws from the posterior): and for ASD (Figure 3) and and for BPD (Figure 4).

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Program in Cell and Molecular Biology, Baylor College of Medicine, Houston, Texas, USA.

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. 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.

Show MeSH
Related in: MedlinePlus