Computational Phenotyping of Two-Person Interactions Reveals Differential Neural Response to Depth-of-Thought

dc.contributor.authorXiang, Tingen
dc.contributor.authorRay, Debajyotien
dc.contributor.authorLohrenz, Terryen
dc.contributor.authorDayan, Peteren
dc.contributor.authorMontague, P. Readen
dc.date.accessioned2014-07-03T14:13:00Zen
dc.date.available2014-07-03T14:13:00Zen
dc.date.issued2012-12-27en
dc.description.abstractReciprocating exchange with other humans requires individuals to infer the intentions of their partners. Despite the importance of this ability in healthy cognition and its impact in disease, the dimensions employed and computations involved in such inferences are not clear. We used a computational theory-of-mind model to classify styles of interaction in 195 pairs of subjects playing a multi-round economic exchange game. This classification produces an estimate of a subject's depth-of-thought in the game (low, medium, high), a parameter that governs the richness of the models they build of their partner. Subjects in each category showed distinct neural correlates of learning signals associated with different depths-of-thought. The model also detected differences in depth-of-thought between two groups of healthy subjects: one playing patients with psychiatric disease and the other playing healthy controls. The neural response categories identified by this computational characterization of theory-of-mind may yield objective biomarkers useful in the identification and characterization of pathologies that perturb the capacity to model and interact with other humans.en
dc.description.sponsorshipThis work was supported by a Wellcome Trust Principal Research Fellowship (PRM), The Kane Family Foundation (PRM), NIDA grant R01DA11723 (PRM), NIMH grant R01MH085496 (PRM), NIA grant RC4AG039067 (PRM), and The Gatsby Charitable Foundation (DR, PD). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.en
dc.identifier.citationXiang T, Ray D, Lohrenz T, Dayan P, Montague PR (2012) Computational Phenotyping of Two-Person Interactions Reveals Differential Neural Response to Depth-of-Thought. PLoS Comput Biol 8(12): e1002841. doi:10.1371/journal.pcbi.1002841en
dc.identifier.issn1553-7358en
dc.identifier.urihttp://hdl.handle.net/10919/49307en
dc.language.isoen_USen
dc.publisherPublic Library of Scienceen
dc.rightsCreative Commons CC0 1.0 Universal Public Domain Dedicationen
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/en
dc.subjectAgent-based modelingen
dc.subjectBehavioren
dc.subjectDiagnostic medicineen
dc.subjectGamesen
dc.subjectLearningen
dc.subjectNeostriatumen
dc.subjectPersonality disordersen
dc.subjectSimulation and modelingen
dc.titleComputational Phenotyping of Two-Person Interactions Reveals Differential Neural Response to Depth-of-Thoughten
dc.typeArticle - Refereeden

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
journal.pcbi.1002841.pdf
Size:
537.58 KB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
Name:
license.txt
Size:
1.5 KB
Format:
Item-specific license agreed upon to submission
Description: