Differential Valuation and Learning From Social and Nonsocial Cues in Borderline Personality Disorder
Volatile interpersonal relationships are a core feature of borderline personality disorder (BPD) and lead to devastating disruption of patients’ personal and professional lives. Quantitative models of social decision making and learning hold promise for defining the underlying mechanisms of this pro...
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| Vydáno v: | Biological psychiatry (1969) Ročník 84; číslo 11; s. 838 - 845 |
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| Hlavní autoři: | , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
Elsevier Inc
01.12.2018
Elsevier |
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| ISSN: | 0006-3223, 1873-2402, 1873-2402 |
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| Abstract | Volatile interpersonal relationships are a core feature of borderline personality disorder (BPD) and lead to devastating disruption of patients’ personal and professional lives. Quantitative models of social decision making and learning hold promise for defining the underlying mechanisms of this problem. In this study, we tested BPD and control subject weighting of social versus nonsocial information and their learning about choices under stable and volatile conditions. We compared behavior using quantitative models.
Subjects (n = 20 BPD, n = 23 control subjects) played an extended reward learning task with a partner (confederate) that requires learning about nonsocial and social cue reward probability (the social valuation task). Task experience was measured using language metrics: explicit emotions/beliefs, talk about the confederate, and implicit distress (using the previously established marker self-referentiality). Subjects’ weighting of social and nonsocial cues was tested in mixed-effect regression models. Subjects’ learning rates under stable and volatile conditions were modeled (Rescorla–Wagner approach) and group × condition interactions tested.
Compared to control subjects, BPD subject debriefings included more mentions of the confederate and less distress language. BPD subjects also weighted social cues more heavily but had blunted learning responses to (nonsocial and social) volatility.
This is the first report of patient behavior in the social valuation task. The results suggest that BPD subjects expect higher volatility than control subjects. These findings lay the groundwork for a neurocomputational dissection of social and nonsocial belief updating in BPD, which holds promise for the development of novel clinical interventions that more directly target pathophysiology. |
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| AbstractList | Volatile interpersonal relationships are a core feature of borderline personality disorder (BPD) and lead to devastating disruption of patients’ personal and professional lives. Quantitative models of social decision making and learning hold promise for defining the underlying mechanisms of this problem. In this study, we tested BPD and control subject weighting of social versus nonsocial information and their learning about choices under stable and volatile conditions. We compared behavior using quantitative models.
Subjects (n = 20 BPD, n = 23 control subjects) played an extended reward learning task with a partner (confederate) that requires learning about nonsocial and social cue reward probability (the social valuation task). Task experience was measured using language metrics: explicit emotions/beliefs, talk about the confederate, and implicit distress (using the previously established marker self-referentiality). Subjects’ weighting of social and nonsocial cues was tested in mixed-effect regression models. Subjects’ learning rates under stable and volatile conditions were modeled (Rescorla–Wagner approach) and group × condition interactions tested.
Compared to control subjects, BPD subject debriefings included more mentions of the confederate and less distress language. BPD subjects also weighted social cues more heavily but had blunted learning responses to (nonsocial and social) volatility.
This is the first report of patient behavior in the social valuation task. The results suggest that BPD subjects expect higher volatility than control subjects. These findings lay the groundwork for a neurocomputational dissection of social and nonsocial belief updating in BPD, which holds promise for the development of novel clinical interventions that more directly target pathophysiology. Volatile interpersonal relationships are a core feature of borderline personality disorder (BPD) and lead to devastating disruption of patients' personal and professional lives. Quantitative models of social decision making and learning hold promise for defining the underlying mechanisms of this problem. In this study, we tested BPD and control subject weighting of social versus nonsocial information and their learning about choices under stable and volatile conditions. We compared behavior using quantitative models.BACKGROUNDVolatile interpersonal relationships are a core feature of borderline personality disorder (BPD) and lead to devastating disruption of patients' personal and professional lives. Quantitative models of social decision making and learning hold promise for defining the underlying mechanisms of this problem. In this study, we tested BPD and control subject weighting of social versus nonsocial information and their learning about choices under stable and volatile conditions. We compared behavior using quantitative models.Subjects (n = 20 BPD, n = 23 control subjects) played an extended reward learning task with a partner (confederate) that requires learning about nonsocial and social cue reward probability (the social valuation task). Task experience was measured using language metrics: explicit emotions/beliefs, talk about the confederate, and implicit distress (using the previously established marker self-referentiality). Subjects' weighting of social and nonsocial cues was tested in mixed-effect regression models. Subjects' learning rates under stable and volatile conditions were modeled (Rescorla-Wagner approach) and group × condition interactions tested.METHODSSubjects (n = 20 BPD, n = 23 control subjects) played an extended reward learning task with a partner (confederate) that requires learning about nonsocial and social cue reward probability (the social valuation task). Task experience was measured using language metrics: explicit emotions/beliefs, talk about the confederate, and implicit distress (using the previously established marker self-referentiality). Subjects' weighting of social and nonsocial cues was tested in mixed-effect regression models. Subjects' learning rates under stable and volatile conditions were modeled (Rescorla-Wagner approach) and group × condition interactions tested.Compared to control subjects, BPD subject debriefings included more mentions of the confederate and less distress language. BPD subjects also weighted social cues more heavily but had blunted learning responses to (nonsocial and social) volatility.RESULTSCompared to control subjects, BPD subject debriefings included more mentions of the confederate and less distress language. BPD subjects also weighted social cues more heavily but had blunted learning responses to (nonsocial and social) volatility.This is the first report of patient behavior in the social valuation task. The results suggest that BPD subjects expect higher volatility than control subjects. These findings lay the groundwork for a neurocomputational dissection of social and nonsocial belief updating in BPD, which holds promise for the development of novel clinical interventions that more directly target pathophysiology.CONCLUSIONSThis is the first report of patient behavior in the social valuation task. The results suggest that BPD subjects expect higher volatility than control subjects. These findings lay the groundwork for a neurocomputational dissection of social and nonsocial belief updating in BPD, which holds promise for the development of novel clinical interventions that more directly target pathophysiology. |
| Author | Landry, Christopher D. Kronemer, Sharif Alexander-Bloch, Aaron Hunt, Laurence T. Leavitt, Jacob Stahl, Dylan S. Fineberg, Sarah K. Corlett, Philip R. |
| AuthorAffiliation | d Department of Psychology, University of Houston, Houston, Texas g Oxford Health National Health Service Foundation Trust, Oxford, United Kingdom e Columbia University College of Physicians and Surgeons, Columbia University, New York, New York b Yale Child Study Center, Yale University, New Haven, Connecticut c Department of Neurology, Yale University, New Haven, Connecticut a Department of Psychiatry, Yale University, New Haven, Connecticut f Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom |
| AuthorAffiliation_xml | – name: g Oxford Health National Health Service Foundation Trust, Oxford, United Kingdom – name: c Department of Neurology, Yale University, New Haven, Connecticut – name: f Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom – name: e Columbia University College of Physicians and Surgeons, Columbia University, New York, New York – name: d Department of Psychology, University of Houston, Houston, Texas – name: a Department of Psychiatry, Yale University, New Haven, Connecticut – name: b Yale Child Study Center, Yale University, New Haven, Connecticut |
| Author_xml | – sequence: 1 givenname: Sarah K. surname: Fineberg fullname: Fineberg, Sarah K. email: sarah.fineberg@yale.edu organization: Department of Psychiatry, Yale University, New Haven, Connecticut – sequence: 2 givenname: Jacob surname: Leavitt fullname: Leavitt, Jacob organization: Department of Psychology, University of Houston, Houston, Texas – sequence: 3 givenname: Dylan S. surname: Stahl fullname: Stahl, Dylan S. organization: Yale Child Study Center, Yale University, New Haven, Connecticut – sequence: 4 givenname: Sharif surname: Kronemer fullname: Kronemer, Sharif organization: Department of Neurology, Yale University, New Haven, Connecticut – sequence: 5 givenname: Christopher D. surname: Landry fullname: Landry, Christopher D. organization: Columbia University College of Physicians and Surgeons, Columbia University, New York, New York – sequence: 6 givenname: Aaron orcidid: 0000-0001-6554-1893 surname: Alexander-Bloch fullname: Alexander-Bloch, Aaron organization: Department of Psychiatry, Yale University, New Haven, Connecticut – sequence: 7 givenname: Laurence T. surname: Hunt fullname: Hunt, Laurence T. organization: Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom – sequence: 8 givenname: Philip R. surname: Corlett fullname: Corlett, Philip R. organization: Department of Psychiatry, Yale University, New Haven, Connecticut |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30041970$$D View this record in MEDLINE/PubMed |
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| Copyright | 2018 Society of Biological Psychiatry Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved. 2018 Society of Biological Psychiatry. All rights reserved. 2018 Society of Biological Psychiatry |
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| Keywords | Associative learning Computational psychiatry Trust Borderline personality disorder Prediction error Social cognition |
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| Title | Differential Valuation and Learning From Social and Nonsocial Cues in Borderline Personality Disorder |
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