A model of risk and mental state shifts during social interaction

Hula, Andreas; Vilares, Iris; Lohrenz, Terry; Dayan, Peter; Montague, P. Read

doi:10.1371/journal.pcbi.1005935

Cited by 43 publications

(68 citation statements)

References 41 publications

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“…This insensitive learning account of BPD social behavior is also consistent with a recent report describing a computational model of BPD trustee responses in the 10-round Trust Game (24). They had previously found that people with BPD fail to coax a defecting partner to re-engage in economic exchange.…”

Section: Discussionsupporting

confidence: 89%

Differential valuation and learning from social and non-social cues in Borderline Personality Disorder

Fineberg

Leavitt

Stahl

et al. 2018

Preprint

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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 non-social information, and their learning about choices under stable and volatile conditions. We compared behavior using quantitative models.MethodsSubjects (n=20 BPD, n=23 control) played an extended reward learning task with a partner (confederate) that requires learning about non-social 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 non-social cues was tested in mixed-effects regression models. Subjects’ learning rates under stable and volatile conditions were modelled (Rescorla-Wagner approach) and group x condition interactions tested.ResultsCompared to controls, 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 (non-social and social) volatility.ConclusionsThis is the first report of patient behavior in the Social Valuation Task. The results suggest that BPD subjects expect higher volatility than do controls. These findings lay the groundwork for a neuro-computational dissection of social and non-social belief updating in BPD, which holds promise for the development of novel clinical interventions that more directly target pathophysiology.

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Section: Discussionsupporting

confidence: 89%

Differential valuation and learning from social and non-social cues in Borderline Personality Disorder

Fineberg

Leavitt

Stahl

et al. 2018

Preprint

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“…In our daily life, we make value-based decisions not only for our own interest but also for the benefit of other individuals (e.g., charitable donation involving decisionmaking about how resources are allocated between oneself and others). In such decision-making, an individual computes the value of each option by considering both self and others' reward outcomes in line with her social preference such as warm-glow, inequity-aversion and envy-aversion (Crockett et al, 2017;Fehr & Shmidt, 1999;Fehr & Camerer, 2007;Fukuda et al, 2019;Harbaugh et al, 2007;Hula et al, 2018;Sanfey et al, 2003;Takahashi et al, 2009), suggesting that multiple types of information are represented in the brain to guide choice. One study (Hutcherson et al, 2015) examined simple decisions about different allocations of monetary reward between oneself and an anonymous partner.…”

Section: Value-based Decision-making For Othersmentioning

confidence: 99%

Breaking human social decision making into multiple components and then putting them together again

Suzuki

O’Doherty

2020

Cortex

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Most of our waking time as human beings is spent interacting with other individuals. In order to make good decisions in this social milieu, it is often necessary to make inferences about the internal states, traits and intentions of others. Recently, some progress has been made to uncover the neural computations underlying human social decision-making by combining functional magnetic resonance neuroimaging (fMRI) with computational modeling of behavior. Modeling of behavioral data allows us to identify key computations necessary for decision-making and how these computations are integrated. Furthermore, by correlating these computational variables against neuroimaging data, it has become possible to elucidate where in the brain various computational variables are implemented during social decision making. Here we review the current state of knowledge in the domain of social computational neuroscience. Findings to date have emphasized that social decisions are driven by multiple computations that are conducted in parallel and which are implemented in distinct brain regions. We suggest that further progress is going to depend on identifying how and where such variables get integrated in order to yield a coherent behavioral output.

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“…Importantly, specific impairments in the ability to model the moral character of others or to respond to social signals are central to a range of psychiatric disorders, including borderline personality disorder and autism spectrum disorder 34,35 . For example, modelling people's modelling of another person's state of mind can identify maladaptive social behaviours 36 . More generally speaking, our study opens the door to broader applications of the tools and models from information sampling to understand social decision-making.…”

Section: Discussionmentioning

confidence: 99%

The Cost of Appearing Suspicious? Information Gathering in Trust Decisions

Sanfey²,

2018

Preprint

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Trust decisions are inherently uncertain, as people have incomplete information about the trustworthiness of the other prior to their decision. Therefore, it is beneficial to gather information about a trustee's past behaviour before deciding whether or not to trust them. However, elaborate inquiries about a trustee's behavior may change the trustee's willingness to reciprocate, causing either a decrease due to the investor appearing suspicious, or an increase because the investor appears to be highly betrayal-averse. Such a change could cause the investor to gather less or more information, respectively. We examine how information acquisition is modulated by social context, monetary cost, and the trustee's trustworthiness. Participants had the opportunity to sequentially sample information about a trustee's reciprocation history before they decided whether or not to invest. On some trials, we induced a social context by telling the participant that the trustee would later learn how much the participant sampled ("overt sampling"). Participants sampled less when there was a monetary cost and when the reciprocation history was more conclusive. Crucially, when sampling was free and overt, participants sampled less, suggesting negative consequences of appearing suspicious. In post-experiment questionnaires, participants indeed reported a belief that the reciprocation probability would decrease when information was overtly sampled. The findings replicated in a second experiment and were well accounted for by a utility-maximizing model in which overt sampling induces a decrease in reciprocation probability.This study opens the door to broader applications of the tools and models of information sampling to social decision-making.

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A model of risk and mental state shifts during social interaction

Cited by 43 publications

References 41 publications

Differential valuation and learning from social and non-social cues in Borderline Personality Disorder

Differential valuation and learning from social and non-social cues in Borderline Personality Disorder

Breaking human social decision making into multiple components and then putting them together again

The Cost of Appearing Suspicious? Information Gathering in Trust Decisions

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