Dataset Information

Differential Valuation and Learning From Social and Nonsocial Cues in Borderline Personality Disorder.

ABSTRACT:

Background

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.

Methods

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.

Results

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.

Conclusions

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.

SUBMITTER: Fineberg SK

PROVIDER: S-EPMC6218635 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Publications

Differential Valuation and Learning From Social and Nonsocial Cues in Borderline Personality Disorder.

Fineberg Sarah K SK Leavitt Jacob J Stahl Dylan S DS Kronemer Sharif S Landry Christopher D CD Alexander-Bloch Aaron A Hunt Laurence T LT Corlett Philip R PR

Biological psychiatry 20180605 11

<h4>Background</h4>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 com ...[more]

PMID: 30041970

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Project description:Humans engage in social interactions and have a fundamental need and motivation to establish and maintain social connections. Neuroimaging studies particularly focused on the neural substrates of social exclusion in healthy subjects (HC), borderline personality disorder (BPD), and major depression (MD). However, there is evidence regarding neural alterations also during social inclusion in BPD that we intended to elucidate in our study. Considering that patients with BPD often have comorbid MD, we investigated patients with BPD, and comorbid MD, patients with MD without BPD, and a sample of HC. By investigating these two clinical samples within one study design, we attempted to disentangle potential confounds arising by psychiatric disorder or medication and to relate neural alterations under social inclusion specifically to BPD. We investigated 48 females (15 BPD and MD, 16 MD, and 17 HC) aged between 18 and 40 years by fMRI (3T), using the established cyberball paradigm with social exclusion, inclusion, and passive watching conditions. Significant group-by-condition interaction effects (p < 0.05, FWE-corrected on cluster level) were observed within the dorsolateral (dlPFC) and dorsomedial prefrontal cortex (dmPFC), the temporo-parietal junction (TPJ), the posterior cingulate cortex (PCC), and the precuneus. Comparisons of estimated neural activations revealed that significant interaction effects were related to a relative increase in neural activations during social inclusion in BPD. In detail, we observed a significant increase in differential (social inclusion vs. passive watching) neural activation within the dmPFC and the PCC in BPD compared to both, MD and HC. However, significant interaction effects within the dlPFC and the TPJ could not specifically be linked to BPD considering that they did not differ significantly between the two clinical groups in post-hoc comparisons. Our study supports previous results on effects of social and inclusion in BPD, and provides further evidence regarding disorder specific neural alterations in BPD for brain regions associated with self-referential and mentalizing processes during social inclusion.

Project description:Psychiatric disorders are ubiquitously characterized by debilitating social impairments. These difficulties are thought to emerge from aberrant social inference. In order to elucidate the underlying computational mechanisms, patients diagnosed with major depressive disorder (N = 29), schizophrenia (N = 31), and borderline personality disorder (N = 31) as well as healthy controls (N = 34) performed a probabilistic reward learning task in which participants could learn from social and non-social information. Patients with schizophrenia and borderline personality disorder performed more poorly on the task than healthy controls and patients with major depressive disorder. Broken down by domain, borderline personality disorder patients performed better in the social compared to the non-social domain. In contrast, controls and major depressive disorder patients showed the opposite pattern and schizophrenia patients showed no difference between domains. In effect, borderline personality disorder patients gave up a possible overall performance advantage by concentrating their learning in the social at the expense of the non-social domain. We used computational modeling to assess learning and decision-making parameters estimated for each participant from their behavior. This enabled additional insights into the underlying learning and decision-making mechanisms. Patients with borderline personality disorder showed slower learning from social and non-social information and an exaggerated sensitivity to changes in environmental volatility, both in the non-social and the social domain, but more so in the latter. Regarding decision-making the modeling revealed that compared to controls and major depression patients, patients with borderline personality disorder and schizophrenia showed a stronger reliance on social relative to non-social information when making choices. Depressed patients did not differ significantly from controls in this respect. Overall, our results are consistent with the notion of a general interpersonal hypersensitivity in borderline personality disorder and schizophrenia based on a shared computational mechanism characterized by an over-reliance on beliefs about others in making decisions and by an exaggerated need to make sense of others during learning specifically in borderline personality disorder.

Project description:BackgroundInterpersonal impairments in borderline personality disorder (BPD) are characterised by a lack in the sense of belonging and the fear of being excluded. One feature of interactions that can promote a sense of social belonging is interpersonal touch. While some studies suggest that individuals with BPD experience social touch as less pleasurable than healthy individuals (HCs), there are no studies that investigated whether this difference is associated with feeling less socially connected. This question is particularly important during the COVID-19 pandemic, since one central behavioural recommendation is "social distancing". An increase in loneliness has been discussed as a consequence and it has been suggested that individuals with BPD may be particularly burdened. However, the primary goal of "social distancing" is not preventing social contacts, but physical proximity. In our study we investigated the interplay between feeling close to others, contact frequency and the appraisal of social touch in BPD. We were additionally interested in whether these factors contribute to the burden through "physical distancing".MethodsWe assessed subjective and objective social isolation, the need, importance, and liking of social touch, as well as the burden through "physical distancing" policies in 130 women (61 BPD and 69 HCs).ResultsParticipants of the BPD group reported higher loneliness, less social contacts and a lower need for, importance and liking of social touch compared to HCs. Larger social networks, higher frequency of in-person contacts and higher liking and importance of social touch were associated with lower levels of loneliness. Both groups did not differ regarding their burden through "physical distancing". A higher need for and lower importance of social touch predicted a higher burden through "physical distancing".ConclusionsA positive appraisal of social touch was associated with less loneliness, independently of an individual's objective social isolation. In BPD, impairments of this fundamental facet of social interaction might hamper forming and strengthening of social bonds and contribute to the patients' interpersonal dysfunction. Changing the attitude towards social touch and in consequence its liking and importance in social interaction might provide one avenue to improve the sense of social connectedness in these patients.

Dataset Information

Differential Valuation and Learning From Social and Nonsocial Cues in Borderline Personality Disorder.

Background

Methods

Results

Conclusions

Publications

Differential Valuation and Learning From Social and Nonsocial Cues in Borderline Personality Disorder.

Similar Datasets

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