Evidence map›Paper›PMID 32997653›Full record

ArticlePLoS computational biology2020

Aberrant computational mechanisms of social learning and decision-making in schizophrenia and borderline personality disorder.

Lara Henco, Andreea O Diaconescu, Juha M Lahnakoski, Marie-Luise Brandi, Sophia Hörmann, Johannes Hennings, Alkomiet Hasan, Irina Papazova, Wolfgang Strube, Dimitris Bolis and 2 more

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
4.4field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 83 citations in OpenAlex.

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  10. The role of affective states in computational psychiatry.The international journal of neuropsychopharmacology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 6 institutions in 5 countries.

Lara HencoIndependent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany.ORCID 0000-0002-9732-6669
Andreea O DiaconescuDepartment of Psychiatry (UPK), University of Basel, Basel, Switzerland.ORCID 0000-0002-3633-9757
Juha M LahnakoskiIndependent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany.
Marie-Luise BrandiIndependent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany.ORCID 0000-0001-5283-2317
Sophia HörmannIndependent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany.ORCID 0000-0003-3205-7426
Johannes HenningsDepartment of Dialectical Behavioral Therapy, kbo-Isar-Amper-Klinikum Munich-East, Munich/Haar, Germany.ORCID 0000-0003-3259-7991
Alkomiet HasanDepartment of Psychiatry and Psychotherapy, University Hospital Munich, LMU Munich, Munich, Germany.
Irina PapazovaDepartment of Psychiatry and Psychotherapy, University Hospital Munich, LMU Munich, Munich, Germany.ORCID 0000-0001-8265-788X
Wolfgang StrubeDepartment of Psychiatry and Psychotherapy, University Hospital Munich, LMU Munich, Munich, Germany.
Dimitris BolisIndependent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany.ORCID 0000-0001-9656-8685
Leonhard SchilbachIndependent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany.ORCID 0000-0001-5547-8309
Christoph MathysTranslational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.ORCID 0000-0003-4079-5453
Max Planck Institute of Psychiatry · DELMU Klinikum · DECentre for Addiction and Mental Health · CAIsar-Amper-Klinikum München-Ost · DEScuola Internazionale Superiore di Studi Avanzati · ITUniversity of Augsburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Borderline Personality DisorderSchizophrenic PsychologyAnhedoniaBayes TheoremDecision MakingHumansMajor Depressive DisorderModels, PsychologicalRewardSchizophreniaSocial LearningTask Performance and Analysis

Identifiers

PMID32997653
PMCPMC7588082
OpenAlexW3089555705

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.