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Elevated Effort Cost Identified by Computational Modeling as a Distinctive Feature Explaining Multiple Behaviors in Patients With Depression

  • Fabien Vinckier
    Correspondence
    Address correspondence to Fabien Vinckier, M.D. Ph.D.
    Affiliations
    Motivation, Brain & Behavior lab Institut du Cerveau, Hôpital Pitié-Salpêtrière, Paris, France

    Université Paris Cité, Paris, France

    Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neurosciences, Paris, France
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  • Claire Jaffre
    Affiliations
    Motivation, Brain & Behavior lab Institut du Cerveau, Hôpital Pitié-Salpêtrière, Paris, France

    Université Paris Cité, Paris, France

    Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neurosciences, Paris, France
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  • Claire Gauthier
    Affiliations
    Université Paris Cité, Paris, France

    Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neurosciences, Paris, France
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  • Sarah Smajda
    Affiliations
    Université Paris Cité, Paris, France

    Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neurosciences, Paris, France
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  • Pierre Abdel-Ahad
    Affiliations
    Université Paris Cité, Paris, France

    Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neurosciences, Paris, France
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  • Raphaël Le Bouc
    Affiliations
    Motivation, Brain & Behavior lab Institut du Cerveau, Hôpital Pitié-Salpêtrière, Paris, France

    Urgences cérébro-vasculaires, Pitié-Salpêtrière Hospital, Sorbonne University, Assistance Publique Hôpitaux de Paris, Paris, France

    Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland
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  • Jean Daunizeau
    Affiliations
    Motivation, Brain & Behavior lab Institut du Cerveau, Hôpital Pitié-Salpêtrière, Paris, France

    Sorbonne Universités, Inserm, CNRS, Paris, France
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  • Mylène Fefeu
    Affiliations
    Université Paris Cité, Paris, France

    Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neurosciences, Paris, France
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  • Nicolas Borderies
    Affiliations
    Motivation, Brain & Behavior lab Institut du Cerveau, Hôpital Pitié-Salpêtrière, Paris, France
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  • Marion Plaze
    Affiliations
    Université Paris Cité, Paris, France

    Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neurosciences, Paris, France
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  • Raphaël Gaillard
    Affiliations
    Université Paris Cité, Paris, France

    Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neurosciences, Paris, France

    Institut Pasteur, experimental neuropathology unit, Paris, France
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  • Mathias Pessiglione
    Affiliations
    Motivation, Brain & Behavior lab Institut du Cerveau, Hôpital Pitié-Salpêtrière, Paris, France

    Sorbonne Universités, Inserm, CNRS, Paris, France
    Search for articles by this author
Open AccessPublished:August 08, 2022DOI:https://doi.org/10.1016/j.bpsc.2022.07.011

      Abstract

      Background

      Motivational deficit is a core clinical manifestation of depression and a strong predictor of treatment failure. However, the underlying mechanisms, which cannot be accessed through conventional questionnaire-based scoring, remain largely unknown. According to decision theory, apathy could result either from biased subjective estimates (of action costs or outcomes) or from dysfunctional processes (in making decisions or allocating resources).

      Methods

      Here, we combined a series of behavioral tasks with computational modeling to elucidate the motivational deficits of 35 patients with unipolar or bipolar depression under various treatments compared with 35 matched healthy control subjects.

      Results

      The most striking feature, which was observed independent of medication across preference tasks (likeability ratings and binary decisions), performance tasks (physical and mental effort exertion), and instrumental learning tasks (updating choices to maximize outcomes), was an elevated sensitivity to effort cost. By contrast, sensitivity to action outcomes (reward and punishment) and task-specific processes were relatively spared.

      Conclusions

      These results highlight effort cost as a critical dimension that might explain multiple behavioral changes in patients with depression. More generally, they validate a test battery for computational phenotyping of motivational states, which could orientate toward specific medication or rehabilitation therapy, and thereby help pave the way for more personalized medicine in psychiatry.

      Keywords

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