IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-023-44569-1.html
   My bibliography  Save this article

Mapping expectancy-based appetitive placebo effects onto the brain in women

Author

Listed:
  • Iraj Khalid

    (INSERM, CNRS, APHP, Hôpital de la Pitié-Salpêtrière)

  • Belina Rodrigues

    (INSERM, CNRS, APHP, Hôpital de la Pitié-Salpêtrière)

  • Hippolyte Dreyfus

    (INSERM, CNRS, APHP, Hôpital de la Pitié-Salpêtrière)

  • Solène Frileux

    (INSERM, CNRS, APHP, Hôpital de la Pitié-Salpêtrière)

  • Karin Meissner

    (Medical Faculty, LMU Munich
    Faculty of Applied Natural Sciences and Health, Coburg University of Applied Sciences and Arts)

  • Philippe Fossati

    (INSERM, CNRS, APHP, Hôpital de la Pitié-Salpêtrière
    APHP, Hôpital de la Pitié-Salpêtrière)

  • Todd Anthony Hare

    (University of Zürich)

  • Liane Schmidt

    (INSERM, CNRS, APHP, Hôpital de la Pitié-Salpêtrière)

Abstract

Suggestions about hunger can generate placebo effects on hunger experiences. But, the underlying neurocognitive mechanisms are unknown. Here, we show in 255 women that hunger expectancies, induced by suggestion-based placebo interventions, determine hunger sensations and economic food choices. Functional magnetic resonance imaging in a subgroup (n = 57/255) provides evidence that the strength of expecting the placebo to decrease hunger moderates medial prefrontal cortex activation at the time of food choice and attenuates ventromedial prefrontal cortex (vmPFC) responses to food value. Dorsolateral prefrontal cortex activation linked to interference resolution formally mediates the suggestion-based placebo effects on hunger. A drift-diffusion model characterizes this effect by showing that the hunger suggestions bias participants’ food choices and how much they weigh tastiness against the healthiness of food, which further moderates vmPFC–dlPFC psychophysiological interactions when participants expect decreased hunger. Thus, suggestion-induced beliefs about hunger shape hunger addressing economic choices through cognitive regulation of value computation within the prefrontal cortex.

Suggested Citation

  • Iraj Khalid & Belina Rodrigues & Hippolyte Dreyfus & Solène Frileux & Karin Meissner & Philippe Fossati & Todd Anthony Hare & Liane Schmidt, 2024. "Mapping expectancy-based appetitive placebo effects onto the brain in women," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-023-44569-1
    DOI: 10.1038/s41467-023-44569-1
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-44569-1
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-44569-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Silvia U. Maier & Anjali Raja Beharelle & Rafael Polanía & Christian C. Ruff & Todd A. Hare, 2020. "Dissociable mechanisms govern when and how strongly reward attributes affect decisions," Nature Human Behaviour, Nature, vol. 4(9), pages 949-963, September.
    2. Henk R Cremers & Tor D Wager & Tal Yarkoni, 2017. "The relation between statistical power and inference in fMRI," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-20, November.
    3. Nicolette J. Sullivan & Scott A. Huettel, 2021. "Healthful choices depend on the latency and rate of information accumulation," Nature Human Behaviour, Nature, vol. 5(12), pages 1698-1706, December.
    4. Leonie Koban & Sangil Lee & Daniela Schelski & Marie-Christine Simon & Caryn Lerman & Bernd Weber & Joseph Kable & Hilke Plassmann, 2023. "An fMRI-based brain marker of individual differences in delay discounting," Post-Print hal-03957745, HAL.
    5. Marion Rouault & Jan Drugowitsch & Etienne Koechlin, 2019. "Prefrontal mechanisms combining rewards and beliefs in human decision-making," Nature Communications, Nature, vol. 10(1), pages 1-16, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Evan M. Russek & Rani Moran & Yunzhe Liu & Raymond J. Dolan & Quentin J. M. Huys, 2024. "Heuristics in risky decision-making relate to preferential representation of information," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    2. Geoffrey Fisher, 2023. "Measuring the Factors Influencing Purchasing Decisions: Evidence From Cursor Tracking and Cognitive Modeling," Management Science, INFORMS, vol. 69(8), pages 4558-4578, August.
    3. Joshua C Gray & Max M Owens & Courtland S Hyatt & Joshua D Miller, 2018. "No evidence for morphometric associations of the amygdala and hippocampus with the five-factor model personality traits in relatively healthy young adults," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-15, September.
    4. Antoine Bichat & Christophe Ambroise & Mahendra Mariadassou, 2022. "Hierarchical correction of p-values via an ultrametric tree running Ornstein-Uhlenbeck process," Computational Statistics, Springer, vol. 37(3), pages 995-1013, July.
    5. Ricardo Pio Monti & Alex Gibberd & Sandipan Roy & Matthew Nunes & Romy Lorenz & Robert Leech & Takeshi Ogawa & Motoaki Kawanabe & Aapo Hyvärinen, 2020. "Interpretable brain age prediction using linear latent variable models of functional connectivity," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-25, June.
    6. Fadong Chen & Jiehui Zheng & Lei Wang & Ian Krajbich, 2024. "Attribute latencies causally shape intertemporal decisions," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    7. Ming-Hua Chung & Bradford Martins & Anthony Privratsky & G Andrew James & Clint D Kilts & Keith A Bush, 2018. "Individual differences in rate of acquiring stable neural representations of tasks in fMRI," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-17, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-023-44569-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.