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Bayesian prediction of placebo analgesia in an instrumental learning model

Placebo analgesia can be primarily explained by the Pavlovian conditioning paradigm in which a passively applied cue becomes associated with less pain. In contrast, instrumental conditioning employs an active paradigm that might be more similar to clinical settings. In the present study, an instrume...

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Autores principales: Jung, Won-Mo, Lee, Ye-Seul, Wallraven, Christian, Chae, Younbyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5321416/
https://www.ncbi.nlm.nih.gov/pubmed/28225816
http://dx.doi.org/10.1371/journal.pone.0172609
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author Jung, Won-Mo
Lee, Ye-Seul
Wallraven, Christian
Chae, Younbyoung
author_facet Jung, Won-Mo
Lee, Ye-Seul
Wallraven, Christian
Chae, Younbyoung
author_sort Jung, Won-Mo
collection PubMed
description Placebo analgesia can be primarily explained by the Pavlovian conditioning paradigm in which a passively applied cue becomes associated with less pain. In contrast, instrumental conditioning employs an active paradigm that might be more similar to clinical settings. In the present study, an instrumental conditioning paradigm involving a modified trust game in a simulated clinical situation was used to induce placebo analgesia. Additionally, Bayesian modeling was applied to predict the placebo responses of individuals based on their choices. Twenty-four participants engaged in a medical trust game in which decisions to receive treatment from either a doctor (more effective with high cost) or a pharmacy (less effective with low cost) were made after receiving a reference pain stimulus. In the conditioning session, the participants received lower levels of pain following both choices, while high pain stimuli were administered in the test session even after making the decision. The choice-dependent pain in the conditioning session was modulated in terms of both intensity and uncertainty. Participants reported significantly less pain when they chose the doctor or the pharmacy for treatment compared to the control trials. The predicted pain ratings based on Bayesian modeling showed significant correlations with the actual reports from participants for both of the choice categories. The instrumental conditioning paradigm allowed for the active choice of optional cues and was able to induce the placebo analgesia effect. Additionally, Bayesian modeling successfully predicted pain ratings in a simulated clinical situation that fits well with placebo analgesia induced by instrumental conditioning.
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spelling pubmed-53214162017-03-09 Bayesian prediction of placebo analgesia in an instrumental learning model Jung, Won-Mo Lee, Ye-Seul Wallraven, Christian Chae, Younbyoung PLoS One Research Article Placebo analgesia can be primarily explained by the Pavlovian conditioning paradigm in which a passively applied cue becomes associated with less pain. In contrast, instrumental conditioning employs an active paradigm that might be more similar to clinical settings. In the present study, an instrumental conditioning paradigm involving a modified trust game in a simulated clinical situation was used to induce placebo analgesia. Additionally, Bayesian modeling was applied to predict the placebo responses of individuals based on their choices. Twenty-four participants engaged in a medical trust game in which decisions to receive treatment from either a doctor (more effective with high cost) or a pharmacy (less effective with low cost) were made after receiving a reference pain stimulus. In the conditioning session, the participants received lower levels of pain following both choices, while high pain stimuli were administered in the test session even after making the decision. The choice-dependent pain in the conditioning session was modulated in terms of both intensity and uncertainty. Participants reported significantly less pain when they chose the doctor or the pharmacy for treatment compared to the control trials. The predicted pain ratings based on Bayesian modeling showed significant correlations with the actual reports from participants for both of the choice categories. The instrumental conditioning paradigm allowed for the active choice of optional cues and was able to induce the placebo analgesia effect. Additionally, Bayesian modeling successfully predicted pain ratings in a simulated clinical situation that fits well with placebo analgesia induced by instrumental conditioning. Public Library of Science 2017-02-22 /pmc/articles/PMC5321416/ /pubmed/28225816 http://dx.doi.org/10.1371/journal.pone.0172609 Text en © 2017 Jung et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Jung, Won-Mo
Lee, Ye-Seul
Wallraven, Christian
Chae, Younbyoung
Bayesian prediction of placebo analgesia in an instrumental learning model
title Bayesian prediction of placebo analgesia in an instrumental learning model
title_full Bayesian prediction of placebo analgesia in an instrumental learning model
title_fullStr Bayesian prediction of placebo analgesia in an instrumental learning model
title_full_unstemmed Bayesian prediction of placebo analgesia in an instrumental learning model
title_short Bayesian prediction of placebo analgesia in an instrumental learning model
title_sort bayesian prediction of placebo analgesia in an instrumental learning model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5321416/
https://www.ncbi.nlm.nih.gov/pubmed/28225816
http://dx.doi.org/10.1371/journal.pone.0172609
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