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Understanding the Neurocomputational Mechanisms of Antidepressant Placebo Effects

Over the last two decades, neuroscientists have used antidepressant placebo probes to examine the biological mechanisms implicated in antidepressant placebo effects. However, findings from these studies have not yet elucidated a model-based theory that would explain the mechanism through which antid...

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Autores principales: Peciña, Marta, Dombrovski, Alexandre Y., Price, Rebecca, Karim, Helmet T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7963355/
https://www.ncbi.nlm.nih.gov/pubmed/33732892
http://dx.doi.org/10.20900/jpbs.20210001
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author Peciña, Marta
Dombrovski, Alexandre Y.
Price, Rebecca
Karim, Helmet T.
author_facet Peciña, Marta
Dombrovski, Alexandre Y.
Price, Rebecca
Karim, Helmet T.
author_sort Peciña, Marta
collection PubMed
description Over the last two decades, neuroscientists have used antidepressant placebo probes to examine the biological mechanisms implicated in antidepressant placebo effects. However, findings from these studies have not yet elucidated a model-based theory that would explain the mechanism through which antidepressant expectancies evolve to induce persistent mood changes. Emerging evidence suggests that antidepressant placebo effects may be informed by models of reinforcement learning (RL). Such that an individual’s expectation of improvement is updated with the arrival of new sensory evidence, by incorporating a reward prediction error (RPE), which signals the mismatch between the expected (expected value) and perceived improvement. Consistent with this framework, neuroimaging studies of antidepressant placebo effects have demonstrated placebo-induced μ-opioid activation and increased blood-oxygen-level dependent (BOLD) responses in regions tracking expected values (e.g., ventromedial prefrontal cortex (vmPFC)) and RPEs (e.g., ventral striatum (VS)). In this study, we will demonstrate the causal contribution of reward learning signals (expected values and RPEs) to antidepressant placebo effects by experimentally manipulating expected values using transcranial magnetic stimulation (TMS) targeting the vmPFC and μ-opioid striatal RPE signal using pharmacological approaches. We hypothesized that antidepressant placebo expectancies are represented in the vmPFC (expected value) and updated by means of μ-opioid-modulated striatal learning signal. In a 3 × 3 factorial double-blind design, we will randomize 120 antidepressant-free individuals with depressive symptoms to one of three between-subject opioid conditions: the μ-opioid agonist buprenorphine, the μ-opioid antagonist naltrexone, or an inert pill. Within each arm, individuals will be assigned to receive three within-subject counterbalanced forms of TMS targeting the vmPFC—intermittent Theta Burst Stimulation (TBS) expected to potentiate the vmPFC, continuous TBS expected to de-potentiate the vmPFC, or sham TBS. These experimental manipulations will be used to modulate trial-by-trial reward learning signals and related brain activity during the Antidepressant Placebo functional MRI (fMRI) Task to address the following aims: (1) investigate the relationship between reward learning signals within the vmPFC-VS circuit and antidepressant placebo effects; (2) examine the causal contribution of vmPFC expected value computations to antidepressant placebo effects; and (3) investigate the causal contribution of μ-opioid-modulated striatal RPEs to antidepressant placebo effects. The proposed study will be the first to investigate the causal contribution of μ-opioid-modulated vmPFC-VS learning signals to antidepressant placebo responses, paving the way for developing novel treatments modulating learning processes and objective means of quantifying and potentially reducing placebo effects during drug development. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04276259.
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spelling pubmed-79633552021-03-16 Understanding the Neurocomputational Mechanisms of Antidepressant Placebo Effects Peciña, Marta Dombrovski, Alexandre Y. Price, Rebecca Karim, Helmet T. J Psychiatr Brain Sci Article Over the last two decades, neuroscientists have used antidepressant placebo probes to examine the biological mechanisms implicated in antidepressant placebo effects. However, findings from these studies have not yet elucidated a model-based theory that would explain the mechanism through which antidepressant expectancies evolve to induce persistent mood changes. Emerging evidence suggests that antidepressant placebo effects may be informed by models of reinforcement learning (RL). Such that an individual’s expectation of improvement is updated with the arrival of new sensory evidence, by incorporating a reward prediction error (RPE), which signals the mismatch between the expected (expected value) and perceived improvement. Consistent with this framework, neuroimaging studies of antidepressant placebo effects have demonstrated placebo-induced μ-opioid activation and increased blood-oxygen-level dependent (BOLD) responses in regions tracking expected values (e.g., ventromedial prefrontal cortex (vmPFC)) and RPEs (e.g., ventral striatum (VS)). In this study, we will demonstrate the causal contribution of reward learning signals (expected values and RPEs) to antidepressant placebo effects by experimentally manipulating expected values using transcranial magnetic stimulation (TMS) targeting the vmPFC and μ-opioid striatal RPE signal using pharmacological approaches. We hypothesized that antidepressant placebo expectancies are represented in the vmPFC (expected value) and updated by means of μ-opioid-modulated striatal learning signal. In a 3 × 3 factorial double-blind design, we will randomize 120 antidepressant-free individuals with depressive symptoms to one of three between-subject opioid conditions: the μ-opioid agonist buprenorphine, the μ-opioid antagonist naltrexone, or an inert pill. Within each arm, individuals will be assigned to receive three within-subject counterbalanced forms of TMS targeting the vmPFC—intermittent Theta Burst Stimulation (TBS) expected to potentiate the vmPFC, continuous TBS expected to de-potentiate the vmPFC, or sham TBS. These experimental manipulations will be used to modulate trial-by-trial reward learning signals and related brain activity during the Antidepressant Placebo functional MRI (fMRI) Task to address the following aims: (1) investigate the relationship between reward learning signals within the vmPFC-VS circuit and antidepressant placebo effects; (2) examine the causal contribution of vmPFC expected value computations to antidepressant placebo effects; and (3) investigate the causal contribution of μ-opioid-modulated striatal RPEs to antidepressant placebo effects. The proposed study will be the first to investigate the causal contribution of μ-opioid-modulated vmPFC-VS learning signals to antidepressant placebo responses, paving the way for developing novel treatments modulating learning processes and objective means of quantifying and potentially reducing placebo effects during drug development. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04276259. 2021-02-15 2021 /pmc/articles/PMC7963355/ /pubmed/33732892 http://dx.doi.org/10.20900/jpbs.20210001 Text en This is an open access article distributed under the terms and conditions of Creative Commons Attribution 4.0 International License. http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Peciña, Marta
Dombrovski, Alexandre Y.
Price, Rebecca
Karim, Helmet T.
Understanding the Neurocomputational Mechanisms of Antidepressant Placebo Effects
title Understanding the Neurocomputational Mechanisms of Antidepressant Placebo Effects
title_full Understanding the Neurocomputational Mechanisms of Antidepressant Placebo Effects
title_fullStr Understanding the Neurocomputational Mechanisms of Antidepressant Placebo Effects
title_full_unstemmed Understanding the Neurocomputational Mechanisms of Antidepressant Placebo Effects
title_short Understanding the Neurocomputational Mechanisms of Antidepressant Placebo Effects
title_sort understanding the neurocomputational mechanisms of antidepressant placebo effects
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7963355/
https://www.ncbi.nlm.nih.gov/pubmed/33732892
http://dx.doi.org/10.20900/jpbs.20210001
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