JAMA psychiatry · 2023
Dynamic Feedback Between Antidepressant Placebo Expectancies and Mood.
Клиническое исследованиеСтатьяПоддержка NIH: внешняя программаResearch Support, N.I.H., IntramuralНазвание и аннотация: Перевод в очереди
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Peciña Marta, Chen Jiazhou, Karp Jordan F, Dombrovski Alexandre Y
Аннотация
IMPORTANCE: Despite high antidepressant placebo response rates, the mechanisms underlying the persistence of antidepressant placebo effects are still poorly understood.
OBJECTIVE: To investigate the neurobehavioral mechanisms underlying the evolution of antidepressant placebo effects using a reinforcement learning (RL) framework.
DESIGN, SETTING, AND PARTICIPANTS: In this acute within-patient cross-sectional study of antidepressant placebos, patients aged 18 to 55 years not receiving medication for major depressive disorder (MDD) were recruited at the University of Pittsburgh between February 21, 2017, to March 1, 2021.
INTERVENTIONS: The antidepressant placebo functional magnetic resonance imaging task manipulates placebo-associated expectancies using visually cued fast-acting antidepressant infusions and controls their reinforcement with sham visual neurofeedback while assessing expected and experienced mood improvement.
MAIN OUTCOMES AND MEASURES: The trial-by-trial evolution of expectancies and mood was examined using multilevel modeling and RL, relating model-predicted signals to spatiotemporal dynamics of blood oxygenation level-dependent (BOLD) response.
RESULTS: A bayesian RL model comparison in 60 individuals (mean [SE] age, 24.5 [0.8] years; 51 females [85%]) with MDD revealed that antidepressant placebo trial-wise expectancies were updated by composite learning signals multiplexing sensory evidence (neurofeedback) and trial-wise mood (bayesian omnibus risk <0.001; exceedance probability = 97%). Placebo expectancy, neurofeedback manipulations, and composite learning signals modulated the visual cortex and dorsal attention network (threshold-free cluster enhancement [TFCE] = 1 - P >.95). As participants anticipated antidepressant infusions, learned placebo expectancies modulated the salience network (SN, TFCE = 1 - P >.95), positively scaling with depression severity.
CONCLUSIONS AND RELEVANCE: Results of this cross-sectional study suggest that on a timescale of minutes, antidepressant placebo effects were maintained by positive feedback loops between expectancies and mood improvement. During learning, representations of placebos and their perceived effects were enhanced in primary and secondary sensory cortices. Latent learned placebo expectancies were encoded in the SN.
OBJECTIVE: To investigate the neurobehavioral mechanisms underlying the evolution of antidepressant placebo effects using a reinforcement learning (RL) framework.
DESIGN, SETTING, AND PARTICIPANTS: In this acute within-patient cross-sectional study of antidepressant placebos, patients aged 18 to 55 years not receiving medication for major depressive disorder (MDD) were recruited at the University of Pittsburgh between February 21, 2017, to March 1, 2021.
INTERVENTIONS: The antidepressant placebo functional magnetic resonance imaging task manipulates placebo-associated expectancies using visually cued fast-acting antidepressant infusions and controls their reinforcement with sham visual neurofeedback while assessing expected and experienced mood improvement.
MAIN OUTCOMES AND MEASURES: The trial-by-trial evolution of expectancies and mood was examined using multilevel modeling and RL, relating model-predicted signals to spatiotemporal dynamics of blood oxygenation level-dependent (BOLD) response.
RESULTS: A bayesian RL model comparison in 60 individuals (mean [SE] age, 24.5 [0.8] years; 51 females [85%]) with MDD revealed that antidepressant placebo trial-wise expectancies were updated by composite learning signals multiplexing sensory evidence (neurofeedback) and trial-wise mood (bayesian omnibus risk <0.001; exceedance probability = 97%). Placebo expectancy, neurofeedback manipulations, and composite learning signals modulated the visual cortex and dorsal attention network (threshold-free cluster enhancement [TFCE] = 1 - P >.95). As participants anticipated antidepressant infusions, learned placebo expectancies modulated the salience network (SN, TFCE = 1 - P >.95), positively scaling with depression severity.
CONCLUSIONS AND RELEVANCE: Results of this cross-sectional study suggest that on a timescale of minutes, antidepressant placebo effects were maintained by positive feedback loops between expectancies and mood improvement. During learning, representations of placebos and their perceived effects were enhanced in primary and secondary sensory cortices. Latent learned placebo expectancies were encoded in the SN.