Expectancy-Mood Neural Dynamics Predict Mechanisms of Short- and Long-Term Antidepressant Placebo Effects

Area of Science:

• Neuroscience
• Psychiatry
• Medical Imaging

Background:

• Antidepressant placebo effects are linked to expectancies within the salience network (SN).
• Prior research suggests expectancies are reinforced by sensory input and mood changes.
• The long-term dynamics of these neural processes in depression remain unclear.

Purpose of the Study:

• To investigate the role of salience network (SN) and default mode network (DMN) functional connectivity.
• To examine how SN-DMN connectivity facilitates the shift from salience attribution to belief-induced mood responses.
• To assess these processes acutely and over an 8-week treatment period in major depressive disorder.

Main Methods:

• Sixty patients with major depressive disorder underwent functional magnetic resonance imaging (fMRI) during an acute placebo challenge.
• Expectancies and their reinforcement were manipulated and assessed.
• Participants then entered an 8-week double-blind trial of SSRI or placebo.

Main Results:

• Learned antidepressant expectancies, modeled via reinforcement learning, modulated SN-DMN connectivity.
• Acute modulation predicted greater effects of expectancy and reinforcement on expectancies and mood.
• Over 8 weeks, belief in receiving an antidepressant predicted mood improvement, irrespective of actual treatment; increased SN-DMN connectivity was particularly linked to mood improvement in placebo responders who believed they received active medication.

Conclusions:

• Salience network (SN) and default mode network (DMN) interactions are crucial for antidepressant response expectancies.
• Drug-assignment beliefs significantly influence mood outcomes in depression.
• These neural interactions underscore the importance of psychological factors in treatment efficacy.