Pharmacologic and expectancy effects in depression: Associations with inter-network resting-state connectivity

Area of Science:

• Neuroscience
• Psychiatry
• Medical Imaging

Background:

• Depression exhibits significant heterogeneity in resting-state functional connectivity (rsFC) across patients.
• Understanding treatment mechanisms is limited by this heterogeneity.
• Predicting response to pharmacological versus expectancy-driven treatments based on baseline network architecture remains unclear.

Purpose of the Study:

• To investigate whether baseline functional connectivity between specific neural networks predicts antidepressant treatment response.
• To determine if these predictions differ based on drug assignment (SSRI vs. placebo) and patient treatment beliefs.
• To explore the relationship between network reorganization and mood improvement during treatment.

Main Methods:

• 60 depressed participants underwent resting-state fMRI at baseline and after 8 weeks of double-blind SSRI or placebo treatment.
• Connectivity between the dorsal attention network (DAN), salience network (SN), and default mode network (DMN) was analyzed.
• Treatment response was assessed in relation to baseline connectivity, drug assignment, and placebo beliefs.

Main Results:

• Baseline connectivity between attention and salience networks predicted response in participants with placebo beliefs.
• Baseline connectivity between salience and default mode networks showed a double dissociation: higher connectivity favored SSRI response, while lower connectivity favored placebo response.
• Network reorganization occurred post-mood improvement and only when drug assignment and beliefs aligned.

Conclusions:

• Baseline neural connectivity patterns can differentiate between pharmacological and expectancy-driven antidepressant treatment response pathways.
• These findings suggest trait-like neural markers for personalized treatment strategies.
• Network reorganization appears to be a consequence, not a predictor, of aligned treatment effects.