Pharmacologic and expectancy effects in depression: Associations with inter-network resting-state connectivity.
TL;DR
It is suggested that baseline connectivity patterns serve as trait-like neural markers differentiating pharmacological from expectancy-driven response pathways, and that network reorganization reflects a consequence of aligned pharmacological and psychological treatment effects.
Abstract
Depression involves dysregulation across large-scale neural networks, yet substantial heterogeneity in resting-state functional connectivity (rsFC) across patients limits our understanding of treatment mechanisms. A key unresolved question is whether baseline network architecture differentially predicts response to pharmacological versus expectancy-driven treatment effects. In this mechanistic, hypothesis-generating study, 60 depressed participants completed resting-state fMRI at baseline and after 8 weeks of double-blind randomization to an SSRI or placebo. We tested whether connectivity between three networks - the dorsal attention (DAN), salience (SN), and default mode (DMN) networks - predicted treatment response as a function of drug assignment and treatment beliefs. We identified dissociable neural pathways for pharmacological and expectancy effects. Baseline connectivity between attention and salience networks, circuits involved in contextual processing, predicted response specifically among participants who developed placebo beliefs. Baseline connectivity between salience and default mode networks, circuits involved in mood regulation and internal state prediction, showed a double dissociation by drug assignment: higher connectivity predicted better outcomes with the SSRI, while lower connectivity predicted better outcomes with placebo. Network reorganization over treatment followed rather than predicted mood improvement and occurred only when drug assignment and belief aligned. These findings suggest that baseline connectivity patterns serve as trait-like neural markers differentiating pharmacological from expectancy-driven response pathways, and that network reorganization reflects a consequence of aligned pharmacological and psychological treatment effects. Replication in larger samples is warranted, but these results offer a novel framework for understanding and ultimately resolving heterogeneity in antidepressant treatment response.