Enhanced default mode network functional connectivity links with electroconvulsive therapy response in major depressive disorder

Background: Electroconvulsive therapy (ECT) is an effective neuromodulatory treatment for major depressive disorder (MDD), especially for cases resistant to antidepressant drugs. While the precise mechanisms underlying ECT efficacy are still unclear, it is speculated that ECT modulates brain connectivity. The current study aimed to investigate the longitudinal effects of ECT on resting-state functional connectivity (FC) in MDD patients and test if baseline FC can be used to predict therapeutic response.Method: Resting-state functional magnetic resonance imaging data were collected at baseline and following ECT from 33 MDD patients. Whole-brain multi-voxel pattern analysis (MVPA) and region of interest-wise FC analysis were employed to fully investigate ECT effects on brain connectivity. Linear support vector regression was further utilized to predict the improvement in depressive symptoms based on baseline connectivity.Results: MVPA revealed a significant ECT effect on FC in the default mode network (DMN), central executive network (CEN), sensorimotor network (SMN), and cerebellar posterior lobe. The FCs within the DMN and between DMN and CEN were enhanced in patients after ECT, and the changed FC between the medial prefrontal cortex and ventrolateral prefrontal cortex was negatively correlated with depressive symptom improvement. Moreover, baseline FC within the DMN and between the DMN and CEN could effectively predict the improvement of depressive symptoms.Conclusions: The findings suggest that the FCs within the DMN and between DMN and CEN may be critical therapeutic targets for effective antidepressant treatment as well as neuromarkers for predicting treatment response.

Automated summary

This study investigates the longitudinal effects of electroconvulsive therapy (ECT) on resting-state functional connectivity (FC) in patients with major depressive disorder (MDD). The findings suggest that the changes in FC within the default mode network (DMN) and between DMN and central executive network (CEN) may be critical for effective antidepressant treatment and can also serve as neuromarkers for predicting treatment response.