Investigation reveals DMN connectivity predicts treatment response in major depressive disorder, suggesting clinical relevance.
Key Points
This study aims to explore how default mode network connectivity relates to antidepressant response in major depressive disorder.
Analyzed resting-state fMRI data from four large cohorts with major depressive disorder
Examined effective connectivity within the default mode network using Granger causality
Compared connectivity measures across recurrent MDD patients, first-episode patients, and healthy controls
Employed support vector machine classifiers to predict treatment response based on connectivity data
Recurrent MDD patients showed significantly reduced effective connectivity from the medial prefrontal cortex to the posterior cingulate cortex compared to controls
Reduced connectivity correlated with antidepressant medication use and illness duration
Predictive models demonstrated high accuracy for predicting therapeutic outcomes based on DMN connectivity