Abstract:

Patients with major depressive disorder (MDD) exhibit higher levels of rumination, i.e., repetitive thinking patterns and exaggerated focus on negative states. Rumination is known to be associated with the cortical midline structures / default mode network (DMN) region activity, although the brain network topological organization underlying rumination remains unclear. Implementing a graph theoretical analysis based on ultra-high field 7-Tesla functional MRI data, we tested whether whole brain network connectivity hierarchies during resting state are associated with rumination in a dimensional manner across 20 patients with MDD and 20 healthy controls. Applying this data-driven approach we found a significant correlation between rumination tendency and connectivity strength degree of the right precuneus, a key node of the DMN. In order to interrogate this region further, we then applied the Dependency Network Analysis (DEPNA), a recently developed method used to quantify the connectivity influence of network nodes. This revealed that rumination was associated with lower connectivity influence of the left medial orbito-frontal cortex (MOFC) cortex on the right precuneus. Lastly, we used an information theory entropy measure that quantifies the cohesion of a network's correlation matrix. We show that subjects with higher rumination scores exhibit higher entropy levels within the DMN i.e. decreased overall connectivity within the DMN. These results emphasize the general DMN involvement during self-reflective processing related to maladaptive rumination in MDD. This work specifically highlights the impact of the MOFC on the precuneus, which might serve as a target for clinical neuromodulation treatment. Keywords: Default mode network, Depression, Entropy, Graph Theory, High-field MRI, Precuneus