Brain network properties in depressed patients receiving seizure therapy: A graph theoretical analysis of peri-treatment resting EEG.

Abstract

Electroconvulsive therapy (ECT), the most efficacious antidepressant therapy for treatment-resistant depression, has been reported to alter functional brain network architecture by down-regulating connectivity in frontotemporal circuitry. Magnetic seizure therapy (MST), which induces therapeutic seizures with high dose repetitive transcranial magnetic stimulation, has been introduced to improve the seizure therapy risk/benefit ratio. Unfortunately, there is limited understanding of seizure therapy's underlying mechanisms of action. In this study, we apply graph theory-based connectivity analysis to peri-treatment, resting-state, topographical electroencephalography (EEG) in patients with depression receiving seizure therapy. Functional connectivity was assessed using the de-biased weighted phase lag index, a measure of EEG phase synchronization. Brain network structure was quantified using graph theory metrics, including betweenness centrality, clustering coefficient, network density, and characteristic path length. We found a significant reduction in the phase synchronization and aberration of the small-world architecture in the beta frequency band, which could be related to acute clinical and cognitive effects of seizure therapy.