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

Published

Conference Paper

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.

Full Text

Duke Authors

Cited Authors

  • Deng, Z-D; McClinctock, SM; Lisanby, SH

Published Date

  • August 2015

Published In

Volume / Issue

  • 2015 /

Start / End Page

  • 2203 - 2206

PubMed ID

  • 26736728

Pubmed Central ID

  • 26736728

International Standard Serial Number (ISSN)

  • 1557-170X

Digital Object Identifier (DOI)

  • 10.1109/embc.2015.7318828