Publication

Dynamic Functional Connectivity Predicts Treatment Response to Electroconvulsive Therapy in Major Depressive Disorder

Downloadable Content

Persistent URL
Last modified
  • 05/15/2025
Type of Material
Authors
    Hossein Dini, Aalborg UniversityMohammad S. E. Sendi, Georgia Institute of TechnologyJing Sui, Georgia Institute of TechnologyZening Fu, Georgia Institute of TechnologyRandall Espinoza, University of California Los AngelesKatherine L. Narr, University of California Los AngelesShile Qi, Georgia Institute of TechnologyChristopher C. Abbott, University of New MexicoSanne van Rooij, Emory UniversityPatricio Riva Posse, Emory UniversityLuis Emilio Bruni, Aalborg UniversityHelen Mayberg, Emory UniversityVince Calhoun, Emory University
Language
  • English
Date
  • 2021-07-06
Publisher
  • Frontiers Media
Publication Version
Copyright Statement
  • © 2021 Dini, Sendi, Sui, Fu, Espinoza, Narr, Qi, Abbott, van Rooij, Riva-Posse, Bruni, Mayberg and Calhoun.
License
Final Published Version (URL)
Title of Journal or Parent Work
Volume
  • 15
Grant/Funding Information
  • The following NIH grants funded this work: R01AG063153, R01EB020407, R01MH094524, R01MH119069, R01MH118695, R01MH121101, R61MH125126, R01MH117107, and U01MH111826.
Abstract
  • Electroconvulsive therapy (ECT) is one of the most effective treatments for major depressive disorder. Recently, there has been increasing attention to evaluate the effect of ECT on resting-state functional magnetic resonance imaging (rs-fMRI). This study aims to compare rs-fMRI of depressive disorder (DEP) patients with healthy participants, investigate whether pre-ECT dynamic functional network connectivity network (dFNC) estimated from patients rs-fMRI is associated with an eventual ECT outcome, and explore the effect of ECT on brain network states.
Author Notes
Keywords
Research Categories
  • Health Sciences, Radiology
  • Psychology, Cognitive
  • Biology, Neuroscience

Tools

Relations

In Collection:

Items

Thumbnail Title File Description Date Uploaded Visibility Actions
file details Publication File - w08b3.pdf Primary Content 2025-05-13 Public Download