Zening Fu1, Jing Sui2, Randall Espinoza3, Katherine Narr3, Shile Qi1, Mohammad S E Sendi4, Christopher C Abbott5, Vince D Calhoun6. 1. Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia. 2. Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China. 3. Departments of Neurology, Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California. 4. Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia; Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia. 5. Department of Psychiatry, University of New Mexico, Albuquerque, New Mexico. Electronic address: CAbbott@salud.unm.edu. 6. Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia; Department of Psychology, Computer Science, Neuroscience Institute, and Physics, Georgia State University, Atlanta, Georgia; Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia; Department of Psychiatry, Yale School of Medicine, Yale University, New Haven, Connecticut.
Abstract
BACKGROUND: Depressive episodes (DEPs), characterized by abnormalities in cognitive functions and mood, are a leading cause of disability. Electroconvulsive therapy (ECT), which involves a brief electrical stimulation of the anesthetized brain, is one of the most effective treatments used in patients with DEP due to its rapid efficacy. METHODS: In this work, we investigated how dynamic brain functional connectivity responds to ECT and whether the dynamic responses are associated with treatment outcomes and side effects in patients. We applied a fully automated independent component analysis-based pipeline to 110 patients with DEP (including diagnosis of unipolar depression or bipolar depression) and 60 healthy control subjects. The dynamic functional connectivity was analyzed by a combination of the sliding window approach and clustering analysis. RESULTS: Five recurring connectivity states were identified, and patients with DEPs had fewer occurrences in one brain state (state 1) with strong positive and negative connectivity. Patients with DEP changed the occupancy of two states (states 3 and 4) after ECT, resulting in significantly different occurrences of one additional state (state 3) compared with healthy control subjects. We further found that patients with DEP had diminished global metastate dynamism, two of which recovered to normal after ECT. The changes in dynamic connectivity characteristics were associated with the changes in memory recall and Hamilton Depression Rating Scale of DEP after ECT. CONCLUSIONS: These converging results extend current findings on subcortical-cortical dysfunction and dysrhythmia in DEP and demonstrate that ECT might cause remodeling of brain functional dynamics that enhance the neuroplasticity of the diseased brain.
BACKGROUND: Depressive episodes (DEPs), characterized by abnormalities in cognitive functions and mood, are a leading cause of disability. Electroconvulsive therapy (ECT), which involves a brief electrical stimulation of the anesthetized brain, is one of the most effective treatments used in patients with DEP due to its rapid efficacy. METHODS: In this work, we investigated how dynamic brain functional connectivity responds to ECT and whether the dynamic responses are associated with treatment outcomes and side effects in patients. We applied a fully automated independent component analysis-based pipeline to 110 patients with DEP (including diagnosis of unipolar depression or bipolar depression) and 60 healthy control subjects. The dynamic functional connectivity was analyzed by a combination of the sliding window approach and clustering analysis. RESULTS: Five recurring connectivity states were identified, and patients with DEPs had fewer occurrences in one brain state (state 1) with strong positive and negative connectivity. Patients with DEP changed the occupancy of two states (states 3 and 4) after ECT, resulting in significantly different occurrences of one additional state (state 3) compared with healthy control subjects. We further found that patients with DEP had diminished global metastate dynamism, two of which recovered to normal after ECT. The changes in dynamic connectivity characteristics were associated with the changes in memory recall and Hamilton Depression Rating Scale of DEP after ECT. CONCLUSIONS: These converging results extend current findings on subcortical-cortical dysfunction and dysrhythmia in DEP and demonstrate that ECT might cause remodeling of brain functional dynamics that enhance the neuroplasticity of the diseased brain.
Authors: Zening Fu; Yiheng Tu; Xin Di; Yuhui Du; Jing Sui; Bharat B Biswal; Zhiguo Zhang; N de Lacy; V D Calhoun Journal: Neuroimage Date: 2018-06-06 Impact factor: 6.556
Authors: Chi-Hua Chen; John Suckling; Cinly Ooi; Cynthia H Y Fu; Steve C R Williams; Nicholas D Walsh; Martina T Mitterschiffthaler; Emilio Merlo Pich; Ed Bullmore Journal: Neuropsychopharmacology Date: 2007-11-07 Impact factor: 7.853
Authors: Christian Otte; Stefan M Gold; Brenda W Penninx; Carmine M Pariante; Amit Etkin; Maurizio Fava; David C Mohr; Alan F Schatzberg Journal: Nat Rev Dis Primers Date: 2016-09-15 Impact factor: 52.329
Authors: Anke Schat; Walter W van den Broek; Paul G H Mulder; Tom K Birkenhäger; Ruud van Tuijl; Jaap M J Murre Journal: J ECT Date: 2007-09 Impact factor: 3.635