Electroconvulsive therapy treatment responsive multimodal brain networks
Qi, Shile9; Abbott, Christopher C.8; Narr, Katherine L.7; Jiang, Rongtao4,5,6; Upston, Joel8; McClintock, Shawn M.3; Espinoza, Randall7; Jones, Tom8; Zhi, Dongmei4,5,6; Sun, Hailun4,5,6
刊名HUMAN BRAIN MAPPING
2020-01-06
卷号41期号:7页码:11
关键词depressive episodes electroconvulsive therapy multimodal fusion treatment response
ISSN号1065-9471
DOI10.1002/hbm.24910
英文摘要

Electroconvulsive therapy is regarded as the most effective antidepressant treatment for severe and treatment-resistant depressive episodes. Despite the efficacy of electroconvulsive therapy, the neurobiological underpinnings and mechanisms underlying electroconvulsive therapy induced antidepressant effects remain unclear. The objective of this investigation was to identify electroconvulsive therapy treatment responsive multimodal biomarkers with the 17-item Hamilton Depression Rating Scale guided brain structure-function fusion in 118 patients with depressive episodes and 60 healthy controls. Results show that reduced fractional amplitude of low frequency fluctuations in the prefrontal cortex, insula and hippocampus, linked with increased gray matter volume in anterior cingulate, medial temporal cortex, insula, thalamus, caudate and hippocampus represent electroconvulsive therapy responsive covarying functional and structural brain networks. In addition, relative to nonresponders, responder-specific electroconvulsive therapy related brain networks occur in frontal-limbic network and are associated with successful therapeutic outcomes. Finally, electroconvulsive therapy responsive brain networks were unrelated to verbal declarative memory. Using a data-driven, supervised-learning method, we demonstrated that electroconvulsive therapy produces a remodeling of brain functional and structural covariance that was unique to antidepressant symptom response, but not linked to memory impairment.

资助项目China Natural Science Foundation[61773380] ; National Science Foundation[1539067] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDBS03040100] ; National Institute of Health[P20GM103472] ; Beijing Municipal Science and Technology Commission[Z181100001518005] ; National Institute of Health[1R56MH117107] ; National Institute of Health[1R01EB005846] ; National Institute of Health[1R01MH094524] ; National Institute of Health[P30GM122734] ; National Institute of Health[R01EB020407] ; National Institute of Mental Health[U01MH111826]
WOS关键词MAJOR DEPRESSION ; SUBSEQUENT ; ECT ; PHARMACOTHERAPY ; CONSORTIUM ; PREDICTION ; REMISSION ; DIAGNOSIS ; RBANS
WOS研究方向Neurosciences & Neurology ; Radiology, Nuclear Medicine & Medical Imaging
语种英语
出版者WILEY
WOS记录号WOS:000505639000001
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/29471]  
专题自动化研究所_脑网络组研究中心
通讯作者Abbott, Christopher C.; Sui, Jing
作者单位1.Sichuan Univ, West China Hosp, Huaxi Brain Res Ctr, Chengdu, Sichuan, Peoples R China
2.Chinese Acad Sci, Ctr Excellence Brain Sci, Inst Automat, Beijing, Peoples R China
3.Univ Texas Southwestern Med Ctr Dallas, Dept Psychiat, Dallas, TX 75390 USA
4.Univ Chinese Acad Sci, Beijing, Peoples R China
5.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
6.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing, Peoples R China
7.Univ Calif Los Angeles, Dept Neurol Psychiat & Biobehav Sci, Los Angeles, CA 90024 USA
8.Univ New Mexico, Dept Psychiat, Albuquerque, NM 87131 USA
9.Emory Univ, Georgia State Univ, Georgia Inst Technol, Triinst Ctr Translat Res Neuroimaging & Data Sci, Atlanta, GA 30322 USA
推荐引用方式
GB/T 7714
Qi, Shile,Abbott, Christopher C.,Narr, Katherine L.,et al. Electroconvulsive therapy treatment responsive multimodal brain networks[J]. HUMAN BRAIN MAPPING,2020,41(7):11.
APA Qi, Shile.,Abbott, Christopher C..,Narr, Katherine L..,Jiang, Rongtao.,Upston, Joel.,...&Calhoun, Vince D..(2020).Electroconvulsive therapy treatment responsive multimodal brain networks.HUMAN BRAIN MAPPING,41(7),11.
MLA Qi, Shile,et al."Electroconvulsive therapy treatment responsive multimodal brain networks".HUMAN BRAIN MAPPING 41.7(2020):11.
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