@article{aa324a05c362491dbc88a25b3858c4fc,
title = "Large-scale dynamic causal modeling of major depressive disorder based on resting-state functional magnetic resonance imaging",
abstract = "Major depressive disorder (MDD) is a serious mental illness characterized by dysfunctional connectivity among distributed brain regions. Previous connectome studies based on functional magnetic resonance imaging (fMRI) have focused primarily on undirected functional connectivity and existing directed effective connectivity (EC) studies concerned mostly task-based fMRI and incorporated only a few brain regions. To overcome these limitations and understand whether MDD is mediated by within-network or between-network connectivities, we applied spectral dynamic causal modeling to estimate EC of a large-scale network with 27 regions of interests from four distributed functional brain networks (default mode, executive control, salience, and limbic networks), based on large sample-size resting-state fMRI consisting of 100 healthy subjects and 100 individuals with first-episode drug-naive MDD. We applied a newly developed parametric empirical Bayes (PEB) framework to test specific hypotheses. We showed that MDD altered EC both within and between high-order functional networks. Specifically, MDD is associated with reduced excitatory connectivity mainly within the default mode network (DMN), and between the default mode and salience networks. In addition, the network-averaged inhibitory EC within the DMN was found to be significantly elevated in the MDD. The coexistence of the reduced excitatory but increased inhibitory causal connections within the DMNs may underlie disrupted self-recognition and emotional control in MDD. Overall, this study emphasizes that MDD could be associated with altered causal interactions among high-order brain functional networks.",
keywords = "brain networks, drug-naive, dynamic causal modeling, effective connectivity, first-episode, major depressive disorder, parametric empirical Bayes, resting-state fMRI",
author = "Guoshi Li and Yujie Liu and Yanting Zheng and Danian Li and Xinyu Liang and Yaoping Chen and Ying Cui and Yap, {Pew Thian} and Shijun Qiu and Han Zhang and Dinggang Shen",
note = "Funding Information: China Scholarship Council; Innovation and Strong School Project of Guangdong Provincial Education Department, Grant/Award Number: 2014GKXM034; National Institute of Biomedical Imaging and Bioengineering, Grant/Award Number: EB022880; National Institute of Mental Health, Grant/Award Number: MH108560; National Institute on Aging, Grant/Award Numbers: AG041721, AG042599, AG049371; National Institute on Deafness and Other Communication Disorders, Grant/Award Number: DC013872; National Natural Science Foundation of China, Grant/Award Numbers: 81920108019, 81471251, 81771344, 91649117; Science and Technology Plan Project of Guangzhou, Grant/Award Number: 2018‐1002‐SF‐0442; Excellent Doctoral and PhD Thesis Research Papers Project of Guangzhou University of Chinese Medicine, Grant/Award Number: A1‐AFD018181A55 Funding information Funding Information: G. Li was supported by NIH grants (DC013872 and EB022880). Y.L., Y.Z., and S.Q. were supported by National Natural Science Foundation of China (81920108019, 91649117, 81771344, and 81471251), Science and Technology Plan Project of Guangzhou (2018-1002-SF-0442), and Innovation and Strong School Project of Guangdong Provincial Education Department (2014GKXM034). Y.L. was also supported by China Scholarship Council (201708440259) and Excellent Doctoral and PhD Thesis Research Papers Project of Guangzhou University of Chinese Medicine (A1-AFD018181A55). P.-T.Y. was supported by an NIH grant (EB022880). H.Z. and D.S. were supported by NIH grants (AG042599, AG049371, and AG041721). H.Z. was also supported by an NIH grant (MH108560). Funding Information: G. Li was supported by NIH grants (DC013872 and EB022880). Y.L., Y.Z., and S.Q. were supported by National Natural Science Foundation of China (81920108019, 91649117, 81771344, and 81471251), Science and Technology Plan Project of Guangzhou (2018‐1002‐SF‐0442), and Innovation and Strong School Project of Guangdong Provincial Education Department (2014GKXM034). Y.L. was also supported by China Scholarship Council (201708440259) and Excellent Doctoral and PhD Thesis Research Papers Project of Guangzhou University of Chinese Medicine (A1‐AFD018181A55). P.‐T.Y. was supported by an NIH grant (EB022880). H.Z. and D.S. were supported by NIH grants (AG042599, AG049371, and AG041721). H.Z. was also supported by an NIH grant (MH108560). Publisher Copyright: {\textcopyright} 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.",
year = "2020",
month = mar,
day = "1",
doi = "10.1002/hbm.24845",
language = "English",
volume = "41",
pages = "865--881",
journal = "Human Brain Mapping",
issn = "1065-9471",
publisher = "Wiley-Liss Inc.",
number = "4",
}