Large‐scale dynamic causal modeling of major depressive disorder based on resting‐state functional magnetic resonance imaging

• Published in: Human brain mapping Vol. 41; no. 4; pp. 865 - 881
• Main Authors: Li, Guoshi, Liu, Yujie, Zheng, Yanting, Li, Danian, Liang, Xinyu, Chen, Yaoping, Cui, Ying, Yap, Pew‐Thian, Qiu, Shijun, Zhang, Han, Shen, Dinggang
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.03.2020
• Subjects: Adult; Bayesian analysis; Brain; Brain mapping; brain networks; Coexistence; Connectome; Default Mode Network - diagnostic imaging; Default Mode Network - physiopathology; Depressive Disorder, Major - diagnostic imaging; Depressive Disorder, Major - physiopathology; drug‐naive; dynamic causal modeling; effective connectivity; Emotional Regulation - physiology; Executive function; Female; first‐episode; Functional magnetic resonance imaging; Humans; Magnetic Resonance Imaging; Major depressive disorder; Male; Mental depression; Mental disorders; Mental illness; Modelling; Models, Theoretical; Nerve Net - diagnostic imaging; Nerve Net - physiopathology; Networks; Neural Inhibition - physiology; Neural networks; Neuroimaging; parametric empirical Bayes; Resonance; resting‐state fMRI; Salience; Self Concept; Young Adult; first-episode; drug-naive; major depressive disorder; effective connectivity; parametric empirical Bayes; brain networks; dynamic causal modeling; resting-state fMRI

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 directe...