Affiliation:
1. CAS Key Laboratory of Behavioral Science Institute of Psychology Beijing 100101 China
2. Sino‐Danish College University of Chinese Academy of Sciences Beijing 101400 China
3. Sino‐Danish Center for Education and Research Beijing 101400 China
4. CFIN and PET Center Aarhus University Nørrebrogade 44 8000 Aarhus Denmark
5. Magnetic Resonance Imaging Research Center Institute of Psychology Chinese Academy of Sciences Beijing 100101 China
6. International Big‐Data Center for Depression Research Chinese Academy of Sciences Beijing 100101 China
7. Department of Psychology University of Chinese Academy of Sciences Beijing 100049 China
Abstract
BackgroundAs one of the leading causes of global disability, major depressive disorder (MDD) places a noticeable burden on individuals and society. Despite the great expectation on finding accurate biomarkers and effective treatment targets of MDD, studies in applying functional magnetic resonance imaging (fMRI) are still faced with challenges, including the representational ambiguity, small sample size, low statistical power, relatively high false positive rates, etc. Thus, reviewing studies with solid methodology may help achieve a consensus on the pathology of MDD.MethodsIn this systematic review, we screened fMRI studies on MDD through strict criteria to focus on reliable studies with sufficient sample size, adequate control of head motion, and a proper multiple comparison control strategy.ResultsWe found consistent evidence regarding the dysfunction within and among the default mode network (DMN), the frontoparietal network (FPN), and other brain regions. However, controversy remains, probably due to the heterogeneity of participants and data processing strategies.ConclusionFuture studies are recommended to apply a comprehensive set of neuro‐behavioral measurements, consider the heterogeneity of MDD patients and other potentially confounding factors, apply surface‐based neuroscientific network fMRI approaches, and advance research transparency and open science by applying state‐of‐the‐art pipelines along with open data sharing.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
China Postdoctoral Science Foundation
Subject
Applied Mathematics,Computer Science Applications,Biochemistry, Genetics and Molecular Biology (miscellaneous),Modeling and Simulation
Cited by
1 articles.
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