Brain Imaging and Behavior

, Volume 12, Issue 6, pp 1708–1719 | Cite as

Common and distinct changes of default mode and salience network in schizophrenia and major depression

  • Junming Shao
  • Chun Meng
  • Masoud Tahmasian
  • Felix Brandl
  • Qinli Yang
  • Guangchun Luo
  • Cheng Luo
  • Dezhong Yao
  • Lianli Gao
  • Valentin Riedl
  • Afra Wohlschläger
  • Christian SorgEmail author


Brain imaging reveals schizophrenia as a disorder of macroscopic brain networks. In particular, default mode and salience network (DMN, SN) show highly consistent alterations in both interacting brain activity and underlying brain structure. However, the same networks are also altered in major depression. This overlap in network alterations induces the question whether DMN and SN changes are different across both disorders, potentially indicating distinct underlying pathophysiological mechanisms. To address this question, we acquired T1-weighted, diffusion-weighted, and resting-state functional MRI in patients with schizophrenia, patients with major depression, and healthy controls. We measured regional gray matter volume, inter-regional structural and intrinsic functional connectivity of DMN and SN, and compared these measures across groups by generalized Wilcoxon rank tests, while controlling for symptoms and medication. When comparing patients with controls, we found in each patient group SN volume loss, impaired DMN structural connectivity, and aberrant DMN and SN functional connectivity. When comparing patient groups, SN gray matter volume loss and DMN structural connectivity reduction did not differ between groups, but in schizophrenic patients, functional hyperconnectivity between DMN and SN was less in comparison to depressed patients. Results provide evidence for distinct functional hyperconnectivity between DMN and SN in schizophrenia and major depression, while structural changes in DMN and SN were similar. Distinct hyperconnectivity suggests different pathophysiological mechanism underlying aberrant DMN-SN interactions in schizophrenia and depression.


Functional MRI Diffusion tensor imaging Schizophrenia Depression Default mode network Salience network 


Author Contributions

JS and CS designed the study; CM, MT, AM, MS and DS recruited participants and acquired data; JB and HF acquired data; JS, QY, GL, CL, DY and LG analysed data; CZ, VR, AW and CS interpreted data; JS and CS drafted the article; all authors critically revised and approved the final version of the article.


This study was supported by the National Natural Science Foundation of China (61403062, 61433014 to J.S.), China Postdoctoral Science Foundation (2015M580786 to J.S., 2014M552344, 2015T80973 to Q.Y.), Science-Technology Foundation for Young Scientist of SiChuan Province (2016JQ0007 to J.S.) and the German Federal Ministry of Education and Research (BMBF 01EV0710 to A.M.W., BMBF 01ER0803 to C.S.)

Compliance with Ethical Standards

Conflict of interest

The authors declare no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Junming Shao
    • 1
    • 2
    • 3
    • 4
  • Chun Meng
    • 5
    • 6
  • Masoud Tahmasian
    • 7
  • Felix Brandl
    • 5
    • 6
  • Qinli Yang
    • 3
  • Guangchun Luo
    • 2
  • Cheng Luo
    • 1
  • Dezhong Yao
    • 1
  • Lianli Gao
    • 2
  • Valentin Riedl
    • 4
    • 5
    • 6
  • Afra Wohlschläger
    • 5
    • 6
  • Christian Sorg
    • 5
    • 6
    • 8
    Email author
  1. 1.Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina
  3. 3.Big Data Research CenterUniversity of Electronic Science and Technology of ChinaChengduChina
  4. 4.Department of Nuclear MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
  5. 5.Department of NeuroradiologyTechnische Universität MünchenMunichGermany
  6. 6.TUM-Neuroimaging Center of Klinikum rechts der IsarTechnische Universität MünchenMunichGermany
  7. 7.Institute of Medical Science and TechnologyShahid Beheshti UniversityTehranIran
  8. 8.Department of PsychiatryKlinikum rechts der Isar Technische Universität MünchenMunichGermany

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