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Author Notes:

Yuhui Du, Email: duyuhui@sxu.edu.cn

Y.D. proposed the whole analysis framework and implemented the analyses on spatial networks from ICA, functional connectivity network, ROI-based connectivity, gray matter volume and density, as well as the association analyses between neuroimaging measures and medication/symptom scores. Y.D. drafted and revised the whole manuscript, and prepared the tables and figures. Y.D. programed the orginial code of GIG-ICA. Z.F. downloaded and organized the datasets, preprocessed the fMRI and sMRI data, performed brain mask generation and GIG-ICA on each dataset, drafted, and revised the paper. Y.X. performed the classification experiments under the guidance of Y.D. D.L. preprocessed the COBRE and FBIRN datasets, and edited the paper. A.A., M.S., and S.Q. discussed the framework and revised the paper. P.K. and L.E.H. provided the MPRC data and revised the paper. G.P. edited the paper. V.D.C. supervised the work and edited the paper. All authors have given final approval of this version of the article.

Special thanks to Srinivas Rachakonda, as he added the GIG-ICA method to the GIFT toolbox and provided the batch script for performing GIG-ICA more easily. We also acknowledge the FBIRN team who coordinated and performed the data acquisition including Theo G.M. van Erp, Aysenil Belger, Juan R. Bustillo, Kelvin O. Lim, Daniel S. O’Leary, Judith M. Ford, Daniel H. Mathalon, Jessica A. Turner, and Steven G. Potkin.

The authors declare no competing interests.

Subject:

Research Funding:

This work was supported by National Natural Science Foundation of China (Grant number 62076157 and 61703253, to Y.D.), Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province (to Y.D.), the 1331 Engineering Project of Shanxi Province of China, and the National Institutes of Health grant (Grant number R01MH118695, to V.D.C.).

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Biology
  • Multidisciplinary Sciences
  • Life Sciences & Biomedicine - Other Topics
  • Science & Technology - Other Topics
  • DEFAULT MODE NETWORK
  • BIPOLAR DISORDER
  • GRAY-MATTER
  • CONNECTIVITY
  • PSYCHOSIS
  • ABNORMALITIES
  • INDIVIDUALS
  • INFORMATION
  • BRAINNETOME
  • CEREBELLUM

Evidence of shared and distinct functional and structural brain signatures in schizophrenia and autism spectrum disorder

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Journal Title:

COMMUNICATIONS BIOLOGY

Volume:

Volume 4, Number 1

Publisher:

, Pages 1073-1073

Type of Work:

Article | Final Publisher PDF

Abstract:

Schizophrenia (SZ) and autism spectrum disorder (ASD) share considerable clinical features and intertwined historical roots. It is greatly needed to explore their similarities and differences in pathophysiologic mechanisms. We assembled a large sample size of neuroimaging data (about 600 SZ patients, 1000 ASD patients, and 1700 healthy controls) to study the shared and unique brain abnormality of the two illnesses. We analyzed multi-scale brain functional connectivity among functional networks and brain regions, intra-network connectivity, and cerebral gray matter density and volume. Both SZ and ASD showed lower functional integration within default mode and sensorimotor domains, but increased interaction between cognitive control and default mode domains. The shared abnormalties in intra-network connectivity involved default mode, sensorimotor, and cognitive control networks. Reduced gray matter volume and density in the occipital gyrus and cerebellum were observed in both illnesses. Interestingly, ASD had overall weaker changes than SZ in the shared abnormalities. Interaction between visual and cognitive regions showed disorder-unique deficits. In summary, we provide strong neuroimaging evidence of the convergent and divergent changes in SZ and ASD that correlated with clinical features.

Copyright information:

© The Author(s) 2021

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/rdf).
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