It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
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.
Du et al used fMRI data from patients with schizophrenia (SZ) and autism spectrum disorder (ASD) to analyze multi-scale brain functional connectivity and cerebral grey matter density and volume. They demonstrated the presence of convergent and divergent changes in SZ and ASD that correlated with clinical features.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details



1 Shanxi University, School of Computer and Information Technology, Taiyuan, China (GRID:grid.163032.5) (ISNI:0000 0004 1760 2008); Emory University, Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Atlanta, USA (GRID:grid.189967.8) (ISNI:0000 0001 0941 6502)
2 Emory University, Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Atlanta, USA (GRID:grid.189967.8) (ISNI:0000 0001 0941 6502)
3 Shanxi University, School of Computer and Information Technology, Taiyuan, China (GRID:grid.163032.5) (ISNI:0000 0004 1760 2008)
4 Yale University, Department of Psychiatry, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710)
5 University of Maryland, School of Medicine, Maryland Psychiatric Research Center, Department of Psychiatry, Baltimore, USA (GRID:grid.411024.2) (ISNI:0000 0001 2175 4264)