scholarly journals Shared and Specific Intrinsic Functional Connectivity Patterns in Unmedicated Bipolar Disorder and Major Depressive Disorder

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Ying Wang ◽  
Junjing Wang ◽  
Yanbin Jia ◽  
Shuming Zhong ◽  
Meiqi Niu ◽  
...  
2018 ◽  
Vol 24 (11) ◽  
pp. 1063-1072 ◽  
Author(s):  
Qing-Mei Kong ◽  
Hong Qiao ◽  
Chao-Zhong Liu ◽  
Ping Zhang ◽  
Ke Li ◽  
...  

2019 ◽  
Vol Volume 15 ◽  
pp. 2629-2638 ◽  
Author(s):  
Shao-Wei Xue ◽  
Donglin Wang ◽  
Zhonglin Tan ◽  
Yan Wang ◽  
Zhenzhen Lian ◽  
...  

Neuroreport ◽  
2019 ◽  
Vol 30 (16) ◽  
pp. 1115-1120
Author(s):  
Donglin Wang ◽  
Shao-Wei Xue ◽  
Zhonglin Tan ◽  
Yan Wang ◽  
Zhenzhen Lian ◽  
...  

2019 ◽  
Author(s):  
Chao Li ◽  
Ke Xu ◽  
Mengshi Dong ◽  
Yange Wei ◽  
Jia Duan ◽  
...  

AbstractDynamic functional connectivity (DFC) analysis can capture time-varying properties of connectivity and may provide further information about transdiagnostic psychopathology across major psychiatric disorders. In this study, we used resting state functional MRI and a sliding-window method to study DFC in 150 schizophrenia (SZ), 100 bipolar disorder(BD), 150 major depressive disorder (MDD), and 210 healthy controls (HC). DFC were clustered into two functional connectivity states. Significant 4-group differences in DFC were found only in state 2. Post hoc analyses showed that transdiagnostic dysconnectivity among there disorders featured decreased connectivity within visual, somatomotor, salience and frontoparietal networks. Our results suggest that decreased connectivity within both lower-order (visual and somatomotor) and higher-order (salience and frontoparietal) networks may serve as transdiagnostic marker of these disorders, and that these dysconnectivity is state-dependent. Targeting these dysconnectivity may improve assessment and treatment for patients that having more than one of these disorders at the same time.


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