The following publications are possibly variants of this publication:
- Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive DisorderMohammad S. Eslampanah Sendi, Elaheh Zendehrouh, Jing Sui, Zening Fu, Dongmei Zhi, Luxian Lv, Xiaohong Ma, Qing Ke, Xianbin Li, Chuanyue Wang, Christopher C. Abbott, Jessica A. Turner, Robyn L. Miller, Vince D. Calhoun. brain, 11(10):838-849, 2021. [doi]
- Aberrant Functional Network Connectivity Transition Probability in Major Depressive DisorderElaheh Zendehrouh, Mohammad S. Eslampanah Sendi, Jing Sui, Zening Fu, Dongmei Zhi, Luxian Lv, Xiaohong Ma, Qing Ke, Xianbin Li, Chuanyue Wang, Christopher C. Abbott, Jessica A. Turner, Robyn L. Miller, Vince D. Calhoun. embc 2020: 1493-1496 [doi]
- Major Depressive Disorder Shows Frequency-specific Abnormal Functional Connectivity Patterns Associated with AnhedoniaYajing Pang, Qian Cui, Yifeng Wang, Yuyan Chen, Qi Yang, Huafu Chen. icmhi 2019: 65-70 [doi]
- Morphologic and Functional Connectivity Alterations in Patients with Major Depressive DisorderYang Yang, Changqing Hu, Kazuyuki Imamura, Xiaojing Yang, Huaizhou Li, Gang Wang, Lei Feng, Bin Hu, Shengfu Lu, Ning Zhong. brain 2015: 33-42 [doi]
- Visualizing Functional Network Connectivity Difference between Healthy Control and Major Depressive Disorder Using an Explainable Machine-learning MethodJi Ye Chun, Mohammad S. Eslampanah Sendi, Jing Sui, Dongmei Zhi, Vince D. Calhoun. embc 2020: 1424-1427 [doi]