|Table of Contents|

[1] Mo Zhaoqi, Wang Qiang, Tian Shui, Yan Rui, et al. Evaluating treatment via flexibilityof dynamic MRI community structures in depression [J]. Journal of Southeast University (English Edition), 2017, 33 (3): 273-276. [doi:10.3969/j.issn.1003-7985.2017.03.004]

Evaluating treatment via flexibilityof dynamic MRI community structures in depression()

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

2017 3
Research Field:
Computer Science and Engineering
Publishing date:


Evaluating treatment via flexibilityof dynamic MRI community structures in depression
Mo Zhaoqi1 Wang Qiang2 Tian Shui1 Yan Rui2 Geng Jiting2 Yao Zhijian2 Lu Qing1
1Key Laboratory of Child Development and Learning Science of Ministry of Education, Southeast University, Nanjing 210096, China
2Department of Psychiatry, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing 210029, China
dynamic community structure magnetic resonance imaging(MRI) depression treatment effect
The flexibility of dynamic community structure is adopted to analyze the depressive resting-state functional magnetic resonance imaging(rfMRI)signals in order to improve the accuracy of evaluating depression treatment. The rfMRI signals of each brain network were obtained by the independent component correlation algorithm(ICA). Dynamic functional connections were computed with sliding windows and L1 norm. Then, the connections were used to calculate the dynamic community structure via the community-detection algorithm. The result of structure’s community assignment has the general character with the brain activity changing over time. The flexibility index is one of traits of dynamic community structure, meaning the number of times a region changes. In this study, 16 patients who achieved clinical remission joined the experiment and were scanned before and after treatment. Pair permutation tests compare the difference of six brain networks’ flexibility between pre-therapy and post-treatment. The results show that the distribution of the flexibility values declines in a default network and cognitive control network between pre-therapy and post-treatment patients with statistical difference. Therefore, flexibility is a suitable approach to accurately evaluate the depression treatment effect.


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Biographies: Mo Zhaoqi(1992—), male, graduate; Lu Qing(corresponding author), female, doctor, professor, luq@seu.edu.cn.
Foundation items: The National High Technology Research and Development Program of China(863 program)(No.2015AA020509), the National Natural Science Foundation of China(No.81571639, 81371522, 61372032).
Citation: Mo Zhaoqi, Wang Qiang, Tian Shui, et al. Evaluating treatment via flexibility of dynamic MRI community structures in depression[J].Journal of Southeast University(English Edition), 2017, 33(3):273-276.DOI:10.3969/j.issn.1003-7985.2017.03.004.
Last Update: 2017-09-20