Abnormal dynamic functional network connectivity and graph theoretical analysis in major depressive disorder
文献类型：会议论文
| 作者 | Zhi DM(支冬梅)
|
| 出版日期 | 2018 |
| 会议日期 | 2018/07/17 |
| 会议地点 | Honolulu |
| 关键词 | Major depressive disorder, dynamic functional network connectivity |
| 英文摘要 | Major depressive disorder (MDD) is a complex mood disorder characterized by persistent and overwhelming depression. Previous studies have identified abnormalities in large scale functional brain networks in MDD, yet most of them were based on static functional connectivity. By contrast, here
we explored disrupted topological organization of dynamic functional network connectivity (dFNC) in MDD based on graph theory. 182 MDD patients and 218 healthy controls were included in this study, all Chinese Han people. By applying group information guided independent component analysis (GIG-ICA) on resting-state fMRI data, the dFNCs of each subject were estimated using a sliding window method and k-means clustering. Five dynamic functional states were identified, three of which demonstrated significant group difference on the percentage of state occurrence. Interestingly, MDD patients spent much more time in a weakly-connected state 2, which is associated with self-focused thinking, a representative feature of depression. In addition, the abnormal FNCs in MDD were observed connecting different networks, especially among prefrontal, sensorimotor and cerebellum networks. As to network properties, MDD patients exhibited increased node efficiency in prefrontal and cerebellum. Moreover, three dFNCs with disrupted node properties were commonly identified in different states, which are also correlated with depressive symptom severity and cognitive performance. This study is the first attempt to investigate the dynamic functional abnormalities in Chinese MDD using a relatively large sample size, which provides new evidence
on aberrant time-varying brain activity and its network disruptions in MDD, which might underscore the impaired cognitive functions in this mental disorder. |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/44995]  |
| 专题 | 自动化研究所_脑网络组研究中心 |
| 作者单位 | Institute of Automation, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Zhi DM. Abnormal dynamic functional network connectivity and graph theoretical analysis in major depressive disorder[C]. 见:. Honolulu. 2018/07/17. |
入库方式： OAI收割
来源：自动化研究所
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