Knowledge Commons of Institute of Automation,CAS
Test-retest Reliability of Functional Connectivity and Graph Metrics in the Resting Brain Network | |
Jin, Dan1,2![]() ![]() ![]() ![]() ![]() | |
2018-07 | |
会议名称 | International Conference of the IEEE Engineering in Medicine and Biology Society |
会议日期 | July 18-21 |
会议地点 | Honolulu, HI, USA |
出版者 | IEEE |
摘要 | The combination of graph theoretical approaches and neuroimaging data provides a powerful way to explore the characteristics of brain network. Recently, the temporal variability of spontaneous brain activity and functional connectivity has attracted wide attention. Thus, it is essential to evaluate the reliability of functional network connectivity and properties from the dynamic perspective. However, previous test-retest (TRT) studies have explored this reliability with a static point of view. In this study, using a large rs-fMRI dataset from Human Connectome Project (HCP), we investigated TRT reliability of functional connectivity and graph metrics derived from the most commonly used method – sliding window at three time intervals (short: 72 seconds, middle: 15 minutes and long: >24 hours). The results revealed that reliable connectivities and related brain regions are mainly distributed in primary cortex, such as visual area and sensorimotor area and default mode network. Notably, connectivity strength and global efficiency have better reliability than other metrics. Finally, short scan time interval and long scan duration can increase the TRT reliability of metrics. Findings of present study provide important guidance for searching reliable network markers in future research. |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39157 |
专题 | 脑图谱与类脑智能实验室_脑网络组研究 |
通讯作者 | Liu, Yong |
作者单位 | 1.Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.University of Chinese Academy of Sciences, Beijing, China 3.CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室; 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Jin, Dan,Xu, Kaibin,Liu, Bing,et al. Test-retest Reliability of Functional Connectivity and Graph Metrics in the Resting Brain Network[C]:IEEE,2018. |
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