Effective Connectivity of Resting-state Functional Magnetic Resonance Imaging in Normal Adults
10.3969/j.issn.1006-9771.2014.06.010
- VernacularTitle:正常人脑静息态功能磁共振的脑功能连接
- Author:
Qingli SHI
;
Hao YAN
;
Hongyan CHEN
;
Kai WANG
;
Jingyao YAO
;
Zaizhu HAN
;
Yumei ZHANG
;
Guiyun ZHANG
;
Yuping GAO
- Publication Type:Journal Article
- Keywords:
resting-state functional magnetic resonance imaging, brain network connection, independent component analysis
- From:
Chinese Journal of Rehabilitation Theory and Practice
2014;(6):543-547
- CountryChina
- Language:Chinese
-
Abstract:
Objective To detect the effective connectivity of resting- state functional magnetic resonance imaging (fMRI) in normal adults. Methods 36 normal adults were performed resting-state fMRI scanning, and 5 brain netwokes were included as regions of interests. Independent component (ICA) was used to evaluate the effective connectivity, and multivariate Granger causality analysis (mGCA) was used to analyze the casuality between the networks. All preprocessing steps were carried out using Statistical Parametric Mapping 5.0 software. Results 5 classic resting brain networks including default mode network (DMN), memory network (MeN), motor network (MoN), auditory network (AN) and executive control network (ECN) were aquired. The mGCA presented significant casuality between DMN and other 4 networks, MeN and ECN, AN and MoN, ECN and AN. Conclusion There are specific brain effective connectivity of resting-state fMRI in normal adults, and there is significant causal link between these networks.
