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论文类型：会议论文

发表时间：2017-01-01

收录刊物：EI、CPCI-S

卷号：10262

页面范围：559-566

关键字：Functional network connectivity; Granger causality; Resting state fMRI; Group ICA; Default mode network

摘要：Functional network connectivity (FNC) and Granger causality have been widely used to identify functional and effective connectivity for resting functional magnetic resonance imaging (fMRI) data. However, the relationship between these two approaches is still unclear, making it difficult to compare results. In this study, we investigate the relationship by constraining the FNC lags and the causality coherences for analyzing resting state fMRI data. The two techniques were applied respectively to examine the connectivity within default mode network related components extracted by group independent component analysis. The results show that FNC and Granger causality provide complementary results. In addition, when the temporal delays between two nodes were larger and the causality coherences were distinct, the two approaches exhibit consistent functional and effective connectivity. The consensus between the two approaches provides additional confidence in the results and provides a link between functional and effective connectivity.