@inproceedings{f5a14d0813d34b2f9d5ea0acce8dc4a6,
title = "Comparison of functional network connectivity and granger causality for resting state fMRI data",
abstract = "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.",
keywords = "Default mode network, Functional network connectivity, Granger causality, Group ICA, Resting state fMRI",
author = "Ce Zhang and Lin, {Qiu Hua} and Zhang, {Chao Ying} and Hao, {Ying Guang} and Gong, {Xiao Feng} and Fengyu Cong and Calhoun, {Vince D.}",
note = "Funding Information: This work was supported by National Natural Science Foundation of China under Grants 61379012, 61671106, and 81471742, NSF grants 0840895 and 0715022, NIH grants R01EB005846 and 5P20GM103472, the Fundamental Research Funds for the Central Universities (China, DUT14RC(3)037), and the China Scholarship Council. Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 14th International Symposium on Neural Networks, ISNN 2017 ; Conference date: 21-06-2017 Through 26-06-2017",
year = "2017",
doi = "10.1007/978-3-319-59081-3_65",
language = "English (US)",
isbn = "9783319590806",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "559--566",
editor = "Fengyu Cong and Qinglai Wei and Andrew Leung",
booktitle = "Advances in Neural Networks - ISNN 2017 - 14th International Symposium, ISNN 2017, Proceedings",
}