Comparison of functional network connectivity and granger causality for resting state fMRI data

Ce Zhang, Qiu Hua Lin, Chao Ying Zhang, Ying Guang Hao, Xiao Feng Gong, Fengyu Cong, Vince Daniel Calhoun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationAdvances in Neural Networks - ISNN 2017 - 14th International Symposium, ISNN 2017, Proceedings
PublisherSpringer Verlag
Pages559-566
Number of pages8
Volume10262 LNCS
ISBN (Print)9783319590806
DOIs
StatePublished - 2017
Externally publishedYes
Event14th International Symposium on Neural Networks, ISNN 2017 - Sapporo, Hakodate, and Muroran, Hokkaido, Japan
Duration: Jun 21 2017Jun 26 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10262 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th International Symposium on Neural Networks, ISNN 2017
CountryJapan
CitySapporo, Hakodate, and Muroran, Hokkaido
Period6/21/176/26/17

Keywords

  • Default mode network
  • Functional network connectivity
  • Granger causality
  • Group ICA
  • Resting state fMRI

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Comparison of functional network connectivity and granger causality for resting state fMRI data'. Together they form a unique fingerprint.

Cite this