Increasing fMRI Sampling Rate Improves Granger Causality Estimates

Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show tha...

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Main Authors:	Lin, Fa-Hsuan, Ahveninen, Jyrki, Raij, Tommi, Witzel, Thomas, Chu, Ying-Hua, Jääskeläinen, Iiro P., Tsai, Kevin Wen-Kai, Kuo, Wen-Jui, Belliveau, John W.
Format:	Online
Language:	English
Published:	Public Library of Science 2014
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4072680/

id	pubmed-4072680
recordtype	oai_dc
spelling	pubmed-40726802014-07-02 Increasing fMRI Sampling Rate Improves Granger Causality Estimates Lin, Fa-Hsuan Ahveninen, Jyrki Raij, Tommi Witzel, Thomas Chu, Ying-Hua Jääskeläinen, Iiro P. Tsai, Kevin Wen-Kai Kuo, Wen-Jui Belliveau, John W. Research Article Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI) is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD) contrast based whole-head inverse imaging (InI). Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain. Public Library of Science 2014-06-26 /pmc/articles/PMC4072680/ /pubmed/24968356 http://dx.doi.org/10.1371/journal.pone.0100319 Text en © 2014 Lin et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Lin, Fa-Hsuan Ahveninen, Jyrki Raij, Tommi Witzel, Thomas Chu, Ying-Hua Jääskeläinen, Iiro P. Tsai, Kevin Wen-Kai Kuo, Wen-Jui Belliveau, John W.
spellingShingle	Lin, Fa-Hsuan Ahveninen, Jyrki Raij, Tommi Witzel, Thomas Chu, Ying-Hua Jääskeläinen, Iiro P. Tsai, Kevin Wen-Kai Kuo, Wen-Jui Belliveau, John W. Increasing fMRI Sampling Rate Improves Granger Causality Estimates
author_facet	Lin, Fa-Hsuan Ahveninen, Jyrki Raij, Tommi Witzel, Thomas Chu, Ying-Hua Jääskeläinen, Iiro P. Tsai, Kevin Wen-Kai Kuo, Wen-Jui Belliveau, John W.
author_sort	Lin, Fa-Hsuan
title	Increasing fMRI Sampling Rate Improves Granger Causality Estimates
title_short	Increasing fMRI Sampling Rate Improves Granger Causality Estimates
title_full	Increasing fMRI Sampling Rate Improves Granger Causality Estimates
title_fullStr	Increasing fMRI Sampling Rate Improves Granger Causality Estimates
title_full_unstemmed	Increasing fMRI Sampling Rate Improves Granger Causality Estimates
title_sort	increasing fmri sampling rate improves granger causality estimates
description	Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI) is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD) contrast based whole-head inverse imaging (InI). Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain.
publisher	Public Library of Science
publishDate	2014
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4072680/
_version_	1612106822155501568

Increasing fMRI Sampling Rate Improves Granger Causality Estimates

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