Increasing fMRI sampling rate improves Granger causality estimates

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題名:	Increasing fMRI sampling rate improves Granger causality estimates
作者:	郭文瑞;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.
貢獻者:	生醫理工學院認知神經科學研究所
關鍵詞:	Adult;Biology and Life Sciences;Biomedical engineering;Brain;Brain - physiology;Brain mapping;Brain Mapping - methods;Causality;Cognition;Cointegration analysis;Connectivity analysis;Data points;Economic models;Engineering;Engineering and Technology;Estimates;Female;Functional magnetic resonance imaging;Head;Hemodynamics;Humans;Image Processing, Computer-Assisted;Information flow;Magnetic resonance;Magnetic resonance imaging;Magnetic Resonance Imaging - methods;Male;Medical schools;Medicine and Health Sciences;Neural networks;Neuroimaging;Neurosciences;Oxygenation;Research and Analysis Methods;Sampling;Sensorimotor integration;Temporal resolution;Time Factors;Time series;Young Adult
日期:	2014-06-26
上傳時間:	2026-04-23 14:27:55 (UTC+8)
出版者:	Public Library of Science;United States: Public Library of Science
摘要:	摘要： 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. 其他題名： PLoS One 出版者： United States: Public Library of Science 出版日期： 2014-06-26 出處： PloS one, 2014-06, Vol.9 (6), p.e100319 資源來源： Agricultural & Environmental Science Collection 版權： COPYRIGHT 2014 Public Library of Science 版權： 2014 Lin et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 版權： 2014 Lin et al 2014 Lin et al 識別號： ISSN: 1932-6203 識別號： EISSN: 1932-6203 識別號： DOI: 10.1371/journal.pone.0100319 識別號： PMID: 24968356
顯示於類別:	[認知與神經科學研究所 ] 期刊論文

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