期刊
NEUROIMAGE
卷 65, 期 -, 页码 540-555出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2012.09.049
关键词
Granger causality; Functional connectivity; Functional MRI; Hemodynamic response function; Computational modeling
资金
- EPSRC [EP/G007543/1]
- Dr. Mortimer and Theresa Sackler Foundation via the Sackler Centre for Consciousness Science
- EPSRC [EP/G007543/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/G007543/1] Funding Source: researchfish
Granger causality is a method for identifying directed functional connectivity based on time series analysis of precedence and predictability. The method has been applied widely in neuroscience, however its application to functional MRI data has been particularly controversial, largely because of the suspicion that Granger causal inferences might be easily confounded by inter-regional differences in the hemodynamic response function. Here, we show both theoretically and in a range of simulations, that Granger causal inferences are in fact robust to a wide variety of changes in hemodynamic response properties, including notably their time-to-peak. However, when these changes are accompanied by severe downsampling, and/or excessive measurement noise, as is typical for current fMRI data, incorrect inferences can still be drawn. Our results have important implications for the ongoing debate about lag-based analyses of functional connectivity. Our methods, which include detailed spiking neuronal models coupled to biophysically realistic hemodynamic observation models, provide an important 'analysis-agnostic' platform for evaluating functional and effective connectivity methods. (C) 2012 Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据