Mapping directed influence over the brain using Granger causality and fMRI

被引:733
作者
Roebroeck, A [1 ]
Formisano, E [1 ]
Goebel, R [1 ]
机构
[1] Univ Maastricht, Fac Psychol, Dept Cognit Neurosci, NL-6200 MD Maastricht, Netherlands
关键词
effective connectivity; fMRE Granger causality; autoregressive models;
D O I
10.1016/j.neuroimage.2004.11.017
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
We propose Granger causality mapping (GCM) as an approach to explore directed influences between neuronal populations (effective connectivity) in fMRI data. The method does not rely on a priori specification of a model that contains pre-selected regions and connections between them. This distinguishes it from other fMRI effective connectivity approaches that aim at testing or contrasting specific hypotheses about neuronal interactions. Instead, GCM relies on the concept of Granger causality to define the existence and direction of influence from information in the data. Temporal precedence information is exploited to compute Granger causality maps that identify voxels that are sources or targets of directed influence for any selected region-of-interest. We investigated the method by simulations and by application to fMRI data of a complex visuomotor task. The presented exploratory approach of mapping influences between a region of interest and the rest of the brain can form a useful complement to existing models of effective connectivity. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:230 / 242
页数:13
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