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Computational Intelligence and Neuroscience
Volume 2009, Article ID 369341, 9 pages
Research Article

A Theoretical Investigation of the Relationship between Structural Equation Modeling and Partial Correlation in Functional MRI Effective Connectivity

1Inserm, U678, Laboratoire d’Imagerie Fonctionnelle, F-75013 Paris, France
2UPMC Univ Paris 06, UMR-S 678, Laboratoire d’Imagerie Fonctionnelle, F-75013 Paris, France

Received 31 October 2008; Accepted 15 May 2009

Academic Editor: Fabio Babiloni

Copyright © 2009 Guillaume Marrelec and Habib Benali. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


An important field of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) is the investigation of effective connectivity, that is, the actions that a given set of regions exert on one another. We recently proposed a data-driven method based on the partial correlation matrix that could provide some insight regarding the pattern of functional interaction between brain regions as represented by structural equation modeling (SEM). So far, the efficiency of this approach was mostly based on empirical evidence. In this paper, we provide theoretical fundaments explaining why and in what measure structural equation modeling and partial correlations are related. This gives better insight regarding what parts of SEM can be retrieved by partial correlation analysis and what remains inaccessible. We illustrate the different results with real data.