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

机译:功能性MRI有效连通性中结构方程建模与部分相关关系的理论研究

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摘要

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.
机译:依赖于血氧水平(BOLD)的功能磁共振成像(fMRI)的重要领域是对有效连通性的研究,即对给定区域集相互作用的作用。我们最近提出了一种基于偏相关矩阵的数据驱动方法,该方法可以提供有关结构方程模型(SEM)表示的大脑区域之间功能相互作用模式的一些见解。到目前为止,这种方法的效率主要基于经验证据。在本文中,我们提供了理论基础,解释了结构方程建模和部分相关为何以及在何种程度上相关。通过部分相关分析可以检索到SEM的哪些部分,以及哪些仍然无法访问,从而提供了更好的见解。我们用实际数据说明了不同的结果。

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