标题： 因果关系作为fMRI数据激活和连通性分析之间的统一方法 显示英文标题

标题： Causality as a unifying approach between activation and connectivity analysis of fMRI data

摘要： 本文表明因果关系是统一分析脑区激活和连接性的工具，该分析基于fMRI数据。 因果关系分析通常用于研究连接性，因此本工作重点是证明激活的检测也可以通过因果关系分析来处理。 我们在手指敲击数据上测试了我们的方法，在此过程中比较了GLM和格兰杰因果关系方法在寻找激活方面的表现。 格兰杰因果关系不仅很好地完成了任务，而且我们确实获得了更好的激活定位（即精度）。 因此，我们主张因果关系必须是研究激活的主要工具，因为它是一种衡量刺激如何影响BOLD信号的指标，并且它将连接性和激活分析统一在同一领域内。 显示英文摘要

摘要： This paper indicates causality as the tool that unifies the analysis of both activations and connectivity of brain areas, obtained with fMRI data. Causality analysis is commonly applied to study connectivity, so this work focuses on demonstrating that also the detection of activations can be handled with a causality analysis. We test our method on finger tapping data, in which GLM and Granger Causality approaches are compared in finding activations. Granger causality not only performs the task well, but indeed we obtained a better localization (i.e. precision) of activations. As a result we claim that causality must be the main tool to investigate activations, since it is a measure of "how much" the stimulus influences the BOLD signal, and since it unifies connectivity and activations analysis under the same area.