Path analysis: A method to estimate altered pathways in time-varying graphs of neuroimaging data.

Haleh Falakshahi, Hooman Rokham, Zening Fu, Armin Iraji, Daniel H Mathalon, Judith M Ford, Bryon A Mueller, Adrian Preda, Theo G M van Erp, Jessica A Turner, Sergey Plis, Vince D Calhoun
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引用次数: 1

Abstract

Graph-theoretical methods have been widely used to study human brain networks in psychiatric disorders. However, the focus has primarily been on global graphic metrics with little attention to the information contained in paths connecting brain regions. Details of disruption of these paths may be highly informative for understanding disease mechanisms. To detect the absence or addition of multistep paths in the patient group, we provide an algorithm estimating edges that contribute to these paths with reference to the control group. We next examine where pairs of nodes were connected through paths in both groups by using a covariance decomposition method. We apply our method to study resting-state fMRI data in schizophrenia versus controls. Results show several disconnectors in schizophrenia within and between functional domains, particularly within the default mode and cognitive control networks. Additionally, we identify new edges generating additional paths. Moreover, although paths exist in both groups, these paths take unique trajectories and have a significant contribution to the decomposition. The proposed path analysis provides a way to characterize individuals by evaluating changes in paths, rather than just focusing on the pairwise relationships. Our results show promise for identifying path-based metrics in neuroimaging data.

Abstract Image

Abstract Image

Abstract Image

路径分析:在神经影像数据的时变图中估计改变路径的一种方法。
图论方法已被广泛用于研究精神疾病中的人脑网络。然而,焦点主要集中在全局图形度量上,很少关注连接大脑区域的路径中包含的信息。这些通路破坏的细节可能对了解疾病机制有很大的帮助。为了检测患者组中多步路径的缺失或增加,我们提供了一种算法来估计与对照组相关的这些路径的边缘。接下来,我们通过使用协方差分解方法检查两组中通过路径连接的节点对。我们应用我们的方法来研究精神分裂症患者与对照组的静息状态fMRI数据。结果显示,在精神分裂症的功能域内和功能域之间,特别是在默认模式和认知控制网络中,存在一些分离。此外,我们识别新的边产生额外的路径。此外,尽管两组中都存在路径,但这些路径具有独特的轨迹,并且对分解有重要贡献。所提出的路径分析提供了一种通过评估路径变化来描述个体的方法,而不仅仅是关注成对关系。我们的研究结果显示了在神经成像数据中识别基于路径的指标的希望。
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