Combining Graph Analysis and Recurrence Plot on fMRI data

A. Lombardi, P. Guccione, L. Mascolo, P. Taurisano, L. Fazio, G. Nico
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引用次数: 2

Abstract

In this work we investigate on the nonlinear properties of the brain networks using Graph Analysis and Cross Recurrence Plot. The nonlinear dynamics of the brain is analyzed using time series coming from fMRI data. Two groups of human subjects, one affected by schizophrenia and the other of healthy controls, are imaged during the completion of a working memory task. To examine the spatio-temporal properties of the BOLD signal, nonlinear recurrence properties are extracted from the time series of the most relevant voxels, using the cross recurrence plots and the corresponding measures. Then, a graph is built using such measures as weights between different brain regions (the nodes). The purpose of the paper is to give a description of the most relevant functional areas activated during the task completion and to capture the differences between the groups. Results are promising, since the methodology is still to be fully developed and explored.
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fMRI数据的图分析与递归图相结合
在这项工作中,我们使用图分析和交叉递归图来研究大脑网络的非线性特性。利用来自功能磁共振成像数据的时间序列分析了大脑的非线性动力学。两组人类受试者,一组患有精神分裂症,另一组健康对照,在完成工作记忆任务时进行成像。为了检验BOLD信号的时空特性,利用交叉递归图和相应的度量,从最相关体素的时间序列中提取非线性递归特性。然后,使用诸如不同大脑区域(节点)之间的权重之类的度量来构建图。本文的目的是描述在任务完成过程中激活的最相关的功能区域,并捕捉组之间的差异。结果是有希望的,因为该方法仍有待充分发展和探索。
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