A method for functional network connectivity among spatially independent resting-state components in schizophrenia
A method for functional network connectivity among spatially independent resting-state components in schizophrenia
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DOI：
10.1016/j.neuroimage.2007.11.001
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发表时间：
2008-02-15
期刊：
影响因子：
5.7
通讯作者：
Calhoun, Vince D.
中科院分区：
文献类型：
--
作者：
Jafri, Madiha J.;Pearlson, Godfrey D.;Calhoun, Vince D.
已经通过分析健康个体以及患有脑疾病的患者中的种子体素或区域与脑的其他体素之间的时间过程的相关性差异来研究脑的功能连接性。在休息期间共同激活的强时间相干的大脑区域的空间范围也被检查使用独立成分分析（伊卡）。然而，伊卡组件的时间过程中，我们操作定义为功能网络连接（FNC）的措施，较弱的时间关系尚未被研究。在这项研究中，我们提出了一种评估FNC的方法，并将其应用于从精神分裂症患者和健康对照组收集的功能磁共振成像（fMRI）数据。我们研究了伊卡组件的时间过程之间的连接和延迟来检验这一假设，即精神分裂症患者将显示出增加的功能连接和增加的静息状态网络之间的滞后与对照组相比。静息状态的功能磁共振成像数据进行了收集和相互关系的7个选定的静息状态网络（确定使用组伊卡）进行了评估，通过相互关联每个主题的伊卡时间过程。在大多数占主导地位的静息状态网络中，患者表现出比对照组更高的相关性。与对照组相比，患者在功能连接方面的变异性也略多。我们提出了一种新的方法来量化空间伊卡识别的大脑网络之间的功能连接。患者和控制连接在不同的网络之间的显着差异被揭示可能反映在患者的皮层处理的缺陷。(C)2007年爱思唯尔公司All rights reserved.
Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in healthy individuals as well as in patients with brain disorders. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the interrelationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject's ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients. (C) 2007 Elsevier Inc. All rights reserved.