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精神分裂症静息态功能网络连接的拓扑性质改变:一项小世界脑网络研究。

Altered topological properties of functional network connectivity in schizophrenia during resting state: a small-world brain network study.

机构信息

The Mind Research Network, Albuquerque, New Mexico, United States of America.

出版信息

PLoS One. 2011;6(9):e25423. doi: 10.1371/journal.pone.0025423. Epub 2011 Sep 28.

Abstract

Aberrant topological properties of small-world human brain networks in patients with schizophrenia (SZ) have been documented in previous neuroimaging studies. Aberrant functional network connectivity (FNC, temporal relationships among independent component time courses) has also been found in SZ by a previous resting state functional magnetic resonance imaging (fMRI) study. However, no study has yet determined if topological properties of FNC are also altered in SZ. In this study, small-world network metrics of FNC during the resting state were examined in both healthy controls (HCs) and SZ subjects. FMRI data were obtained from 19 HCs and 19 SZ. Brain images were decomposed into independent components (ICs) by group independent component analysis (ICA). FNC maps were constructed via a partial correlation analysis of ICA time courses. A set of undirected graphs were built by thresholding the FNC maps and the small-world network metrics of these maps were evaluated. Our results demonstrated significantly altered topological properties of FNC in SZ relative to controls. In addition, topological measures of many ICs involving frontal, parietal, occipital and cerebellar areas were altered in SZ relative to controls. Specifically, topological measures of whole network and specific components in SZ were correlated with scores on the negative symptom scale of the Positive and Negative Symptom Scale (PANSS). These findings suggest that aberrant architecture of small-world brain topology in SZ consists of ICA temporally coherent brain networks.

摘要

先前的神经影像学研究已经证明,精神分裂症(SZ)患者的小世界人脑网络存在拓扑性质异常。先前的静息态功能磁共振成像(fMRI)研究也发现 SZ 患者存在功能网络连接(FNC,独立成分时间进程之间的时间关系)异常。然而,尚无研究确定 FNC 的拓扑性质是否也在 SZ 中发生改变。在这项研究中,我们在健康对照组(HCs)和 SZ 受试者中检查了静息状态下 FNC 的小世界网络度量。从 19 名 HCs 和 19 名 SZ 中获得了 fMRI 数据。通过组独立成分分析(ICA)将脑图像分解为独立成分(ICs)。通过 ICA 时间进程的偏相关分析构建了 FNC 图。通过对 FNC 图进行阈值处理构建了一组无向图,并评估了这些图的小世界网络度量。我们的结果表明,与对照组相比,SZ 中 FNC 的拓扑性质发生了明显改变。此外,与对照组相比,涉及额叶、顶叶、枕叶和小脑区域的许多 IC 的拓扑测度也发生了改变。具体而言,SZ 中整个网络和特定组件的拓扑测度与阳性和阴性症状量表(PANSS)的阴性症状量表评分相关。这些发现表明,SZ 中小世界脑拓扑结构的异常结构由 ICA 时间上一致的脑网络组成。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83bf/3182226/3a314d1e3fab/pone.0025423.g001.jpg

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