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脑网络枢纽在病变模型中的研究:基于患者病变模式预测功能网络拓扑结构

Brain hubs in lesion models: Predicting functional network topology with lesion patterns in patients.

机构信息

National Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.

Department of Neurology, China Rehabilitation Research Center, Rehabilitation College of Capital Medical University, Beijing, 100068, China.

出版信息

Sci Rep. 2017 Dec 20;7(1):17908. doi: 10.1038/s41598-017-17886-x.

Abstract

Various important topological properties of healthy brain connectome have recently been identified. However, the manner in which brain lesion changes the functional network topology is unknown. We examined how critical specific brain areas are in the maintenance of network topology using multivariate support vector regression analysis on brain structural and resting-state functional imaging data in 96 patients with brain damages. Patients' cortical lesion distribution patterns could significantly predict the functional network topology and a set of regions with significant weights in the prediction models were identified as "lesion hubs". Intriguingly, we found two different types of lesion hubs, whose lesions associated with changes of network topology towards relatively different directions, being either more integrated (global) or more segregated (local), and correspond to hubs identified in healthy functional network in complex manners. Our results pose further important questions about the potential dynamics of the functional brain network after brain damage.

摘要

最近已经确定了健康大脑连接组的各种重要拓扑性质。然而,大脑损伤改变功能网络拓扑的方式尚不清楚。我们使用多元支持向量回归分析,对 96 名脑损伤患者的脑结构和静息状态功能成像数据进行了研究,探讨了特定关键脑区在维持网络拓扑中的作用。患者的皮质损伤分布模式可以显著预测功能网络拓扑,并且在预测模型中具有显著权重的一组区域被确定为“损伤枢纽”。有趣的是,我们发现了两种不同类型的损伤枢纽,它们的损伤与网络拓扑朝着相对不同的方向变化有关,要么更加整合(全局),要么更加隔离(局部),并且以复杂的方式对应于健康功能网络中的枢纽。我们的结果进一步提出了关于脑损伤后功能脑网络潜在动力学的重要问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecfb/5738424/2eeba0f46c5c/41598_2017_17886_Fig1_HTML.jpg

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