动态脑功能网络Rich-club时空观测方法
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作者单位:

1.昆明理工大学信息工程与自动化学院,昆明,650500;2.昆明理工大学云南省人工智能重点实验室,昆明,650500;3.云南省公安厅禁毒局,昆明,650228

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国家自然科学基金 (81771926;61763022;61863018) 资助项目。


Spatiotemporal Observation Method of Rich-club in Dynamic Brain Function Network
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Affiliation:

1.Faculty of Information Engineering & Automation, Kunming University of Science & Technology, Kunming,650500,China;2.Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming, 650500, China;3.Narcotics Control Administration of Yunnan Provincial Public Security Department, Kunming, 650228, China

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    摘要:

    基于fMRI-BOLD信号的脑功能网络重要脑区时变特征辨识问题,提出了一种动态脑网络Rich-club时空观测模型的构建方法。该方法通过将样本所有时间采样点的Rich-club集合相似性进行聚类,从而将脑功能网络的空间与时间融合在一起,并构建脑网络中动态Rich-club重要性评价模型,定量地描述脑网络中Rich-club集合在时间以及空间两个维度的综合重要程度,从而为脑功能网络重要脑区的动态特征观测提供了一种有效的方法,也为分析健康人与自闭症患者之间的脑区重要性差异提供了依据。

    Abstract:

    Aiming at time-varying feature identification of important brain regions in brain functional network based on fMRI-BOLD signal, a method of constructing time-varying observation model of dynamic brain network Rich-club is proposed in this paper. By clustering the similarity of Rich-club set of all time sampling points for one people, the temporal and spatial information of the brain function network is fused, and then the dynamic Rich-club importance evaluation model for brain network is built, which can describe the spatiotemporal comprehensive importance of the important brain regions quantitatively. Our work presents an effective method for the dynamic feature observation of the important brain regions in brain dynamic function network, and it also provides a basis technology for analyzing the differences of the important brain regions between healthy people and autistic people.

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盛景业,王彬,薛洁,淡杨超,刘畅.动态脑功能网络Rich-club时空观测方法[J].数据采集与处理,2020,35(2):239-250

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  • 收稿日期:2019-12-04
  • 最后修改日期:2020-02-22
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  • 在线发布日期: 2020-03-25