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作 者:柯铭[1] 许迪 王常亮 刘光耀[2] KE Ming;XU Di;WANG Changliang;LIU Guangyao(College of Computer and Communication,Lanzhou University of Technology,Lanzhou 730050,China;Department of Magnetic Resonance,Lanzhou University Second Hospital,Lanzhou 730050,China)
机构地区:[1]兰州理工大学计算机与通信学院,甘肃兰州730050 [2]兰州大学第二医院磁共振科,甘肃兰州730050
出 处:《华中科技大学学报(自然科学版)》2024年第5期76-82,共7页Journal of Huazhong University of Science and Technology(Natural Science Edition)
基 金:国家自然科学基金资助项目(61966023,82160326).
摘 要:为探究多层脑功能网络和单层脑功能网络的联系与差异,收集34位健康个体在静息状态下的功能磁共振成像数据,分别构建单层网络和多层网络模型并进行社区检测,分析两种模型的模块划分差异、网络拓扑指标间的联系及脑节点的分类情况.研究结果表明:多层网络的模块数量和质量显著高于单层网络,两种模型的网络拓扑指标间存在显著相关性,多层网络将脑节点划分为21个provincial hubs,49个connector non-hubs和20个peripheral non-hubs.显示了多层网络在研究大脑动态性具有独特优势,揭示了大脑功能的模块化特征,为深入理解大脑动态性提供了重要的思路和方法.To explore the connections and differences between multilayer brain functional network and single-layer brain functional network,the resting-state functional magnetic resonance imaging(rs-fMRI)data of 34 healthy individuals were collected.The single-layer network and multilayer network model were constructed respectively,and community detection was performed.The differences in module division,the connections between network topology metrics and classification of brain nodes were analyzed between multilayer brain functional network and single-layer brain functional network.Research results show that the quantity and quality of modules in the multilayer network are significantly higher than those in the single-layer network.There are significant correlations between the network topology metrics of the two models.The multilayer network divides the brain nodes into 21 provincial hubs,49 connector non-hubs and 20 peripheral non-hubs.It is shown that the multilayer network has unique advantages in the study of brain dynamics.The multilayer network reveals the modular characteristics of brain functions and provides important ideas and methods for in-depth understanding of brain dynamics.
关 键 词:多层网络 单层网络 社区检测 网络拓扑指标 大脑动态性
分 类 号:R318[医药卫生—生物医学工程]
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