计算机应用研究2024，Vol.41Issue(4)：1094-1103,10.DOI:10.19734/j.issn.1001-3695.2023.09.0367
MCI患者高阶动态功能连接的图论网络构建方法及分类
Graph theory network construction method and classification of high-order dynamic functional connections in MCI patients
摘要
Abstract
The application of graph theory to low-order brain networks ignores the high-order dynamics of functional connec-tions.To address these issues,this paper proposed a graph-theoretic network construction method based on high-order dynamic functional connectivity(GNC-HodFC),to analyze and classify the difference between patients with mild cognitive impairment and healthy subjects by extracting the graph theory features of higher-order FC network.Firstly,the algorithm defined graph theoretic nodes and edges that represented high-order dynamic brain network connections.Then,the algorithm used sliding window technology to extract low-order functional connection information,and put forward the stability criterion for selecting the optimal feature subset to build graph nodes.Finally,the algorithm proposed adaptive threshold strategy selection of high order dynamic functional connection information so as to build the edge of graph theory,which completed the graph construc-tion of the higher-order dynamic brain network.The experimental results show that the average classification accuracy of GNC-HodFC is 70.5％,which is better than the other three comparison methods,and there are significant differences in the graph theory characteristics between the patient group and the healthy group.GNC-HodFC method can provide a new auxiliary means for the diagnosis of mild cognitive impairment.关键词
轻度认知障碍/动态功能连接/图论/低阶网络/高阶网络Key words
mild cognitive impairment(MCI)/dynamic functional connectivity/graph-theoretic/low-order network/high-order network分类
信息技术与安全科学引用本文复制引用
王霞,王勇,吴海锋,张珊,王卓然..MCI患者高阶动态功能连接的图论网络构建方法及分类[J].计算机应用研究,2024,41(4):1094-1103,10.基金项目
云南省科技厅面上项目(202201AT070021) （202201AT070021）
云南省教育厅科学研究基金资助项目(2022J0439) （2022J0439）
