Harmonic Holes as the Submodules of Brain Network and Network Dissimilarity
Harmonic Holes as the Submodules of Brain Network and Network Dissimilarity
复制标题
谐波空穴作为脑网络和网络相异性的子模块
DOI：
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复制
发表时间：
2018
期刊：
影响因子：
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通讯作者：
Dong Soo Lee
中科院分区：
文献类型：
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作者：
Hyekyoung Lee;M. Chung;Hongyoon Choi;Hyejin Kang;Seunggyun Ha;Yu Kyeong Kim;Dong Soo Lee
持续同源性已被应用于大脑网络分析，以发现跨多个阈值的大脑网络的形状。在持久同调中，网络的形状通常由k维洞的序列和Betti数来量化。在拓扑脑网络分析中，贝蒂数比洞本身更广泛地使用。然而，洞显示了网络的局部连通性，它们在分析中可以提供非常丰富的信息。在这项研究中，我们提出了一种新的方法来衡量网络差异的基础上的相异性措施的谐波洞（HH）。HHS代表了大脑网络的子结构，通过大脑网络的Hodge Laplacian来提取。我们还找到了最有助于HH的网络差异的基础上HH相异度。我们应用我们提出的方法聚类网络的4组，正常对照组（NC），稳定和进行性轻度认知障碍（sMCI和pMCI），阿尔茨海默病（AD）。实验结果表明，该方法的聚类性能优于仅基于全局拓扑变化的网络距离。
Persistent homology has been applied to brain network analysis for finding the shape of brain networks across multiple thresholds. In the persistent homology, the shape of networks is often quantified by the sequence of k-dimensional holes and Betti numbers. The Betti numbers are more widely used than holes themselves in topological brain network analysis. However, the holes show the local connectivity of networks, and they can be very informative features in analysis. In this study, we propose a new method of measuring network differences based on the dissimilarity measure of harmonic holes (HHs). The HHs, which represent the substructure of brain networks, are extracted by the Hodge Laplacian of brain networks. We also find the most contributed HHs to the network difference based on the HH dissimilarity. We applied our proposed method to clustering the networks of 4 groups, normal controls (NC), stable and progressive mild cognitive impairment (sMCI and pMCI), and Alzheimer’s disease (AD). The results showed that the clustering performance of the proposed method was better than that of network distances based on only the global change of topology.
影响因子：
1.8
作者：
G. Singh;F. Mémoli;T. Ishkhanov;G. Sapiro;G. Carlsson;D. Ringach
通讯作者：
G. Singh;F. Mémoli;T. Ishkhanov;G. Sapiro;G. Carlsson;D. Ringach
DOI：
10.1073/pnas.0500334102
发表时间：
2005-05-24
影响因子：
11.1
作者：
Coifman, RR;Lafon, S;Zucker, SW
通讯作者：
Zucker, SW
影响因子：
24.8
作者：
Sporns O;Betzel RF
通讯作者：
Betzel RF