Comparative Analysis of Robustness of Resting Human Brain Functional Hypernetwork Model

Abstract

As a kind of dynamic behavior,robustness is also a research hotspot in the field of hypernetworks,which has important practical significance for the construction of robust networks.Although there are more and more researches on hypernetwork,the dynamic research is relatively less,especially in the field of neural imaging.Most of the existing researches on brain functional hypernetworks are about the static topological properties of the networks,and there is no relevant research on the dynamic characteristics robustness of brain functional hypernetworks.To solve these problems,lasso,group lasso and sparse group lasso me-thods are used to solve the sparse linear regression model to construct a hypernetwork.Then,based on the two experimental mo-dels of deliberate attack,node degree and node betweenness attack,the robustness of brain functional hypernetwork in response to node failure is explored by using the global efficiency and the relative size of the largest connected subgraph.Finally,a comparative analysis is made to explore a more stable network.The experimental results show that the hypernetwork constructed by group lasso and sparse group lasso is more robust in intentional attack mode.At the same time,the hypernetwork constructed by group lasso method is the most stable.

Keywords

• brain network|hypernetwork|lasso|group lasso|sparse group lasso|intentional attack|robustness