Computer Science ›› 2022, Vol. 49 ›› Issue (2): 241-247.doi: 10.11896/jsjkx.201200067

• Artificial Intelligence • Previous Articles     Next Articles

Comparative Analysis of Robustness of Resting Human Brain Functional Hypernetwork Model

ZHANG Cheng-rui, CHEN Jun-jie, GUO Hao   

  1. School of Information and Computer,Taiyuan University of Technology,Jinzhong,Shanxi 030600,China
  • Received:2020-12-07 Revised:2021-05-17 Online:2022-02-15 Published:2022-02-23
  • About author:ZHANG Cheng-rui,born in 1996,M.S candidate.Her main research interests include intelligent information proces-sing,brain informatics.
    GUO Hao,born in 1981,Ph.D,professor,is a senior member of China Computer Federation.His main research interests include artificial intelligence,intelligent information processing,brain informatics.
  • Supported by:
    National Natural Science Foundation of China(61672374,61741212,61876124,61873178),Applied Basic Research Project of Shanxi Provincial Department of Science and Technology Youth General Project(201601D021073,201801D121135),Science and Technology Innovation Research Project of Shanxi(2016139),CERNET Innovation Project Provincial Department of Education(NGII20170712),Key R & D projects In Shanxi Province(201803D31043),Study Abroad Program Supported by National Study Fund(201708140216) and General Projects of National Fund(61976150).

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.

Key words: Brain network, Group lasso, Hypernetwork, Intentional attack, Lasso, Robustness, Sparse group lasso

CLC Number: 

  • TP393
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