DocumentCode :
3265300
Title :
Robustness of community structure algorithm of complex network in the task state brain function
Author :
Hongyong Li ; Ming Ke ; Xuhui Chen
Author_Institution :
Coll. of Comput. & Commun., Lanzhou Univ. of Technol., Lanzhou, China
fYear :
2013
fDate :
2-5 July 2013
Firstpage :
88
Lastpage :
93
Abstract :
We used the seed-voxel method to construct a brain function network and divided the community structure by greedy algorithm based on the n-back task. And then, we explored brain function network community structure robustness based on improved perturbation model. The results showed that random disturbance has little effect on the community structure, brain function network showed strong robustness. However, the brain function network showed vulnerability in the case of deliberate disturbance. Finally, we found that community connection strength was negatively correlated with robustness, community structure in the best divided state not mean the community robustness reach best, and no synchronization between them.
Keywords :
complex networks; greedy algorithms; neurophysiology; perturbation techniques; random processes; synchronisation; brain function network community structure robustness; community connection strength; community structure algorithm; complex network; greedy algorithm; n-back task; perturbation model; random disturbance; seed-voxel method; synchronization; task state brain function; Brain modeling; Communities; Complex networks; Power system faults; Power system protection; Robustness; Brain function network; Community structure; Robustness; n-back;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Ubiquitous and Future Networks (ICUFN), 2013 Fifth International Conference on
Conference_Location :
Da Nang
ISSN :
2165-8528
Type :
conf
DOI :
10.1109/ICUFN.2013.6614784
Filename :
6614784
Link To Document :
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