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Identification of Active Targets in Primate Brain Network
被引:0
|作者:
Ying, Long
[2
]
Ding, De-wu
[1
]
机构:
[1] Chizhou Coll, Dept Math & Comp Sci, Chizhou, Peoples R China
[2] Natl Univ Def Technol, Dept Educ, Changsha, Hunan, Peoples R China
来源:
关键词:
brain network;
centrality;
complex network;
scale-free;
small-world;
RETRIEVAL;
D O I:
10.1109/ICICSE.2013.31
中图分类号:
TP39 [计算机的应用];
学科分类号:
081203 ;
0835 ;
摘要:
The huge developments (e.g., small-world and scale-free network theories) in complex networks have inspired new applications in neuroscience fields. To data, lots of studies have suggested that complex networks could also be used in the complex brain systems. In despite of the analysis in brain networks, the centrality methods that could be help to seek for important units in networks have been proved powerful tool in many complex networks. We thus engage PageRank centrality method to study a primate brain network in this paper. We constructed the whole and the giant strong component of macaque brain, and analyzed the top 20 important active targets (regions) in the network.
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页码:122 / 124
页数:3
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