Abstract：The connectome analysis can help us to have a better understanding of human brain networks. In order to detect the influence of the multi-scale parcellation on connectome analysis, this paper studied the brain network from three scales(32 nodes, 128 nodes and 512 nodes). The results revealed that small-world property existed over those brain networks, and the network features showed some trends related to the parcellation scale. For example, the shortest path length increased with the decrease of the parcellation scale, clustering coefficient decrease with the decrease of the parcellation scale, while the degree increased firstly and then decreased. Additionally, this paper also found that multi-scale parcellation had no significant effect on the network modularity structure, but had somewhat impact on hub regions.
靳聪，林岚，付振荣，宾光宇，高宏建，吴水才. 多尺度分割对脑连接组分析的影响[J]. 中国医疗设备, 2015, 30(6): 18-22.
JIN Cong, LIN Lan, FU Zhen-rong, Bin Guang-yu, GAO Hong-jian, WU Shui-cai. Influence of Multi-Scale Parcellation on Connectome Analysis. China Medical Devices, 2015, 30(6): 18-22.
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