计算机应用与软件2018，Vol.35Issue(2)：65-68,85,5.DOI:10.3969/j.issn.1000-386x.2018.02.011
CLM相继故障模型在正常人静息态fMRI脑网络上的研究
STUDY ON CLM CASCADING FAILURE MODEL IN NORMAL PERSON'S RESTING-STATE FMRI BRAIN NETWORK
摘要
Abstract
We investigated the robustness and vulnerability of functional networks of brain by using the CLM model to simulate the resting state of the brain.The complex brain network was modeled with resting-state functional magnetic resonance imaging(fMRI)of 18 volunteers.Then the significant encephalic region was simulated to attack.The global efficiency showed a positive correlation with the capacity parameter when the node with the most loads was attacked. Besides,the whole network has a high efficiency.The result demonstrated that the network of brain had a stable topology and a strong robustness.关键词
相继故障/容量系数/效率/最短路径/功能磁共振成像Key words
Cascading failure/Capacity parameter/Efficiency/Shortest path/Functional magnetic resonance ima-ging分类
信息技术与安全科学引用本文复制引用
柯铭,曹黎..CLM相继故障模型在正常人静息态fMRI脑网络上的研究[J].计算机应用与软件,2018,35(2):65-68,85,5.基金项目
国家自然科学基金项目(61263047). （61263047）
