摘要
利用CLM模型对正常人静息态的大脑模拟攻击,研究人脑功能网络的鲁棒性及脆弱性。对18例正常志愿者的静息态f MRI数据进行复杂网络建模,然后对关键脑区模拟攻击。攻击负荷最大节点,发现脑网络全局效率与容量系数呈正相关。同时,整个脑网络具有较高效率。结果表明,脑网络具有较稳定的拓扑结构和较强鲁棒性。
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.
出处
《计算机应用与软件》
北大核心
2018年第2期65-68,85,共5页
Computer Applications and Software
基金
国家自然科学基金项目(61263047)
关键词
相继故障
容量系数效率
最短路径功能
磁共振成像
Cascading failure
Capacity parameter
Efficiency
Shortest path
Functional magnetic resonance imaging
