CLM相继故障模型在正常人静息态fMRI脑网络上的研究

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fMRI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.