摘要
分析静息状态下人脑中不同区域之间的功能连接模式对研究静息状态下人脑正常功能活动具有重要意义。基于复杂网络理论对脑功能网络进行建模,考察静息状态脑功能网络的结构和拓扑特性。结果显示,网络具有小世界性质和无标度特性。进一步引入一种概率混合模型分析网络社团结构,得到的10个子网络中包含视觉系统、听觉系统、运动系统、默认网络以及与执行和工作记忆相关的脑区。推测出静息状态脑功能网络是由这些相对独立又彼此关联的子网络组成,其中楔前叶和扣带回作为网络的关键节点,在信息调度和传递中占据重要地位。
It is important to understand the functional activity of the human brain during the resting state by analyzing the functional connectivity between the regions. The resting-state brain functional network was constructed based on the complex network theory. The result of analyzing the structure and topology of network showed that the resting-state brain functional network was a sparse and scale-free small-world network. Furthermore, a probabilistic mixture models was introduced to detect the community structure, which revealed 10 sub-networks underlying the network, including the visual system, auditory system, motor system, and default-mode network, as well as the brain regions associated with the executive and working memory function. Our findings suggested that the resting-state functional network of human brain was composed of these relatively independent and overlapping sub-networks, and the preeuneus and eingulate gyrus played important roles in dispatching and transferring information of network.
出处
《国防科技大学学报》
EI
CAS
CSCD
北大核心
2010年第1期147-151,共5页
Journal of National University of Defense Technology
基金
国家部委资助项目(2007CB311001)
国家自然科学基金资助项目(60835005
60771062
90820304)
关键词
功能连接
复杂网络
静息状态
中心化
社团
功能磁共振成像
functional connectivity
complex network
resting state
centralization
community
fimetional magnetic resonance imaging
