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静息脑功能连接性是研究脑功能的重要技术手段。我们提出了利用空域独立成分分析(Independent component analysis,ICA)来处理静息态功能磁共振(Functional magnetic resonance i maging,f MRI)数据,首次将静息态脑功能的低频振荡理论应用于ICA静态数据分析的成分选择,通过Z分数选择静息态下的活动点并去除独立噪点,然后通过频谱分析选择主要能量集中在0.01~0.1Hz的独立成分,进而采用聚类分析得出脑功能连接网络。
Resting Cerebral Function Connectivity is an important technique for studying brain function. We proposed the use of Independent Component Analysis (ICA) to process fMRI data. For the first time, the theory of low frequency oscillation of resting brain function was applied to ICA static The components of data analysis are selected, the active points in rest state are selected by Z score and the independent noise is removed, and then the independent components with the main energy concentration in 0.01 ~ 0.1Hz are selected by spectrum analysis, and then the cluster analysis is used to obtain the brain function connection network .