独立成分分析在视觉运动核磁共振数据处理中的应用

摘要

Objective To verify the effectiveness of independent component analysis (ICA) in visuomotor functional magnetic resonance imaging (fMRI) data processing.Methods ICA was applied in the visuomotor fMRI data processing.According to the effective screening criteria,the proper independent components were obtained with FastICA algorithm.The obtained independent components were compared with the function template data.Results FastICA algorithm was used for the ICA processing of data.Component 8 was selected to compare with the functional data,and the comparison showed that the brain activation areas revealed with component 8 were close to that obtained with functional data.Conclusion Components obtained with FastICA method clearly and accurately reveal the brain activation areas related to the visuomotor,which also verifys the effectiveness of ICA in the data processing for dorsal stream.%目的:验证独立成分分析(ICA)方法在处理视觉运动核磁共振数据中的有效性.方法:将ICA方法应用于视觉运动任务态的功能磁共振的数据处理.选用FastICA算法,根据有效的筛选标准选择最佳的独立成分,并将独立成分与功能模板数据进行比较.结果:选用FastICA算法进行数据的ICA处理,并选取成分8与功能数据进行对比.结果显示成分8显示的脑部活跃区域与功能数据较为相符.结论:采用FastICA方法所分离出来的独立成分,能够比较准确地显示脑部与运动视觉相关的活跃区域,同时也验证了ICA方法在分离视觉信息处理的背侧通路的有效性.