【摘要】 独立成分分析(ICA)作为盲源分离的一种有效方法已经被成功的用于处理功能磁共振成像(fMRI)数据,但是通常人们只是考虑处理单个被试的数据,对于多个被试的情况却很少有人考虑,本文中分析了目前国际上比较流行的三种用 ICA来处理多个被试的 fMRI数据的方法,并且利用其中最好的一种方法对我们实验中获得的 fMRI数据进行处理,结果表明这种方法可以快速有效地处理多个被试的 fMRI数据。更多还原

【Abstract】 Independent component analysis (ICA) has been used for processing the functional magnetic resonance imaging (fMRI) data as an effective method of blind source separation, but usually we just analyze the data from one subject, rarely from a group of subjects. In this article we analyzed three popular methods about performing an ICA analysis on a group of subjects. And we used the best method to process the fMRI data from our experiment, the results showed that this method can analyze the fMRI data from a group of subjects fast and effectively.更多还原