ANALYSIS AND PROCESSING OF MAGNATO ENCEPHATO GRAPHY(MEG) DATA BASED ON INDEPENDENT COMPONENT ANALYSIS (ICA)
基于独立元分析的MEG(脑磁图)数据分析和处理

It has been verified that the ICA can isolate artifacts from overlapping MEG signals. Removing these artifacts from ICA representation, and then projecting the remaining components back into the data space, cleaned MEG data can be obtained. Other independent components can be separately projected back onto the scalp to show the patterns of activities related to the human brain. That the evoked signals in response to stim-ulation can also be separated from the overlapping MEG data is extremely attractive for the study of brain functions. Thus, a simple and efficient method for the analysis of MEG data has been proposed. Some practical problems for application were been studied and discussed, and some interesting results for auditory evoked ex-periments were been shown in the paper. The results demonstrate that ICA is an extremely promising tool for the processing and analysis of MEG data.