Independent component analysis for synthesized MEG data

Proc. of the Saitama Institute of Technology Wakate Kenkyuu Forum, pp. 173-176, 2003 (in Japanese)

Independent component analysis for synthesized MEG data

Y. Konno, J. Cao and T. Arai

Abstract: Independent component analysis (ICA) has bee applied to electroencephalographic (EEG) or magnetoencephalographic (MEG) data to determine the behavior and localization of brain sources. In this study, we apply our ICA aigorithm to synthesized MEG data and evaluate the results of decomposition. The main advantage of our synthesized data set is that dipole location of evoked responses and its dynamics are known in advance, which facilitates the evaluation of the decomposed components. In this paper, we demonstrate that not only the location, but also the direction vector of evoked fields (EFs) can be obtained by applying our method.

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