Analysing MEG-Data by a Combination of Different Neural Networks

The localization of intracerebral dipole sources for detecting pathological events is one object of magnetoencephalography (MEG). Another one is the analysis of brain processing and brain structures. We present a system consisting of two different types of Artificial Neural Networks. One for the separation of temporally overlapping sources and the other one for the determination of the different magnetic dipoles.1

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