Non-independent BSS: A Model for Evoked MEG Signals with Controllable Dependencies

Authors:
Florian Kohl;Gerd Wübbeler;Dorothea Kolossa;Clemens Elster;Markus Bär;Reinhold Orglmeister
Affiliations:
EMSP Group, Berlin University of Technology, Berlin, Germany and Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany;Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany;EMSP Group, Berlin University of Technology, Berlin, Germany;Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany;Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany;EMSP Group, Berlin University of Technology, Berlin, Germany
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

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Abstract

ICA is often employed for the analysis of MEG stimulus experiments. However, the assumption of independence for evoked source signals may not be valid. We present a synthetic model for stimulus evoked MEG data which can be used for the assessment and the development of BSS methods in this context. Specifically, the signal shapes as well as the degree of signal dependency are gradually adjustable. We illustrate the use of the synthetic model by applying ICA and independent subspace analysis (ISA) to data generated by this model. For evoked MEG data, we show that ICA may fail and that even results that appear physiologically meaningful, can turn out to be wrong. Our results further suggest that ISA via grouping ICA results is a promising approach to identify subspaces of dependent MEG source signals.