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Analyzing coupled brain sources: Distinguishing true from spurious interaction

: Nolte, G.; Ziehe, A.; Meinecke, F.; Müller, K.-R.

Weiss, Y.:
Advances in neural information processing systems 18 : Proceedings of the 2005 conference. 18th Annual Conference on Neural Information Processing Systems (NIPS), held in Vancouver, British Columbia, Canada, from December 5-10, 2005
Cambridge, Mass.: MIT, 2006
ISBN: 0-262-23253-7
ISBN: 978-0-262-23253-1
Neural Information Processing Systems Conference (NIPS) <18, 2005, Vancouver>
Conference Paper
Fraunhofer FIRST ()

When trying to understand the brain, it is of fundamental importance to analyse (e.g. from EEG/MEG measurements) what parts of the cortex interact with each other in order to infer more accurate models of brain activity. Common techniques like Blind Source Separation (BSS) can estimate brain sources and single out artifacts by using the underlying assumption of source signal independence. However, physiologically interesting brain sources typically interact, so BSS will-by construction - fail to characterize them properly. Noting that there are truly interacting sources and signals that only seemingly interact due to effects of volume conduction, this work aims to contribute by distinguishing these effects. For this a new BSS technique is proposed that uses anti-symmetrized cross-correlation matrices and subsequent diagonalization. The resulting decomposition consists of the truly interacting brain sources and suppresses any spurious interaction stemming from volume con duction. Our new concept of interacting source analysis (ISA) is successfully demonstrated on MEG data.