TY - GEN
T1 - Analyzing coupled brain sources
T2 - 2005 Annual Conference on Neural Information Processing Systems, NIPS 2005
AU - Nolte, Guido
AU - Ziehe, Andreas
AU - Meinecke, Frank
AU - Müller, Klaus Robert
PY - 2005
Y1 - 2005
N2 - 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 conduction. Our new concept of interacting source analysis (ISA) is successfully demonstrated on MEG data.
AB - 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 conduction. Our new concept of interacting source analysis (ISA) is successfully demonstrated on MEG data.
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M3 - Conference contribution
AN - SCOPUS:84857309112
SN - 9780262232531
T3 - Advances in Neural Information Processing Systems
SP - 1027
EP - 1034
BT - Advances in Neural Information Processing Systems 18 - Proceedings of the 2005 Conference
Y2 - 5 December 2005 through 8 December 2005
ER -