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  Source Separation and Higher-Order Causal Analysis of MEG and EEG

Zhang, K., & Hyvärinen, A. (2010). Source Separation and Higher-Order Causal Analysis of MEG and EEG. In P. Grünwald, & P. Spirtes (Eds.), 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010) (pp. 709-716). Corvallis, OR, USA: AUAI Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-BF4A-6 Version Permalink: https://hdl.handle.net/21.11116/0000-0006-E529-A
Genre: Conference Paper

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https://event.cwi.nl/uai2010/papers/UAI2010_0292.pdf (Publisher version)
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 Creators:
Zhang, K1, 2, Author           
Hyvärinen, A, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Separation of the sources and analysis of their connectivity have been an important topic in EEG/MEG analysis. To solve this problem in an automatic manner, we propose a twolayer model, in which the sources are conditionally uncorrelated from each other, but not independent; the dependence is caused by the causality in their time-varying variances (envelopes). The model is identified in two steps. We first propose a new source
separation technique which takes into account the autocorrelations (which may be time-varying) and time-varying variances of the sources. The causality in the envelopes is then discovered by exploiting a special
kind of multivariate GARCH (generalized autoregressive
conditional heteroscedasticity) model. The resulting causal diagram gives the effective connectivity between the separated sources; in our experimental results on MEG data, sources with similar functions are grouped together, with negative influences between groups, and the groups are
connected via some interesting sources.

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 Dates: 2010-07
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 6630
 Degree: -

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Title: 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010)
Place of Event: Catalina Island, CA, USA
Start-/End Date: 2010-07-08 - 2010-07-11

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Title: 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010)
Source Genre: Proceedings
 Creator(s):
Grünwald, P, Editor
Spirtes, P, Editor
Affiliations:
-
Publ. Info: Corvallis, OR, USA : AUAI Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 709 - 716 Identifier: ISBN: 978-0-9749039-6-5