[Eeglablist] Two step source connectivity analysis (as implemented in SIFT)

Thu Feb 6 17:27:30 PST 2014

Hi Tim and the list,

I am just in need of a clarification regarding the ICA source reconstruction and the subsequent MVAR -based effective connectivity analysis using the components, which is the basis of the SIFT toolbox. I was trying to use this approach in my work but was questioned on the validity using ICA and subsequent MVAR analysis by my colleagues.

"When using independent component analysis (ICA), we assume the mutual independence
of underlying sources, however when we try to estimate connectivity between EEG sources,
we implicitly assume that the sources may be  influenced by each other. This contradicts the
fundamental assumption of mutual independence between sources in ICA [Cheung et al., 2010, Chiang et al., 2012, Haufe et al., 2009 ]. "

So due to this reason different approaches such as MVARICA, CICAAR(convolution ICA+MVAR),  SCSA and state space-based methods have been proposed as ICA+MVAR based source connectivity analysis techniques.

*         So, how would you support the valid use of SIFT ( ICA+MVAR as a two-step procedure) for the source connectivity analysis?

*         If I argue that I do not assume independent sources but rely on the fact that ICA will decompose the EEG signals and output 'maximally independent' sources and then, I subsequently model for the dependency, will you agree with me? How valid would my argument be?

It would be really great to see different thoughts and opinions.

Kind regards


Dr. Imali Thanuja Hettiarachchi
Centre for Intelligent Systems research
Deakin University, Geelong 3217, Australia.

Mobile : +61430321972
Email: ith at deakin.edu.au<mailto:ith at deakin.edu.au>
Web :www.deakin.edu.au/cisr<http://www.deakin.edu.au/cisr>

[Description: Description: cid:1216BE20-1800-4A47-8B9F-E7B9D94831CD at deakin.edu.au]

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