[Eeglablist] ICA vs. regression-based artifact correction effects on sensor level phase

[Spencer, Kevin M.]

Hi Baris,

I don't have any answers to a-c, but regarding d, I'm not aware of any sensory-based connectivity measures that aren't confounded by volume conduction and common reference. This problem has been well known for decades but not dealt with or ignored by many, unfortunately (including myself).

In principle one could perform phase synchronization analyses on CSD-transformed electrode data, which would attenuate volume conduction and eliminate the reference issue. In my experience, though, CSD estimates are too noisy for phase synchrony measures.

Kevin

________________________________________
From: eeglablist-bounces at sccn.ucsd.edu [eeglablist-bounces at sccn.ucsd.edu] On Behalf Of Baris Demiral [demiral.007 at googlemail.com]
Sent: Thursday, February 16, 2012 3:20 PM
To: eeglablist
Subject: [Eeglablist] ICA vs. regression-based artifact correction effects      on sensor level phase

Hi,

Here are the questions:

a) If we take out artifactual ICs (say, eye blinks), do the final
sensor data loose their crucial phase information?
b) If we apply linear regression based algorithms to exclude
artifacts, will this influence the sensor level phase information?
c) How do these two methods influence sensor based connectivity analysis?
d) Which sensor-based connectivity measures are robust against volume
conduction?

I favor source- and ICA-based multivariate connectivity analyses where
you really do not need to take out ICs, but work on the components of
interest.
But, there are plenty of papers out there reporting only pairwise
sensor connectivity while ignoring the effects of volume conduction
and artifact correction.

Thanks,
Baris
--
Ş. Barış Demiral, PhD.
Department of Psychiatry
Washington University
School of Medicine
660 S. Euclid Avenue
Box 8134
Saint Louis, MO 63110
Phone: +1 (314) 747 1603

_______________________________________________
Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
To unsubscribe, send an empty email to eeglablist-unsubscribe at sccn.ucsd.edu
For digest mode, send an email with the subject "set digest mime" to eeglablist-request at sccn.ucsd.edu