[Eeglablist] line noise removal issues
David Contreras Ros
davcr at ugr.es
Thu Jan 10 06:53:31 PST 2008
Try SOBI instead of ICA infomax. It seems to isolate line noise better
(at least from my limited experience). SOBI is also implemented in EEGLAB.
Tim Mullen wrote:
> Dear EEGLAB users,
> I have a question regarding the use of ICA for line noise removal.
> I have some electrocorticographic (ECoG) data with a strong 60Hz line
> noise artifact as well as a 180Hz harmonic (only odd harmonics seem to
> be present, probably due to symmetrical clipping).
> I am applying frequency-domain granger causality to this data, but
> have run into some serious problems with the presence of this line
> noise. Oddly enough, the line noise dominates as a /directional
> /effect in the granger causality (unless there is an apparent temporal
> delay between channels at 60 Hz, a peak at 60 Hz should only be
> present in the instantaneous causality). This is likely because the
> phase at 60Hz appears to differ between channels. The strength of the
> directional effect at 60 and 180Hz is so strong that it dominates any
> other interesting nearby features, making it impossible to analyze
> causal interactions within a wide range of frequencies of interest.
> The noise band is far too wide for notch filtering to be considered a
> suitable solution. I have then tried extended infomax ICA (as
> implemented in EEGLAB's /runica/ function), to isolate the subgaussian
> noise components. I have attempted this both in automatically
> estimating the number of sub-gaussian sources and also fixing the
> number of subgaussian sources to 1, 2, etc. None of these approaches
> have been successful. ICA appears to converge properly and the
> covariance matrix of the estimated components is the identity matrix
> (it's at least second-order independent).
> It is possible that the tanh function used to model the subgaussian
> source distributions is unsuitable for this line noise source. Has
> anyone used or implemented any other families of distributions to
> calculate the score function for ICA?
> Des anyone have any recommendations on how to remove this line noise,
> either via source separation or other techniques? In particular, if
> anyone has developed a plugin for EEGLAB or their own code for
> automatic line noise removal, that would be optimal.
> Thanks much for your input!
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