[Eeglablist] line noise removal issues

[David Contreras Ros]

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.

Regards,

David.

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!
>
> Regards,
> Tim
> ------------------------------------------------------------------------
>
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