[Eeglablist] filters, ICA and erp

Fri Oct 14 08:40:00 PDT 2011

Hi,
I think that my email posted yesterday skipped your attention though it was closely related to the topic but under different 'subject'.
I wonder if this all precaution with filters is necessary if one analyse ERP during cue based motor imagination task where time to prepare for movement is limited to 1s?
Many thanks,
Alex

Sent from my iPhone

On 14 Oct 2011, at 15:25, "Rey Ramirez" <rrramir at uw.edu<mailto:rrramir at uw.edu>> wrote:

Hi Steve and Sara,

As far as I know there's absolutely no 'technical reason' why my suggestion wouldn't work. And actually it does work! Actually, if people have not been doing this I'm not sure what kind of results they are getting since the two main issues under discussion: 1) that 1 Hz high-pass filtering on ERP data can seriously distort the ERP; and 2) that ICA will not work so well for data that has not been 1 Hz high-passed filtered, are indeed quite uncontroversial. David's suggestion (hi  David!), pretty much does something similar but detrending via DC offsetting.

There are of course BSS algorithms that work in the frequency domain (e.g., complex infomax, or better Independent Vector Analysis (IVA)), that could be used to study activity at specific frequency bands, including the slow oscillation (<1 Hz), but that's an overkill, and for simple ERP analysis just running the ICA on the 1 Hz data, and applying the decomposition to the 0.1 Hz data is much more practical and it's what I would recommend, that is, if you want to bother doing ICA analysis at all.

Rey

On Thu, Oct 13, 2011 at 9:09 AM, Steve Luck <<mailto:sjluck at ucdavis.edu>sjluck at ucdavis.edu<mailto:sjluck at ucdavis.edu>> wrote:
Hi Sara.  Unless you care about frequencies per se, epoching and baseline-correcting the data won't be a problem.  From a time-domain perspective, this won't change anything.

BTW, someone else suggested using the 1-Hz high-pass cutoff, performing ICA, and then applying the component coefficients to the unfiltered data.  That sounds like a great suggestion, although I don't know if there is a technical reason why it wouldn't work.  Does anyone out there know if there would be a problem with this?

Steve

ps- The email trail on this topic has gotten out of hand, so I deleted everything except the most recent message and your original message.

On Oct 13, 2011, at 7:20 AM, Sara Graziadio wrote:

Steve,
actually I was refering to your book when I was writing that the filter would deforme/reduce the erp. But following David Groppe's suggestion would mean to reduce activity at different frequency all across the spectrum, wihtout exactly knowing which frequencies I am reducing, am I right? If I want to look at the psd as well as at the erps, would this analysis just be correct? I am always concerned about applying data modification that I cannot fully control..if you know what I mean...
Thank you very much
Best

Sara

On Wed, Oct 5, 2011 at 10:46 AM, Sara Graziadio
<<mailto:sara.graziadio at newcastle.ac.uk>sara.graziadio at newcastle.ac.uk<mailto:sara.graziadio at newcastle.ac.uk>> wrote:
Hello,
I would like just a suggestion about some data cleaning/analysis I am doing. I
am doing an ERP analysis and I want to clean my data first with the ICA. In
theory, though, I should not use an high-pass cutoff higher than 0.1 Hz to not
reduce the erp amplitude. On the other side the ICA does not work well if the
high-pass cutoff is lower than 0.5 Hz...what is then the best method to apply?
Has anybody tested how robust the ica is with a 0.1Hz filter?
I have also another question: I am doing the analysis on 94 electrodes
referenced to Fz. I planned to average reference the data but actually there is
quite a large spread of noise on all the electrodes with this method (muscular
artefacts for example from the temporal electrodes). But actually almost all
the papers are using the average reference so I was surprised, am I the only
one having this problem of noise? Would not be better just to keep the Fz
reference and then perhaps to average the erps for every different cortical
area and do the analysis on these averaged erps?

Thank you very much

Best wishes

Sara Graziadio
Research Associate
Newcastle University

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