[Eeglablist] Filter distortion around boundary events

Mon Jul 23 09:41:51 PDT 2018

Andreas, thanks for your detailed response. Regarding line noise, I think
there's some kind of power substation box in the room. It is "non-ideal" to
be sure, but presently that's what we're working with. Your suggestion for
filtering in two steps with those filter orders is working much better than
the automatic order option.

A question for all - to further ameliorate the DC shift, would a linear
detrend over the unepoched data prior to any other step potentially help
with this problem? In a test on one file it seems to help. Then, I could
potentially remove the mean of each channel over the whole recording?

Thank you,
Brian

*Brian Erickson**, Ph.D.*
*Postdoctoral Researcher, CogNeW Lab*

*Drexel University*
3141 Chestnut Street
Stratton Hall Room 320
Philadelphia, PA 19104

On Wed, Jul 18, 2018 at 3:04 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
wrote:

> Dear Andreas,
>
> Just a quick input,
>
> > Not sure how Cleanline copes with the TMS artifacts, however.
>
> Good point. CleanLine assumes that the noise (in this case, specifically
> 50/60Hz line noise) to be stationary across time (and purely sinusoidal).
> Temporally sparse noise like TMS artifact cannot be removed by CleanLine.
>
> Makoto
>
> On Tue, Jul 17, 2018 at 10:39 PM Andreas Widmann <widmann at uni-leipzig.de>
> wrote:
>
>> Hi Brian,
>>
>> this is indeed a prototypical filter edge artifact. Most commonly this
>> type of artifact is observed with notch filters (but only because notch
>> filters are most commonly applied for this type of interference) but can
>> also be observed with low-pass or high-pass filters.
>>
>> I'm afraid that you will not get completely rid of this problem. Your
>> line noise interference is very strong (~1 mV peak-to-peak max on AF3 and
>> ~500 µV peak-to-peak on average across channels). Filters need some time to
>> achieve full attenuation. The problem can, however, be significantly
>> reduced using somewhat different filter settings.
>>
>> First, I would suggest to separate high-pass and low-pass filter. You may
>> then use lower low-pass filter orders considerably reducing the temporal
>> extent of the artifact. Further, I would suggest to use a lower low-pass
>> cutoff frequency, e.g. 45 Hz (i.e., passband edge 40 Hz).
>> EEG = pop_eegfiltnew(EEG, 1,[],6600,0,[],1);
>> EEG = pop_eegfiltnew(EEG, [],40,660,0,[],1);
>>
>> When filtering, the data have to be padded at the edges. We do pad with a
>> DC constant to reliably avoid DC artifacts. With a harmonic oscillation in
>> the data, padding with a constant implies amplitude modulation and
>> amplitude modulation spectrally smears the line noise interference to
>> adjacent bands at the edges of the signal. Therefore you have to use cutoff
>> frequencies further away from the line noise interference frequency if the
>> signal edges are important and cannot be cut away. Intuitively, mirror
>> padding might might be an apparent solution to this problem. However, this
>> will introduce other nice edge artifacts due to phase reset and DC shifts.
>>
>> Usually, I would recommend to try other ways to remove the line noise
>> interference, for example Cleanline or DFT filters. Not sure how Cleanline
>> copes with the TMS artifacts, however. One more comment: The line noise
>> interference is really strong, even for a recording in an unshielded
>> environment. Might there possibly be a problem with common mode rejection
>> in your EEG setup?
>>
>> Hope this helps! Best,
>> Andreas
>>
>> > Am 16.07.2018 um 20:48 schrieb Erickson <ericksonb.eng at gmail.com>:
>> >
>> > Thanks for your responses.
>> >
>> > Andreas, I used the "basic FIR filter" on automatic order calculation
>> filtering from 1 to 55.
>> >
>> > Here is a drive link to a zip file with 30s of example data. These data
>> were imported using fileIO and the event channel (65) was imported as
>> events (Nothing else has been done to this example data).
>> > https://drive.google.com/open?id=1KPlpeBCrCnQJHCJOcMYsnNSJVOjj0bTO
>> >
>> > Then I plotted the data and cut out one section around a TMS event, and
>> another section NOT around a TMS event;
>> > EEG = eeg_eegrej( EEG, [4615 5372;11482 12002]);
>> > [ALLEEG EEG CURRENTSET] = pop_newset(ALLEEG, EEG, 1,'setname','with
>> Rejections','gui','off');
>> >
>> > filtered the data using the FIR filter from 1 to 55hz;
>> > EEG = pop_eegfiltnew(EEG, 1,55,6600,0,[],1);
>> > [ALLEEG EEG CURRENTSET] = pop_newset(ALLEEG, EEG, 2,'setname','with
>> Rejections and Filter','gui','off');
>> >
>> > then plotting the data, the artifact is visible as a "pinching" around
>> each boundary, with a faster oscillation riding on top. So basically just
>> reject any section of data and filter and the artifact appears.
>> >
>> > Makoto, to answer the question about the spectra - if I cut out the
>> TMS pulses and then filter, the PSD looks pretty normal. Prior to filtering
>> there is so much DC power I can't visually inspect the data very well.
>> >
>> > The room is very noisy, but this artifact appears only wherever I make
>> a boundary and filter so it seems like an edge effect due to filtering -
>> but I've never encountered this kind of artifact before since EEGLAB knows
>> not to filter over boundaries. Perhaps I cannot use the automatic filter
>> order here due to some noise profile in my data?
>> >
>> > Thanks to you both for considering the problem!
>> >
>> > Brian
>> >
>> >
>> > On Thu, Jul 12, 2018 at 8:54 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
>> wrote:
>> > Dear Erickson
>> >
>> > Is this really a distortion introduced by the filter? Rather, isn't it
>> the case that that portion of the data was poorly filtered i.e., your
>> original data, before filtering, had that noise constantly? Could you
>> please check your original data by eyeballing the raw time series and by
>> checking power spectral density?
>> >
>> > Makoto
>> >
>> > On Thu, Jul 12, 2018 at 10:33 AM Erickson <ericksonb.eng at gmail.com>
>> wrote:
>> > Hello EEGLAB list,
>> >
>> > We are experiencing a strange artifact on only some of our EEG data.
>> For some subjects, when we cut out portions of data (creating boundary
>> events) and then filter (from 1 to 40 or 50hz) we observe a distortion
>> around the boundary.
>> >
>> > Specifically, we see a rising or falling wave on either side of the
>> boundary, with a fast oscillation riding on top of it. See here:
>> https://drive.google.com/open?id=1yt6h_WLgI6jWAApVd52nwVLuiduYgXIH
>> >
>> > Although this data is from concurrent TMS-EEG recording, the distortion
>> has nothing to do with the TMS pulse itself - we get the same
>> boundary-related distortion when we filter after cutting out a random
>> section of continuous data (a section with no TMS in it).
>> >
>> > I am at a loss - we've tried a few different filters and nothing seems
>> to solve this issue. Meanwhile, on some subjects there is no
>> boundary-related filter distortion at all! There is a lot of noise in the
>> room but I'm not sure how that could create this specific issue.
>> >
>> > Any perspectives on this issue are appreciated! Thank you,
>> >
>> > Brian
>> >
>> > Brian Erickson, Ph.D.
>> > Postdoctoral Researcher, CogNeW Lab
>> >
>> > Drexel University
>> > 3141 Chestnut Street
>> <https://maps.google.com/?q=3141+Chestnut+Street&entry=gmail&source=g>
>> > Stratton Hall Room 320
>> > Philadelphia, PA 19104
>> >
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>> >
>> > --
>> > Makoto Miyakoshi
>> > Swartz Center for Computational Neuroscience
>> > Institute for Neural Computation, University of California San Diego
>> >
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>
>
> --
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>
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