[Eeglablist] high frequency oscillation- eeg advice

Fri Jan 27 12:34:54 PST 2017

Dear Andreas,

>> And I still don't like 0.1Hz high-pass if you use FIR
> Why? What is the problem?

Assuming people just enter '0.1' to EEGLAB default FIR filter GUI, it'll
apply 0.05Hz cut-off high-pass filter with Hamming window. When the
sampling rate is 250Hz, the model order it calculates is 8251, which is 33
sec long. Meanwhile, people are usually only interested in the first few
hundreds milliseconds of the averaged signal. And they subtract
pre-stimulus baseline mean value from the entire epoch anyway. I don't see
much reason to apply 0.1-Hz high-pass filter in these cases. Of course, I
saw papers discussing this issue and I have no objection, but intuitively
it is still weird to me. I think the point is that people want to claim
that ERP is a broadband phenomenon, but the way they demonstrate it is not
satisfactory to me.

By the way, people often complain about our recommended -1 to 2 sec epoch
to be too long, and our recommended 1-Hz high-pass filter too aggressive.
But doesn't it makes more sense to apply 1-Hz high-pass filter to 3-sec
epoch data, compared with applying 0.1-Hz high-pass for 0.8 sec epoch data?
This kind of unbalancedness makes me feel weird.

> What would be your suggested alternative?

I thought IIR would be more reasonable for such a low cutoff frequency, but
I have never tried it myself (as far as I know, clean_rawdata plugin comes
with its IIR filter, which could be a part of BCILAB for online
processing). It depends on your relative time scale. If I analyze hour-long
resting state data to target minute-long slow changes, I would use FIR with
no problem.

I did not know much about stability issue, but this time you made me learn
it a little bit. Thank you Andreas for always pushing my back in this way.

Makoto

On Fri, Jan 27, 2017 at 3:28 AM, Andreas Widmann <widmann at uni-leipzig.de>
wrote:

> Dear Makoto,
>
> > And I still don't like 0.1Hz high-pass if you use FIR
> Why? What is the problem? What would be your suggested alternative?
>
> > (and I do not know how bad it is to use IIR... I've heard it can become
> 'unstable' but I've never seen it myself)
> Here you go:
> [b,a]=butter(4,0.1/500,'high');
> isstable(b,a)
> freqz(b,a)
>
> But note that possible instability is not the main problem with IIR
> application in electrophysiology. There are workarounds (e.g. for this
> example using zpk: [z,p,k]=butter(4,0.1/500,'high'); sos=zp2sos(z,p,k);
> isstable(sos)).
>
> Best,
> Andreas
>
>
> >
> > > I won't be using granger causality but I will be estimating phase
> during ITC.
> >
> > Should be ok.
> >
> > Makoto
> >
> > On Thu, Jan 26, 2017 at 2:12 PM, Ahmad, Jumana <jumana.ahmad at kcl.ac.uk>
> wrote:
> > Dear Makoto,
> > I actually switched to the pop eeg filt eeglab function and it now
> Really attenuated anything >40Hz, and my ERPs are cleaner. However I
> filtering between 0.1-40Hz at the same time in the GUI (I interned the high
> pass and low pass simultaneously). Is this OK to do? The frequency response
> looks OK.
> >
> > The filter order was automatically set very high by the GUI, but it's
> continuous data and I have room without events at the beginning and end of
> the data so any edge effects can be disgusted. What do you think?
> >
> > Also, this is for my ERP analysis- I trained ICA on a 1Hz high pass
> filtered set.
> > I won't be using granger causality but I will be estimating phase during
> ITC.
> > Best wishes, and thanks,
> > Jumana
> >
> > ------------------------------------------
> > Jumana Ahmad
> > Post-Doctoral Research Worker in Cognitive Neuroscience
> > EU-AIMS Longitudinal European Autism Project (LEAP) & SynaG Study
> > Room M1.26.Department of Forensic and Neurodevelopmental Sciences (PO
> 23) | Institute of Psychiatry, Psychology & Neuroscience | King’s College
> London | 16 De Crespigny Park | London SE5 8AF
> >
> > Phone: 0207 848 5359| Email: jumana.ahmad at kcl.ac.uk | Website:
> www.eu-aims.eu | Facebook: www.facebook.com/euaims
> >
> > From: Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
> > Sent: 26 January 2017 23:49:50
> > To: Ahmad, Jumana
> > Cc: eeglablist at sccn.ucsd.edu
> > Subject: Re: [Eeglablist] high frequency oscillation- eeg advice
> >
> > Dear Jumana,
> >
> > It's a bad idea to perform ICA with 0.1Hz high-pass filtered data. The
> cutoff frequency is too low. See this page and the referenced paper.
> >
> > https://sccn.ucsd.edu/wiki/Makoto%27s_preprocessing_
> pipeline#High-pass_filter_the_data_at_1-Hz_.28for_ICA.2C_
> ASR.2C_and_CleanLine.29
> >
> > > A 30Hz low pass does not help to get rid of the oscillation, which is
> really significant in the data.
> >
> > Check the channel frequency spectra and tell me if you see peaks in it.
> If necessary, you can cut it off using a designed low-pass filter (not like
> Butterworth...)
> >
> > > I use a butterworth filter, which is good for ERP analysis with low
> phase distortion.
> >
> > Do not make qualitative judgement just because something is NOT a
> classic Butterworth. Of course, if the attenuation is small, the phase
> 'distortion' is small. But if such small attenuation is not useful, it does
> not help at all! Also, be careful with the word 'phase'. Particularly
> people who do not know basics of signal processing believe phase as some
> magical thing. If you are not performing Granger Causality Analysis or
> something, you don't need to be so worried about phase issue in practice.
> >
> > > I also already run ICA, but in some datasets there is a very
> significant high frequency oscillation.
> >
> >
> > Remember, to eliminate this is more important than being afraid of
> qualitative phase issue.
> >
> > > However, I can see the high frequency oscillations in my ERP, which is
> not ideal and now I need to try and get rid of it further.
> >
> > Can I filter again on top of the data which already has already
> undergone ICA- I only use ICA to remove blinks?
> >
> >
> > You'd better to filter the data on continuous state. If you need to
> filter the epoched data, the half of filter length from both ends becomes
> unreliable.
> >
> > > Should I do cleanline, although it would have to be after ICA now- I
> read this is not advisable.
> >
> > > Should I use a notch filter?
> >
> >
> > If you see > 20dB line noise, Cleanline may not help. In this case, I
> would simply apply a designed low-pass filter, either Hamming (-50dB) or
> Blackman (-70dB) using firfilt(). See 'Tools' -> 'Filter the data' ->
> 'Windowed sinc FIR filter'.
> >
> > There are different guys saying different things about data
> preprocessing. It is confusing, I know! The only good solution for this is
> to become an engineer yourself...
> >
> > Makoto
> >
> >
> >
> > On Tue, Jan 24, 2017 at 7:00 AM, Ahmad, Jumana <jumana.ahmad at kcl.ac.uk>
> wrote:
> > Hi  Everyone,
> >
> > I am running a large scale ERP analysis. I filtered 1-40Hz (ICA AMICA),
> or 0.1-40Hz for the ERP dataset. A 30Hz low pass does not help to get rid
> of the oscillation, which is really significant in the data. I use a
> butterworth filter, which is good for ERP analysis with low phase
> distortion.
> >
> > I also already run ICA, but in some datasets there is a very significant
> high frequency oscillation.
> >
> > I do not use cleanline, which is not typical in the literature I have
> been basing my pipeline on.
> >
> >
> >
> > However, I can see the high frequency oscillations in my ERP, which is
> not ideal and now I need to try and get rid of it further.
> >
> > Can I filter again on top of the data which already has already
> undergone ICA- I only use ICA to remove blinks?
> >
> > Should I do cleanline, although it would have to be after ICA now- I
> read this is not advisable.
> >
> > Should I use a notch filter?
> >
> >
> >
> > Any help would be appreciated.
> >
> > Best wishes,
> >
> > Jumana
> >
> >
> >
> > ------------------------------------------
> >
> > Jumana Ahmad
> >
> > Post-Doctoral Research Worker in Cognitive Neuroscience
> >
> > EU-AIMS Longitudinal European Autism Project (LEAP) & SynaG Study
> >
> > Room M1.09. Department of Forensic and Neurodevelopmental Sciences (PO
> 23) | Institute of Psychiatry, Psychology & Neuroscience | King’s College
> London | 16 De Crespigny Park | London SE5 8AF
> >
> >
> >
> > Phone: 0207848 0260| Email: jumana.ahmad at kcl.ac.uk | Website:
> www.eu-aims.eu | Facebook: www.facebook.com/euaims
> >
> >
> >
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> >
> > --
> > Makoto Miyakoshi
> > Swartz Center for Computational Neuroscience
> > Institute for Neural Computation, University of California San Diego
> >
> >
> >
> > --
> > 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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