[Eeglablist] high frequency oscillation- eeg advice

Fri Jan 27 12:47:07 PST 2017

Dear Jumana,

> Do you think this would be wrong? I thought it seemed a bit odd to report
it like this in a paper.

0.1Hz IIR high-pass filter can be found in EEG amplifiers, so in that sense
it is not strange at all. But I'm not sure if using IIR for high-pass and
FIR for low-pass is the better than using FIR filter for both. I would
appreciate if Andreas can comment on this.

Makoto

On Fri, Jan 27, 2017 at 8:55 AM, Ahmad, Jumana <jumana.ahmad at kcl.ac.uk>
wrote:

> Hi both, Based upon the suggestion of FIR not being suitable for 0.1Hz
> high pass, I have now changed my data to do a butterworth IIR filter from
> ERP lab to remove <0.1, and I used the EEGlab FIR filter to remove 40hz+.
> Do you think this would be wrong? I thought it seemed a bit odd to report
> it like this in a paper.
> Best wishes,
> Jumana
>
> -----Original Message-----
> From: eeglablist-bounces at sccn.ucsd.edu [mailto:eeglablist-bounces@
> sccn.ucsd.edu] On Behalf Of Andreas Widmann
> Sent: 27 January 2017 11:28
> To: mmiyakoshi at ucsd.edu
> Cc: eeglablist at sccn.ucsd.edu
> Subject: Re: [Eeglablist] high frequency oscillation- eeg advice
>
> 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:
> > https://emea01.safelinks.protection.outlook.com/?url=www.eu-aims.eu&da
> > ta=01%7C01%7Cjumana.ahmad%40kcl.ac.uk%7C11c9eb49db93488cde6308d446d4d6
> > a5%7C8370cf1416f34c16b83c724071654356%7C0&sdata=drS3rsxWBbt9DqEZs%2BuB
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> >
> > 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://emea01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscc
> > n.ucsd.edu%2Fwiki%2FMakoto%2527s_preprocessing_pipeline%23High-pass_fi
> > lter_the_data_at_1-Hz_.28for_ICA.2C_ASR.2C_and_CleanLine.29&data=01%7C
> > 01%7Cjumana.ahmad%40kcl.ac.uk%7C11c9eb49db93488cde6308d446d4d6a5%7C837
> > 0cf1416f34c16b83c724071654356%7C0&sdata=%2BhfaaFL0gA4PnSYSmZDqjehiCGAe
> > 64MWj%2F2Pbw6FLDk%3D&reserved=0
> >
> > > 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:
> > https://emea01.safelinks.protection.outlook.com/?url=www.eu-aims.eu&da
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> >
> >
> >
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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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