[Eeglablist] Dear list, about line noise.

Thu Apr 15 12:54:48 PDT 2021

Dear Ramtin,

> Does my reasoning sound sensible? Please let me know if any of my
thoughts is inaccurate.

As is typical with you, the question did not make sense to me unfortunately.
But I could see you have a question about the difference between ZapLine
and CleanLine.

For ZapLine, if a time-series of line noise artifact is added via a spatial
filter of a *FIXED* scalp topography (i.e. the combination of the whole
electrodes oscillate along with the time series), it can be beautifully
subtracted out. This FIXEDNESS is the meaning of 'stationary'.

If a source of line noise run around across the regions of scalp, ZapLine
cannot model it with a fixed scalp topography. In this case, CleanLine can
still take care of it. CleanLine deals with every single electrode one by
one (which is called univariate approach; ZapLine is multivariate) without
caring how the electrodes are correlated.

Let me know if this explanation helps, and whether it answered your
question directly or indirectly.

Makoto

On Thu, Apr 15, 2021 at 10:13 AM Ramtin Mehraram <
ramtin.mehraram at kuleuven.be> wrote:

> Dear Makoto,
>
> I have a bit of confusion on how the two approaches deal with stationary
> noise.
>
> Being based on spatial filtering the ZapLine approach can only deal with
> the stationary part of the noise.
>
> The CleanLine approach is non-stationary as it is based on a sliding
> windows, hence there is no prior-assumption about stationarity. However,
> any residual activity here would still be non-stationary.
>
> If my understanding is correct, if one or the other approach is applied
> before, some non-stationary residual would still remain, although reduced
> by the application of CleanLine.
>
> Based on this, the method which is applied as second will have to deal
> with a reduced amount of stationary noise, and the final output should not
> depend much on in which order the methods are applied.
>
> Does my reasoning sound sensible? Please let me know if any of my thoughts
> is inaccurate.
>
> Many thanks again for your help.
>
>
> Kind regards,
> Ramtin
>
> -----Original Message-----
> From: eeglablist <eeglablist-bounces at sccn.ucsd.edu> On Behalf Of Makoto
> Miyakoshi via eeglablist
> Sent: giovedì 15 aprile 2021 00:22
> To: eeglablist at sccn.ucsd.edu
> Subject: Re: [Eeglablist] Dear list, about line noise.
>
> Dear Ramtin,
>
> > Although you specifically suggest the use of CleanLine after ZapLine,
> > I
> was wondering whether the opposite makes any difference.
>
> Interesting question.
> The residual line noise after CleanLine is probably non-stationary
> (because CleanLine uses a sliding window approach). Because ZapLine makes
> an assumption of stationarity, I thought ZapLine may not be able to deal
> with it very well. But strictly speaking, ZapLine's performance there of
> course depends on the stationarity of the residual line noise.
>
> If you are interested, you may want to run the test. Both methods are
> published, so it is just a matter of time.
> And if you find my prediction is wrong, please do let me know! I'm very
> curious.
>
> Thank you for your interest Ramtin.
>
> Makoto
>
>
>
> On Wed, Apr 14, 2021 at 6:04 AM Ramtin Mehraram <
> ramtin.mehraram at kuleuven.be>
> wrote:
>
> > Dear Makoto,
> >
> > I see that you recommend in that paper a combined usage of ZapLine and
> > CleanLine for optimal results. Although you specifically suggest the
> > use of CleanLine after ZapLine, I was wondering whether the opposite
> > makes any difference.
> >
> >
> > Thank you in advance for your help.
> >
> > Kind regards,
> > Ramtin
> >
> > -----Original Message-----
> > From: eeglablist <eeglablist-bounces at sccn.ucsd.edu> On Behalf Of
> > Makoto Miyakoshi via eeglablist
> > Sent: martedì 16 marzo 2021 17:47
> > To: EEGLAB List <eeglablist at sccn.ucsd.edu>
> > Subject: Re: [Eeglablist] Dear list, about line noise.
> >
> > ⚠ External sender. Take care when opening links or attachments. Do not
> > provide your login details.
> >
> > Dear Hsin-An and Meha,
> >
> > Here is the recently published comparison between CleanLine
> > (cleanLineNoise) and ZapLine.
> >
> > https://urldefense.com/v3/__https://eur03.safelinks.protection.outlook
> > .com/?url=https*3A*2F*2Furldefense.com*2Fv3*2F__https*3A*2F*2Fpubmed.n
> > cbi.nlm.nih.gov*2F33584237*2F__*3B!!Mih3wA!SNPuomg5uPwruRY1ELie8uo9D7P
> > fRRhCS9Sdb3sznjFPoh_hJ_-ID3V4-enETszcFZ_OiQ*24&data=04*7C01*7CR.Me
> > hraram2*40newcastle.ac.uk*7C6f0001c617114b813b9808d8e89c1437*7C9c5012c
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> > zzIQgUArd5inHE3ocME5_O0L_DLA7L0j7wH6B6XfllYAb3xzne9F7yPdxefpmg$
> >
> > I think CleanLine is good for general purposes if you need to retain
> > the original signal in the line noise frequency range. The assumption
> > here is that line noise has much slower time constant to modulate
> amplitude (i.e.
> > line-noise signal nvelope) than the genuine EEG signal. The same goal
> > can be achieved by ZapLine if the spatial filter of the line noise is
> > stationary, but this assumption is less likely.
> >
> > Makoto
> >
> > On Mon, Mar 15, 2021 at 8:40 AM Meha Fatima via eeglablist <
> > eeglablist at sccn.ucsd.edu> wrote:
> >
> > > Dear Chang,
> > >
> > > I have found Cleanline very useful for 60 Hz line noise removal, so
> > > you can try it :)
> > >
> > >
> > >
> > > On Sun, 14 Mar 2021 at 23:54, <chang.ha at msa.hinet.net> wrote:
> > >
> > > >
> > > >
> > > >
> > > > Dear list,
> > > >
> > > >
> > > > Which is the most effective plugin to remove line noise (i.e., 60Hz)?
> > > >
> > > > Filter the data (Basic FIR filter, new default) - Notch filter the
> > > > data instead of pass band?
> > > >
> > > > Cleanline?
> > > >
> > > > PREP pipeline?
> > > >
> > > > Or any other plugin?
> > > >
> > > > Thanks.
> > > >
> > > >
> > > > Hsin-An Chang  M.D.
> > > >
> > > > Tri-Service General Hospital, Taipei, Taiwan
> > > >
> > > >
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> > >
> > > --
> > >
> > > *  Dr. Meha Fatima BSMT, Ph.D.*
> > >                                          Assistant Professor
> > >                                          Dow Institute of Medical
> > > Technology
> > >                                          Dow University of Health
> > Sciences
> > >                                           *mehafatima1 at gmail.com
> > > <mehafatima1 at gmail.com>.*
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