[Eeglablist] New noise removal plugin released: Zapline-plus

Thu Mar 24 11:16:27 PDT 2022

Hi Cedric,

thanks for your interest! Zapline internally makes use of a combination of
a spectral and spatial filter, which unfortunately means that single
electrodes or very low-density setups will not work. In our paper, we used
it on datasets ranging from 32 to >200 channels, but I did not test it with
any lower channel count. If you try it out, let me know how it goes!

We have not compared Zapline-plus directly with cleanline. However, as it
was already shown by Miyakoshi et al (2021;
https://urldefense.proofpoint.com/v2/url?u=https-3A__www.frontiersin.org_articles_10.3389_fninf.2020.597079_full&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=Y3sPAvIyoxNWwDAIeXw7Tcno9kNQfH80nAm5S0KAeKduFimNIAKu0coOebWWuZ7e&s=vncCIqCCVqkZL3OXPG5E-I1Jb_grKNmW57F66fww6Vs&e= ), the
two tools may complement each other. Thus far I did not feel the need for
additional cleaning after using Zapline-plus in most cases, but one could
imagine having a check if the final cleaned dataset has a ratio of noise to
surroundings >1.1 and then perform additional cleanline cleaning in the
given frequency for example. Luckily, these values are outputs of the
function and you can probably try this out easily yourself! :)

Marius

Am Do., 24. März 2022 um 16:30 Uhr schrieb Cedric Cannard <
ccannard at protonmail.com>:

> Hello,
>
> Thank you for sharing this new tool. Looking forward to trying it.
>
> Does it work on single EEG channels (or low-density montages as with
> wearable systems) or does it require high-density montages to perform well?
>
> Just curious, have you compared it to CleanLine (available in EEGLAB)?
>
>
> Cedric Cannard
>
>
>
> ‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐
> On Thursday, March 24, 2022 5:31 AM, Marius Klug <marius.s.klug at gmail.com>
> wrote:
>
> > Dear list,
> >
> > we are happy to announce that we released Zapline-plus, a new artifact
> > removal tool, available for download in the EEGLAB plugins manager now!
> >
> > Zapline-plus (Klug & Kloosterman, 2022) is a wrapper for Zapline (de
> > Cheveigné, 2020) that automatically removes spectral peaks like line
> noise
> > or other oscillations (e.g. stemming from a VR display) from your data
> > while ensuring minimal negative impact. It preserves both the non-noise
> > spectrum for analysis, as well as the full data rank for subsequent ICA
> > processing. It searches for noise frequencies (can also select line
> only),
> > divides the data into spatially stable chunks, and adapts the cleaning
> > strength automatically. Finally, a detailed plot is created that allows
> > checking the cleaning in depth.
> >
> > A detailed guide for usage and interpretations of the plot can be found
> in
> > our git repository:
> https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_MariusKlug_zapline-2Dplus&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=wbP5PlkQa6_ySLwuQmZU5o5ujtc10iYE6mO-XQLhS8o1iR7UvaP1hpSVBSaU6mhl&s=YAYPKsOoV-TL7zZTkeLSVHGomZegtK6bU643JMBGdvc&e=
> >
> > The plugin is published as an open-access paper and can be cited as
> follows:
> >
> > Klug, M., & Kloosterman, N. A. (2022). Zapline-plus: A Zapline extension
> > for automatic and adaptive removal of frequency-specific noise artifacts
> in
> > M/EEG. Human Brain Mapping,1–16.
> https://urldefense.proofpoint.com/v2/url?u=https-3A__doi.org_10.1002_hbm.25832&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=wbP5PlkQa6_ySLwuQmZU5o5ujtc10iYE6mO-XQLhS8o1iR7UvaP1hpSVBSaU6mhl&s=j8ROaEga0jUmAd_swgDFv5C12ibztk6ENG0VtqirPlw&e=
> >
> > de Cheveigne, A. (2020) ZapLine: a simple and effective method to remove
> > power line artifacts. NeuroImage, 1, 1-13.
> >
> https://urldefense.proofpoint.com/v2/url?u=https-3A__doi.org_10.1016_j.neuroimage.2019.116356&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=wbP5PlkQa6_ySLwuQmZU5o5ujtc10iYE6mO-XQLhS8o1iR7UvaP1hpSVBSaU6mhl&s=8r9J1RqyzNfwqw8ctz7mU1mbQ7uVHd3huMd0qCXYhjE&e=
> >
> > Any feedback about usability and functional issues is welcome.
> > We hope you find this plugin useful and wish you success and happy
> cleaning!
> >
> > Regards,
> > Marius Klug and Niels Kloosterman
> >
> >
> -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
> >
> > Marius Klug
> > Research Associate / PhD Student at TU Berlin, Germany
> > Department of Biological Psychology and Neuroergonomics
> > +49 (0)30 314-79 528
> > Project Homepage
> > <
> https://urldefense.proofpoint.com/v2/url?u=https-3A__blogs.tu-2Dberlin.de_bpn-5Fbemobil_projects_neuroergonomics-2Dof-2Dsituation-2Dawareness-2Dnesita_&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=wbP5PlkQa6_ySLwuQmZU5o5ujtc10iYE6mO-XQLhS8o1iR7UvaP1hpSVBSaU6mhl&s=apCVZ01yHBhUG-VfgdLTuuiktGW9taRmLAUBjgj5orc&e=
> >
> >
> > Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
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>
>

-- 
Marius Klug
Research Associate / PhD Student at TU Berlin, Germany
Department of Biological Psychology and Neuroergonomics
+49 (0)30 314-79 528
Project Homepage
<https://urldefense.proofpoint.com/v2/url?u=https-3A__blogs.tu-2Dberlin.de_bpn-5Fbemobil_projects_neuroergonomics-2Dof-2Dsituation-2Dawareness-2Dnesita_&d=DwIFaQ&c=-35OiAkTchMrZOngvJPOeA&r=kB5f6DjXkuOQpM1bq5OFA9kKiQyNm1p6x6e36h3EglE&m=Y3sPAvIyoxNWwDAIeXw7Tcno9kNQfH80nAm5S0KAeKduFimNIAKu0coOebWWuZ7e&s=PFZZGoqb12bWnKOMNYU_QEdyJWDAT8okejlsKbp-sp8&e= >