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

Fri Mar 25 11:17:17 PDT 2022

Kudos on the plugin and paper Markus (version 1.1 of the plugin released today).

Based on our exchanges off the list, I think many expert EEGLAB users/developers are excited about it (Cyril Pernet, Makoto Miyakoshi), and it is a great addition to EEGLAB. I encourage everybody to try it out.

Cheers,

Arno

> On Mar 24, 2022, at 11:16 AM, Marius Klug <marius.s.klug at gmail.com> wrote:
> 
> 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=
>>> 
>>> 
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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= >
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