[Eeglablist] Announcing GEDAI: A new EEGLAB Plugin for unsupervised artifact correction

Wed Nov 12 07:30:23 PST 2025

Hi Alejandro,

Thanks for sending the reference to your work, much appreciated! Looks
like both GEDAI and RBSL methods go beyond standard "blind" methods (like
PCA/ICA) by incorporating biophysical models (the leadfield matrix) to
achieve separation of brain signals and artifacts.
I guess the main difference is that GEDAI performs sensor-space denoising
(so no explicit inverse solution required) whilst RSBL is a source-space
imaging and demixing method. Also, GEDAI does not require building an
artifact dictionary, so the artifacts can be of any type really. Related
work in the latter category of inverse-source denoising also includes work
recently highlighted by Makoto:
https://urldefense.com/v3/__https://www.sciencedirect.com/science/article/pii/S1053811914005825__;!!Mih3wA!BKdcJSbYRxdXZ5MKvIFC0o3AoiqZiIFqvKox6cPLi88VaNOXuxuF8e8eJrB7AfTK6wJZ5t01J-xKL6dzbAwwGQ$ 

All the best,
Tomas

▬▬▬

*Tomas Ros, PhD*

Lecturer, Department of Clinical Neurosciences
Research Staff Scientist, CIBM EEG HUG-UNIGE Section
University of Geneva, Switzerland
https://urldefense.com/v3/__https://www.tomasros.com/__;!!Mih3wA!BKdcJSbYRxdXZ5MKvIFC0o3AoiqZiIFqvKox6cPLi88VaNOXuxuF8e8eJrB7AfTK6wJZ5t01J-xKL6dFlFvcoQ$ 

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On Tue, 11 Nov 2025 at 19:43, Alejandro Ojeda via eeglablist <
eeglablist at sccn.ucsd.edu> wrote:

> Hi Tomas,
>
> Your method seems to be very similar to an earlier one proposed here:
>
> https://urldefense.com/v3/__https://doi.org/10.1162/neco_a_01415__;!!Mih3wA!H_aYzLvzhjkSGle4cUl8-F0NuyhKgbVd9MZLP9H6UOmD0cfWKsnxgydDcbO1fcidugThUPVbNxSCBR3PSwu_T5Gh8SKi$
> There is also code that plays within EEGLAB here:
>
> https://urldefense.com/v3/__https://github.com/aojeda/dsi/tree/master__;!!Mih3wA!H_aYzLvzhjkSGle4cUl8-F0NuyhKgbVd9MZLP9H6UOmD0cfWKsnxgydDcbO1fcidugThUPVbNxSCBR3PSwu_TwmFtgr-$
> (currently unmaintained by me but
> last time I checked nothing was broken).
> Perhaps for the peer-reviewed version it is worthwhile to comment on their
> differences (or not, just a random idea ;-)).
>
> Best,
> Alejandro
>
>
> On Sat, Nov 8, 2025 at 7:50 PM Makoto Miyakoshi via eeglablist <
> eeglablist at sccn.ucsd.edu> wrote:
>
> > Hi Tomas,
> >
> > Using a forward model in defining 'clean' brain signals is a great idea.
> > The idea reminds me of REST by Dezhong Yao.
> > Though I still need to read details, intuitively I think this could be a
> > better way to go than ASR.
> >
> > Makoto
> >
> > On Mon, Oct 20, 2025 at 8:59 PM Tomas Ros via eeglablist <
> > eeglablist at sccn.ucsd.edu> wrote:
> >
> > > Dear EEGLAB community,
> > > We are writing to announce our new plugin, the Generalized Eigenvalue
> > > De-Artifacting Instrument (GEDAI), which is now available in the
> > Extension
> > > Manager.
> > > GEDAI was developed to provide robust and rapid artifact removal, even
> > for
> > > highly contaminated data, without requiring user supervision. It
> > introduces
> > > a novel approach called "leadfield filtering," which uses a theoretical
> > EEG
> > > forward model to separate brain activity from artifacts.
> > > GEDAI was designed to address key limitations of current ICA- or PCA-
> > > based denoising, such as speed, challenging artifact mixtures, or need
> > for
> > > calibration data.
> > > Our benchmark tests<
> > >
> >
> https://urldefense.com/v3/__https://www.biorxiv.org/content/10.1101/2025.10.04.680449v1__;!!Mih3wA!AUK0DyQeIgIlJl7UGbrzSjRIorBGG-rXomeQ_Z4PbNBQiWBRFkCrHDO-8gYgLImNW83Yh6iO78ayvq0yjDaFEJxo2w$
> > > > using real-world data indicate that GEDAI preprocessing can result in
> > > more accurate neurobehavioral prediction compared to competing methods.
> > > Nevertheless, it has not been tested under all EEG scenarios and we
> would
> > > welcome both positive and negative feedback on its performance.
> > > You can also download the plugin and find its documentation here:
> > >
> >
> https://urldefense.com/v3/__https://neurotuning.github.io/GEDAI-master/__;!!Mih3wA!AUK0DyQeIgIlJl7UGbrzSjRIorBGG-rXomeQ_Z4PbNBQiWBRFkCrHDO-8gYgLImNW83Yh6iO78ayvq0yjDYaj2FnGg$
> > > <
> > >
> >
> https://urldefense.com/v3/__https://github.com/neurotuning/GEDAI-master__;!!Mih3wA!AUK0DyQeIgIlJl7UGbrzSjRIorBGG-rXomeQ_Z4PbNBQiWBRFkCrHDO-8gYgLImNW83Yh6iO78ayvq0yjDYf-A47VA$
> > > >
> > > We hope GEDAI becomes a valuable tool for the community.
> > > Best regards,
> > > the GEDAI development team
> > >
> > > ▬▬▬
> > >
> > >
> > > Tomas Ros, PhD
> > >
> > > Lecturer, Department of Clinical Neurosciences
> > >
> > > Research Staff Scientist, CIBM EEG HUG-UNIGE Section
> > > University of Geneva, Switzerland
> > >
> > >
> >
> https://urldefense.com/v3/__https://www.tomasros.com/__;!!Mih3wA!AUK0DyQeIgIlJl7UGbrzSjRIorBGG-rXomeQ_Z4PbNBQiWBRFkCrHDO-8gYgLImNW83Yh6iO78ayvq0yjDZ-36KFHg$
> > >
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> > >
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> > >
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> > >
> >
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> --
> Alejandro Ojeda, Ph.D.
>
> ResearchGate <
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