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

[Makoto Miyakoshi]

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
>
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>
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