[Eeglablist] Let's test whether GEDAI is a post-ASR EEG artifact rejection champion

[Makoto Miyakoshi]

Hi Cedric,

Thank you for your very quick response and sharing your impression.

I think one nice additional advantage of GEDAI over ASR is that it is
probably more developer friendly. GEDAI is composed of more general
concepts: lead field and GED, while ASR is based more on free and unique
ideas supported by empirical parameter optimization. For example, the use
of truncated Gaussian, geometric median across covariance matrices, or its
Riemanian variant, etc etc., ending up with SD==20 being a de facto
default, which is obviously unusual but few can explain where exactly it
comes from.

Hi Norbert,

Yes, GEDAI supports EEGLAB. You can use it as an EEGLAB plugin. However,
you have to manually download the file and move them under /eeglab/plugins
as we used to do before the modern GUI-based management system was
introduced. Please see this page. You can find both the download package
and an instruction of how to 'install' it to EEGLAB

https://urldefense.com/v3/__https://github.com/neurotuning/GEDAI-master__;!!Mih3wA!Ewu6iAWopqNjHfgqD4a5dp_o_Vr__gyjZ5WkzwJdtVEVKBZQjhjnGnfHoDT7gomOKfuHRXEwSD9QN5hM_p2yJKR8DKM$ 

Makoto

On Mon, Mar 30, 2026 at 6:58 PM Cedric Cannard via eeglablist <
eeglablist at sccn.ucsd.edu> wrote:

> Hi Makoto,
>
> I’ve been playing with it and was impressed. It feels like the thresholds
> may be a little too aggressive to me (the ‘auto-‘ was better), but I
> haven’t done any formal comparisons yet. I’ll share here if I do. I’ve been
> also very curious to learn more but haven’t had the time to dig more yet.
>
>
> Cedric
>
> Sent from Proton Mail for iOS.
>
> -------- Original Message --------
> On Monday, 03/30/26 at 14:56 Makoto Miyakoshi via eeglablist <
> eeglablist at sccn.ucsd.edu> wrote:
> Hi EEGLAB mailing list subscribers,
>
> I watched this Youtube video on GEDAI, a relatively new EEG artifact
> rejection algorithm, and got very impressed. If you are interested in, or
> looking for, an effective artifact rejection method, you definitely want to
> check it out.
>
> https://urldefense.com/v3/__https://www.youtube.com/watch?v=qSM5narynzc__;!!Mih3wA!CLlPjuH-5y0g4OtnG1F8KKjQoNScMgDneZVoRYZ1yoUGb_ySMhoAaf4jO0oLiDxE_IZRlBbTXuSFkSA4XgNw9TOfbZ8$
> Do not miss the scene in which Tomas shows a comparison before and after
> removing the TMS-induced artifact (about 20 min position). I've never seen
> a more dramatic demo than this. It is only comparable to successful demo of
> gradient artifact removal from fMRI-EEG recording.
>
> Here is a suggestion to this community:
> If you have been already using ASR, why don't you please use GEDAI as well
> in parallel, compare the results, and share your impression with us? I'll
> do so in my next project and report it here.
>
> The reason why I like GEDAI is that the concept of combining lead field +
> GED is elegant. The idea of 'learning from data's own cleanest part' is the
> same as ASR, but GEDAI does it more explicitly and simply. GEDAI is like
> ASR + REST (a reference method using a forward model).
>
> Makoto
> _______________________________________________
> To unsubscribe, send an empty email to
> eeglablist-unsubscribe at sccn.ucsd.edu or visit
> https://sccn.ucsd.edu/mailman/listinfo/eeglablist   .
>
> _______________________________________________
> To unsubscribe, send an empty email to
> eeglablist-unsubscribe at sccn.ucsd.edu or visit
> https://sccn.ucsd.edu/mailman/listinfo/eeglablist  .