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

[Cedric Cannard]

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
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