[Eeglablist] IClabel help

[Makoto Miyakoshi]

Dear Ugo,

I have never been the official anything of SCCN, but here is my personal
opinion.

> 1.  At what percentile does the team considers good enough to remove? 95%
and above? 99%?

I would use EEG probability of 0.7 for the accepting criterion.

> 2.  Do the team advises to use other data cleaning processes such as
CORRMAP, or can I use IClabel only to clean the data?

I would use ICLable with 0.7 for EEG or my PSD-based semi-manual IC
rejection.
https://sccn.ucsd.edu/wiki/Std_selectICsByCluster#As_a_group-level_filter_to_manually_exclude_non-EEG_ICs


But for the application, use this one. This is the updated one.
https://sccn.ucsd.edu/wiki/Std_clust2ch

> 3.  Could I theoretically use it in a loop until I find something above
95% to remove?

Oh are you talking about identifying artifacts?
Hmm, it is actually more fuzzy than identifying brain components. You would
not achieve completely satisfactory results even if you try hard to find
the magical threshold. So unfortunately it is up to you. One good thing is
that in theory no one can blame you for the choice of the threshold. Just
choose any number which you can take responsibility.

Makoto


On Fri, Jul 12, 2019 at 9:53 PM Bruzadin Nunes, Ugo <ugob at siu.edu> wrote:

> Hi,
>
> I have three quick questions about the new IC label plugin.
>
>   1.  At what percentile does the team considers good enough to remove?
> 95% and above? 99%?
>   2.  Do the team advises to use other data cleaning processes such as
> CORRMAP, or can I use IClabel only to clean the data?
>   3.  Could I theoretically use it in a loop until I find something above
> 95% to remove?
>
> Thanks a lot,
>
> Ugo Bruzadin Nunes, M.A.
> PSYC 312 Instructor - Sensation and Perception
> Brain and Cognitive Sciences Ph.D Program || Department of Psychology
>
> Southern Illinois University - Carbondale
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-- 
Makoto Miyakoshi
Assistant Project Scientist, Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego