[Eeglablist] Different methods to automatically remove faulty channels

[Katarzyna Dudzikowska]

Hi all,

I am preprocessing EEG datasets for the first time ever and trying to
figure out how to take care of any potential unsound channels. Just
scrolling through the data none of the channels really jump out as bad, but
that is probably down to my lack of expertise. So to get closer to some
level of understanding I ran and took notes on all the methods of automatic
rejection that I am aware of: using probability, kurtosis and spectrum as a
measure, as well as channel rejection encompassed in clean_raw_data
function.
It took me a good moment, but I am just as confused as I was before,
because there is no coherence whatsoever in the results of these four
methods.
There is some overlap between rejection based on Kurtosis and Probability
(though Probability measure usually suggests to reject only one or two
channels of several suggested through Kurtosis measure). Results of
Spectrum measure are usually null, sometimes one of the channels picked up
through other measures also gets labeled for rejection. The algorithm used
by clean_raw_data always comes up with multiple channels for rejection,
many more than any other method, but they virtually never overlap with
channels labelled by other methods.

In my naivete I kind of thought that there would be at least some
agreement: if a channel is in some way faulty wouldn't it at least
sometimes be captured by different methods? In a couple datasets I also
tried to run automatic channel rejection after doing some artifact
rejection with ASR and got completely different results to those from
before artifact rejection which confused me too. I am applying the
functions to continuous data, after downsampling (to 250 Hz), low pass
filtering at 0.5Hz and high pass filtering at 45Hz. The channel locations
are imported and right mastoid channel was added as a reference. Am I
missing something?

I am really curious why there is such a massive discrepancy between
different methods. On a more practical side could you give me some advice
on how to decide on the best method to choose (I have watched/read several
tutorials, but I am still really confused). Which method should I trust? My
end goal is to calculate frontal alpha asymmetry, in case that makes any
difference: is any of the methods more suitable for frequency analysis?

I would be really grateful for some advice.

All the best,
Katia