Possibly misleading documentation about clean_rawdata HOT 2 CLOSED

Thanks, Arno.

Here's what I notice.
Subject 2 has the following number of events, as indexed by "cell2mat({EEG.event.type})":

1 has 181 events (stimulus onset, Easy Trial)
2 has 149 events (stimulus onset, Hard Trial)
3 has 152 events (Correct Response, Easy)
4 has 141 events (Correct Response, Hard)
9 has 19 events (Incorrect Response, Easy)
10 has 21 events (Incorrect Response, Hard)
254 has 1 events (Start task code)

This is a basic Flankers task with 2 events per trial (stimulus onset and the subject response) and 330 trials.

After running EEG = clean_artifacts(EEG,'FlatlineCriterion',5,'ChannelCriterion',0.8,'LineNoiseCriterion',4,'Highpass',[0.25 0.75],'BurstCriterion',10,'Distance','Euclidian','WindowCriterionTolerances',[-Inf 7]), the events count will match the original file's events count.

If I run the full clean_artifacts function from the GUI with BurstRejection 'On' and Window Criterion set to 0.25), then the events are converted to cell arrays, probably because of 'boundary'. In any case, I can only count the events using '{ EEG.event.type }':

1 has 180 events
10 has 5 events
2 has 134 events
3 has 82 events
4 has 87 events
9 has 6 events
boundary has 345 events

Thus, the full default clean_artifacts removed a large portion of subject response codes without removing many stimulus codes, but also added a tremendous number of "boundary" event flags. Using a more lax or more aggressive value for Window Criterion does not help the situation.

Data is collected with a Biosemi system and 34 channels of EEG plus VEGO+, VEGO-, HEOG+, HEOG-, Mastoid 1, Mastoid 2. I’m using eeglab2019b on Matlab 9.7.0.1190202, 64-bit.

from clean_rawdata.

I have checked and using a higher value is less agressive.

from clean_rawdata.