GregPerlman
commented
4 years ago 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.
arnodelorme
Setting manually 'WindowCriterion' to 0.4 instead of default 0.25 tends to reject more data (according to Greg Perlman). This is in contradiction with the documentation which indicate that "Generally a lower value makes the criterion more aggressive"