[Eeglablist] automatic artifact rejection

Fri May 8 01:13:27 PDT 2015

Dear Dana et al,

ERPlab has a couple of functions that do this kind of artefact detection.
http://erpinfo.org/erplab/erplab-documentation/documentation-archive-for-previous-versions/v1.x-documentation/erplab-manual/Artifact_Detection.htm

For example the moving window peak to peak threshold would be something
very close to what you want to do. If you would not want to use ERPlab,
these functions shouldn't be too hard to adapt for EEGlab.

Good luck!

Berry

On 8 May 2015 at 05:26, Makoto Miyakoshi <mmiyakoshi at ucsd.edu> wrote:

> Dear Stephen,
>
> You are absolutely right. This is what Dana asked.
>
> > e.g.; I would like to remove epochs where the *difference between the
> maximum and minimum* in an interval of a selectable length, and the
> difference between the maximum and minimum in the epoch itself, exceeds a
> specific value.
>
> > which would be similar to what eeg_rejthresh does (I think)
>
> I don't know either :-)
>
> I often use this simple amplitude thresholding for epoch rejection, and it
> works well. I wonder why. Maybe it's because noise in EEG recording is
> often associated with high amplitude. In the sense we are lucky, aren't we?
> There could be a parallel universe where EEG noise has nothing to do with
> amplitude...
>
> Makoto
>
> On Thu, May 7, 2015 at 7:44 PM, Stephen Politzer-Ahles <spa268 at nyu.edu>
> wrote:
>
>> Hm, good point. Since the OP asked for the difference between the epoch
>> maximum and minimum, this seemed like the best way to do it (although there
>> might be a cleaner way to code it. Looking at max(abs(EEG.data,[],2)) seems
>> like it would instead find the greatest voltage in either direction, which
>> would be similar to what eeg_rejthresh does (I think)
>>
>> Best,
>> Seve
>>
>>
>>
>> Stephen Politzer-Ahles
>> New York University, Abu Dhabi
>> Neuroscience of Language Lab
>> http://www.nyu.edu/projects/politzer-ahles/
>>
>> On Thu, May 7, 2015 at 11:01 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
>> wrote:
>>
>>> Dear Stephen,
>>>
>>> Very smart, as usual!
>>>
>>> By the way, could you please tell me why you subtract min from max?
>>> > diffs = squeeze( max(EEG.data,[],2) - min(EEG.data,[],2) );
>>>
>>> What if you have max 10150 and min 10000?  (after high-pass filtering it
>>> is not likely to happen though)
>>>
>>> I thought this would be more straightforward
>>> > diffs = squeeze(max(abs(EEG.data,[],2)));
>>>
>>> Am I missing something here? I appreciate your comment. Thank you!
>>>
>>> Makoto
>>>
>>> On Mon, May 4, 2015 at 9:07 PM, Stephen Politzer-Ahles <spa268 at nyu.edu>
>>> wrote:
>>>
>>>> Hi Dana,
>>>>
>>>> I also would have thought these would be implemented, but I couldn't
>>>> find t hem just now; maybe they're in ERPLAB.
>>>>
>>>> It shouldn't be hard, though, to code this yourself. Below is a quick
>>>> sample I just made; I can't guarantee this will work in all cases but it
>>>> gives you an idea. You could easily run some simple code like this and then
>>>> just add the bad trial list into the EEG.reject structure.
>>>>
>>>> Best,
>>>> Steve
>>>>
>>>>
>>>> %%% MAXMIN CRITERION
>>>>
>>>> % Finds the difference between the maximum and minimum of each epoch.
>>>> Could
>>>> % be tweaked to look only at a certain time range within the epoch
>>>> diffs = squeeze( max(EEG.data,[],2) - min(EEG.data,[],2) );
>>>>
>>>> % We'll kick out any trials whose difference exceeds this uV threshhold
>>>> threshold = 200;
>>>>
>>>> % Find samples that exceed the threshhold
>>>> [chanidx, epochidx] = find( diffs > threshold );
>>>>
>>>> % Find epochs that have at least one sample, at any channel, exceeding
>>>> the
>>>> % threshhold
>>>> badepochs.maxmin = unique( epochidx );
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> %%% NEIGHBORING SAMPLES CRITERION
>>>>
>>>> % Find the difference between neighboring samples each pair of
>>>> neighboring samples
>>>> diffs = arrayfun( @(x)( squeeze (EEG.data(:,x,:) - EEG.data(:,x-1,:) )
>>>> ), 2:size(EEG.data,2), 'UniformOutput', false );
>>>>
>>>> % organize that cell array into a matrix, which will be easier to work
>>>> with
>>>> n_chan = size(diffs{1},1);
>>>> n_samp = length(diffs);
>>>> n_trial = size(diffs{1},2);
>>>> diffs = reshape(cell2mat(diffs), n_chan, n_samp, n_trial);
>>>>
>>>> % get the max difference across samples, for each trial
>>>> diffs = squeeze( max(diffs,[],2) );
>>>>
>>>> % We'll kick out any trials whose difference exceeds this uV threshhold
>>>> threshold = 75;
>>>>
>>>> % Find samples that exceed the threshhold
>>>> [chanidx, epochidx] = find( diffs > threshold );
>>>>
>>>> % Find epochs that have at least one sample, at any channel, exceeding
>>>> the
>>>> % threshhold
>>>> badepochs.neighbsamp = unique( epochidx );
>>>>
>>>>
>>>>
>>>> Stephen Politzer-Ahles
>>>> New York University, Abu Dhabi
>>>> Neuroscience of Language Lab
>>>> http://www.nyu.edu/projects/politzer-ahles/
>>>>
>>>> On Thu, Apr 30, 2015 at 12:37 PM, Son, D.M.E. van <
>>>> d.m.e.van.son at fsw.leidenuniv.nl> wrote:
>>>>
>>>>>  Dear Eeglab members,
>>>>>
>>>>> Before manually selecting artifacts in my data, I would like to
>>>>> pre-select artifacts automatically. I have seen that Eeglab provides an
>>>>> automatic epoch rejection toolbox, but specific epoch selection that I
>>>>> would like to make, does not seem to be provided.
>>>>> e.g.; I would like to remove epochs where the difference between the
>>>>> maximum and minimum in an interval of a selectable length, and the
>>>>> difference between the maximum and minimum in the epoch itself, exceeds a
>>>>> specific value. Also, I’d like to remove epochs wherin the absolute
>>>>> difference between two neighboring sampling points exceeds a certain
>>>>> value.
>>>>>
>>>>> Does anyone have an idea if this is possible in Eeglab automatically?
>>>>> Or perhaps it is possible that I script this separately?
>>>>>
>>>>> Many thanks in advance
>>>>>
>>>>> Dana
>>>>>
>>>>>
>>>>> _______________________________________________
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>>>>>
>>>>
>>>>
>>>> _______________________________________________
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>>>
>>>
>>>
>>> --
>>> Makoto Miyakoshi
>>> Swartz Center for Computational Neuroscience
>>> Institute for Neural Computation, University of California San Diego
>>>
>>
>>
>
>
> --
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>
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-- 
Berry van den Berg
email: berryv.dberg at gmail.com
website: berryvdberg.org
mobile: +31612585275
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