[Eeglablist] automatic artifact rejection

[Stephen Politzer-Ahles]

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
>
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