[Eeglablist] std_erpimage error mesage

Li, Lucia M lucia.li at imperial.ac.uk
Thu Jun 18 09:22:13 PDT 2015

Dear Makoto,

Thank you for taking the time to answer my questions.

>From your reply, it sounds like I need to know how many trials I have per condition per subject (e.g. subject1 has 25 trials for condition1, subject2 has 20 trials for condition1 etc.). Does this mean that there is a minimum number of trials required for doing ERP analysis in eeglab? What is the minimum number? One of my subjects only has 5 trials for a condition - does that mean I can't calculate ERPs using for that condition?

Have I understood correctly? (I ask because the code you've written seems to be extracting the event markers (ALLEEG.event.type) from all entries into a study, and I'm not sure how that helps?)

Many thanks again & kind regards,
From: Makoto Miyakoshi [mmiyakoshi at ucsd.edu]
Sent: Monday, June 15, 2015 6:23 PM
To: Li, Lucia M; Ramón Martinez
Cc: eeglablist at sccn.ucsd.edu
Subject: Re: [Eeglablist] std_erpimage error mesage

Dear Lucia,

You need to know (or the application should figure it out) the minimum number of available trials across all conditions and subjects. To code it, it should be something like this:

numTrialList = zeros(length(ALLEEG),3)) % if there are 3 conditions
for n = 1:length(ALLEEG)
tmpEEG = ALLEEG(1,n);
allEventTypes = {tmpEEG.event.type}';
numTrialList(n,1) = find(strcmp(allEventTypes, 'event1')));
numTrialList(n,2) = find(strcmp(allEventTypes, 'event2')));
numTrialList(n,3) = find(strcmp(allEventTypes, 'event3')));

I wrote it without opening Matlab so there may be mistake.

I believe this should be really implemented in EEGLAB so that the application suggests the upper bound. Ramon, would you please add it to Bugzilla?


On Mon, Jun 8, 2015 at 8:40 AM, Li, Lucia M <lucia.li at imperial.ac.uk<mailto:lucia.li at imperial.ac.uk>> wrote:
Dear eeglab users & experts,

I was wondering if someone might be able to help me decipher this error message.

I have datasets from 12 people which I wish to combine into a study. There are 15 different bin types.

Having created my study by loading all the datasets in, I tried to "precompute channel measures". I attempted to pre-compute: ERP, Power spectrum, ERP-image, ERSP & ITCs. I clicked 'Test' as well to make sure that the parameters I entered produced sensible results. All other options I left as default ('Spherical interpolation' ticked, 'Remove ICA artifactual components pre-tagged' and 'Remove artifactual ICA cluster' unticked).

Unfortunately, the pre-compute throws up this error message:

"The default number of ERPimage lines is too large for one of the dataset, {Error occurred in function std_erpimage() at line 169'

I'm not entirely sure what the problem is. I have also tried to pre-compute with fewer bin types and it's worked perfectly.

My two thoughts about why the full study won't precompute properly:
- some of the bins overlap e.g. a bin for responses from the first half of the task, and a bin for left hand responses from the first half of the task
- some bins have <10 trials

Any thoughts and help on this matter greatly appreciated!

Kind regards,

L M Li
Wellcome Trust Clinical Fellow
Imperial College London

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Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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