[FieldTrip] Weird repetition trails…. (.cnt files)

[Ines Bramao]

Dear fieldtripers,

I am having problems for fieldtrip to read the .cnt neuroscan files. I noticed that, when I am plotting my trials (using ft_databrower), I get trials that are exactly the same. The data in each sample of that trial, for each channel, looks exactly the same! I don’t really know the reason for this and I have tried and checked different things:


1.       My trl matrix is properly defined. It could be that the same sample numbers were used for extracting different trial numbers, but that is not the case.

2.       Using curry to visualize the data showed that there is nothing wrong while converting my .dat into a .cnt file.

3.       I notice that fieldtrip is using the loadcnt function from eeglab. For this reason I used eeglab to read the data. When I plot the trials using eeglab I don’t find these weird trials repetitions.

4.       The trials that are repeated do not seem to be real (when I look into those trials repetitions using both with curry and eeglab the trials are completely different from what fieldtrip give me). Besides those weird repetitions or the other trials seems to match.

5.       I do not get more trials then what I am asking for. My trl matrix has 312 rows and I get 312 trials. So those repeated trials are replacing some relevant information…

6.       The data in each sample of those trials are the same, but the triggers are different. If I would continue with data analysis exactly the same trial would be latter classified as belonging to different experimental conditions.

7.       Importantly while I am extracting the trials from the data using ft_preprocessing I get a warning message saying “events imported with a time shift might be innacurate”.

8.       I am using the most recent version of fieldtrip (fieldtrip-20141021)


Do you have any idea of what can be going on? I have been using fieldtrip before (.bdf files) and I never had this problem… Also, a colleague of mine is having the same exactly problem…

Thank you very much in advance!
Inês Bramão
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