[FieldTrip] Starting at ft_timelockstatistics

[Danielle Farrar]

Hello,

My apologies if this has been covered before, I just joined the list and am
having trouble searching the archives.

I have a set of EEG data that was recorded from a Biosemi apparatus using a
128-channel cap. The dataset is in text files, is post-processed and is the
result of filtering, epoching, and averaging, and has been imported into
matlab.  I created trial structs out of the datasets.  It is a dataset of
21 subjects with two conditions.  I'm trying to do some non-parametric
clustering statistics on the dataset and I don't have access to the
original bdf files.

I have the electrode names and coordinates saved in matlab matrices.  Now,
I'd like to do clustering analysis using a monte carlo simulation to
determine areas of significant differences between the two conditions, but
am having trouble ensuring that my datasets are structured appropriately
for input. It seems that the tutorials mostly assume that the data is in a
raw output format from one of the systems.

I know that for ft_timelockstatistics, the data is supposed to be output
from the ft_timelockanalysis. I was trying to use ft_timelockanalysis as an
entry point  However, I am having trouble constructing the data struct
appropriate for the timelock function.  Can this be done?  Should I be
starting further upstream? I'm attaching some of the code. I'm know the
data struct needs additional information but am not sure how to go about
using it.

The error I get when I run the following code is "Error using ft_checkdata
(line 480). This function requires raw+comp or raw data as input."

Thanks!
Danielle

********************************

for i=size(CD_condition.data,3),
      CD_trial{i} = CD_condition.data(:,:,i);
end

CD.trial = CD_trial;

cfg.channel = 'all';
cfg.trials = 'all';
cfg.covariance = 'yes';
cfg.covariancewindow = 'prestim';
cfg.removemean = 'yes';
cfg.vartrllength = 0;

CD.type = 'raw+comp';
ft_timelockanalysis(cfg,CD);
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