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ft_freqstatistics for EEG data (cluster correction) #519
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How are we supposed to reproduce your error? |
Thanks, François, for your reply. That's what I wanted to know (files are good, it should work as is). I'll thus download the last version (I had 20170401) and try on a different computer. |
Hi again, Error in findcluster (line 90) Error in clusterstat (line 197) Error in ft_statistics_montecarlo (line 347) Error in ft_freqstatistics (line 193) |
which version of fieldtrip are you using (which date or which git version code), which version of MATLAB are you using and on which operating system are you running this? |
and what is the exact (and full) error message that you see on screen? |
Hi, that I can retrieve. |
I suppose you are running into something like this http://bugzilla.fieldtriptoolbox.org/show_bug.cgi?id=3330. SPM mex files are in external and not maintained by the FieldTrip team. Please recompile the spm mex files for your platform or contact the SPM team. |
Hi,
I would like to use the Fieldtrip function ft_freqstatistics to perform cluster statistics at the channel level on frequency-resolved (but not time-resolved) EEG data (63 channels), comparing 2 conditions. For each participant and condition the data have the following size: 63x2x20 (channels/time/frequency). When I run the process, even with only 2 participants (and 100 permutations), I obtain after 2 minutes a Java exception (OutOfMemoryError).
I run the process on a mac book pro 2016 (3,1 GHz Intel Core i7). I have a java heap size of 4,096MB on MATLAB.
This exception does not occur if I use another type of correction (bonferroni, fdr...).
Might you please help me to resolve this issue ?
Please find enclosed the input data (cfg = statcfg, and the 2*2 (2 participants * 2 conditions) data = ftAllFiles): thedata.mat.zip
thank you,
Benjamin Morillon
ps: the info appearing on the Matlab screen when I run the process:
the call to "ft_selectdata" took 0 seconds and required the additional allocation of an estimated 9 MB
using "ft_statistics_montecarlo" for the statistical testing
using "ft_statfun_depsamplesT" for the single-sample statistics
constructing randomized design
total number of measurements = 4
total number of variables = 2
number of independent variables = 1
number of unit variables = 1
number of within-cell variables = 0
number of control variables = 0
using a permutation resampling approach
repeated measurement in variable 2 over 2 levels
number of repeated measurements in each level is 2 2
computing a parametric threshold for clustering
computing statistic
estimated time per randomization is 0.07 seconds
computing statistic 100 from 100
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