FieldTrip support
Thomas Sauvigny
tsauvigny at GOOGLEMAIL.COM
Wed Aug 25 11:26:03 CEST 2010
Dear fieldtrip users!
May I ask for your support because of a problem concerning my within-subject
permutation test (EEG-Data)?
The goal is to compare two grandaverages with two different conditions,
each grandaverage consisting of 4 datasets from 4 subjects, each dataset
about 40-50 single trials.
I did the preprocessing, timelock and grandaverage: 4 datasets (called x1,
x4) for the first condition with the following command:
cfg = [];
cfg.keeptrials = 'yes';
timelock1 = timelockanalysis(cfg, x1);
timelock2 = timelockanalysis(cfg, x2);
timelock3 = timelockanalysis(cfg, x3);
timelock4 = timelockanalysis(cfg, x4);
cfg.channel = 'all'
cfg.latency = 'all'
cfg.keepindividual = 'yes'
cfg.normalizevar = 'N-1'
da_test1= timelockgrandaverage (cfg, timelock1, timelock2, timelock3,
timelock4)
save da_test1
Same way for the second condition: da_test2
Now I start the permutation test (file attached). As result there are no
significant clusters highlighted (although there are quite large
differences in the ERP-plot). I think because there is a mistake concerning
the number of single-trials which fieldtrip takes as the basis for the
statistic test.
Because the output in the command window shows:
selected 30 channels
selected 2501 time bins
selected 1 frequency bins
total number of measurements = 8
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 1 over 4 levels
number of repeated measurements in each level is 2 2 2 2
computing a parmetric threshold for clustering
computing statistic
estimated time per randomization is 0 seconds
computing statistic 1 from 100
found 7 positive clusters in observed data
found 11 negative clusters in observed data
stat =
prob: [30x2501 double]
posclusters: [1x7 struct]
posclusterslabelmat: [30x2501 double]
posdistribution: [1x100 double]
negclusters: [1x11 struct]
negclusterslabelmat: [30x2501 double]
negdistribution: [1x100 double]
mask: [30x2501 logical]
stat: [30x2501 double]
ref: [30x2501 double]
dimord: 'chan_time'
label: {30x1 cell}
time: [1x2501 double]
cfg: [1x1 struct]
cfg =
xlim: [0 0.1000]
zlim: 'maxmin'
the input is timelock data with 30 channels and 4000 timebins
applying preprocessing options
averaging trials
averaging trial 1 of 4
averaging trial 2 of 4
averaging trial 3 of 4
averaging trial 4 of 4
reading layout from file easycap32ch-avg.lay
So, could this be the mistake that fieldtrip guesses 4 to be the number of
all trials (perhaps because 4 datasets in each grandaverage??) And how can
I solve this problem? Is there a way to account for the single-trial number
when using the permutation test?
Thank you very much for your help!!
Kind regards
Thomas Sauvigny
Tübingen University
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The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip.
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