[FieldTrip] Problem with ft_timelockstatistics, within subject comparison of two conditions

[Clara A. Scholl]

Dear Barbara,

Just three thoughts:

1) Should cfg.ivar and cfg.uvar both be single values, i.e. the dimension
of the design matrix that contains the independent and unit variables?
Then you'd have cfg.ivar=1 and cfg.uvar=2 (or vise versa, depending on the
design matrix).

2) I think the design matrix itself might be off, right now it just seems
to have dimensions of 1 x (# targets+standards).  It should have a second
dimension which counts the # of trials, something like:

design(1,:) = [ones(size(targetclean_tlt.trial,1),1);
2*ones(size(standardclean_tlt.trial,1),1)]';
 design(2,:)= ([1:size(targetclean_tlt.trial) 1:size(standardclean_tlt.trial
,1)])

3) Since this is a design where each trial is an observation, I think you
should be using indepsamplesT for cfg.statistic (the trials aren't paired
and there aren't necessarily identical #'s of trials for each condition.

What do you think?
Respectfully,
Clara


On Tue, Oct 7, 2014 at 9:42 AM, <barbara.schorr at uni-ulm.de> wrote:

> Dear fieldtripers,
>
> I would like to compare to conditions of an auditory oddball paradigm
> (target tones and standard tones).
> For the identification of the electrodes which show the biggest P300, I
> would like to use cluster based permutation test, i.e. I want to use
> ft_timelockstatistics, to identify the clusters with a significant
> difference between the target and the standardtones.
> Important: I don't want to do a group statistic, but I want to compare
> these two conditions within each subject, to identify interesting clusters
> for each subject separately.
>
>
> I wrote the script following the tutorials on the fieldtrip homepage.
>
> I already wrote a code but it does not work:
> %%
>
> for i = 3:10 % subject number
>     mypfad = 'G:\BackUp07.07.14_DatenPrepr\Daten1\P300'
>     cd(mypfad)
>     cd Kontrollen;
>     List = dir
>     cd (List(i).name);
>     for j = 1:4 %session number
>         cd (mypfad);
>         cd Kontrollen;
>         List = dir
>         cd (List(i).name);
>         eval(['cd M' num2str(j)]);
>         load cleandata_tlt; %preprocessed timelocked data
> standardclean_tlt  and targetclean_tlt
>
>         cfg = []
>         cfg.neighbourdist = .09;
>         cfg.layout= ulmegilay;
>         cfg.method = 'distance';
>
>         Neighbours = ft_prepare_neighbours(cfg, standardclean_tlt)
>
>         cfg = []
>         cfg.method = 'montecarlo' ; %significance probability
>         cfg.statistic = 'ft_statfun_depsamplesT'
>         cfg.correctm = 'cluster'
>         cfg.clusteralpha = 0.05 %alpha level of the sample specific test
> statistic that will
>                                 % be used for thresholding
>         cfg.clusterstatistic = 'maxsum'
>         cfg.minnbchan = 4
>         cfg.latency = [0.25 0.8]
>         cfg.neighbours = Neighbours
>         cfg.tail = 0
>         cfg.clustertail = 0
>         cfg.alpha = 0.025
>         cfg.numrandomization = 1000
>
>         design = [ones(size(targetclean_tlt.trial,1),1);
> 2*ones(size(standardclean_tlt.trial,1),1)]';
>         design([1:size(targetclean_tlt.trial) 1:size(standardclean_tlt.
> trial,1)])
>
>
>         cfg.design = design
>         cfg.ivar = [ones(size(targetclean_tlt.trial,1),1);
> 2*ones(size(standardclean_tlt.trial,1),1)]'
>         cfg.uvar = [1:size(targetclean_tlt.trial) 1:size(standardclean_tlt.
> trial,1)]
>
>         tlt_statsnew = ft_timelockstatistics(cfg, targetclean_tlt,
> standardclean_tlt )
>
>         cd 'G:\BackUp07.07.14_DatenPrepr\Daten1\P300';
>         cd Kontrollen;
>         List2 = dir
>         cd (List2(i).name);
>         eval(['cd M' num2str(j)]);
>         save statnew tlt_statsnew
>
>     end
> end
>
>
> This is what gets displayed while running the script:
>
> selected 245 channels
> selected 139 time bins
> selected 1 frequency bins
> using "ft_statistics_montecarlo" for the statistical testing
> using "ft_statfun_depsamplesT" for the single-sample statistics
> constructing randomized design
> total number of measurements     = 189
> total number of variables        = 1
> number of independent variables  = 189
> number of unit variables         = 189
> number of within-cell variables  = 0
> number of control variables      = 0
> using a permutation resampling approach
>
> Then, this error occurs:
>
> Error using resampledesign (line 168)
> A within-units shuffling requires a at least one unit variable and at least
> one independent variable
>
> Error in ft_statistics_montecarlo (line 241)
> resample = resampledesign(cfg, design);
>
> Error in statistics_wrapper (line 310)
>     [stat, cfg] = statmethod(cfg, dat, design);
>
> Error in ft_timelockstatistics (line 113)
> [stat, cfg] = statistics_wrapper(cfg, varargin{:});
>
> I have no clue where I made a mistake. I have unit variables and
> independent variables (189 if I understand it correctly).
> Is there anything I am missing? Any additional information or is the
> design matrix wrong?
>
>
> I really appreciate your help.
>
> Best regards,
> Barbara
>
>
>
>
> Barbara Schorr, MSc
> Clinical and Biological Psychology
> University of Ulm
> Albert-Einstein-Allee 47
> 89069 Ulm
>
>
>
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> fieldtrip at donders.ru.nl
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>
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