[FieldTrip] Cluster-based permutation tests for between-subject design

Dylan DeLosAngeles dylan.delosangeles at gmail.com
Tue Oct 21 03:41:01 CEST 2014


Dear Eelke,

Thank you for help regarding cluster-based permutation analysis of two or
more conditions.

I am using time-frequency data (not time-lock structures). My first problem
seems to be getting my 12 subjects into the 4D powspectrum.

My code below loads 12 subjects from the first group, but I end up with a 1
x 12 struct where each struct's .powspctrm is 1 subject x 11 electrodes x 3
frequencies x 2049 time points, rather than one struct with a 4D powspctrm
with 12 subjects as rows x electrodes x freqs x time points.

for k = 1:Nmt, % states
    for i = 1%:Ng, % groups
        for j = 1:Ns, % subjects

            % load files
            p(j) = eeg3.eeg.load(fullfile(fpath,fname2));

            % convert to eeglab to get channel locations
            EEG(j) = eeg2eeglab( p(j));
            EEG(j) = pop_chanedit( EEG(j), 'lookup', chanlocfile);

            % preprocessing in fieldtrip
            d(j) = eeglab2fieldtrip( EEG(j), 'preprocessing');

            % specify length of time to use in config
            time = EEG(j).xmax-EEG(j).xmin;

            % setup configuration for freqanalysis
            cfg = [];      % clear cfg
            cfg.output     = 'pow';
            cfg.channel    = 'EEG';
            cfg.method     = 'mtmconvol';
            cfg.taper      = 'hanning';
            cfg.foi        = 0.5:3; % delta
            cfg.toi        = 1:0.05:time; % length of each state
            cfg.t_ftimwin  = 7./cfg.foi; % 7 cycles
            cfg.keeptrials = 'yes';

            % do freqanalysis
            freqdata(j) = ft_freqanalysis( cfg, d(j));
        end
    end
end

My second problem is loading in the second group of 12 subjects and what
that will look like when I run ft_freqstatistics.

Lastly, I just want to confirm what you said in your previous email, that I
should be using indepsamplesF for more than two conditions (I have 11), and
therefore my design should look like this;
1     2     1     2     1     2     1     2     1     2     1     2     1
  2      1     2     1     2     1     2      1      2     (two groups)
1     1     2     2     3     3     4     4     5     5     6     6     7
  7      8     8     9     9    10    10    11    11     (11 conditions)

Any help would be appreciated.

Kind regards,
Dylan




On Wed, Sep 24, 2014 at 3:29 PM, Eelke Spaak <eelke.spaak at donders.ru.nl>
wrote:

> Hello Dylan,
>
> You can analyse a between-subjects design exactly as you would a
> between-trials design (at least as far as the statistics step is
> concerned), in both cases the two conditions correspond to two groups
> of observations, and not to the same group of observations measured in
> two separate conditions (which would be a within-UO design). In
> FieldTrip, you would typically compute averages per subject, then use
> an "indepsamplesT" (or indepsamplesF with >2 conditions) statistic
> (not depsamples). indepsamplesT only requires one row in the design
> matrix, indicating the condition.
>
> Note that if you have e.g. timelock structures in two (or more) cell
> arrays, corresponding to the conditions, you can input them into the
> statistics function as follows:
>
> stat = ft_timelockstatistics(cfg, tlCondA{:}, tlCondB{:});
>
> without having to call ft_timelockgrandaverage. In fact, the above is
> the preferred way to do statistics now. (The same holds for
> ft_freqstatistics.)
>
> Hope that helps,
> Best,
> Eelke
>
> On 24 September 2014 02:32, Dylan DeLosAngeles
> <dylan.delosangeles at gmail.com> wrote:
> > Hello,
> >
> > So far, the tutorial on "Cluster-based permutation tests on
> time-frequency
> > data" has been very helpful.
> >
> > Out of the four combinations from the two UO-types (subjects and trials)
> and
> > the two experimental designs (between- and within-UO), the tutorial
> covers
> > statistics on data in two conditions in a between-trials, in a
> within-trials
> > and in a within-subjects design. However, I am wondering if there is any
> > information about the fourth type of experiment design: between-subjects.
> >
> > I have data for 2 groups with 12 subjects in each group. Both groups are
> > measured during 11 conditions.
> > Can I approach this in a similar fashion to within-subjects design
> (multiple
> > subjects in multiple experimental conditions), such that my design is
> > multiple groups in multiple experimental conditions. Is it a case of
> first
> > averaging over all trials belonging to each of the experimental
> conditions
> > for each subject (as instructed in tutorial), and then averaging over all
> > subjects in each group?
> >
> > Configuration code for setting up the design currently looks like this;
> > grp = 2;
> > subj = 11;
> > design = zeros(2, subj*grp);
> >
> > for i = 1:grp
> >     design(1,i:2:end) = i;
> > end
> >
> > idx = 1;
> > for i = 1:subj
> >     design(2,idx:idx+1) = i;
> >     idx = idx+2;
> > end
> >
> > Is there anything else I need to take into consideration when doing these
> > statistics?
> >
> > Thank you,
> > Dr Dylan DeLosAngeles
> > Research Fellow
> > Brain Signal Laboratory
> > Flinders University
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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