[FieldTrip] cluster-based permutation test on WPLI

[Zsolt Turi]

Hi Tzvetan,

thanks for your suggestions.
I am still stucked at the ft_freqstatistics, as I keep on receiving the
following error and would be glad if you could make a comment on this as
well:

####
Reference to non-existent field 'label'.

Error in ft_freqgrandaverage (line 123)
        cfg.channel = ft_channelselection(cfg.channel, varargin{i}.label);
###

Is it because I have labelcomb in the WPLI data?

labelcmb: {9x2 cell}
        dimord: 'chan_freq_time'
    wplispctrm: [9x7x16 double]
          freq: [3 4 5 6 7 8 9]
          time: [-0.5000 -0.4004 -0.3008 -0.1992 -0.0996 0 0.0996 0.1992
0.3008 0.4004 0.5000 0.5996 0.6992 0.8008 0.9004 1]
           cfg: [1x1 struct]

And this is my specification (I couldn't fine the option cfg.channelcmb for
ft_freqgrandaverage in the reference documentation):

cfg                          = [];
cfg.keepindividual    = 'yes';
cfg.cfg.foilim           = 'all';
cfg.toilim                = 'all';
cfg.channel            = 'all';
cfg.parameter         = 'wplispctrm';

Thanks again for the answer in advance!

Best,
Zsolt

ps.I can provide other parts of my code but I don't want to make this mail
too long :



2015-05-13 19:14 GMT+02:00 Tzvetan Popov <tzvetan.popov at uni-konstanz.de>:

> Hi Zsolt,
>
>
> Dear all,
>
>
> I would like to perform a cluster-based permutation test on weighted phase
> lag index values by using a within-subjects experimental design. I have two
> conditions (congruent and incongruent one) and my goal is to compute WPLI
> between certain channel combinations (FCz and F3 for instance) and see the
> WPLI change let’s say in 3-9 Hz and -100 to 500 ms between the two
> conditions.
>
>
> I experienced some difficulties after the point when I calculated the
> WPLI data for each participant. To perform the above-mentioned comparison,
> shall I use ‘ft_freqstatistics’for the cluster-based permutation test?
>
> You could. Stick with the tutorial you are currently working with. You
> should organize your data into cell arrays and call ft_freqstatistics like
> this: stat = ft_freqstatistics(cfg, congruent{:}, incongruent{:}).
> Furthermore you should specify cfg.parameter = ‘wplispctrm’ otherwise
> ft_freqstatistics will default to ‘powspctrm’ which will be not present in
> the data.
> good luck
> tzvetan
>
>
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> fieldtrip at donders.ru.nl
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>



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Ph.D.
Department of Clinical Neurophysiology
Georg-August University, Göttingen
Robert-Koch-Str. 40
37075 Goettingen
Web: http://www.uni-goettingen.de/en/222525.html
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