[FieldTrip] Questions about coherence statistics on source level data

[Q Meng]

Dear list,

I'm running source analysis using DICS on my MEG data following the
cortical-muscular coherence tutorial and now would like to compare the
source level coherence value between 2 conditions in a between subject
design.

I found some older posts on this topic from the discuss list (
https://mailman.science.ru.nl/pipermail/fieldtrip/2011-September/004279.html)
(https://mailman.science.ru.nl/pipermail/fieldtrip/2016-March/010166.html).
Following the instructions, I Z-transformed the coherence manually and
specified cfg.statistic = 'ft_statfun_diff' and then did the cluster based
non-parametric permutation test. However, I got an error message says *"Error
using ft_statistics_montecarlo (line 242) could not determine the
parametric critical value for clustering"* right after the statistical
analysis started. Please see below a snippet of code:

...
Z- transform coherence manually and creating 0-coherence data
...

cfg                     = [];
cfg.method        = 'montecarlo';
% cfg.statistic           = 'ft_statfun_depsamplesT';
cfg.statistic        = 'ft_statfun_diff';
cfg.parameter    = 'coh';
cfg.correctm      = 'cluster';
cfg.numrandomization    = 1000;
cfg.alpha               = 0.05;
cfg.clusteralpha        = 0.05;
cfg.tail                = 0;
cfg.clustertail         = 0;
cfg.correcttail         = 'alpha';
cfg.connectivity        = VertConn;

nsubj                   = 19;
cfg.design(1,:)         = [1:nsubj 1:nsubj];
cfg.design(2,:)         = [ones(1,nsubj) ones(1,nsubj)*2];
cfg.uvar                = 1; % row of design matrix that contains unit
variable (in this case: subjects)
cfg.ivar                = 2; % row of design matrix that contains
independent variable (the conditions)


stat = ft_sourcestatistics(cfg,
data_meg_source_cohe_sentence_dics_parsing_B2_ICA{:},
data_meg_source_cohe_sentence_dics_parsing_B5_ICA{:});


Before this, I just used  cfg.statistic = 'ft_statfun_depsamplesT' to
compare the coherence value between two conditions and the program itself
worked well.

Does anyone have an idea where my problem could be or what I should do instead?3

Thanks for your help!

Best,

Qing
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