[FieldTrip] One-sample monte-carlo permutation statistics in Fieldtrip?

[Lars Costers]

Hi all,

I was wondering whether there are any one-sample permutation statistics to test for a difference from zero implemented in Fieldtrip, ideally to work with monte-carlo permutations? Didn’t find any standard of 'statfun’ options in the documentation.

My goal is to do maxstat correction on ERF MEG data over voxel space.
cfg.latency = [-0.2 0.8];
cfg.parameter = 'avg';
cfg.method = 'montecarlo';
cfg.numrandomization = 2000;
cfg.correctm = 'max'; % MaxStat correction
cfg.design    = ones(1,nsub);
cfg.ivar = 1;  % independent variable
cfg.statistic = ???;
[stat] = ft_timelockstatistics (cfg, timelock{:,1});

 I read the discussions about one-sample cluster-based permutation tests (e.g. https://mailman.science.ru.nl/pipermail/fieldtrip/2018-August/012314.html <https://mailman.science.ru.nl/pipermail/fieldtrip/2018-August/012314.html>). However, for me it's not possible to permute the baseline and post stimulus condition because I have expectation reactions in the baseline. 
Anybody could suggest me how I could validly test whether my ERF is signficantly different from zero at every time-frame and electrode?  

Thanks, 

Lars
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https://doi.org/10.1371/journal.pcbi.1002202