cfg = []; cfg.layout = 'easycap32ch-avg.lay'; cfg.channel = {'EEG'}; cfg.latency = [0 2.5]; cfg.method = 'montecarlo'; cfg.statistic = 'depsamplesT'; cfg.correctm = 'cluster'; cfg.clusteralpha = 0.05; cfg.clusterstatistic = 'maxsum'; cfg.minnbchan = 2; cfg.tail = 0; cfg.clustertail = 0; cfg.alpha = 0.025; cfg.numrandomization = 100; subj = 4; design = zeros(2,2*subj); for i = 1:subj design(1,i) = i; end for i = 1:subj design(1,subj+i) = i; end design(2,1:subj) = 1; design(2,subj+1:2*subj) = 2; cfg.design = design; cfg.uvar = 1; cfg.ivar = 2; [stat] = timelockstatistics(cfg, da_test1, da_test2) GA_VALvsINV = da_test1; GA_VALvsINV.avg = da_test1.avg - da_test2.avg; figure; timestep = 0.10; %(in seconds) sampling_rate = da_test1.fsample; sample_count = length(stat.time); j = [0:timestep:2.5]; % Temporal endpoints (in seconds) of the ERP average computed in each subplot m = [1:timestep*sampling_rate:sample_count]; % temporal endpoints in MEEG samples pos_cluster_pvals = [stat.posclusters(:).prob]; pos_signif_clust = find(pos_cluster_pvals < stat.cfg.alpha); pos = ismember(stat.posclusterslabelmat, pos_signif_clust); for k = 1:25; subplot(5,5,k); cfg = []; cfg.xlim=[j(k) j(k+1)]; cfg.zlim = 'maxmin' pos_int = all(pos(:, m(k):m(k+1)), 2); cfg.highlight = 'on'; cfg.highlightchannel = find(pos_int); cfg.comment = 'xlim'; cfg.commentpos = 'title'; cfg.layout = 'easycap32ch-avg.lay'; topoplotER(cfg, GA_VALvsINV); end ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip.