<div dir="ltr">Hi J.M.,<div><br></div><div>Thanks so much for your reply. The tip to not trust the topographic maps too much helped in my sleuthing. I realized that adjusting the minnbchan parameter actually <i>does</i> result in the topographic changes I thought I should see if I was understanding the algorithm correctly (and that I just wasn't seeing these changes in the map that I was using as a quick-check, but that they were present in the stats themselves).</div><div><br></div><div>Problem solved! Thank you!</div><div>Alea</div><div><br></div><div><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Oct 18, 2017 at 11:19 PM, Schoffelen, J.M. (Jan Mathijs) <span dir="ltr"><<a href="mailto:jan.schoffelen@donders.ru.nl" target="_blank">jan.schoffelen@donders.ru.nl</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
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Hi Alea,
<div><br>
</div>
<div>I think that it all looks OK. I guess that the P5-PO1-O1 cluster is spatially disjoint from the bulk of the suprathreshold data points. Don’t be mislead by the topographical image, where both the contour lines, and the 2D placement of the electrodes
might reflect a picture that is different from what you would expect.</div>
<div><br>
</div>
<div>Note, that providing cirange as extra information is not the most informative. Better would have been to show posclusterslabelmat. This data field provides for each sample, whether and to which ‘cluster’ it belongs.</div>
<div><br>
</div>
<div>Best wishes,</div>
<div>Jan-Mathijs</div>
<div><br>
</div>
<div><br>
</div>
<div>
<div style="word-wrap:break-word">
J.M.Schoffelen, MD PhD<br>
Senior Researcher, VIDI-fellow - PI, language in interaction<br>
Telephone: <a href="tel:+31%2024%20361%204793" value="+31243614793" target="_blank">+31-24-3614793</a></div>
<div style="word-wrap:break-word">
Physical location: room 00.028</div>
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Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands<br>
<br>
</div>
</div>
<div> <br>
<div>
<blockquote type="cite"><div><div class="h5">
<div>On 18 Oct 2017, at 23:05, Alea Skwara <<a href="mailto:acskwara@ucdavis.edu" target="_blank">acskwara@ucdavis.edu</a>> wrote:</div>
<br class="m_-2719057107531985243Apple-interchange-newline">
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<div dir="ltr"><div><div class="h5">Hi All,
<div><br>
</div>
<div>I have been conducting a permutation based cluster analysis using the method = 'montecarlo' correctm= 'cluster' options in ft_freqstatistics to examine longitudinal changes in spectral power. Everything runs just fine and it identifies clusters
successfully.</div>
<div><br>
</div>
<div>However, when I examine the results of the analysis, some of the stats strike me as strange. Electrodes that have the highest F values (I am comparing across 3 timepoints) do not test as significant, while electrodes with lower F values do. At
first I thought this was because I had a single "hot" electrode that was not part of a larger cluster, but looking more closely at the stats, it appears that this is not the case.</div>
<div><br>
</div>
<div>I have tried double-checking my neighbor definition method and electrode locations to assure that it is not an issue with neighbors being incorrectly registered. I have also tried adjusting the minimum cluster size using the minnbchan option to
ensure it was not an issue of a cluster not reaching the minimum extent. Neither of these options seem to have any impact on the result.</div>
<div><br>
</div>
<div>At this point I'm at a loss. Is there something I'm misunderstanding about the algorithm?</div>
<div><br>
</div>
<div>Code below and plot below, channel-by-channel stats attached.</div>
<div><br>
</div>
<div>Thanks!</div>
</div></div><div><div><div class="h5">Alea<br clear="all">
<div><br>
</div>
<div>One funky thing to note about this code is that I am inputting average values into the analysis (averaged across time as participants have slightly differing lengths of data, and within bands as I am running this analysis on IAF-based bands, thus
"7" is a dummy code for "mean beta band power", not 7 Hz)</div>
<div><br>
</div>
<div><br>
</div>
<div>
<div>%% THREE CONDITIONS</div>
<div> %Set up the analysis cfg for 3 conditions (pre- to mid- to post-)</div>
<div>cfg = []; </div>
<div>cfg.channel = {'all'};</div>
<div>cfg.latency = 'all'; </div>
<div>cfg.frequency = [7 7]; %frequency band indicator</div>
<div>cfg.avgoverfreq = 'no'; %working on bands not frequencies, so nothing to average</div>
<div>cfg.method = 'montecarlo'; </div>
<div>cfg.statistic = 'depsamplesFmultivariate'; %three time points</div>
<div>cfg.correctm = 'cluster'; </div>
<div>cfg.clusteralpha = 0.1; %change to .1 because we're computing over averaged bands and time (losing power)</div>
<div>cfg.clusterstatistic = 'maxsum'; </div>
<div>cfg.minnbchan = 2; </div>
<div>cfg.tail = 1; %this has to be 1 for depsamplesF, 0 otherwise</div>
<div>cfg.clustertail = 1; %this has to be 1 for depsamplesF, 0 otherwise</div>
<div>cfg.alpha = 0.05; %this has to be 0.05 for depsamplesF, 0.025 otherwise</div>
<div>cfg.numrandomization = 10000; %to get a min p-value of 0.0001 to account for 500 tests and correction by Bonferroni method.</div>
<div>%specify which electrodes can form clusters</div>
<div>cfg_neighb.method = 'distance';</div>
<div>cfg.neighbours = ft_prepare_neighbours(cfg_<wbr>neighb, r1t1r_struct);</div>
<div>%cfg.neighbours = cfgManish.neighbours;</div>
<div>%cfg = getNeighbours(cfg); % using fixed neighbours</div>
<div>cfg.layout = layout';</div>
<div> </div>
<div><br>
</div>
<div>% Set up the design matrixfor 3 conditions</div>
<div>subj = 27; %will differ based on condition</div>
<div><br>
</div>
<div>design = zeros(2,3*subj);</div>
<div>for isub = 1:1:subj</div>
<div> design(1,isub) = isub;</div>
<div> design(1,subj+isub) = isub;</div>
<div> design(1,2*subj+isub) = isub;</div>
<div>end</div>
<div>design(2,1:subj) = 1;</div>
<div>design(2,subj+1:2*subj) = 2;</div>
<div>design(2,2*subj+1:3*subj) = 3;</div>
<div><br>
</div>
<div>cfg.design = design;</div>
<div>cfg.uvar = 1;</div>
<div>cfg.ivar = 2;</div>
<div><br>
</div>
<div><br>
</div>
<div>% Run the analysis</div>
<div>[r1r_stat_beta] = ft_freqstatistics(cfg, r1t1r_struct, r1t2r_struct, r1t3r_struct); </div>
</div>
<div><br>
</div>
<div><br>
</div>
<div>
<div>%Plot the results</div>
<div>cfg1 = [];</div>
<div>cfg1.alpha = 0.1;</div>
<div>cfg1.parameter = 'stat';</div>
<div>%cfg1.zlim = [0 18.1];</div>
<div>cfg1.layout = layout';</div>
<div>cfg1.marker = 'o';</div>
<div>cfg1.subplotsize = [1 1];</div>
<div>cfg1.saveaspng = 'r1r_betacluster';</div>
<div><br>
</div>
<div>ft_clusterplot(cfg1, r1r_stat_beta);</div>
</div>
<div><br>
</div>
<div><br>
</div>
<div>***Note non-significant hot spot over left parietal*** </div>
<div><br>
</div>
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<div dir="ltr"><span style="font-size:12.8px"><font color="#0b5394"><span id="m_-2719057107531985243cid:ii_15f31436d6cb6214"><r1r_betacluster_fig1.png></span><br>
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<div dir="ltr"><span style="font-size:12.8px"><font color="#0b5394">Alea C. Skwara</font></span>
<div>
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