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Dear Johannes,
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<div class="">Could you explain a bit more what you attempt to do? Specifically: what is the parcellation that you are using? Ideally, you should use one that is defined on exactly the same surface as your data. Otherwise (e.g. when using a parcellation defined
in 3D space) some on-the-fly interpolation is required, and this may not work robustly enough. One possible cause is the fact that some parcels in the input parcellation will not get assigned any of the locations at which your functional data is represented.
Which is probably the cause of the error you are facing.</div>
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<div class="">Best wishes,</div>
<div class="">Jan-Mathijs</div>
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<div class="">PS: as a side note, in general I would recommend to compute connectivity in parcellated space, rather than in ‘dipole space’. Apart from potential memory issues, the sheer number of pairwise combination makes the interpretation / statistical evaluation
quite complicated.<br class="">
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<div class="">On 7 Oct 2021, at 09:08, Johannes Gehrig via fieldtrip <<a href="mailto:fieldtrip@science.ru.nl" class="">fieldtrip@science.ru.nl</a>> wrote:</div>
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Dear Stefan,</div>
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thanks for your reply. At the moment I use simple "coherence" following the „whole brain connectivity“ tutorial. However, if there was a memory efficient solution for dwPLI that is also an option. If I followed the discussion correctly, this is not yet fully
implemented?</div>
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<o:p class=""> </o:p></div>
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Have you tried to parcellate your data before doing the connectivity analysis? I suspect that my problem could be related with ft_sourceinterpollate, because the output of the source analysis (avg.csd, avg.mom, avg.noisecsd, computed withels pcc) is no longer
present after ft_sourceinterpolate and without the source interpolation the source parcellation doesn't work, so far my impression...</div>
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<o:p class=""> </o:p></div>
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Thanks and best regards,</div>
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Johannes<span lang="EN-GB" class=""><o:p class=""></o:p></span></div>
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<o:p class=""> </o:p></div>
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<b class="">Von:<span class="Apple-converted-space"> </span></b><a href="mailto:stefan.dvoretskii@tum.de" style="color: blue; text-decoration: underline;" class="">Stefan Dvoretskii</a><br class="">
<b class="">Gesendet:<span class="Apple-converted-space"> </span></b>Mittwoch, 6. Oktober 2021 17:39<br class="">
<b class="">An:<span class="Apple-converted-space"> </span></b><a href="mailto:fieldtrip@science.ru.nl" style="color: blue; text-decoration: underline;" class="">FieldTrip discussion list</a><br class="">
<b class="">Cc:<span class="Apple-converted-space"> </span></b><a href="mailto:jgehrig@med.uni-frankfurt.de" style="color: blue; text-decoration: underline;" class="">Johannes Gehrig</a>;<span class="Apple-converted-space"> </span><a href="mailto:cristina.gil@tum.de" style="color: blue; text-decoration: underline;" class="">Gil
Avila, Cristina</a><br class="">
<b class="">Betreff:<span class="Apple-converted-space"> </span></b>Re: [FieldTrip] problem using ft_sourceparcellate</div>
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Dear Johannes, </div>
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which connectivity measure are you using? There is a potential bottleneck in the 'ft_connectivityanalysis', which can however be circumvented with custom code, at least for dwPLI. Then you won't even need to parcelate.</div>
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We are currently working to incorporate it into the Fieldtrip code.</div>
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Best regards,</div>
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Stefan</div>
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пн, 4 окт. 2021 г., 11:06 Johannes Gehrig via fieldtrip <<a href="mailto:fieldtrip@science.ru.nl" style="color: blue; text-decoration: underline;" class="">fieldtrip@science.ru.nl</a>>:</div>
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<p class="">Dear Fieldtrip-user,</p>
<p class="">I am facing a problem using ft_sourceinterpolate. I am following the "Whole brain connectivity and network analysis"- Tutorial and as I can not compute the connectivity directly with the source data ("out of memory") I would like to perform the
source parcellation before computing the connectivity. Unfortunately (fieldtrip 20211001 and matlab2018b) ft_sourceparcellate crashes after calling it. Before computing the source data the sourcemodel was interpolated with the atlas using ft_sourceinterpolate.
Therefore the amount of positions in the atlas and the source data is the same (8004).</p>
<p class="">load('atlas_MMP1.0_4k.mat');<span class="Apple-converted-space"> </span><br class="">
cfg = [];<br class="">
cfg.parcellation = 'parcellation';<br class="">
cfg.method = 'mean';<br class="">
cfg.parameter = 'all';<span class="Apple-converted-space"> </span><br class="">
parc_sourceOn = ft_sourceparcellate(cfg, source_ON, atlas);</p>
<p class="">Error message:"<br class="">
there are in total 8004 positions, 4544 positions are inside the brain, 8004 positions have a label<br class="">
4544 of the positions inside the brain have a label<br class="">
4544 of the labeled positions are inside the brain<br class="">
0 of the positions inside the brain do not have a label<br class="">
creating 362 parcels for parameter csd by taking the mean<br class="">
computing parcellation<br class="">
232 tmp(j,:,:) = cellmean1(dat(tissue==j));<br class="">
computing parcellation for L_V1_ROI<br class="">
Index exceeds array bounds.<br class="">
<br class="">
Error in ft_sourceparcellate>cellmean1 (line 494)<br class="">
y = x{1};<br class="">
<br class="">
Error in ft_sourceparcellate (line 232)<br class="">
tmp(j,:,:) = cellmean1(dat(tissue==j));</p>
<p class="">"</p>
<p class="">Any help and ideas are very much appreciated!</p>
<p class="">Best regards, Johannes</p>
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