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<DIV>Hi Gio, Jan-Mathijs and Jörn,</DIV>
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<DIV>thank you all for your helpful replies. Gio, a special 'thank you' for your very detailled response. These are very interesting points, though somewhat beyond of what I try to do. I will be working through the suggested literature and the new tutorial and might come back later if there are further questions. <BR>Best regard,</DIV>
<DIV>Gregor</DIV>
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<DIV>-- <BR>Dr. rer. nat. Gregor Volberg <<A href="mailto:gregor.volberg@psychologie.uni-regensburg.de">gregor.volberg@psychologie.uni-regensburg.de</A>> ( <A href="mailto:gregor.volberg@psychologie.uni-regensburg.de">mailto:gregor.volberg@psychologie.uni-regensburg.de</A> )<BR>University of Regensburg<BR>Institute for Experimental Psychology<BR>93040 Regensburg, Germany<BR>Tel: +49 941 943 3862 <BR>Fax: +49 941 943 3233<BR><A href="http://www.psychologie.uni-regensburg.de/Greenlee/team/volberg/volberg.html">http://www.psychologie.uni-regensburg.de/Greenlee/team/volberg/volberg.html</A><BR>>>> Gio Piantoni <gio@gpiantoni.com> 05.03.2013 09:20 >>><BR>Hi Gregor,<BR><BR>I also like the surface approach a lot, but things get really<BR>complicated when you have to average across subjects. I don't know if<BR>you are familiar with statistics in freesurfer, but what they do is to<BR>convert the source points of the single subject to a subject-specific<BR>sphere. Then the sphere is averaged across subjects. The<BR>coregistration between these spheres takes advantage of landmarks.<BR><BR>See my attempt at:<BR><A href="http://mailman.science.ru.nl/pipermail/fieldtrip/2012-September/005585.html">http://mailman.science.ru.nl/pipermail/fieldtrip/2012-September/005585.html</A><BR>If I understand you correctly, you are at step 3). You can use smudge<BR>to get to the high-resolution smoothwm (or pial). Then the number of<BR>vertices in smoothwm corresponds to the number of vertices in the<BR>sphere.<BR><BR>Here you have two options: use fieldtrip code or MNE code. I tried<BR>using fieldtrip code, but where I got stuck was to do statistics on<BR>the averaged sphere (taken from fsaverage). I used this code:<BR><A href="https://github.com/gpiantoni/eventbased/blob/77c3f85ef94baf9d4ab629d48a31e8046c924518/powsource_grand.m#L136-L158">https://github.com/gpiantoni/eventbased/blob/77c3f85ef94baf9d4ab629d48a31e8046c924518/powsource_grand.m#L136-L158</A><BR>where data{i1,i2,p,h} is already projected onto the subject-specific sphere.<BR>However, after projecting to the averaged sphere, you need to do<BR>statistics on a 2-d cortical sheet and, from my understanding, the<BR>subfunctions to create clusters do not work all that well. I think<BR>it'd be very powerful to do statistics on a 2d sheet. See<BR><A href="http://mailman.science.ru.nl/pipermail/fieldtrip/2012-January/004749.html">http://mailman.science.ru.nl/pipermail/fieldtrip/2012-January/004749.html</A><BR>and <A href="http://mailman.science.ru.nl/pipermail/fieldtrip/2012-February/004766.html">http://mailman.science.ru.nl/pipermail/fieldtrip/2012-February/004766.html</A><BR>for discussion. I did not get far because the clustering methods<BR>needed updated to work on cortical sheets in an efficient manner.<BR><BR>Another route you can try is to use the MNE/freesurfer software to do<BR>that. See for example: <A href="http://martinos.org/mne/manual/morph.html">http://martinos.org/mne/manual/morph.html</A> You'd<BR>just write the surface to disk and use MNE/freesurfer. I personally<BR>don't like the method to correct for multiple comparisons in<BR>freesurfer (which I think might give false positive) and I think that<BR>the fieldtrip stats is better, but I had some problems getting to work<BR>on 2-d cortical sheets.<BR><BR>For the moment, I decided to go with the volume-based approach,<BR>although I have the feeling that it's less accurate and less<BR>sensitive. See also: Tucholka, A., Fritsch, V., Poline, J.-B., and<BR>Thirion, B. (2012). An empirical comparison of surface-based and<BR>volume-based group studies in neuroimaging. Neuroimage 63, 1443–1453.<BR><BR>Maybe I confused you more than helped, but if you manage to do<BR>statistics on surfaces, please let me know because I'd be interested<BR>in using it.<BR><BR>Hope this helps.<BR><BR>Gio<BR><BR>--<BR>Giovanni Piantoni, MSc<BR>Dept. Sleep & Cognition<BR>Netherlands Institute for Neuroscience<BR>Meibergdreef 47<BR>1105 BA Amsterdam (NL)<BR><BR>+31 20 5665492<BR>gio@gpiantoni.com<BR>www.gpiantoni.com<BR><BR>On Mon, Mar 4, 2013 at 6:45 PM, Gregor Volberg<BR><Gregor.Volberg@psychologie.uni-regensburg.de> wrote:<BR>> Dear Fieldtrippers,<BR>><BR>> I need to ask for a helpful hint on MNE source reconstructions. Following<BR>> this tutorial <A href="http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate">http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate</A> I<BR>> obtained nice individual cortical meshes and source points; the MNE forward<BR>> and inverse solution for the individuals all work well. I would now like to<BR>> normalize the individual grids to a template brain in order to do statistics<BR>> and averaging for plotting. I figured out that I could use<BR>> ft_sourceinterpolate to tranform the grid into a volumetric representation,<BR>> and then use ft_volumenormalise to normalise to a standard brain. But this<BR>> did not work too well for source structures containing time series (like<BR>> 'mne'-stcutures) where the computational load gets very high. I also tried<BR>> to use a grid of one subject as a template for the other subject's grids<BR>> with ft_sourceinterpolate and cfg.interpmethod = 'smudge', but this seems to<BR>> require two grids with the same number of source points as input(?).<BR>> Is there a way to do a normalisation directly on brain triangulations /<BR>> source grids ? Thanks for any help!<BR>> Best regards,<BR>> Gregor<BR>><BR>> --<BR>> Dr. rer. nat. Gregor Volberg <gregor.volberg@psychologie.uni-regensburg.de><BR>> ( mailto:gregor.volberg@psychologie.uni-regensburg.de )<BR>> University of Regensburg<BR>> Institute for Experimental Psychology<BR>> 93040 Regensburg, Germany<BR>> Tel: +49 941 943 3862<BR>> Fax: +49 941 943 3233<BR>> <A href="http://www.psychologie.uni-regensburg.de/Greenlee/team/volberg/volberg.html">http://www.psychologie.uni-regensburg.de/Greenlee/team/volberg/volberg.html</A><BR>><BR>> _______________________________________________<BR>> fieldtrip mailing list<BR>> fieldtrip@donders.ru.nl<BR>> <A href="http://mailman.science.ru.nl/mailman/listinfo/fieldtrip">http://mailman.science.ru.nl/mailman/listinfo/fieldtrip</A><BR></DIV></BODY></HTML>