[FieldTrip] source reconstruction on emfs

Robert Oostenveld r.oostenveld at donders.ru.nl
Tue Aug 21 21:56:20 CEST 2012


Dear Nuria

For the earliest components from S1, and just to get started and get a feel for your data, a traditional dipole fit using FT_DIPOLEFITTING should work fine. Following the initial localization of S1, you indeed could continue with an LCMV beamformer. There is an example at http://fieldtrip.fcdonders.nl/example/fit_a_dipole_to_the_tactile_erf_after_mechanical_stimulation

The example is on CTF data with Braille-cell stimulation (i.e. mechanical instead of electrical),. Since the example data is available from the ftp you can try the example out before translating it to your own data. Furthermore I should note that the example is rather old and probably has not been run for quite some time, so there might be some pieces of the example script on the wiki that need updating to reflect the current state of the fieldtrip code. I suggest you also have a look here http://fieldtrip.fcdonders.nl/tutorial/headmodel_meg, which is a new tutorial that Lilla Magyari (CC) made available last week.

best regards
Robert


 

On 21 Aug 2012, at 12:50, Nuria DoƱamayor Alonso wrote:

> Dear fieldtrippers,
> I am currently analyzing a study, measured with a Neuromag 306 system, in which we stimulated the median nerve. I had never done source reconstruction with fieldtrip, so I followed the tutorial using MNE for EMF source analysis (which worked fine), only to find out that I could neither average individual sources nor perform stats, which is exactly what I need to do... 
> So the question is: What would you guys recommend? Should I just try using the LCMV beamfomer? However, that might not be the best solution according to this thread http://mailman.science.ru.nl/pipermail/fieldtrip/2011-September/004321.html... Is there any way I could efficiently export my preprocessed/averaged data to some other software (MNE/SPM/Brainstorm...) and compute my source reconstruction and stats there? What do you guys usually do?
> Thanks a lot for your help,
> Nuria
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