[Mne_analysis] Localizing spontaneous activity: Best method / pipeline
alexandre.gramfort at telecom-paristech.fr
Thu Nov 3 09:40:46 EDT 2016
I will not comment on what's best but you can use all linear inverse solvers
(beamformers, MNE/dSPM/sLORETA) on epochs or even raw data.
Have a look at
On Wed, Nov 2, 2016 at 11:48 PM, Leonardo Barbosa <lsbarbosa at gmail.com>
> Dear MNE users!
> I've been trying to localize spontaneous activity for a week now, and
> couldn't find much about this topic in the MNE list archives:
> I think my main question for the moment would be: which method / pipeline
> would be the most appropriate?
> Looking into the literature, it seems like DICS is most used, probably
> because normally you are interested in some form of oscillatory component,
> and DICS uses the cross-spectral density matrix
> Interestingly, tf_dics seems to be the only source localization / inverse
> calculation that accept Epochs as parameter (although it calculates the csd
> for each epoch, averages afterwards and return one source localization for
> the average)
> All the other methods expect Evoked data
> So a more specific question would be:* How can I source localize each
> epoch using for instance mne.inver_sparse, perform a PSD/TF tranformation
> *source space for each epoch, and then average the results? **Is there
> some example in this sense?*
> There is an interesting post by Matti Hamalainen about that
> And taking into consideration the other posts and all the technical
> aspects, I would prefer to apply the TF in source space and avoid
> introducing temporal correlations in the signal if possible.
> Thank you in advance for any help!
> Leonardo S. Barbosa, PhD
> Postdoctoral Research Scientist
> University of Wisconsin, Madison
> Center for Sleep and Consciousness Studies
> Mne_analysis mailing list
> Mne_analysis at nmr.mgh.harvard.edu
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