[Mne_analysis] LCMV with common spatial filter?

[Alexandre Gramfort]

        External Email - Use Caution        

hi Elena,

make_lcmv compute the filters and apply_lcmv allow you to apply them
to any condition. it's the recommended way when you compare conditions.

are you observing different results on the same data between Fieldtrip and MNE?

we have just published
https://www.sciencedirect.com/science/article/pii/S1053811920302846

Amit Jaiswal, Jukka Nenonen, Matti Stenroos, Alexandre Gramfort,
Sarang S. Dalal, Britta U. Westner, Vladimir Litvak, John C. Mosher,
Jan-Mathijs Schoffelen, Caroline Witton, Robert Oostenveld, Lauri
Parkkonen,
Comparison of beamformer implementations for MEG source localization,
NeuroImage, Volume 216, 2020,

and our results show very similar results between packages.

HTH

Alex


On Wed, May 20, 2020 at 12:43 PM Elena Orekhova
<orekhova.elena.v at gmail.com> wrote:
>
>         External Email - Use Caution
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> Dear MNE experts,
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> We use LCMV for localization of visual gamma oscillations in several experimental conditions. We expect that the power will differ between conditions, but that in all these conditions the source will be approximately in the same area. Therefore, we would like to use a common spatial filter for all conditions.
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> We calculated noise_cov and data_cov on the full data and then applied the resulting common filter to separate conditions, as described in  ‘examples’: https://mne.tools/0.15/auto_examples/inverse/plot_lcmv_beamformer_volume.html
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> This approach visibly reduced signal power in comparison with using specific filters for each condition.
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> We have earlier used the common spatial filter with LCMV beamformers in Fieldtrip and it worked well. However, I guess there is different approach to assessment of covariance in the Fieldtrip.
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> What approach to calculation of the LCMV spatial filter would you recommend  us to use in the MNE?
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> Best,
>
> Elena
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> --
> Best regards,
> Elena V. Orekhova
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