LCMV analysis in MNE-python and in Fieldtrip

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Dear MNE-python experts,

We try to localize induced visual gamma activity using LCMV beamformers by first localizing single epochs and then doing multitaper analysis on ?virtual sensors?.
To do this we filter our raw data ( 25 -115 Hz), compute noise covariance matrix [-1 - 0] and data covariance matrix [0 - 1.2] (method=?shrinkage?, rank=None) on epochs, apply ?make_lcmv? function (reg=0.05, pick_ori=?max-power?, weight_norm=?nai?, rank=None) and then ?apply_lcmv_epochs? function with parameter max_ori_out=?signed?. Next we compute power spectral density with multitaper method (psd_array_multitaper: bandwidth=5) and average the result over epochs.
The result looks reasonable: there is a clear increase in gamma amplitude during stimulation relative to the prestimulus baseline. However, the amplitude of this gamma increase is approximately 2 times lower than that obtained using the similar analysis in Fieldtrip/LCMV.
We tried different approaches to calculation of the noise covariance matrix in the MNE-python, but it does not make much difference. Actually, in the Fieldtrip the noise covariance is not used at all. They use the ?lambda? parameter (e.g. 5%). Could it be the main reason for the differences in the results?
We still would like to use MNE-python for the LCMV analysis. What do you think could help us to increase the signal amplitude?

Best,
Viktoria
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You could try not passing any noise covariance (noise_cov=None), just
supplying the data covariance. This might be closer to what fieldtrip does.

If it does not work, it might be worth opening an MNE issue and sharing
your covariances, info, and forward so that we can compute the filters and
check against fieldtrip.

Eric

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Hi Viktoria,

as Eric already mentioned, you can omit the noise covariance matrix (it is
only needed if you have different channels types in your input).
Fieldtrip's lambda parameter corresponds to the reg parameter in MNE-Python.
Did you use the NAI in FieldTrip as well (cfg.lcmv.weightnorm = 'nai') ?

HTH,
Britta