[FieldTrip] EEG Source Reconstruction using mne

[Juan Pablo Neira]

Hello,

I have been working with fieldtrip the last two weeks to do source
reconstruction using Minimun Norm Estimation (mne).  Now I am
analyzing real data (EEG) with individual MRI, it seems I am not
having the right solution.   So maybe someone can help me with the
next questions:

1.  How do I define the source space?  I would like to have my sources
in the whole brain or only in gray matter. When I calculated the
source reconstruction (mne method) I had sources outside of the brain.

2.  What are the possibilities to calculate or estimate the
regularization parameter lambda in the Minimum Norm Estimation  (mne)
Method?
    Reading in some mne tutorials, they calculate the noise covariance
matrix of the data using ft_timelockanalysis function, and then the
ft_sourceanalysis uses this matrix to calculate labda for the mne
method.  Are there other possibilities?

3.  We want to implement Fieldtrip to do the Preprocessing, forward
and inverse (mne) calculations.  But we have not found exact or close
information of the complete task.  These are the steps we are
performing:

-  Read the EEG signals
-  Reject undesired channels
-  Referencing
-  Time domain analysis (ft_timelockanalysis)

- Read, realign and segment individual MRI
- Volume creation:  we create the scalp, skull and brain meshes and
then use ft_headmodel_bem_openmeeg
- EEG sensor positions alignment with the scalp mesh of the volume.
- Calculate the leadfield matrix

- Finally the Source Analysis (method mne)

Are we missing an important step?

Best regards,

Juan Pablo Neira Vesga
University - Clinic Kiel, Germany