Compute the Source Estimates (mne_make_movie)

Applying the Inverse Operator

This script applies the inverse operator to MEG data and outputs the current estimates. The current estimates are morphed to the average brain (see below), for grand-averaging (see further below). The results (*.stc-files) can be viewed in mne_analyze, and read into Matlab using mne_read_stc_file. You can get infos on your stc-files (e.g. maximum value, relevant for scaling your display) using mne_process_stc.

The main ingredients are

* the inverse operator

* the MEG data (fiff-files)

* the average cortical surface (see below)

The parameters below are reasonable choices for standard analyses. However, these Wiki pages are not supposed to substitute the [http://www.nmr.mgh.harvard.edu/meg/manuals/MNE-manual-2.6.pdf MNE manual], [http://imaging.mrc-cbu.cam.ac.uk/meg/MEGpapers reading papers], and [http://imaging.mrc-cbu.cam.ac.uk/imaging/ImagersInterestGroup discussions] with more experienced researchers.

#

## Your variables

datapath='<myMEGdatapath>'    # root directory for your MEG data

MRIpath='/myMRIdirectory/'    # where your MRI subdirectories are

outpath='/myoutpath'  # path for output files

#condition names as used in file names to which inverse operator shall be applied
conds=('cond1' 'cond2' 'cond3')


# subjects names used for MRI data
subjects=(\
        'Subject1' \
        'Subject2' \
        'Subject3' \
)

# MEG IDs (your directory structure may differ)
subj_pre=(\
        'meg10_0001' \
        'meg10_0002' \
        'meg10_0003' \
        )

# MEG subdirectories (your directory structure may differ)      
subj_dir=(\
         '100001' \
         '100002' \
         '100003' \
        )

## Processing:

nsubjects=${#subjects[*]}
lastsubj=`expr $nsubjects - 1`

nconds=${#conds[*]}
lastcond=`expr $nconds - 1`


for m in `seq 0 ${lastsubj}`
do
  echo " "
  echo " Computing movies  for SUBJECT  ${subjects[m]}"
  echo " "
 
        for c in `seq 0 ${lastcond}`
        do
        
                # Current Estimates
                mne_make_movie \
                --subject {subjects[m]} \
                --inv ${datapath}/${subj_pre[m]}/${subj_dir[m]}/YourName_1L-MEG-loose0.2-inv.fif \
                --meas ${datapath}/${subj_pre[m]}/${subj_dir[m]}/${conds[c]}.fif \
                --morph average \
                --smooth 5 \
                --bmin -100 \
                --bmax 0 \
                --stc ${outpath}/${subj_pre[m]}_${conds[c]}
                        
        done # conditions

done # subjects

Computing the Average Cortical Surface

#

make_average_subject --subjects   Subject1 Subject2 Subject3

Grand-averaging STC-files

For grand-averaging, STC-files should have been created using the --morph option in mne_make_movie (see above). You can then average them using the command

mne_average_estimates --desc <descriptionfile.txt>

where descriptionfile.txt is of the form

stc /yourpath/filetoaverage1.stc
stc /yourpath/filetoaverage2.stc
stc /yourpath/filetoaverage3.stc

deststc <youroutputfile>

You can create description files for every average you want to compute, and execute them in one script

#

mne_average_estimates --desc <descriptionfile1.txt>
mne_average_estimates --desc <descriptionfile2.txt>
mne_average_estimates --desc <descriptionfile3.txt>