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| 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. The results (*.stc-files) can be viewed in mne_analyze. | 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. |
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= 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 }}} You can create description files for every average you want to compute, and execute them in one script {{{ #!/bin/sh # mne_average_estimates --desc <descriptionfile1.txt> mne_average_estimates --desc <descriptionfile2.txt> mne_average_estimates --desc <descriptionfile3.txt> }}} |
Applying the Inverse Operator (mne_make_movie)
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.
The main ingredients are
* the inverse operator
* the MEG data (fiff-files)
* the average cortical surface (see below)
For more details and further options see the MNE manual.
#
## Your variables
path='<myMEGdatapath>' # where your MEG fiff-files are
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' \
'Subject1' \
'Subject1' \
)
# 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 ${path}/${subj_pre[m]}_0${subjects[m]}/${subj_dir[m]}/YourName_1L-MEG-loose0.2-inv.fif \
--meas ${path}/${subj_pre[m]}/${subj_dir[m]}/${conds[c]}.fif \
--morph average \
--smooth 5 \
--bmin -100 \
--bmax 0 \
--stc ${outpath}/STC/${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
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>
