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path='<myMEGdatapath>' # where your MEG fiff-files are | datapath='<myMEGdatapath>' # root directory for your MEG data |
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--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 \ |
--inv ${datapath}/${subj_pre[m]}_0${subjects[m]}/${subj_dir[m]}/YourName_1L-MEG-loose0.2-inv.fif \ --meas ${datapath}/${subj_pre[m]}/${subj_dir[m]}/${conds[c]}.fif \ |
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, and read into Matlab using mne_read_stc_file.
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 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' \ '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 ${datapath}/${subj_pre[m]}_0${subjects[m]}/${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 ${outpath}/STC/${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>