Computing the Noise Covariance Matrix

The noise covariance matrix is needed for the computation of the inverse operator.

Ingredients for this script are

* raw MEG data files (which are used for averaging, after maxfilter)

* a description file ([#covdescription see below])

The end result is a fiff-file containing the noise covariance matrix, which can be read into Matlab using mne_read_noise_cov.

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='<myrawMEGdatapath>'    # root directory for your MEG data

# 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`


for m in `seq 0 ${lastsubj}`
do
  echo " "
  echo " Computing covariance matrix for SUBJECT  ${subjects[m]}"
  echo " "

  mne_process_raw  \
                --raw ${datapath}/${subj_pre[m]}/${subj_dir[m]}/rawMEGfile_raw1.fif \
                --raw ${datapath}/${subj_pre[m]}/${subj_dir[m]}/rawMEGfile_raw2.fif \
                --raw ${datapath}/${subj_pre[m]}/${subj_dir[m]}/rawMEGfile_raw3.fif \
                --eventsout ${datapath}/${subj_pre[m]}/${subj_dir[m]}/rawMEGfile_raw1-eve.txt \
                --eventsout ${datapath}/${subj_pre[m]}/${subj_dir[m]}/rawMEGfile_raw2-eve.txt \
                --eventsout ${datapath}/${subj_pre[m]}/${subj_dir[m]}/rawMEGfile_raw3-eve.txt \         
                --projoff \
                --cov cov_desc1.cov \
                --cov cov_desc2.cov \
                --cov cov_desc3.cov \
                --savecovtag -cov \
                --gcov ${datapath}/${subj_pre[m]}/${subj_dir[m]}/covmat-cov.fif


done # subjects

Anchor(covdescription) where the covariance description files cov_desc?.cov are of the form

cov {
        gradReject      2000e-13
        magReject       3e-12
        eegReject       120e-6
        eogReject       150e-6
        logfile         YourLogFileName.txt

        def {
                event   1
                tmin    -0.2
                tmax    0
                basemin -0.2
                basemax 0.0
        }

        def {
                event   2
                tmin    -0.2
                tmax    0
                basemin -0.2
                basemax 0.0
        }


        def {
                event   3
                tmin    -0.2
                tmax    0
                basemin -0.2
                basemax 0.0
        }
        
}

If the parameters are the same for all input files, you only have to specify one description file. For more details and options see the MNE manual.