Averaging data in MNE
The following script is an example for a standard averaging procedure. Obviously, you may want to use different parameters - have a look at the manual for details and more options.
You should have processed your raw data using [http://imaging.mrc-cbu.cam.ac.uk/meg/Maxfilter Maxfilter].
Note that MNE will not process EEG data from the CBU correctly unless you apply "mne_check_eeg_locations" to your files ([#checkeeglocs see below]).
You can [#markbadchannels mark bad channels] in your fif-files using mne_mark_bad_channels. These bad channels will be excluded from further MNE operations (forward solution, inverse operator etc.).
The end result will be fiff-files with averages for each condition defined in the specification file (see below). They can be [#readwritesubtract read into Matlab] using fiff_read_evoked.
The following script requires a [#avgspecfile specification file] with averaging parameters (thresholds etc.).
## Your variables
datapath='<myMEGdatapath>' # 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=${#subj_pre[*]}
lastsubj=`expr $nsubjects - 1`
# REPORT number of files to be processed:
for m in `seq 0 ${lastsubj}`
do
echo " "
echo " Averaging SUBJECT ${subjects[m]}"
echo " "
inpath=${path}'/'${subj_dir[m]}'/'${subjects[m]}
echo ${inpath}
mne_process_raw \
--raw ${datapath}/${subj_pre[m]}/${subj_dir[m]}/yourrawMEGfile1.fif \
--raw ${datapath}/${subj_pre[m]}/${subj_dir[m]}/yourrawMEGfile2.fif \
--raw ${datapath}/${subj_pre[m]}/${subj_dir[m]}/yourrawMEGfile3.fif \
--eventsout ${datapath}/${subj_pre[m]}/${subj_dir[m]}/yourrawMEGfile1-eve.txt \
--eventsout ${datapath}/${subj_pre[m]}/${subj_dir[m]}/yourrawMEGfile2-eve.txt \
--eventsout ${datapath}/${subj_pre[m]}/${subj_dir[m]}/yourrawMEGfile3-eve.txt \
--ave YourSpecificationFile.ave \
--gave ${datapath}/${subj_pre[m]}/${subj_dir[m]}/gave.fif \
--saveavetag _avg \
--highpass 0.1 \
--projoff
done # subjectsNote: You can modify the event information in the eve.txt-files, and read the modified information later using the --events option. This is useful when you want to average with respect to trigger combinations (e.g. correct responses only) etc.
Anchor(avgspecfile) The specification file YourSpecificationFile.ave should be of the form:
average {
# Rejection values
#
gradReject 20e-15 # artefact rejection thresholds
magReject 3e-12
eegReject 120e-6
eogReject 150e-6
logfile ave_logfile.txt # log-file for some useful information
# Category specifications
#
category {
name "Cond1" # name of condition
event 1 # trigger/event code for condition
tmin -0.1 # duration of epochs with respect to trigger
tmax 1.0
bmin -0.1 # interval for baseline correction
bmax 0.0
}
category {
name "Cond2"
event 2
tmin -0.1
tmax 1.0
bmin -0.1
bmax 0.0
}
}Fixing EEG electrode positions
Unless you apply mne_check_eeg_locations to your data, MNE will get confused with the EEG electrode digitisation used at the CBU, and e.g. the creation of the forward solution for EEG will fail.
# Your variables
datapath='<myMEGdatapath>' # root directory for your MEG data
# MEG IDs (your directory structure may differ)
subj_pre=(\
'meg10_0001' \
'meg10_0002' \
'meg10_0003' \
)
# MEG subdirectories (your directory structure may differ)
subj_dir=(\
'100001' \
'100002' \
'100003' \
)
#condition names as used in file names
conds=('cond1' 'cond2' 'cond3')
# Processing:
nsubjects=${#subj_pre[*]}
lastsubj=`expr $nsubjects - 1`
nconds=${#conds[*]}
lastcond=`expr $nconds - 1`
for m in `seq 0 ${lastsubj}`
do
echo " "
echo " Fixing electrodes for SUBJECT ${subjects[m]}"
echo " "
for c in `seq 0 ${lastcond}`
do
mne_check_eeg_locations \
--file ${datapath}/${subj_pre[m]}/${subj_dir[m]}/${conds[c]}.fif \
--fix
done # conditions
done # subjectsMarking Bad Channels
You can mark channels already for raw MEG data files - these channels will then be excluded from artefact rejection during averaging.
datapath='<myMEGdatapath>' # root directory for your MEG data
mne_mark_bad_channels \
--bad yoursubjectbads.txt \ # File with bad channel information
${datapath}/YourSubjectDir/YourSubjectFile1.fif \
${datapath}/YourSubjectDir/YourSubjectFile2.fif \
${datapath}/YourSubjectDir/YourSubjectFile3.fif \where yoursubjectbads.txt could look like this
EEG001 EEG044
if EEG channels 1 and 44 are bad. I had problems when I created these text files in Windows - if in doubt, open the file under Linux (e.g. using nedit), use "save as" and make sure it's in Linux (not Dos) format.
Reading, Writing, Subtracting Fiff-files
This is a simple example of how you can read and write fiff-files, e.g. for subtracting conditions etc. Note that if you apply an inverse operator with the --dSPM option to subtracted data, you may have to adjust the number of effective averages (see manual).
data1 = fiff_read_evoked( fiff_file1 ); % Read file 1
data2 = fiff_read_evoked( fiff_file2 ); % Read file 2
data3 = data2; % data3 will contain the subtracted data, plus other information from file 2
data3.evoked.epochs = data2.evoked.epochs - data1.evoked.epochs; % subtract file 1 from file 2
fiff_write_evoked(out_fiff_file, data3); % write subtracted data to fiff-file