This section describes the typical workflow needed to produce the minimum-norm estimate movies using the MNE software. The workflow is summarized in Workflow of the MNE software.
Workflow of the MNE software
Before starting the data analysis, setup the environment variable SUBJECTS_DIR to select the directory under which the anatomical MRI data are stored. Optionally, set SUBJECT as the name of the subject’s MRI data directory under SUBJECTS_DIR. With this setting you can avoid entering the --subject option common to many MNE programs and scripts. In the following sections, files in the FreeSurfer directory hierarchy are usually referred to without specifying the leading directories. Thus, bem/msh-7-src.fif is used to refer to the file $SUBJECTS_DIR/$SUBJECT/bem/msh-7-src.fif.
It is also recommended that the FreeSurfer environment is set up before using the MNE software.
The first processing stage is the creation of various surface reconstructions with FreeSurfer . The recommended FreeSurfer workflow is summarized on the FreeSurfer wiki pages: https://surfer.nmr.mgh.harvard.edu/fswiki/RecommendedReconstruction. Please refer to the FreeSurfer wiki pages (https://surfer.nmr.mgh.harvard.edu/fswiki/) and other FreeSurfer documentation for more information.
Note
Only the latest (4.0.X and later) FreeSurfer distributions contain a version of tkmedit which is compatible with mne_analyze, see Working with the MRI viewer.
If you have the Neuromag software installed, the Neuromag MRI viewer, MRIlab, can be used to access the MRI slice data created by FreeSurfer . In addition, the Neuromag MRI directories can be used for storing the MEG/MRI coordinate transformations created with mne_analyze , see Coordinate frame alignment. During the computation of the forward solution, mne_do_forwand_solution searches for the MEG/MRI coordinate in the Neuromag MRI directories, see Computing the forward solution. The fif files created by mne_setup_mrit can be loaded into Matlab with the fiff_read_mri function, see The Matlab toolbox.
These functions require running the script mne_setup_mri which requires that the subject is set with the --subject option or by the SUBJECT environment variable. The script processes one or more MRI data sets from $SUBJECTS_DIR/$SUBJECT/mri , by default they are T1 and brain. This default can be changed by specifying the sets by one or more --mri options.
The script creates the directories mri/ <name> -neuromag/slices and mri/ <name> -neuromag/sets . If the input data set is in COR format, mne_setup_mri makes symbolic links from the COR files in the directory mri/ <name> into mri/ <name> -neuromag/slices , and creates a corresponding fif file COR.fif in mri/ <name> -neuromag/sets .. This “description file” contains references to the actual MRI slices.
If the input MRI data are stored in the newer mgz format, the file created in the mri/ <name> -neuromag/sets directory will include the MRI pixel data as well. If available, the coordinate transformations to allow conversion between the MRI (surface RAS) coordinates and MNI and FreeSurfer Talairach coordinates are copied to the MRI description file. mne_setup_mri invokes mne_make_cor_set , described in Converting MRI data into the fif format to convert the data.
For example:
mne_setup_mri --subject duck_donald --mri T1
This command processes the MRI data set T1 for subject duck_donald.
Note
If the SUBJECT environment variable is set it is usually sufficient to run mne_setup_mri without any options.
Note
If the name specified with the --mri option contains a slash, the MRI data are accessed from the directory specified and the SUBJECT and SUBJECTS_DIR environment variables as well as the --subject option are ignored.
This stage consists of the following:
All of the above is accomplished with the convenience script mne_setup_source_space . This script assumes that:
The script accepts the following options:
—subject <*subject*>
Defines the name of the subject. If the environment variable SUBJECT is set correctly, this option is not required.
—morph <*name*>
Name of a subject in SUBJECTS_DIR. If this option is present, the source space will be first constructed for the subject defined by the –subject option or the SUBJECT environment variable and then morphed to this subject. This option is useful if you want to create a source spaces for several subjects and want to directly compare the data across subjects at the source space vertices without any morphing procedure afterwards. The drawback of this approach is that the spacing between source locations in the “morph” subject is not going to be as uniform as it would be without morphing.
—spacing <*spacing/mm*>
Specifies the grid spacing for the source space in mm. If not set, a default spacing of 7 mm is used. Either the default or a 5-mm spacing is recommended.
—ico <*number*>
Instead of using the traditional method for cortical surface decimation it is possible to create the source space using the topology of a recursively subdivided icosahedron (<number> > 0) or an octahedron (<number> < 0). This method uses the cortical surface inflated to a sphere as a tool to find the appropriate vertices for the source space. The benefit of the --ico option is that the source space will have triangulation information for the decimated vertices included, which future versions of MNE software may be able to utilize. The number of triangles increases by a factor of four in each subdivision, starting from 20 triangles in an icosahedron and 8 triangles in an octahedron. Since the number of vertices on a closed surface is, the number of vertices in the k th subdivision of an icosahedron and an octahedron are
and
, respectively. The recommended values for <number> and the corresponding number of source space locations are listed in Recommended subdivisions of an icosahedron and an octahedron for the creation of source spaces. The approximate source spacing and corresponding surface area have been calculated assuming a 1000-cm2 surface area per hemisphere..
—surface <*name*>
Name of the surface under the surf directory to be used. Defaults to ‘white’. mne_setup_source_space looks for files rh. <name> and lh. <name> under the surf directory.
—overwrite
An existing source space file with the same name is overwritten only if this option is specified.
—cps
Compute the cortical patch statistics. This is need if current-density estimates are computed, see Cortical patch statistics. If the patch information is available in the source space file the surface normal is considered to be the average normal calculated over the patch instead of the normal at each source space location. The calculation of this information takes a considerable amount of time because of the large number of Dijkstra searches involved.
| <number> | Sources per hemisphere | Source spacing / mm | Surface area per source / mm2 |
|---|---|---|---|
| -5 | 1026 | 9.9 | 97 |
| 4 | 2562 | 6.2 | 39 |
| -6 | 4098 | 4.9 | 24 |
| 5 | 10242 | 3.1 | 9.8 |
For example, to create the reconstruction geometry for Donald Duck with a 5-mm spacing between the grid points, say
mne_setup_source_space --subject duck_donald --spacing 5
As a result, the following files are created into the bem directory:
Note
<spacing> will be the suggested source spacing in millimeters if the --spacing option is used. For source spaces based on k*th subdivision of an icosahedron, <*spacing> will be replaced by ico- k or oct- k , respectively.
Note
After the geometry is set up it is possible to check that the source space points are located on the cortical surface. This can be easily done with by loading the COR.fif file from mri/T1/neuromag/sets into MRIlab and by subsequently overlaying the corresponding pnt or dip files using Import/Strings or Import/Dipoles from the File menu, respectively.
Note
If the SUBJECT environment variable is set correctly it is usually sufficient to run mne_setup_source_space without any options.
Calculation of the forward solution using the boundary-element model (BEM) requires that the surfaces separating regions of different electrical conductivities are tessellated with suitable surface elements. Our BEM software employs triangular tessellations. Therefore, prerequisites for BEM calculations are the segmentation of the MRI data and the triangulation of the relevant surfaces.
For MEG computations, a reasonably accurate solution can be obtained by using a single-compartment BEM assuming the shape of the intracranial volume. For EEG, the standard model contains the intracranial space, the skull, and the scalp.
At present, no bulletproof method exists for creating the triangulations. Feasible approaches are described in Creating the BEM meshes.
The segmentation algorithms described in Creating the BEM meshes produce either FreeSurfer surfaces or triangulation data in text. Before proceeding to the creation of the boundary element model, standard files (or symbolic links created with the ln -s command) have to be present in the subject’s bem directory. If you are employing ASCII triangle files the standard file names are:
inner_skull.tri
Contains the inner skull triangulation.
outer_skull.tri
Contains the outer skull triangulation.
outer_skin.tri
Contains the head surface triangulation.
The corresponding names for FreeSurfer surfaces are:
inner_skull.surf
Contains the inner skull triangulation.
outer_skull.surf
Contains the outer skull triangulation.
outer_skin.surf
Contains the head surface triangulation.
Note
Different methods can be employed for the creation of the individual surfaces. For example, it may turn out that the watershed algorithm produces are better quality skin surface than the segmentation approach based on the FLASH images. If this is the case, outer_skin.surf can set to point to the corresponding watershed output file while the other surfaces can be picked from the FLASH segmentation data.
Note
The triangulation files can include name of the subject as a prefix <*subject name*>- , e.g., duck-inner_skull.surf .
Note
The mne_convert_surface utility described in Converting surface data between different formats can be used to convert text format triangulation files into the FreeSurfer surface format.
Note
“Aliases” created with the Mac OSX finder are not equivalent to symbolic links and do not work as such for the UNIX shells and MNE programs.
This stage sets up the subject-dependent data for computing the forward solutions:
This step assigns the conductivity values to the BEM compartments. For the scalp and the brain compartments, the default is 0.3 S/m. The default skull conductivity is 50 times smaller, i.e., 0.006 S/m. Recent publications, see Forward modeling, report a range of skull conductivity ratios ranging from 1:15 (Oostendorp et al., 2000) to 1:25 - 1:50 (Slew et al., 2009, Conçalves et al., 2003). The MNE default ratio 1:50 is based on the typical values reported in (Conçalves et al., 2003), since their approach is based comparison of SEF/SEP measurements in a BEM model. The variability across publications may depend on individual variations but, more importantly, on the precision of the skull compartment segmentation.
This processing stage is automated with the script mne_setup_forward_model . This script assumes that:
mne_setup_forward_model accepts the following options:
—subject <*subject*>
Defines the name of the subject. This can be also accomplished by setting the SUBJECT environment variable.
—surf
Use the FreeSurfer surface files instead of the default ASCII triangulation files. Please consult Setting up the triangulation files for the standard file naming scheme.
—noswap
Traditionally, the vertices of the triangles in ‘tri’ files have been ordered so that, seen from the outside of the triangulation, the vertices are ordered in clockwise fashion. The fif files, however, employ the more standard convention with the vertices ordered counterclockwise. Therefore, mne_setup_forward_model by default reverses the vertex ordering before writing the fif file. If, for some reason, you have counterclockwise-ordered tri files available this behavior can be turned off by defining --noswap . When the fif file is created, the vertex ordering is checked and the process is aborted if it is incorrect after taking into account the state of the swapping. Should this happen, try to run mne_setup_forward_model again including the --noswap flag. In particular, if you employ the seglab software to create the triangulations (see Creating the BEM meshes), the --noswap flag is required. This option is ignored if --surf is specified
—ico <*number*>
This option is relevant (and required) only with the --surf option and if the surface files have been produced by the watershed algorithm. The watershed triangulations are isomorphic with an icosahedron, which has been recursively subdivided six times to yield 20480 triangles. However, this number of triangles results in a long computation time even in a workstation with generous amounts of memory. Therefore, the triangulations have to be decimated. Specifying --ico 4 yields 5120 triangles per surface while --ico 3 results in 1280 triangles. The recommended choice is --ico 4 .
—homog
Use a single compartment model (brain only) instead a three layer one (scalp, skull, and brain). Only the inner_skull.tri triangulation is required. This model is usually sufficient for MEG but invalid for EEG. If you are employing MEG data only, this option is recommended because of faster computation times. If this flag is specified, the options --brainc , --skullc , and --scalpc are irrelevant.
—brainc <*conductivity/ S/m*>
Defines the brain compartment conductivity. The default value is 0.3 S/m.
—skullc <*conductivity/ S/m*>
Defines the skull compartment conductivity. The default value is 0.006 S/m corresponding to a conductivity ratio 1/50 between the brain and skull compartments.
—scalpc <*conductivity/ S/m*>
Defines the brain compartment conductivity. The default value is 0.3 S/m.
—innershift <*value/mm*>
Shift the inner skull surface outwards along the vertex normal directions by this amount.
—outershift <*value/mm*>
Shift the outer skull surface outwards along the vertex normal directions by this amount.
—scalpshift <*value/mm*>
Shift the scalp surface outwards along the vertex normal directions by this amount.
—nosol
Omit the BEM model geometry dependent data preparation step. This can be done later by running mne_setup_forward_model without the --nosol option.
—model <*name*>
Name for the BEM model geometry file. The model will be created into the directory bem as <name>- bem.fif . If this option is missing, standard model names will be used (see below).
As a result of running the mne_setup_foward_model script, the following files are created into the bem directory:
After the BEM is set up it is advisable to check that the BEM model meshes are correctly positioned. This can be easily done with by loading the COR.fif file from mri/T1-neuromag/sets into MRIlab and by subsequently overlaying the corresponding pnt files using Import/Strings from the File menu.
Note
The FreeSurfer format BEM surfaces can be also viewed with the tkmedit program which is part of the FreeSurfer distribution.
Note
If the SUBJECT environment variable is set, it is usually sufficient to run mne_setup_forward_model without any options for the three-layer model and with the --homog option for the single-layer model. If the input files are FreeSurfer surfaces, --surf and --ico 4 are required as well.
Note
With help of the --nosol option it is possible to create candidate BEM geometry data files quickly and do the checking with respect to the anatomical MRI data. When the result is satisfactory, mne_setup_forward_model can be run without --nosol to invoke the time-consuming calculation of the solution file as well.
Note
The triangle meshes created by the seglab program have counterclockwise vertex ordering and thus require the --noswap option.
Note
Up to this point all processing stages depend on the anatomical (geometrical) information only and thus remain identical across different MEG studies.
The remaining steps require that the actual MEG/EEG data are available. It is recommended that a new directory is created for the MEG/EEG data processing. The raw data files collected should not be copied there but rather referred to with symbolic links created with the ln -s command. Averages calculated on-line can be either copied or referred to with links.
Note
If you don’t know how to create a directory, how to make symbolic links, or how to copy files from the shell command line, this is a perfect time to learn about this basic skills from other users or from a suitable elementary book before proceeding.
The following MEG and EEG data preprocessing steps are recommended:
The calibration factor of the digital trigger channel used to be set to a value much smaller than one by the Neuromag data acquisition software. Especially to facilitate viewing of raw data in graph it is advisable to change the calibration factor to one. Furthermore, the eighth bit of the trigger word is coded incorrectly in the original raw files. Both problems can be corrected by saying:
mne_fix_stim14 <raw file>
More information about mne_fix_stim14 is available in Fixing the encoding of the trigger channel: mne_fix_stim14. It is recommended that this fix is included as the first raw data processing step. Note, however, the mne_browse_raw and mne_process_raw always sets the calibration factor to one internally.
Note
If your data file was acquired on or after November 10, 2005 on the Martinos center Vectorview system, it is not necessary to use mne_fix_stim14 .
There are two potential discrepancies in the channel information which need to be fixed before proceeding:
These potential problems can be fixed with the utilities mne_check_eeg_locations and mne_fix_mag_coil_types, see Updating EEG location info: mne_check_eeg_locations and Updating magnetometer coil types: mne_fix_mag_coil_types.
Sometimes some MEG or EEG channels are not functioning properly for various reasons. These channels should be excluded from the analysis by marking them bad using the mne_mark_bad_channels utility, see Designating bad channels: mne_mark_bad_channels. Especially if a channel is not show a signal at all (flat) it is most important to exclude it from the analysis, since its noise estimate will be unrealistically low and thus the current estimate calculations will give a strong weight to the zero signal on the flat channels and will essentially vanish. It is also important to exclude noisy channels because they can possibly affect others when signal-space projections or EEG average electrode reference is employed. Noisy bad channels can also adversely affect off-line averaging and noise-covariance matrix estimation by causing unnecessary rejections of epochs.
Recommended ways to identify bad channels are:
Note
It is strongly recommended that bad channels are identified and marked in the original raw data files. If present in the raw data files, the bad channel selections will be automatically transferred to averaged files, noise-covariance matrices, forward solution files, and inverse operator decompositions.
The minimum practical sampling frequency of the Vectorview system is 600 Hz. Lower sampling frequencies are allowed but result in elevated noise level in the data. It is advisable to lowpass filter and downsample the large raw data files often emerging in cognitive and patient studies to speed up subsequent processing. This can be accomplished with the mne_process_raw and mne_browse_raw software modules. For details, see Batch-mode options and Save.
Note
It is recommended that the original raw file is called <name>_raw.fif and the downsampled version <name>_ds_raw.fif , respectively.
The recommended tools for off-line averaging are mne_browse_raw and mne_process_raw . mne_browse_raw is an interactive program for averaging and noise-covariance matrix computation. It also includes routines for filtering so that the downsampling and filtering steps can be skipped. Therefore, with mne_browse_raw you can produce the off-line average and noise-covariance matrix estimates directly. The batch-mode version of mne_browse_raw is called mne_process_raw . Detailed information on mne_browse_raw and mne_process_raw can be found in Processing raw data.
The calculation of the forward solution requires knowledge of the relative location and orientation of the MEG/EEG and MRI coordinate systems. The MEG/EEG head coordinate system is defined in The head and device coordinate systems. The conversion tools included in the MNE software take care of the idiosyncrasies of the coordinate frame definitions in different MEG and EEG systems so that the fif files always employ the same definition of the head coordinate system.
Ideally, the head coordinate frame has a fixed orientation and origin with respect to the head anatomy. Therefore, a single MRI-head coordinate transformation for each subject should be sufficient. However, as explained in The head and device coordinate systems, the head coordinate frame is defined by identifying the fiducial landmark locations, making the origin and orientation of the head coordinate system slightly user dependent. As a result, the most conservative choice for the definition of the coordinate transformation computation is to re-establish it for each experimental session, i.e., each time when new head digitization data are employed.
The interactive source analysis software mne_analyze provides tools for coordinate frame alignment, see Interactive analysis. MEG-MRI coordinate system alignment also contains tips for using mne_analyze for this purpose.
Another useful tool for the coordinate system alignment is MRIlab , the Neuromag MEG-MRI integration tool. Section 3.3.1 of the MRIlab User’s Guide, Neuromag P/N NM20419A-A contains a detailed description of this task. Employ the images in the set mri/T1-neuromag/sets/COR.fif for the alignment. Check the alignment carefully using the digitization data included in the measurement file as described in Section 5.3.1 of the above manual. Save the aligned description file in the same directory as the original description file without the alignment information but under a different name.
Warning
This step is extremely important. If the alignment of the coordinate frames is inaccurate all subsequent processing steps suffer from the error. Therefore, this step should be performed by the person in charge of the study or by a trained technician. Written or photographic documentation of the alignment points employed during the MEG/EEG acquisition can also be helpful.
After the MRI-MEG/EEG alignment has been set, the forward solution, i.e., the magnetic fields and electric potentials at the measurement sensors and electrodes due to dipole sources located on the cortex, can be calculated with help of the convenience script mne_do_forward_solution . This utility accepts the following options:
—subject <*subject*>
Defines the name of the subject. This can be also accomplished by setting the SUBJECT environment variable.
—src <*name*>
Source space name to use. This option overrides the --spacing option. The source space is searched first from the current working directory and then from $SUBJECTS_DIR/ <subject> /bem. The source space file must be specified exactly, including the fif extension.
—spacing <*spacing/mm*> or ``ico-`` <*number or ``oct-`` <*number*>
This is an alternate way to specify the name of the source space file. For example, if --spacing 6 is given on the command line, the source space files searched for are./<subject> -6-src.fif and $SUBJECTS_DIR/$SUBJECT/ bem/<subject> -6-src.fif. The first file found is used. Spacing defaults to 7 mm.
—bem <*name*>
Specifies the BEM to be used. The name of the file can be any of <name> , <name> -bem.fif, <name> -bem-sol.fif. The file is searched for from the current working directory and from bem . If this option is omitted, the most recent BEM file in the bem directory is used.
—mri <*name*>
The name of the MRI description file containing the MEG/MRI coordinate transformation. This file was saved as part of the alignment procedure outlined in Aligning the coordinate frames. The file is searched for from the current working directory and from mri/T1-neuromag/sets . The search order for MEG/MRI coordinate transformations is discussed below.
—trans <*name*>
The name of a text file containing the 4 x 4 matrix for the coordinate transformation from head to mri coordinates, see below. If the option --trans is present, the --mri option is not required. The search order for MEG/MRI coordinate transformations is discussed below.
—meas <*name*>
This file is the measurement fif file or an off-line average file produced thereof. It is recommended that the average file is employed for evoked-response data and the original raw data file otherwise. This file provides the MEG sensor locations and orientations as well as EEG electrode locations as well as the coordinate transformation between the MEG device coordinates and MEG head-based coordinates.
—fwd <*name*>
This file will contain the forward solution as well as the coordinate transformations, sensor and electrode location information, and the source space data. A name of the form <name> -fwd.fif is recommended. If this option is omitted the forward solution file name is automatically created from the measurement file name and the source space name.
—destdir <*directory*>
Optionally specifies a directory where the forward solution will be stored.
—mindist <*dist/mm*>
Omit source space points closer than this value to the inner skull surface. Any source space points outside the inner skull surface are automatically omitted. The use of this option ensures that numerical inaccuracies for very superficial sources do not cause unexpected effects in the final current estimates. Suitable value for this parameter is of the order of the size of the triangles on the inner skull surface. If you employ the seglab software to create the triangulations, this value should be about equal to the wish for the side length of the triangles.
—megonly
Omit EEG forward calculations.
—eegonly
Omit MEG forward calculations.
—all
Compute the forward solution for all vertices on the source space.
—overwrite
Overwrite the possibly existing forward model file.
—help
Show usage information for the script.
The MEG/MRI transformation is determined by the following search sequence:
This search sequence is designed to work well with the MEG/MRI transformation files output by mne_analyze , see Coordinate frame alignment. It is recommended that -trans.fif file saved with the Save default and Save... options in the mne_analyze alignment dialog are used because then the $SUBJECTS_DIR/$SUBJECT directory will be composed of files which are dependent on the subjects’s anatomy only, not on the MEG/EEG data to be analyzed.
Note
If the standard MRI description file and BEM file selections are appropriate and the 7-mm source space grid spacing is appropriate, only the --meas option is necessary. If EEG data is not used --megonly option should be included.
Note
If it is conceivable that the current-density transformation will be incorporated into the inverse operator, specify a source space with patch information for the forward computation. This is not mandatory but saves a lot of time when the inverse operator is created, since the patch information does not need to be created at that stage.
Note
The MEG head to MRI transformation matrix specified with the --trans option should be a text file containing a 4-by-4 matrix:
defined so that if the augmented location vectors in MRI
head and MRI coordinate systems are denoted by ![r_{head}[x_{head}\ y_{head}\ z_{head}\ 1]](../_images/math/392440cb9111a153474a378ed62f5fe39a1e5719.png)
and ![r_{MRI}[x_{MRI}\ y_{MRI}\ z_{MRI}\ 1]](../_images/math/a3523ea4cacdcb820457bcb97a63f6ce0888c288.png)
,
respectively,
Note
It is not possible to calculate an EEG forward solution with a single-layer BEM.
The MNE software employs an estimate of the noise-covariance matrix to weight the channels correctly in the calculations. The noise-covariance matrix provides information about field and potential patterns representing uninteresting noise sources of either human or environmental origin.
The noise covariance matrix can be calculated in several ways:
The new raw data processing tools, mne_browse_raw or mne_process_raw include computation of noise-covariance matrices both from raw data and from individual epochs. For details, see Processing raw data.
The MNE software doesn’t calculate the inverse operator explicitly but rather computes an SVD of a matrix composed of the noise-covariance matrix, the result of the forward calculation, and the source covariance matrix. This approach has the benefit that the regularization parameter (‘SNR’) can be adjusted easily when the final source estimates or dSPMs are computed. For mathematical details of this approach, please consult Minimum-norm estimates.
This computation stage is facilitated by the convenience script mne_do_inverse_operator . It invokes the program mne_inverse_operator with appropriate options, derived from the command line of mne_do_inverse_operator .
mne_do_inverse_operator assumes the following options:
—fwd <*name of the forward solution file*>
This is the forward solution file produced in the computations step described in Computing the forward solution.
—meg
Employ MEG data in the inverse calculation. If neither --meg nor --eeg is set only MEG channels are included.
—eeg
Employ EEG data in the inverse calculation. If neither --meg nor --eeg is set only MEG channels are included.
—fixed
Use fixed source orientations normal to the cortical mantle. By default, the source orientations are not constrained. If --fixed is specified, the --loose flag is ignored.
—loose <*amount*>
Use a ‘loose’ orientation constraint. This means that the source covariance matrix entries corresponding to the current component normal to the cortex are set equal to one and the transverse components are set to <amount> . Recommended value of amount is 0.1...0.6.
—depth
Employ depth weighting with the standard settings. For details, see Depth weighting and Inverse-operator decomposition.
—bad <*name*>
Specifies a text file to designate bad channels, listed one channel name (like MEG 1933) on each line of the file. Be sure to include both noisy and flat (non-functioning) channels in the list. If bad channels were designated using mne_mark_bad_channels in the measurement file which was specified with the --meas option when the forward solution was computed, the bad channel information will be automatically included. Also, any bad channel information in the noise-covariance matrix file will be included.
—noisecov <*name*>
Name of the noise-covariance matrix file computed with one of the methods described in Setting up the noise-covariance matrix. By default, the script looks for a file whose name is derived from the forward solution file by replacing its ending - <anything> -fwd.fif by -cov.fif . If this file contains a projection operator, which will automatically attached to the noise-covariance matrix by mne_browse_raw and mne_process_raw , no --proj option is necessary because mne_inverse_operator will automatically include the projectors from the noise-covariance matrix file. For backward compatibility, –senscov can be used as a synonym for –noisecov.
—noiserank <*value*>
Specifies the rank of the noise covariance matrix explicitly rather than trying to reduce it automatically. This option is sheldom needed,
—megreg <*value*>
Regularize the MEG part of the noise-covariance matrix by this amount. Suitable values are in the range 0.05...0.2. For details, see Regularization of the noise-covariance matrix.
—eegreg <*value*>
Like --megreg but applies to the EEG channels.
—diagnoise
Omit the off-diagonal terms of the noise covariance matrix. This option is irrelevant to most users.
—fmri <*name*>
With help of this w file, an a priori weighting can be applied to the source covariance matrix. The source of the weighting is usually fMRI but may be also some other data, provided that the weighting can be expressed as a scalar value on the cortical surface, stored in a w file. It is recommended that this w file is appropriately smoothed (see About smoothing) in mne_analyze , tksurfer or with mne_smooth_w to contain nonzero values at all vertices of the triangular tessellation of the cortical surface. The name of the file given is used as a stem of the w files. The actual files should be called <name> -lh.pri and <name> -rh.pri for the left and right hemisphere weight files, respectively. The application of the weighting is discussed in fMRI-guided estimates.
—fmrithresh <*value*>
This option is mandatory and has an effect only if a weighting function has been specified with the --fmri option. If the value is in the a priori files falls below this value at a particular source space point, the source covariance matrix values are multiplied by the value specified with the --fmrioff option (default 0.1). Otherwise it is left unchanged.
—fmrioff <*value*>
The value by which the source covariance elements are multiplied if the a priori weight falls below the threshold set with --fmrithresh , see above.
—srccov <*name*>
Use this diagonal source covariance matrix. By default the source covariance matrix is a multiple of the identity matrix. This option is irrelevant to most users.
—proj <*name*>
Include signal-space projection information from this file.
—inv <*name*>
Save the inverse operator decomposition here. By default, the script looks for a file whose name is derived from the forward solution file by replacing its ending -fwd.fif by <options> -inv.fif , where <options> includes options --meg, --eeg, and --fixed with the double dashes replaced by single ones.
—destdir <*directory*>
Optionally specifies a directory where the inverse operator will be stored.
Note
If bad channels are included in the calculation, strange results may ensue. Therefore, it is recommended that the data to be analyzed is carefully inspected with to assign the bad channels correctly.
Note
For convenience, the MNE software includes bad-channel designation files which can be used to ignore all magnetometer or all gradiometer channels in Vectorview measurements. These files are called vv_grad_only.bad and vv_mag_only.bad , respectively. Both files are located in $MNE_ROOT/share/mne/templates .
Once all the preprocessing steps described above have been completed, the inverse operator computed can be applied to the MEG and EEG data and the results can be viewed and stored in several ways: