Tunable Parameters

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All SAM analyses are directed by a named parameter file. The format of this file is plain text and can be created using any convenient text editor (i.e., vi, gedit, emacs, etc.). The parameter file is normally specified with -m.

Parameters may be abbreviated, and except where noted may also be specified on the command line prefixed with two dashes, e.g., --DataSet. Some also have single dash option flags (-h), and some (e.g., ds) may be specified as exported environment variables.

Parameters specified on the command line or environment override those specified in a parameter file. If command line options are used, the actual parameters that the analysis was run with will be reconstituted as a .param file in the SAM director of the MEG dataset.

Finally, you may also define an optional parameter file called .samrc in the directory from which the program is run, which may contain parameters common to a set of analyses.

All parameters appear below. User defined input is given in all capital letters.

Input and Output File Specification


 DataSet DNAME

Specifies the MEG dataset to be analyzed. Specified on the command line using -r.



Only used for 4D/BTi datasets, this specifies the additional PDF file. Specified on the command line using -d.


 MRIDirectory MRIDIR

Specifies the MRI directory root. May also be specified on the command line with -i. Several files, derived from a participant’s anatomical MRI, are used in SAM analysis. By default, they are found using this directory and the MRIPattern. The files are the subject’s hull and ortho-space MRI transformed to Talairach space. By default, these are named hull.shape and ortho+tlrc. If MRIDirectory is absent, the SAM programs will look for hull.shape in the dataset directory. There is no default for the ortho MRI. If the Talairach transform is applied to the SAM beamformer coefficients, this is a required parameter. Using MRIDirectory is highly recommended in applications for batch analysis of large numbers of datasets and especially for using AFNI for group statistics.



This parameter controls how the input MRI files are assumed to be named. The default MRIPattern is %M/%P/%s, where %M represents the MRI root directory, %P is the first N characters of the dataset name (the length of the string can be designated with the PrefixLength parameter), and %s is replaced by the actual file name. Thus, under the default behavior, for dataset ABABABAB_rest_01.ds the hull.shape file would be assumed to have the following path:


Other variables which can be used are: %H (hashcode) is the first “_” delimited field of the dataset name, %S is the study type (2nd field of dataset name), %D is the date (3rd field), and %R is the run number (4th field).


 PrefixLength N

This parameter controls the number of characters at the beginning of the MEG dataset that are used to find the required MRI files, and to name the output files. The default is 8, according to the NIH convention for naming MEG datasets with an 8 digit hash code. For sites having a different number of characters for identifying datasets and participants, PrefixLength can be used.

Marker Specification


 NumMarkers N

N specifies the number of unique event marker names found in the dataset that are to be used in the analysis. Up to six markers are currently permitted. If no named markers are present, the user must specify zero markers for analyses that are not state dependent. The sam_cov and sam_wts programs, together, read this parameter and parse the dataset for the named markers, generating up to six named SAM beamformer coefficient files plus Global and Sum coefficients.



Specify Marker1 through Marker6. The numbered markers must be sequential and agree with NumMarkers. Each MarkerN parameter requires four arguments: the marker name, the start and end time relative to this marker (in seconds) and a flag (TRUE or FALSE) indicating whether this marker is to be included in the SUM covariance and beamformer coefficients. Markers cannot be specified on the command line. For example:

 NumMarkers 3
 Marker1 9r0 -0.25 0.25 TRUE
 Marker2 9r1 -0.25 0.25 TRUE
 Marker3 9r2 -0.25 0.25 TRUE

Frequency Specification


 CovBand LO HI

Passband frequencies (in Hz) for filtering the data prior to computing the covariance matrices. A wide bandwidth covariance (much wider than ImageBand) is useful when analyzing MEG data that has very large artifacts, due to tDCS, tACS, or VNS. In such cases, a wide bandwidth will improve rejection of interference by including interference in the beamformer coefficient computations.


 ImageBand LO HI

Passband frequencies (in Hz) for SAM imaging. In instances where you may want to use a wider bandwidth for calculation of the covariance matrix to improve rejection of interference, you can still calculate your desired image metric with a more narrow bandwidth.


 OrientBand LO HI

A separate covariance matrix, using all data samples is used for estimating the dipole orientation in the two-step scalar SAM beamformer. If OrientBand is present, the data are filtered to this passband prior to computing the Orient.cov file. Otherwise, the Orient.cov file will be identical to Global.cov. This option allows the user to optimize the source orientation by specifying a passband where signal-to-noise is high (such as beta). As a first principle, the source orientation is assumed to be stationary, which is why all data samples are used. For example:


 NoiseBand LO HI

The default method of determining mean sensor noise is finding the rank where the first derivative is at a minimum in the covariance eigenvalue spectrum; this yields only a mean noise value for all sensors. In practice, however, there may be differences in individual SQUID sensor noise. This factor becomes important when imaging high frequency power (fast ripples, etc.) where signal-to-noise is marginal. The mean sensor noise will result in a non-uniform SAM image magnitude, which may be misleading. To overcome this limitation, the user can specify a NoiseBand passband that extends well above the frequencies of interest where the MEG signal is (presumably) vanishingly small. The product of the noise covariance with the SAM beamformer coefficients will give the best estimate of the actual projected noise for each voxel.


 SmoothBand LO HI

Required for sam_4d, sam_4dc, sam_ersc, and sam_hfo, The lowpass filter (the HI value) is used to smooth the moment, Hilbert envelope of power, excess kurtosis or RVE time-series prior to saving multiple images for each latency. If LO is non-zero, then the metric is bandpass filtered (a highpass other than zero is not recommended).



Enables/disables notch filtering for power mains frequency and its harmonics. The default notch frequencies are based on 60 Hz power mains. This can be switched to 50 Hz using the Hz parameter. The default notch width is 4 Hz (+/- 2 Hz), using a 20th-order FFT filter. Up to 6 notch frequencies are used. Usually this is done by filtering the raw dataset using newDs. Notch filtering is recommended when operating on raw datasets.

Image Coordinate Space Specification



Required for sam_wts — except when using an Atlas or a target list (-t option to sam_wts). In the latter case, the image bounds are determined by the atlas ROI limits. XBounds sets the anterior-posterior ROI dimensions in centimeters, where it is positive in the anterior direction. YBounds sets the left-right ROI dimensions, which is positive in the left direction. ZBounds sets the inferior-superior ROI dimensions, which is positive in the superior direction. Units of START and END are in centimeters


 ImageStep STEP

Required for all SAM image analyses — except when using an atlas or a target file list. Units are in centimeters



The hull file estimates the boundary of the inner skull surface, which is used for magnetic field calculations when using the Nolte magnetic field model, and also the boundary of the ROI when using MultiSphere. Voxels in the space defined by XBounds, YBounds, and ZBounds that lie outside the hull are not calculated. Hulls are computed using orthohull.



Instead of using a rectilinear space of voxels, beam former weights can be calculated for each "voxel" or greyordinate on a cortical surface derived from the MRI using FreeSurfer. The atlas file contains the coordinates and orientation vector for each neocortical location. An atlas may be generated by applying FSnormals.py and reduce_surface.py to the subject’s surface data obtained from FreeSurfer. If present, it overrides the XBounds, YBounds, ZBounds, and ImageStep parameters. The default location of the atlas is set using the MRIDirectory and MRIPattern parameters.


  BlockName MARKNAME

This is required only for ste_ers - calculation of transfer entropy. The marker name designates the epochs or blocks to be processed for computation of the covariance matrix and probability distribution functions (PDFs).