Sam epi: Difference between revisions
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==Description== |
==Description== |
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The sam_epi routine is a program designed for detecting sub-threshold epileptiform activity in the brain. It evaluates each voxel time series to determine kurtosis. The recommended pipeline is to run sam_cov, sam_wts, and then sam_epi. The utility [[NIFTIPeak|NIFTIPeak]] can then be used to identify voxels with peak or excess kurtosis values. These voxel locations can then be used as targets for a secondary run of sam_wts. |
The sam_epi routine is a program designed for detecting sub-threshold epileptiform activity in the brain. It evaluates each voxel time series to determine kurtosis. The recommended pipeline is to run sam_cov, sam_wts, and then sam_epi. The utility [[NIFTIPeak|NIFTIPeak]] can then be used to identify voxels with peak or excess kurtosis values. These voxel locations can then be used as targets for a secondary run of sam_cov with a wide bandwidth, an sam_wts. Finally, DataEditor can be used to generate the virtual sensor time series for the targets, and the epileptologist can investigate the time series and mark spikes. Individual spikes can then be modeled with dipole fits. |
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Note that datasets must be continuous, and not epoched into trials. |
Note that datasets must be continuous, and not epoched into trials. |
Revision as of 10:13, 12 March 2019
Return to Source Localization - SAM
Description
The sam_epi routine is a program designed for detecting sub-threshold epileptiform activity in the brain. It evaluates each voxel time series to determine kurtosis. The recommended pipeline is to run sam_cov, sam_wts, and then sam_epi. The utility NIFTIPeak can then be used to identify voxels with peak or excess kurtosis values. These voxel locations can then be used as targets for a secondary run of sam_cov with a wide bandwidth, an sam_wts. Finally, DataEditor can be used to generate the virtual sensor time series for the targets, and the epileptologist can investigate the time series and mark spikes. Individual spikes can then be modeled with dipole fits.
Note that datasets must be continuous, and not epoched into trials.
Usage
sam_epi -r <dataset_name> -m <parameter_file_name> [options]
The -r flag designates the dataset name (with or without the .ds suffix), and -m designates the parameter file name.
Other options:
-v Verbose mode, without this flag sam_wts works silently except for error messages -h Show help
Required Parameters:
CovBand: Bandpass for the covariance matrices (and directory for weights files) ImageBand: Bandpass for the image ImageMetric: Must be KURTOSIS TimeInt: designates the duration for the boxcar integration CovType: Must be GLOBAL
Optional Parameters:
FilterType: choose the applied filter, IIR vs. FFT ImageDirectory: Directory where the output images are written, default is the SAM directory PrefixLength: Number of characters in the MEG dataset name used for naming MRI files
Output Files
Creates a single 3D NIFTI format image of kurtosis (g2). Output file will be named using the PrefixLength parameter.