After starting LOR2SPM utility the following window will appear

User can select type of LORETA file to be converted. There are four types:
next, user can select one of the following formats for output images to be created:
and last user can specify to use internal utility scaling during creation of images. This option may be useful if user is going to apply grand mean scaling for SPM analysis of the converted images. In this case SPM grand mean scaling is not completely appropriate because of images converted from the LORETA data have no noise in the voxels outside the brain, and standart SPM procedure of excluding voxel with values less than 1/8 of average may exclude some important voxels. To use internal scaling user should check "scale to" checkbox and can edit the value to which scaling will be done. Default value 100 means that in every converted image average over all 2394 voxel (2394 is the number of LORETA voxels in the brain) will be equal to 100.
After setting options user should click "Run" buton to start conversion. Immediately "SPMget" dialog from SPM99 will appear and user should select the LORETA files which he wants to convert. All selected files should be the same type and correspond to type selected in combo box "Input file type". After selecting files and clicking "Done" button utility will start creating for each selected LORETA file output triples of files *.img, *.hdr, and *.mat. The number of triples and names are determined by type of input LORETA files.
For current density vector field magnitude in both binary and text formats number of triples will be equal to number of time frames in the input file, and their names will be NAME_F0001, NAME_F0002, etc., where NAME is name of the input file. For all components of the current density vector field in both binary and text formats number of triples will be equal to number of time frames in the input file multiplyed by three. Their names will be NAME_F0001_X, NAME_F0001_Y, NAME_F0001_Z, NAME_F0002_X, NAME_F0002_Y, NAME_F0002_Z, etc.