ROIs are defined by overlays. Whenever an overlay is shown on the image window, the graph data displays information averaged across the overlay, and a new button ("R") appears on the bottom of the graph window. This button can be used to write the ROI to a file that generally is named ".roi"; this file name is shown on the graph window label bar and changes if events are removed from a GLM fit.
The output that goes to the file is the same information that is displayed in the graph window (mostly). For instance, if a time series has been converted to percent signal change with the baseline drift removed, this will go to the file. Additionally, the GLM total fit and the fit for each event will be sent to the output file. This works the same for PET SRTM analyses: the total fit and parameter (BP, etc.) are written below the data vectors in each output column.
ROIs can be sent to a file one by one (right-click on "R" text button) or all at one time (left-click). In the latter case, load pre-defined overlays using the “-o overlay-list.dat” option at program startup from the unix command line, and all overlays will be written at the same time using the names specified in the “overlay-list.dat” file as column headers.
A common analysis procedure is to define a set of overlays in a registered data space. When this is done, every subject can be registered to the standardized space, and standardized ROIs can be output. If a series of overlays have been loaded at program startup using the "-o overlay-list.dat" option, then all ROIs will be output to the file by a single right-click on the "R" text button.
For instance, suppose a functional challenge has been given to a set of subjects, and each subject has been registered to a standardized space using jip-align. To create an average time course for each ROI across subjects, do this:
unix% foreach subject (2011-cocaine*)
unix% cd $subject/glm; pwd
unix% xd -g glm.dat -o overlay-list.dat
Then, apply the first overlay, open the graph window (“g”), remove the baseline (“b”), convert to percent, and right-click on the “R” button.
This same method can be used to determine average signal changes. For instance, the GLM output for "event 1" includes files P-1.bfloat (or .nii), S-1.bfloat, and T-1.bfloat. To see signal changes averaged across an ROI, do this as above:
xd S-1.bfloat S-2.bfloat S-2-1.bfloat -o overlay-list.dat
This will give the average of voxel-wise results, rather than the averaging voxels first and then analyzing the ROI data. For fMRI or PET GLM analyses, the latter information also can be obtained from the text fields on the bottom of the graph window in “jip-display” (xd).