usage : @compute_gcor [options] -input dataset
This program computes the average correlation between every voxel and ever other voxel, over any give mask. This output GCOR value is a single number.
Common examples:
This program can be used for 1D files:
@compute_gcor -input data.1D
HOWEVER, if column selection is desired, please use 1d_tool.py, directly.
1d_tool.py -infile data.1D’[2..17]’ -show_gcor
Simple usage, akin to the afni_proc.py processing script.
@compute_gcor -input errts.FT+orig -mask full_mask.FT+origOR, for +tlrc:
@compute_gcor -input errts.FT+tlrc -mask full_mask.FT+tlrc
- Speed things up slightly, an errts dataset does not need to be demeaned.
@compute_gcor -no_demean -input errts.FT+tlrc -mask full_mask.FT+tlrc
- Be vewy, veeewy, qwiet...
@compute_gcor -verb 0 -input errts.FT+tlrc -mask full_mask.FT+tlrcOR, save the result:
set gcor = @compute_gcor -verb 0 -input errts.FT+tlrc -mask full_mask.FT+tlrc
Output correlation volume: for each voxel, the average correlation with all voxels in mask.
Specify correlation volume prefix, FT_corr.
@compute_gcor -input errts.FT+tlrc -mask full_mask.FT+tlrc -corr_vol FT_corr
Overview of processing steps:
otherwise...
3b. Return GCOR = the length of the resulting average, squared.
terminal options:
-help : show this help
-hist : show modification history
-ver : show version number
important processing options:
-input DSET : specify input dataset to compute the GCOR over -mask DSET : specify mask dataset, for restricting the computation
other processing options:
-corr_vol PREFIX : specify input dataset to compute the GCOR over
-nfirst NFIRST : specify number of initial TRs to ignore -no_demean : do not (need to) demean as first step
-savetmp : save temporary files (do not remove at end) -verb VERB : set verbose level (0=quiet, 3=max)