ciftify_seed_corr

Produces a correlation map of the mean time series within the seed with
every voxel in the functional file.

Usage:
    ciftify_seed_corr [options] <func> <seed>

Arguments:
    <func>          functional data (nifti or cifti)
    <seed>          seed mask (nifti, cifti or gifti)

Options:
    --outputname STR   Specify the output filename
    --output-ts        Also output write the from the seed to text
    --roi-label INT    Specify the numeric label of the ROI you want a seedmap for
    --hemi HEMI        If the seed is a gifti file, specify the hemisphere (R or L) here
    --mask FILE        brainmask
    --weighted         compute weighted average timeseries from the seed map
    --use-TRs FILE     Only use the TRs listed in the file provided (TR's in file starts with 1)
    --debug            Debug logging
    -h, --help         Prints this message

DETAILS:
The default output filename is created from the <func> and <seed> filenames,
(i.e. func.dscalar.nii + seed.dscalar.nii --> func_seed.dscalar.nii)
and written to same folder as the <func> input. Use the --outputname
argument to specify a different outputname. The output datatype matches the <func>
input.

The mean timeseries is calculated using ciftify_meants, --roi-label, --hemi,
--mask, and --weighted arguments are passed to it. See ciftify_meants --help for
more info on their usage. The timeseries output (*_meants.csv) of this step can be
saved to disk using the --output-ts option.

If a mask is provided with the (--mask) option. (Such as a brainmask) it will be
applied to both the seed and functional file.

The --use-TRs argument allows you to calcuate the correlation maps from specific
timepoints (TRs) in the timeseries. This option can be used to exclude outlier
timepoints or to limit the calculation to a subsample of the timecourse
(i.e. only the beggining or end). It expects a text file containing the integer numbers
TRs to keep (where the first TR=1).

Written by Erin W Dickie