AFNI program: 3dTcorrelate

Usage: 3dTcorrelate [options] xset yset
Computes the correlation coefficient between corresponding voxel
time series in two input 3D+time datasets 'xset' and 'yset', and
stores the output in a new 1 sub-brick dataset.

Options:
  -pearson  = Correlation is the normal Pearson (product moment)
                correlation coefficient [default].
  -spearman = Correlation is the Spearman (rank) correlation
                coefficient.
  -quadrant = Correlation is the quadrant correlation coefficient.

  -polort m = Remove polynomical trend of order 'm', for m=-1..3.
                [default is m=1; removal is by least squares].
                Using m=-1 means no detrending; this is only useful
                for data/information that has been pre-processed.

  -ort r.1D = Also detrend using the columns of the 1D file 'r.1D'.
                Only one -ort option can be given.  If you want to use
                more than one, create a temporary file using 1dcat.

  -autoclip = Clip off low-intensity regions in the two datasets,
  -automask =  so that the correlation is only computed between
               high-intensity (presumably brain) voxels.  The
               intensity level is determined the same way that
               3dClipLevel works.

  -prefix p = Save output into dataset with prefix 'p'
               [default prefix is 'Tcorr'].

Notes:
 * The output dataset is functional bucket type, with one
    sub-brick, stored in floating point format.
 * Because both time series are detrended prior to correlation,
    the results will not be identical to using FIM or FIM+ to
    calculate correlations (whose ideal vector is not detrended).
 * This is a quick hack for Mike Beauchamp.  Thanks for you-know-what.

-- RWCox - Aug 2001