NAME

       TimeSCCAN - part of ANTS registration suite

DESCRIPTION

   COMMAND:
              TimeSCCAN

              A tool for sparse statistical analysis on connectivity within a subject :

   OPTIONS:
       -h

              Print the help menu (short version).

       --help

              Print the help menu (long version).  <VALUES>: 1

       -o, --output outputImage

              Output is a 2D correlation matrix.

       -l, --number-consecutive-labels 0

              Number of consecutive labels in data

       -R, --minimum-region-size 1

              Minimum  size  of  a  region:  regions below this size are given a 0.0 connectivity
              value

       -i, --iterations 20

              Number of iterations

       -s, --sparsity 0.10

              Sparsity - a float from (0,1] indicating what fraction of the data to use

       -n, --n_eigenvectors 2

              Number of permutations to use in scca.

       -r, --robustify 0

              rank-based scca

       -l, --l1 0

              use l1 ( > 0 ) or l0 ( < 0 ) penalty, also sets gradient step size e.g. -l 0.5 ( L1
              ) , -l -0.5 (L0) will set 0.5 grad descent step for either penalty

       --ClusterThresh 1

              cluster threshold on view P

       -e, --ridge_cca 0

              Number of permutations to use in scca.

       --partial-scca-option PminusRQ

              Choices for pscca: PQ, PminusRQ, PQminusR, PminusRQminusR

       --timeseriesimage-to-matrix [four_d_image.nii.gz,three_d_mask.nii.gz]

              takes  a  timeseries  (4D)  image  and  converts  it  to  a 2D matrix csv format as
              output.If the mask has multiple labels ( more the  one  )  then  the  average  time
              series in each label will be computed and put in the csv.

       --labelsimage-to-matrix [three_d_mask.nii.gz]

              takes a labeled (3D) image and converts it to a 2D matrix csv format as output.

       --network scca[time-matrix.mhd,label-matrix.mhd]

              region-averaging[time-matrix.mhd,label-matrix.mhd]

              Build the network connectivity matrix