Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_volumenormalise”.

  FT_VOLUMENORMALISE normalises anatomical and functional volume data
  to a template anatomical MRI.
  Use as
    [mri] = ft_volumenormalise(cfg, mri)
  where the input mri should be a single anatomical volume that was for
  example read with FT_READ_MRI.
  Configuration options are
    cfg.spmversion  = string, 'spm2', 'spm8', 'spm12' (default = 'spm8')
    cfg.template    = string, filename of the template anatomical MRI (default = 'T1.mnc'
                      for spm2 or 'T1.nii' for spm8)
    cfg.parameter   = cell-array with the functional data to be normalised (default = 'all')
    cfg.downsample  = integer number (default = 1, i.e. no downsampling)        = string for output filename
    cfg.write       = 'no' (default) or 'yes', writes the segmented volumes to SPM2
                      compatible analyze-file, with the suffix
                      _anatomy for the anatomical MRI volume
                      _param   for each of the functional volumes
    cfg.nonlinear   = 'yes' (default) or 'no', estimates a nonlinear transformation
                      in addition to the linear affine registration. If a reasonably
                      accurate normalisation is sufficient, a purely linearly transformed
                      image allows for 'reverse-normalisation', which might come in handy
                      when for example a region of interest is defined on the normalised
  To facilitate data-handling and distributed computing you can use
    cfg.inputfile   =  ...
    cfg.outputfile  =  ...
  If you specify one of these (or both) the input data will be read from a *.mat
  file on disk and/or the output data will be written to a *.mat file. These mat
  files should contain only a single variable, corresponding with the
  input/output structure.