spread.values.over.subject: Spread the values in the region_value_list and return them...
In neuroconductor/fsbrain: Managing and Visualizing Brain Surface Data

Description Usage Arguments Value See Also Examples

Given an atlas and a list that contains one value for each atlas region, create morphometry data in which all region vertices are assigned the value. Can be used to plot stuff like p-values or effect sizes onto brain regions.

spread.values.over.subject(
  subjects_dir,
  subject_id,
  atlas,
  lh_region_value_list,
  rh_region_value_list,
  value_for_unlisted_regions = NaN,
  silent = FALSE
)

`subjects_dir,`	string. The FreeSurfer SUBJECTS_DIR, i.e., a directory containing the data for all your subjects, each in a subdir named after the subject identifier.
`subject_id,`	string. The subject identifier
`atlas,`	string. The atlas name. E.g., "aparc", "aparc.2009s", or "aparc.DKTatlas". Used to construct the name of the annotation file to be loaded.
`lh_region_value_list,`	named list. A list in which the names are atlas regions, and the values are the value to write to all vertices of that region. Applied to the left hemisphere.
`rh_region_value_list,`	named list. A list in which the names are atlas regions, and the values are the value to write to all vertices of that region. Applied to the right hemisphere.
`value_for_unlisted_regions,`	numeric scalar. The value to assign to vertices which are part of atlas regions that are not listed in region_value_list. Defaults to NaN.
`silent`	logical, whether to suppress mapping info in case of unnamed region value lists (see 'lh_region_value_list' description).

named list with entries 'lh' and 'rh'. Each value is a numeric vector containing the data for the respective hemisphere.

Other atlas functions: get.atlas.region.names(), group.agg.atlas.native(), group.agg.atlas.standard(), group.annot(), group.label.from.annot(), label.from.annotdata(), label.to.annot(), regions.to.ignore(), spread.values.over.annot(), spread.values.over.hemi(), subject.annot(), subject.atlas.agg(), subject.label.from.annot(), subject.lobes()

   fsbrain::download_optional_data();
   subjects_dir = fsbrain::get_optional_data_filepath("subjects_dir");
   lh_region_value_list = list("bankssts"=0.9, "precuneus"=0.7);
   rh_region_value_list = list("bankssts"=0.5);
   morph_like_data =
   spread.values.over.subject(subjects_dir, 'subject1', 'aparc',
   lh_region_value_list, rh_region_value_list);