group.label.from.annot {fsbrain}R Documentation

Extract a region from an atlas annotation as a label for a group of subjects.

Description

The returned label can be used to mask morphometry data, e.g., to set the values of a certain region to NaN or to extract only values from a certain region.

Usage

group.label.from.annot(
  subjects_dir,
  subjects_list,
  hemi,
  atlas,
  region,
  return_one_based_indices = TRUE,
  invert = FALSE,
  error_on_invalid_region = TRUE
)

Arguments

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.

subjects_list

vector of string. The subject identifiers.

hemi

string, one of 'lh' or 'rh'. The hemisphere name. Used to construct the names of the label data files to be loaded.

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.

region

string. A valid region name for the annotation, i.e., one of the regions of the atlas.

return_one_based_indices

logical. Whether the indices should be 1-based. Indices are stored zero-based in label files, but R uses 1-based indices. Defaults to TRUE.

invert

logical. If TRUE, return the indices of all vertices which are NOT part of the region. Defaults to FALSE.

error_on_invalid_region

logical. Whether to throw an error if the given region does not appear in the region list of the annotation. If set to FALSE, this will be ignored and an empty vertex list will be returned. Defaults to TRUE.

Value

named list of integer vectors with label data: for each subject, the list of vertex indices in the label.

See Also

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


[Package fsbrain version 0.5.5 Index]