vis.subject.annot: Visualize an annotation for a subject.
In neuroconductor/fsbrain: Managing and Visualizing Brain Surface Data

Description Usage Arguments Value See Also Examples

Creates a surface mesh, loads the colors from the annotation, and renders the resulting colored mesh in an interactive window. If hemi is 'both', the data is rendered for the whole brain.

vis.subject.annot(
  subjects_dir,
  subject_id,
  atlas,
  hemi = "both",
  surface = "white",
  views = c("t4"),
  rgloptions = rglo(),
  rglactions = list(),
  outline = 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. Can also be a hemilist of already loaded annotations.
`hemi`	string, one of 'lh', 'rh', or 'both'. The hemisphere name. Used to construct the names of the label data files to be loaded.
`surface`	string. The display surface. E.g., "white", "pial", or "inflated". Defaults to "white".
`views`	list of strings. Valid entries include: 'si': single interactive view. 't4': tiled view showing the brain from 4 angles. 't9': tiled view showing the brain from 9 angles.
`rgloptions`	option list passed to `par3d`. Example: `rgloptions = list("windowRect"=c(50,50,1000,1000))`.
`rglactions`	named list. A list in which the names are from a set of pre-defined actions. The values can be used to specify parameters for the action. The following example clips outliers in the data before plotting and writes a screenshot in PNG format: `rglactions = list("snapshot_png"="~/fsbrain.png", "clip_data"=c(0.05, 0.95))`. See `rglactions`.
`outline`	logical, whether to draw an outline only instead of filling the regions. Defaults to 'FALSE'. Instead of passing 'TRUE', one can also pass a list of extra parameters to pass to `annot.outline`, e.g., `outline=list('outline_color'='#000000')`. Using this increases computation time dramatically, sorry for the performance.

list of coloredmeshes. The coloredmeshes used for the visualization.

Other visualization functions: vis.color.on.subject(), vis.data.on.fsaverage(), vis.data.on.subject(), vis.labeldata.on.subject(), vis.mask.on.subject(), vis.region.values.on.subject(), vis.subject.label(), vis.subject.morph.native(), vis.subject.morph.standard(), vis.symmetric.data.on.subject(), vislayout.from.coloredmeshes()

Other region-based visualization functions: vis.region.values.on.subject()

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   fsbrain::download_optional_data();
   subjects_dir = fsbrain::get_optional_data_filepath("subjects_dir");
   vis.subject.annot(subjects_dir, 'subject1', 'aparc', 'both');