Desikan-Killiany cortical atlas plot

This package mainly contains a plotting function ggseg3d and data.frames of different brain atlases for plotting. Plotting results of analyses on regions or networks often involves swapping between statistical tools, like R and Matlab, and software for brain imaging to correctly visualise analysis results.

This package aims to make it possible to plot results directly through R.

The ggseg package comes with a function of the same name which can be used to plot brain segmentations. The function displays the Desikan-Killiany cortical atlas by default, as in the following example

# install.packages("remotes")
# remotes::install_github("LCBC-UiO/ggseg")
library(ggseg)

ggseg()


The function has several arguments that allow selecting the hemisphere, the view or even the color and size of the segmentation lines.

#install.packages("remotes")
#remotes::install_github("LCBC-UiO/ggseg")
library(ggseg)
library(ggplot2)

ggseg(mapping = aes(fill = region),
      colour = "gray3",    # Color of the segmentation
      size = 1,            # Size of the segmentation
      hemisphere = "left", # or "right"
      view = "lateral") +  # or "medial"
  theme(legend.position = "none")

Use cases

The package also provides a geom named geom_brain. In the following example each region is colorized and a legend with four columns is displayed.

# install.packages("remotes")
# remotes::install_github("LCBC-UiO/ggseg")
library(ggseg)
# install.packages("ggplot2")
library(ggplot2)

ggplot() +
  geom_brain(atlas = dk) +
  guides(fill = guide_legend(ncol = 4)) +
  theme_void() +
  theme(legend.position = "bottom",
        legend.text = element_text(size = 8))

Example atlas

The other atlas that comes with the package is aseg, which provides the Freesurfer automatic subcortical segmentation of a brain volume.

# install.packages("remotes")
# remotes::install_github("LCBC-UiO/ggseg")
library(ggseg)
# install.packages("ggplot2")
library(ggplot2)

ggplot() +
  geom_brain(atlas = aseg) +
  theme_void() +
  theme(legend.position = "bottom",
        legend.text = element_text(size = 8)) +
  guides(fill = guide_legend(ncol = 4))