Plotting tool for brain connectivity data

Sidhant Chopra

brainconn

THIS PACKAGE IS NO LONGER ACTIVELY MAINTAINED, USE AT YOUR OWN RISK

The purpose of this package is to allow for flexible, programmatic and
interactive plotting of brain connectivity data within Rstudio -
negating the need to swap to other visualization tools and allowing for
reproducible integration of visualization with analysis scripts that are
written in R.

The primary plotting functions: brainconn() and brainconn3D(). The
primary user input into these function is a connectivity matrix. Several
brain atlases come pre-installed and users can also provide a custom
atlas (see vignette).

The brainconn() function allows users to input a binary/weighted and
directed/non-directed (i.e. symmetric) connectivity matrix which can be
plotted onto MNI coordinates using ggraph.

The brainconn3D() allows users to input a binary and non-directed
connectivity matrix which is plotted in a 3D and interactive way using
plottly.

The atlases currently included with in the package can be listed using
the list_atlases() function: aal116, aal90, craddock200, dk68,
dk82_aspree, dkt62, gordon_333, shen_268, shen_368,
schaefer1000_n7, schaefer1000_n17, schaefer300_n7,
schaefer300_n17 (and all other iterations of the schaefer atlases).
Custom atlases can be easily added as long as you have centroid
coordinates in MNI space, see
vignette.
The check_atlas() function checks that custom atlases meet the
requirements of the plotting functions.

Installation

The package can be installed using devtools.

install.packages("remotes")
remotes::install_github("sidchop/brainconn")

The functions are now installed, and you may load them when you want to
use them.

Citation

If you use this package in your research, please cite:

Sidhant Chopra, Loïc Labache, Elvisha Dhamala, Edwina R Orchard,
Avram Holmes (2023). A Practical Guide for Generating Reproducible and
Programmatic Neuroimaging Visualizations ApertureNeuro.

https://doi.org/10.52294/001c.85104

Use

The package also has a vignette, to help you get started. You can access
it here,
or via R:

library(brainconn)
vignette("brainconn")

The primary user input is a connectivity matrix (conmat).

brainconn(atlas ="schaefer300_n7", conmat=example_unweighted_undirected, view="ortho")

Modifiable features for brainconn include: view, node.size,
node.color, edge.width, edge.color, edge.alpha,
background.alpha, labels and others (see vignette)

x <- example_unweighted_undirected
p <- brainconn3D(atlas ="schaefer300_n7", conmat=x, show.legend = F)
p

Included below is a gif of the interactive output (see
vignette
for more information):

Modifiable features for brainconn3D include: node.size,
node.color, edge.width, edge.color, adge.alpha,
background.alpha, labels and others (see
vignette)

Report bugs or requests

Don’t hesitate to ask for support or new features using github
issues.

Other R packages you might be intrested in:

• ggseg &
  ggseg3D: Plotting tool for
  brain atlases, in ggplot/plotly
• brainGraph: Graph theory
  analysis of brain MRI data
• fsbrain: Provides high-level
  functions to access (read and write) and visualize surface-based brain
  morphometry data (e.g. cortical thickness) for individual subjects and
  groups.
• NBR: Network Based R-statistics for
  Mixed Effects Models
• fslr: FSL-R Interface package