neuroatlas provides a unified interface for working with neuroimaging atlases and parcellations in R. Whether you’re conducting ROI-based analyses, visualizing brain data, or integrating different parcellation schemes, neuroatlas streamlines these tasks with consistent, user-friendly functions.
Features
- Multiple Atlas Support: Access Schaefer (100-1000 parcels), Glasser (360 regions), FreeSurfer ASEG, and Olsen MTL atlases
- Flexible Resampling: Transform atlases to different spaces and resolutions
-
ROI Analysis: Extract and analyze specific regions of interest with
get_roi(),map_atlas(), andreduce_atlas() - Surface & Volume: Work with both volumetric and surface-based parcellations
- TemplateFlow Integration: Access standardized templates via the Python TemplateFlow API
- Visualization: Integration with the ggseg ecosystem for brain visualization
Installation
You can install the development version from GitHub:
# install.packages("pak")
pak::pak("bbuchsbaum/neuroatlas")TemplateFlow Setup
For TemplateFlow functionality, you’ll need Python with the templateflow package:
# After installing neuroatlas:
neuroatlas::install_templateflow()Quick Start
library(neuroatlas)
# Get a Schaefer atlas (200 parcels, 7 networks)
schaefer <- get_schaefer_atlas(parcels = 200, networks = 7)
print(schaefer)
# Extract specific ROIs
roi <- get_roi(schaefer, "DefaultA")
# Get Glasser atlas
glasser <- get_glasser_atlas()
# Access templates via TemplateFlow
mni_brain <- get_template("MNI152NLin2009cAsym", variant = "brain")Palette demos
neuroatlas now includes perceptually-optimised palettes for atlas ROIs. For instance, you can generate a slice-aware palette for the Schaefer 200×7 atlas and feed it directly into ggseg:
library(neuroatlas)
library(dplyr)
library(ggseg)
schaefer <- get_schaefer_atlas(parcels = 200, networks = 7)
meta <- roi_metadata(schaefer)
pal <- roi_colors_maximin_view(
meta,
hemi_col = "hemi",
network_col = "network",
pair_col = "pair_id",
seed = 1
)
ggseg_schaefer(parcels = 200, networks = 7) +
geom_sf(aes(fill = pal$color[match(label, pal$roi)])) +
scale_fill_identity()Available Atlases
| Atlas | Function | Description |
|---|---|---|
| Schaefer | get_schaefer_atlas() |
Cortical parcellations (100-1000 regions, 7 or 17 networks) |
| Glasser | get_glasser_atlas() |
360-region multi-modal cortical parcellation |
| ASEG | get_aseg_atlas() |
FreeSurfer subcortical segmentation |
| Olsen MTL | get_olsen_mtl() |
Medial temporal lobe atlas with hippocampal subfields |
Documentation
- Getting Started - Introduction and basic usage
- Working with TemplateFlow - Template access and management
- Surface Parcellations - Surface-based atlas operations
- Function Reference - Complete API documentation