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mascot

The goal of mascot is to provide easy access to recent macroscale structural connectomes of the Human brain obtained from diffusion MRI data through diffusion modeling and subsequent so-called tractography.

Installation

You can install the development version of mascot from GitHub with:

# install.packages("remotes")
remotes::install_github("astamm/mascot")

Datasets

mascot provides access to two large white matter tractography datasets, both stored as fiber::bundle objects and fetched on demand — no bulky data files are bundled with the package itself.

HCP1065 population-averaged atlas

A whole-brain tractography atlas averaged across 1,065 healthy adults from the Human Connectome Project. It contains 87 white matter bundles, each represented as a single population-level streamline set.

# List all available bundles
available_bundles("HCP1065")

# Load one bundle directly by name
cst_left <- mascot::import_bundle(dataset = "HCP1065", bundle = "CST_left")
# Or use the convenience function
cst_left <- mascot::HCP1065_CST_L()

License: CC BY-SA 4.0.

Citation:

Yeh FC. Population-based tract-to-region connectome of the human brain and its hierarchical topology. Nat Commun 13, 4933 (2022). https://doi.org/10.1038/s41467-022-32595-4

Users must also comply with the HCP data-use terms.

TractSeg per-subject bundles

72 white matter tracts segmented in each of 105 HCP Young Adult subjects using TractSeg, redistributed from the Zenodo archive (DOI: 10.5281/zenodo.1477956). Each bundle is downloaded on first use and cached locally.

# List all available TractSeg bundles
available_bundles("TractSeg")

# Import one bundle (downloads on first call, cached afterwards)
cst_left <- mascot::import_bundle(dataset = "TractSeg", bundle = "CST_left", subjects = 1L)
# Or use the convenience function
cst_left <- mascot::TractSeg_CST_left(subjects = 1L)

License: CC BY-NC 4.0 — non-commercial use only.

Citation:

Wasserthal J, Neher P, Maier-Hein KH. TractSeg — Fast and accurate white matter tract segmentation. NeuroImage 183, 239–253 (2018). https://doi.org/10.1016/j.neuroimage.2018.07.070

Users must also comply with the HCP data-use terms.

Bundle objects

All bundles are returned as fiber::bundle objects with two slots:

  • @streamlines — a list of streamline objects, each carrying:

    • @points - a P×3P \times 3 matrix of 3D coordinates for the PP points along the streamline.
    • @point_data - a list of numeric-only vectors of length PP containing point-level data (e.g., FA, MD, etc.) for each point along the streamline.
    • @streamline_data - a list of scalars (of any type) containing streamline data that are not common across all streamlines in the bundle.

  • @streamline_data - a list of vectors containing streamline-level data that are common across all streamlines in the bundle.

  • @bundle_data — a list of scalars (of any type) containing metadata about the bundle (name, source dataset, etc.).

See the fiber package documentation for full details on working with these objects.