useR! 2026

The MACverse: A unified collection of packages for microstructure-augmented connectivity analysis in R

9 Jul 2026, 11:30

20m

Talks (15-20 minutes) Talks

Speaker

Aymeric Stamm (Department of Mathematics Jean Leray, UMR CNRS 6629, Nantes University)

Description

Diffusion magnetic resonance imaging (MRI) is a non-invasive imaging technique that allows us to probe the microstructure in the brain at a mesoscopic scale by making the MR signal sensitive to the diffusion of water molecules in the brain, which is restricted or hindered by cellular structures such as axons or glial cells. Diffusion MRI suffers from a poor spatial resolution, which yields the use of mixture models to account for multiple tissue populations in each voxel. Many such models have been devised in the literature (see here) for an overview. Microstructure models can then be used to infer the structural connectivity by tracing so-called streamlines that follow the main directions of diffusion throughout the brain. This process is called tractography. Most of the literature so far has analysed either the microstructure or the connectivity separately, but there is a growing interest in combining both types of information to get a more complete picture of the brain's structure and function.

The vast majority of softwares for microstructure and connectivity analysis such as {dmipy}, {dipy} of {scilpy}, are implemented in Python and gather into a single package all the functionalities for microstructure and connectivity analysis, which makes them hard to maintain and extend on the development side and hard to use on the user side. In R, according to the Medical Image Analysis CRAN task view, the only currently available packages for microstructure and connectivity analysis are {dti} and {TractoR}, which share the same drawbacks as the Python packages and do not include ways to model microstructure-augmented connectivity (MAC).

The MACverse aims to develop a unified collection of packages for MAC analysis in R, in which each package performs a single task and all interact seamlessly with each other. The MACverse is currently in development, but we will give an overview of the main packages that will be included in the collection:

• {fiber}: provides a data structure for MAC data;
• {mascot}: provides easy access to recent macroscale structural connectomes of the Human brain obtained from diffusion MRI data through diffusion modeling and tractography;
• {midi}: provides tools to simulate the MR signal attenuation predicted by state-of-the-art microstructure models under different experimental conditions; the package comes with a companion Shiny app;
• {riot}: provides an R interface for importing and exporting tractography data to and from R;
• {rtists}: provides visualization tools for tissue integrity superimposed on tractography streamlines.

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