fMRI IRM Toolbox (fIT) for Matlab – (1792 downloads)

This Matlab toolbox allows you to run the Infinite Relational Model (IRM), Bayesian Community Detection (BCD), Infinite Hofman-Wiggins (IHW), Infinite Diagonal Model (IDM) on functional magnetic resonance imaging (fMRI) data.

Visualization Toolbox for Latent Variable Modeling of fMRI (VITLAM)- v0.9.0, zip

The Visualization Toolbox for Latent Variable Modeling of fMRI holds a collection of 2D and 3D visualization methods for latent variable modeling in functional magnetic resonance imaging (fMRI). The methods are implemented in Matlab™.
Follow on GitHub (
Latest release (

Multisubject Archetypal Analysis (MSAA) Toolbox – v1.0.0, zip

This toolbox extends Archetypal Analysis (AA) to multisubject data, allows subject specific heteroscedastic spatial or temporal noise modeling and can be used to identify either spatial or temporal archetypes in fMRI. The algorithms are implemented in Matlab™ and support the use of graphical processing units (GPUs) for high performance computing.
Follow on GitHub (
Latest release (

The Probabilistic Latent Variable Modeling (PLVM) Toolbox for Multisubject Data – v1.0.0, zip

This toolbox holds a collection of latent variable algorithms implemented in Matlab™. The algorithms support the use of graphical processing units (GPUs) for high performance computing. Version 1.0.0 contain algorithms for probabilistic sparse Principal Component Analysis (psPCA) and probabilistic sparse Factor Analysis (psFA).
Follow on GitHub (
Latest release (

Non-parametric Dynamic Functional Connectivity Modeling (NDFC)- v1.0.2, zip

The non-parametric dynamic functional connectivity modeling (NDFC) software provides code for the non-parametric methods described in the manuscript “Predictive Assesment for Models of Dynamic Functional Connectivity”.

Infinite von Mises-Fisher Mixture Modeling – v0.12-alpha, zip

The infinite von Mises-Fisher Mixture Model as described in the manuscript “Infinite von Mises-Fisher Mixture Modeling of Whole-Brain fMRI Data”.

Stochastic Block-modelling toolbox – SBM_toolbox

This toolbox presents a platform for efficient stochastic block-modelling of large-scaled complex networks. It implements a collection of parametric and non-parametric models for various network topologies, utilizing a fully customization Markov Chain Monte Carlo sampling scheme. The tools are implemented as standalone software in high-performance C++.

Predictive Assessment of Brain Parcellations – software

This software presents the predictive assessment as well as tools to generate synthethic analyses results used in the paper “Using connectomics for predictive assessment of brain parcellations”, NeuroImage 2021.