Robust and Sparse Dynamic Causal Modelling for Functional MRI R package rsDCM version 0.1.0 Provides a robust and sparse method for group-level Dynamic Causal Modelling (DCM) of functional magnetic resonance imaging (fMRI) data: Student-t weighting of subjects for robustness, combined with a nonlocal product-moment (pMOM) spike-and-slab prior for sparse selection of group-level effects (<doi:10.48550/arXiv.2609.06379>). The package also provides an R implementation of single-subject DCM for fMRI using variational Laplace inversion (Friston et al., 2003 <doi:10.1016/S1053-8119(03)00202-7>), including the bilinear neural state equation and the Buxton-Friston hemodynamic response model, ported from the 'SPM25' (version 25.01.02) toolbox for 'MATLAB'. Software Depends: R (>= 4.0.0) Imports: Matrix, expm, MASS, methods, stats, utils Suggests: testthat (>= 3.0.0), knitr, rmarkdown, R.matlab, withr Godfred Arhin <arhin0122@gmail.com> Comprehensive R Archive Network (CRAN) Godfred Arhin [aut, cre, trl], Nilotpal Sanyal [aut], SPM25 Authors [ctb, cph] (Original MATLAB SPM25 (v25.01.02) implementation; see LICENSE.note) GPL-2 2026-10-06 application/tgz https://CRAN.R-project.org/package=rsDCM doi:10.32614/CRAN.package.rsDCM