rsDCM: Robust and Sparse Dynamic Causal Modelling for Functional MRI
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'.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
Matrix, expm, MASS, methods, stats, utils |
| Suggests: |
testthat (≥ 3.0.0), knitr, rmarkdown, R.matlab, withr |
| Published: |
2026-10-06 |
| DOI: |
10.32614/CRAN.package.rsDCM (may not be active yet) |
| Author: |
Godfred Arhin [aut, cre, trl],
Nilotpal Sanyal [aut],
SPM25 Authors [ctb, cph] (Original MATLAB SPM25 (v25.01.02)
implementation; see LICENSE.note) |
| Maintainer: |
Godfred Arhin <arhin0122 at gmail.com> |
| BugReports: |
https://github.com/Kay202/rsDCM/issues |
| License: |
GPL-2 |
| URL: |
https://github.com/Kay202/rsDCM |
| NeedsCompilation: |
no |
| Citation: |
rsDCM citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
rsDCM results |
Documentation:
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