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rsDCM  

Robust and Sparse Dynamic Causal Modelling for Functional MRI
View on CRAN: Click here


Download and install rsDCM package within the R console
Install from CRAN:
install.packages("rsDCM")

Install from Github:
library("remotes")
install_github("cran/rsDCM")

Install by package version:
library("remotes")
install_version("rsDCM", "0.1.0")



Attach the package and use:
library("rsDCM")
Maintained by
Godfred Arhin
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-10-06
Latest Update: 2026-10-06
Description:
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'.
How to cite:
Godfred Arhin (2026). rsDCM: Robust and Sparse Dynamic Causal Modelling for Functional MRI. R package version 0.1.0, https://cran.r-project.org/web/packages/rsDCM. Accessed 24 Oct. 2026.
Previous versions and publish date:
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Complete documentation for rsDCM
Functions, R codes and Examples using the rsDCM R package
Full rsDCM package functions and examples
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