Sparse Independent Component Analysis R package SparseICA version 0.1.4 Provides an implementation of the Sparse ICA method in Wang et al. (2024) <doi:10.1080/01621459.2024.2370593> for estimating sparse independent source components of cortical surface functional MRI data, by addressing a non-smooth, non-convex optimization problem through the relax-and-split framework. This method effectively balances statistical independence and sparsity while maintaining computational efficiency. Software Depends: R (>= 4.1.0) Imports: Rcpp (>= 1.0.13), MASS (>= 7.3-58), irlba (>= 2.3.5), clue (>= 0.3), ciftiTools (>= 0.16), parallel (>= 4.1) LinkingTo: Rcpp, RcppArmadillo Zihang Wang <zhwang0378@gmail.com> Comprehensive R Archive Network (CRAN) Zihang Wang [aut, cre] (ORCID: <https://orcid.org/0000-0001-9032-5412>), Irina Gaynanova [aut] (ORCID: <https://orcid.org/0000-0002-4116-0268>), Aleksandr Aravkin [aut] (ORCID: <https://orcid.org/0000-0002-1875-1801>), Benjamin Risk [aut] (ORCID: <https://orcid.org/0000-0003-1090-0777>) GPL-3 2025-01-29 application/tgz https://CRAN.R-project.org/package=SparseICA doi:10.32614/CRAN.package.SparseICA