templateICAr
Estimate Brain Networks and Connectivity with ICA and Empirical Priors
Implements the template ICA (independent components analysis) model proposed in Mejia et al. (2020) doi:10.1080/01621459.2019.1679638 and the spatial template ICA model proposed in proposed in Mejia et al. (2022) doi:10.1080/10618600.2022.2104289. Both models estimate subject-level brain as deviations from known population-level networks, which are estimated using standard ICA algorithms. Both models employ an expectation-maximization algorithm for estimation of the latent brain networks and unknown model parameters. Includes direct support for 'CIFTI', 'GIFTI', and 'NIFTI' neuroimaging file formats.
- Version0.9.1
- R version≥ 3.6.0
- LicenseGPL-3
- Needs compilation?Yes
- templateICAr citation info
- Last release11/21/2024
Documentation
Team
Amanda Mejia
MaintainerShow author detailsDaniel Spencer
Damon Pham
Mary Beth Nebel
Show author detailsRolesContributor
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- Imports9 packages
- Suggests10 packages