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BayesBrainMap

Estimate Brain Networks and Connectivity with Population-Derived Priors

v0.2.0 · Feb 3, 2026 · GPL-3

Description

Implements Bayesian brain mapping with population-derived priors, including the original model described in Mejia et al. (2020) <doi:10.1080/01621459.2019.1679638>, the model with spatial priors described in Mejia et al. (2022) <doi:10.1080/10618600.2022.2104289>, and the model with population-derived priors on functional connectivity described in Mejia et al. (2025) <doi:10.1093/biostatistics/kxaf022>. Population-derived priors are based on templates representing established brain network maps, for example derived from independent component analysis (ICA), parcellations, or other methods.  Model estimation is based on expectation-maximization or variational Bayes algorithms. Includes direct support for 'CIFTI', 'GIFTI', and 'NIFTI' neuroimaging file formats.

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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
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Dependency Network

Dependencies Reverse dependencies abind fMRItools fMRIscrub foreach Matrix matrixStats pesel SQUAREM BayesBrainMap

Version History

new 0.2.0 Mar 10, 2026