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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "BayesBrainMap" in publications use:'
type: software
license: GPL-3.0-only
title: 'BayesBrainMap: Estimate Brain Networks and Connectivity with Population-Derived
  Priors'
version: 0.2.0
doi: 10.1080/01621459.2019.1679638
identifiers:
- type: doi
  value: 10.32614/CRAN.package.BayesBrainMap
abstract: Implements Bayesian brain mapping with population-derived priors, including
  the original model described in Mejia et al. (2020) <https://doi.org/10.1080/01621459.2019.1679638>,
  the model with spatial priors described in Mejia et al. (2022) <https://doi.org/10.1080/10618600.2022.2104289>,
  and the model with population-derived priors on functional connectivity described
  in Mejia et al. (2025) <https://doi.org/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.
authors:
- family-names: Mejia
  given-names: Amanda
  email: mandy.mejia@gmail.com
- family-names: Pham
  given-names: Damon
  email: damondpham@gmail.com
  orcid: https://orcid.org/0000-0001-7563-4727
preferred-citation:
  type: article
  title: 'Template Independent Component Analysis: Targeted and Reliable Estimation
    of Subject-level Brain Networks Using Big Data Population Priors'
  authors:
  - family-names: Mejia
    given-names: Amanda F
  - family-names: Nebel
    given-names: Mary Beth
  - family-names: Wang
    given-names: Yikai
  - family-names: Caffo
    given-names: Brian S
  - family-names: Guo
    given-names: Ying
  journal: Journal of the American Statistical Association
  year: '2020'
  volume: '115'
  issue: '531'
  publisher:
    name: American Statistical Association
  doi: 10.1080/01621459.2019.1679638
  start: '1151'
  end: '1177'
repository: https://mandymejia.r-universe.dev
repository-code: https://github.com/mandymejia/BayesBrainMap
commit: 343e939bfa5bb91d3062993fffaccaf35050211b
url: https://github.com/mandymejia/BayesBrainMap
date-released: '2026-02-06'
contact:
- family-names: Mejia
  given-names: Amanda
  email: mandy.mejia@gmail.com
references:
- type: article
  title: Template Independent Component Analysis with spatial priors for accurate
    subject-level brain network estimation and inference
  authors:
  - family-names: Mejia
    given-names: Amanda F
  - family-names: Bolin
    given-names: David
  - family-names: Yue
    given-names: Yu Ryan
  - family-names: Wang
    given-names: Jiongran
  - family-names: Caffo
    given-names: Brian S
  - family-names: Nebel
    given-names: Mary Beth
  journal: Journal of Computational and Graphical Statistics
  year: '2022'
  issue: just-accepted
  publisher:
    name: American Statistical Association
  doi: 10.1080/10618600.2022.2104289
  start: '1'
  end: '35'