BayesBrainMap0.2.0 package

Estimate Brain Networks and Connectivity with Population-Derived Priors

add_str

Combine additive terms in string

bdiag_m

Block diagonal matrix

bdiag_m2

Bdiag m2

BrainMap

BrainMap

check_parallel_packages

Check for required parallel packages

check_req_ifti_pkg

Check required packages for the data format

Chol_samp_fun

Cholesky-based FC sampling

compute_LL_std

Compute LL for EM Bayesian brain mapping

compute_mu_s

Compute posterior mean and precision of s

compute_R_inv

Compute SPDE and prior precision matrices for S

dim_reduce

PCA-based Dimension Reduction and Prewhitening

dual_reg2

Dual Regression wrapper

EM_BBM.spatial

EM Algorithms for Bayesian brain maps

engagements

engagements

estimate_nu_matrix

Estimate IW dof parameter nu based on method of moments

estimate_nu

Universally estimate IW dof parameter nu based on method of moments, s...

estimate_prior_FC_Chol

Estimate Cholesky FC prior

estimate_prior_FC_empirical

Estimate empirical FC prior

estimate_prior_FC_IW

Estimate IW FC prior

estimate_prior_from_DR_two

Estimate prior from DR estimates (when there are two measurements)

estimate_prior_from_DR

Estimate prior from DR

estimate_prior

Estimate prior

estimate.ESS

Estimation of effective sample size

export_prior

Export prior

fit_BBM

Bayesian brain mapping

format_engagement_name

Format engagement name

get_FORMAT

Get FORMAT from format

getInvCovAR

Compute inverse covariance matrix for AR process (up to a constant sca...

GSR_Param

GSR

halflogdetX

Half log determinant

hpf_param

hpf

id_engagements

Engagements of (spatial) Bayesian brain mapping

INLA_check

Check for INLA

IW_var_cor

Compute theoretical Inverse-Wishart variance of correlation matrix ele...

IW_var

Compute theoretical Inverse-Wishart variance of covariance matrix elem...

lik

Compute likelihood in SPDE model for ESS estimation

LL_SQUAREM

Log-likelihood SQUAREM

LL2_kappa

Compute part of kappa log-likelihood

loglik_kappa_est

Kappa log-likelihood

make_mask

Create a mask based on vertices that are invalid

make_mesh_2D

Make 2D INLA mesh

make_mesh

Make INLA mesh from "surf" object

make_Pmat

Make permutation matrix

norm_BOLD

Normalize BOLD data

orthonorm

Orthonormalizes a square, invertible matrix

plot.bMap_eng.cifti

Plot engagements

plot.bMap.cifti

Plot fit_BBM estiamte

plot.bMap.matrix

Plot prior

plot.bMap.nifti

Plot prior

plot.prior.cifti

Plot prior

plot.prior.gifti

Plot prior

plot.prior.matrix

Plot prior

plot.prior.nifti

Plot prior

pw_estimate

Estimate residual autocorrelation for prewhitening

Q2_max_check

Check Q2_max

removebs_prior

Remove brain structure from CIFTI prior

resample_prior

Resample CIFTI prior

rm_nuisIC

Remove nuisance ICs from data

scale_Param

scale

sqrt_XtX

Compute matrix square root of X'X

struct_prior

Apply data structure to priors

summary.bMap_eng.cifti

Summarize a "bMap_eng.cifti" object

summary.bMap_eng.matrix

Summarize a "bMap_eng.matrix" object

summary.bMap_eng.nifti

Summarize a "bMap_eng.nifti" object

summary.bMap.cifti

Summarize a "bMap.cifti" object

summary.bMap.matrix

Summarize a "bMap.matrix" object

summary.bMap.nifti

Summarize a "bMap.nifti" object

summary.prior.cifti

Summarize a "prior.cifti" object

summary.prior.gifti

Summarize a "prior.gifti" object

summary.prior.matrix

Summarize a "prior.matrix" object

summary.prior.nifti

Summarize a "prior.nifti" object

TR_param

TR

update_A_Chol

Update A for VB FC Bayesian brain mapping using Cholesky prior for FC

update_A

Update A for VB FC Bayesian brain mapping using IW prior on FC

update_S

Update S for VB FC Bayesian brain mapping

update_tau2

Update tau for VB FC Bayesian brain mapping

UpdateTheta_BBM

Parameter Estimates in EM Algorithm for Bayesian brain map

UpdateThetaSQUAREM_BBM

Update theta SQUAREM

var_sq_err_constrained

Compute the overall error between empirical and theoretical variance o...

var_sq_err

Compute the error between empirical and theoretical variance of covari...

varTol_Param

varTol

VB_FC_BBM

VB_FC_BBM

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.

  • Maintainer: Amanda Mejia
  • License: GPL-3
  • Last published: 2026-02-03