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  "Title": "Estimate Brain Networks and Connectivity with ICA and Empirical\nPriors",
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  "Authors@R": "c(\nperson(given = \"Amanda\",\nfamily = \"Mejia\",\nemail = \"mandy.mejia@gmail.com\",\nrole = c(\"aut\", \"cre\")),\nperson(given = \"Damon\",\nfamily = \"Pham\",\nemail = \"damondpham@gmail.com\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0001-7563-4727\")),\nperson(given = \"Daniel\",\nfamily = \"Spencer\",\nemail = \"danieladamspencer@gmail.com\",\nrole = c(\"ctb\"),\ncomment = c(ORCID = \"0000-0002-9705-3605\")),\nperson(given = \"Mary Beth\",\nfamily = \"Nebel\",\nemail = \"Nebel@kennedykrieger.org\",\nrole = c(\"ctb\"))\n)",
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  "Description": "Implements the template ICA (independent components\nanalysis) model proposed in Mejia et al. (2020)\n<doi:10.1080/01621459.2019.1679638> and the spatial template\nICA model proposed in Mejia et al. (2022)\n<doi:10.1080/10618600.2022.2104289>. Both models estimate\nsubject-level brain as deviations from known population-level\nnetworks, which are estimated using standard ICA algorithms.\nBoth models employ an expectation-maximization algorithm for\nestimation of the latent brain networks and unknown model\nparameters. Includes direct support for 'CIFTI', 'GIFTI', and\n'NIFTI' neuroimaging file formats. Note, this package has been\ndeprecated and superseded by 'BayesBrainMap', which includes\nmodel improvements and new names for the core functions.",
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  "BugReports": "https://github.com/mandymejia/templateICAr/issues",
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  "Repository": "https://mandymejia.r-universe.dev",
  "Date/Publication": "2026-09-17 05:18:29 UTC",
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    "estimate_template_FC",
    "estimate_template_from_DR",
    "export_template",
    "getInvCovAR",
    "groupICA.cifti",
    "make_mesh",
    "make_mesh_2D",
    "norm_BOLD",
    "orthonorm",
    "resample_template",
    "sqrt_XtX",
    "templateICA"
  ],
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    {
      "page": "activations",
      "title": "Activations of (spatial) template ICA",
      "topics": [
        "activations"
      ]
    },
    {
      "page": "bdiag_m2",
      "title": "Bdiag m2",
      "topics": [
        "bdiag_m2"
      ]
    },
    {
      "page": "Chol_samp_fun",
      "title": "Cholesky-based FC sampling",
      "topics": [
        "Chol_samp_fun"
      ]
    },
    {
      "page": "dim_reduce",
      "title": "PCA-based Dimension Reduction and Prewhitening",
      "topics": [
        "dim_reduce"
      ]
    },
    {
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      "title": "Dual Regression",
      "topics": [
        "dual_reg"
      ]
    },
    {
      "page": "dual_reg_parc",
      "title": "Multiple regression for parcel data",
      "topics": [
        "dual_reg_parc"
      ]
    },
    {
      "page": "EM_templateICA",
      "title": "EM Algorithms for Template ICA Models",
      "topics": [
        "EM_templateICA",
        "EM_templateICA.independent",
        "EM_templateICA.spatial"
      ]
    },
    {
      "page": "estimate_nu",
      "title": "Universally estimate IW dof parameter nu based on method of moments, so that no empirical variance is under-estimated",
      "topics": [
        "estimate_nu"
      ]
    },
    {
      "page": "estimate_nu_matrix",
      "title": "Estimate IW dof parameter nu based on method of moments",
      "topics": [
        "estimate_nu_matrix"
      ]
    },
    {
      "page": "estimate_template",
      "title": "Estimate template",
      "topics": [
        "estimate_template",
        "estimate_template.cifti",
        "estimate_template.gifti",
        "estimate_template.nifti"
      ]
    },
    {
      "page": "estimate_template_FC",
      "title": "Estimate FC template",
      "topics": [
        "estimate_template_FC"
      ]
    },
    {
      "page": "estimate_template_from_DR",
      "title": "Estimate template from DR",
      "topics": [
        "estimate_template_from_DR"
      ]
    },
    {
      "page": "estimate.ESS",
      "title": "Estimation of effective sample size",
      "topics": [
        "estimate.ESS"
      ]
    },
    {
      "page": "export_template",
      "title": "Export template",
      "topics": [
        "export_template"
      ]
    },
    {
      "page": "getInvCovAR",
      "title": "Compute inverse covariance matrix for AR process (up to a constant scaling factor)",
      "topics": [
        "getInvCovAR"
      ]
    },
    {
      "page": "groupICA.cifti",
      "title": "Perform group ICA based on CIFTI data",
      "topics": [
        "groupICA.cifti"
      ]
    },
    {
      "page": "IW_var",
      "title": "Compute theoretical Inverse-Wishart variance of covariance matrix elements",
      "topics": [
        "IW_var"
      ]
    },
    {
      "page": "IW_var_cor",
      "title": "Compute theoretical Inverse-Wishart variance of correlation matrix elements",
      "topics": [
        "IW_var_cor"
      ]
    },
    {
      "page": "lik",
      "title": "Compute likelihood in SPDE model for ESS estimation",
      "topics": [
        "lik"
      ]
    },
    {
      "page": "make_mesh",
      "title": "Make INLA mesh from '\"surf\"' object",
      "topics": [
        "make_mesh"
      ]
    },
    {
      "page": "make_mesh_2D",
      "title": "Make 2D INLA mesh",
      "topics": [
        "make_mesh_2D"
      ]
    },
    {
      "page": "norm_BOLD",
      "title": "Normalize BOLD data",
      "topics": [
        "norm_BOLD"
      ]
    },
    {
      "page": "orthonorm",
      "title": "Orthonormalizes a square, invertible matrix",
      "topics": [
        "orthonorm"
      ]
    },
    {
      "page": "plot.template.cifti",
      "title": "Plot template",
      "topics": [
        "plot.template.cifti"
      ]
    },
    {
      "page": "plot.template.gifti",
      "title": "Plot template",
      "topics": [
        "plot.template.gifti"
      ]
    },
    {
      "page": "plot.template.matrix",
      "title": "Plot template",
      "topics": [
        "plot.template.matrix"
      ]
    },
    {
      "page": "plot.template.nifti",
      "title": "Plot template",
      "topics": [
        "plot.template.nifti"
      ]
    },
    {
      "page": "plot.tICA_act.cifti",
      "title": "Plot activations",
      "topics": [
        "plot.tICA_act.cifti"
      ]
    },
    {
      "page": "plot.tICA.cifti",
      "title": "Plot template",
      "topics": [
        "plot.tICA.cifti"
      ]
    },
    {
      "page": "plot.tICA.matrix",
      "title": "Plot template",
      "topics": [
        "plot.tICA.matrix"
      ]
    },
    {
      "page": "plot.tICA.nifti",
      "title": "Plot template",
      "topics": [
        "plot.tICA.nifti"
      ]
    },
    {
      "page": "pw_estimate",
      "title": "Estimate residual autocorrelation for prewhitening",
      "topics": [
        "pw_estimate"
      ]
    },
    {
      "page": "resample_template",
      "title": "Resample CIFTI template",
      "topics": [
        "resample_template"
      ]
    },
    {
      "page": "sqrt_XtX",
      "title": "Compute matrix square root of X'X",
      "topics": [
        "sqrt_XtX"
      ]
    },
    {
      "page": "summary.template.cifti",
      "title": "Summarize a '\"template.cifti\"' object",
      "topics": [
        "print.summary.template.cifti",
        "print.template.cifti",
        "summary.template.cifti"
      ]
    },
    {
      "page": "summary.template.gifti",
      "title": "Summarize a '\"template.gifti\"' object",
      "topics": [
        "print.summary.template.gifti",
        "print.template.gifti",
        "summary.template.gifti"
      ]
    },
    {
      "page": "summary.template.matrix",
      "title": "Summarize a '\"template.matrix\"' object",
      "topics": [
        "print.summary.template.matrix",
        "print.template.matrix",
        "summary.template.matrix"
      ]
    },
    {
      "page": "summary.template.nifti",
      "title": "Summarize a '\"template.nifti\"' object",
      "topics": [
        "print.summary.template.nifti",
        "print.template.nifti",
        "summary.template.nifti"
      ]
    },
    {
      "page": "summary.tICA_act.cifti",
      "title": "Summarize a '\"tICA_act.cifti\"' object",
      "topics": [
        "print.summary.tICA_act.cifti",
        "print.tICA_act.cifti",
        "summary.tICA_act.cifti"
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    },
    {
      "page": "summary.tICA_act.matrix",
      "title": "Summarize a '\"tICA_act.matrix\"' object",
      "topics": [
        "print.summary.tICA_act.matrix",
        "print.tICA_act.matrix",
        "summary.tICA_act.matrix"
      ]
    },
    {
      "page": "summary.tICA_act.nifti",
      "title": "Summarize a '\"tICA_act.nifti\"' object",
      "topics": [
        "print.summary.tICA_act.nifti",
        "print.tICA_act.nifti",
        "summary.tICA_act.nifti"
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    },
    {
      "page": "summary.tICA.cifti",
      "title": "Summarize a '\"tICA.cifti\"' object",
      "topics": [
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        "print.tICA.cifti",
        "summary.tICA.cifti"
      ]
    },
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      "page": "summary.tICA.matrix",
      "title": "Summarize a '\"tICA.matrix\"' object",
      "topics": [
        "print.summary.tICA.matrix",
        "print.tICA.matrix",
        "summary.tICA.matrix"
      ]
    },
    {
      "page": "summary.tICA.nifti",
      "title": "Summarize a '\"tICA.nifti\"' object",
      "topics": [
        "print.summary.tICA.nifti",
        "print.tICA.nifti",
        "summary.tICA.nifti"
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    {
      "page": "templateICA",
      "title": "Template ICA",
      "topics": [
        "templateICA"
      ]
    },
    {
      "page": "UpdateTheta_templateICA",
      "title": "Parameter Estimates in EM Algorithm for Template ICA Model",
      "topics": [
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        "UpdateTheta_templateICA.independent",
        "UpdateTheta_templateICA.spatial"
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    {
      "page": "UT2mat",
      "title": "Transform upper-triangular elements to matrix form",
      "topics": [
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    },
    {
      "page": "var_sq_err",
      "title": "Compute the error between empirical and theoretical variance of covariance matrix elements",
      "topics": [
        "var_sq_err"
      ]
    },
    {
      "page": "var_sq_err_constrained",
      "title": "Compute the overall error between empirical and theoretical variance of CORRELATION matrix elements",
      "topics": [
        "var_sq_err_constrained"
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