plot.prior.nifti

Based on <code>oro.nifti::image</code>.

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.

Amanda Mejia

BayesBrainMap

Estimate Brain Networks and Connectivity with Population-Derived
Priors

Damon Pham

Nohelia Da Silva

plot.prior.nifti function

<dl><dt>x</dt>
<dd>The prior from <code>estimate_prior.nifti</code></dd>
<dt>what</dt>
<dd>The <code>"maps"</code> (default) on the brain, or the <code>"FC"</code>
matrix. If both are desired, use two separate <code>plot</code> calls to first
plot the maps and then plot the FC.
If <code>"FC"</code>, the default color scale will be from blue (-1) to red (1).
This can be changed with the <code>colFUN</code> argument to
<code>plot_FC_gg</code>.</dd>
<dt>stat</dt>
<dd>Which prior statistic to plot: the <code>"mean"</code> (default),
<code>"sd"</code> for the square root of the variance template, or <code>"var"</code>
for the variance template.</dd>
<dt>FC_method</dt>
<dd>If <code>what=="FC"</code>: empirical (<code>"empirical"</code>) (default),
Inverse-Wishart (<code>"IW"</code>), or Cholesky (<code>"Chol"</code>).</dd>
<dt>var_method</dt>
<dd><code>"non-negative"</code> (default) or <code>"unbiased"</code>, for
the variance estimate of the maps. Note that FC variance estimates are
always non-negative.</dd>
<dt>plane, n_slices, slices</dt>
<dd>Anatomical plane and which slice indices to
show.
Default: 9 axial slices.</dd>
<dt>...</dt>
<dd>Additional arguments to <code>oro.nifti::image</code>
if <code>what=="maps"</code>, or <code>plot_FC_gg</code> if
<code>what=="FC"</code>.</dd></dl>

Arguments

Plot prior — plot.prior.nifti

<dl>

<dt>x</dt>
<dd>The prior from <code>estimate_prior.nifti</code></dd>


<dt>what</dt>
<dd>The <code>"maps"</code> (default) on the brain, or the <code>"FC"</code>
matrix. If both are desired, use two separate <code>plot</code> calls to first
plot the maps and then plot the FC.
If <code>"FC"</code>, the default color scale will be from blue (-1) to red (1).
This can be changed with the <code>colFUN</code> argument to
<code>plot_FC_gg</code>.</dd>


<dt>stat</dt>
<dd>Which prior statistic to plot: the <code>"mean"</code> (default),
<code>"sd"</code> for the square root of the variance template, or <code>"var"</code>
for the variance template.</dd>


<dt>FC_method</dt>
<dd>If <code>what=="FC"</code>: empirical (<code>"empirical"</code>) (default),
Inverse-Wishart (<code>"IW"</code>), or Cholesky (<code>"Chol"</code>).</dd>


<dt>var_method</dt>
<dd><code>"non-negative"</code> (default) or <code>"unbiased"</code>, for
the variance estimate of the maps. Note that FC variance estimates are
always non-negative.</dd>


<dt>plane, n_slices, slices</dt>
<dd>Anatomical plane and which slice indices to
show.
Default: 9 axial slices.</dd>


<dt>...</dt>
<dd>Additional arguments to <code>oro.nifti::image</code>
if <code>what=="maps"</code>, or <code>plot_FC_gg</code> if
<code>what=="FC"</code>.</dd>

</dl>

plot.prior.nifti: Plot prior

Description

Usage

Value

Arguments

Details