Bayes_Param

Performs a spatial Bayesian general linear model (GLM) for task
functional magnetic resonance imaging (fMRI) data on the cortical surface.
Additional models include group analysis and inference to detect thresholded
areas of activation. Includes direct support for the 'CIFTI' neuroimaging
file format. For more information see A. F. Mejia, Y. R. Yue, D. Bolin, F.
Lindgren, M. A. Lindquist (2020) <doi:10.1080/01621459.2019.1611582> and D.
Spencer, Y. R. Yue, D. Bolin, S. Ryan, A. F. Mejia (2022)
<doi:10.1016/j.neuroimage.2022.118908>.

Amanda Mejia

BayesfMRI

Spatial Bayesian Methods for Task Functional MRI Studies

Damon Pham

David Bolin

Yu (Ryan) Yue

Daniel Spencer

Sarah Ryan

Bayes_Param function

<dl><dt>Bayes</dt>
<dd>Perform spatial Bayesian modeling? Default: <code>TRUE</code>. If
<code>FALSE</code>, only perform classical (massive univariate) modeling. (The classical GLM
result is always returned, whether <code>Bayes</code> is <code>TRUE</code> or <code>FALSE</code>.)</dd></dl>

Arguments

Bayes — Bayes_Param

<dl>

<dt>Bayes</dt>
<dd>Perform spatial Bayesian modeling? Default: <code>TRUE</code>. If
<code>FALSE</code>, only perform classical (massive univariate) modeling. (The classical GLM
result is always returned, whether <code>Bayes</code> is <code>TRUE</code> or <code>FALSE</code>.)</dd>

</dl>

Bayes

Bayes_Param: Bayes

Description

Arguments