num.threads_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

Daniel Spencer

Damon Pham

David Bolin

Sarah Ryan

Yu (Ryan) Yue

num.threads_Param function

<dl><dt>num.threads</dt>
<dd>The maximum number of threads to use for parallel
computations: prewhitening parameter estimation, and the inla-program model
estimation. Default: <code>4</code>. Note that parallel prewhitening requires the
<code>parallel</code> package.</dd></dl>

Arguments

num.threads — num.threads_Param

<dl>

<dt>num.threads</dt>
<dd>The maximum number of threads to use for parallel
computations: prewhitening parameter estimation, and the inla-program model
estimation. Default: <code>4</code>. Note that parallel prewhitening requires the
<code>parallel</code> package.</dd>

</dl>

num.threads

num.threads_Param: num.threads

Description

Arguments