mask_Param_vertices

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

mask_Param_vertices function

<dl><dt>mask</dt>
<dd>A length \(V\) logical vector indicating if each vertex is
within the input mask.</dd></dl>

Arguments

mask: vertices — mask_Param_vertices

<dl>

<dt>mask</dt>
<dd>A length \(V\) logical vector indicating if each vertex is
within the input mask.</dd>

</dl>

mask: vertices

mask_Param_vertices: mask: vertices

Description

Arguments