scale_design_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

scale_design_Param function

<dl><dt>scale_design</dt>
<dd>Scale the design matrix by dividing each column by its
maximum and then subtracting the mean? Default: <code>TRUE</code>. If
<code>FALSE</code>, the design matrix is centered but not scaled.</dd></dl>

Arguments

scale_design — scale_design_Param

<dl>

<dt>scale_design</dt>
<dd>Scale the design matrix by dividing each column by its
maximum and then subtracting the mean? Default: <code>TRUE</code>. If
<code>FALSE</code>, the design matrix is centered but not scaled.</dd>

</dl>

scale_design

scale_design_Param: scale_design

Description

Arguments