scale_BOLD_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

scale_BOLD_Param function

<dl><dt>scale_BOLD</dt>
<dd>Controls scaling the BOLD response at each location.<dl>
<dt>"mean":</dt>
<dd>Scale the data to percent local signal change.</dd></dl></dd><dt>"sd":</dt>
<dd>Scale the data by local standard deviation.</dd><dt>"none":</dt>
<dd>Center the data but do not scale it.</dd>
</dl>

Arguments

scale_BOLD — scale_BOLD_Param

<dl>

<dt>scale_BOLD</dt>
<dd>Controls scaling the BOLD response at each location.<dl>
<dt>"mean":</dt>
<dd>Scale the data to percent local signal change.</dd>

<dt>"sd":</dt>
<dd>Scale the data by local standard deviation.</dd>

<dt>"none":</dt>
<dd>Center the data but do not scale it.</dd>


</dl></dd>

</dl>

scale_BOLD

scale_BOLD_Param: scale_BOLD

Description

Arguments