scale_design_mat

internal

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_mat function

<dl><dt>design_mat</dt>
<dd>The original (unscaled) design matrix that is T x K, where
T is the number of time points, and k is the number of task covariates</dd></dl>

Arguments

Scale the design matrix — scale_design_mat

<dl>

<dt>design_mat</dt>
<dd>The original (unscaled) design matrix that is T x K, where
T is the number of time points, and k is the number of task covariates</dd>

</dl>

Scale the design matrix

scale_design_mat: Scale the design matrix

Description

Usage

Value

Arguments