galerkin_db

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

galerkin_db function

<dl><dt>FV</dt>
<dd>Matrix of faces in triangularization</dd>
<dt>P</dt>
<dd>Matrix of vertex locations in triangularization</dd>
<dt>surface</dt>
<dd>(logical) Will this create the SPDE matrices for a surface
or not?</dd></dl>

Arguments

Create FEM matrices — galerkin_db

<dl>

<dt>FV</dt>
<dd>Matrix of faces in triangularization</dd>


<dt>P</dt>
<dd>Matrix of vertex locations in triangularization</dd>


<dt>surface</dt>
<dd>(logical) Will this create the SPDE matrices for a surface
or not?</dd>

</dl>

Create FEM matrices

galerkin_db: Create FEM matrices

Description

Usage

Value

Arguments