mean_var_Tol_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

mean_var_Tol_Param function

<dl><dt>meanTol, varTol</dt>
<dd>Tolerance for mean and variance of each data location.
Locations which do not meet these thresholds are masked out of the analysis.
Default: <code>1e-6</code> for both.</dd></dl>

Arguments

mean and variance tolerance — mean_var_Tol_Param

<dl>

<dt>meanTol, varTol</dt>
<dd>Tolerance for mean and variance of each data location.
Locations which do not meet these thresholds are masked out of the analysis.
Default: <code>1e-6</code> for both.</dd>

</dl>

mean and variance tolerance

mean_var_Tol_Param: mean and variance tolerance

Description

Arguments