buffer_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

buffer_Param function

<dl><dt>buffer</dt>
<dd>For volumetric model. The number of extra voxel layers around
the bounding box. Set to <code>NULL</code> for no buffer. (We recommend not
changing <code>buffer</code> unless you know what you're doing. Instead, to reduce
the number of boundary voxels, adjust <code>nbhd_order</code>).</dd></dl>

Arguments

buffer — buffer_Param

<dl>

<dt>buffer</dt>
<dd>For volumetric model. The number of extra voxel layers around
the bounding box. Set to <code>NULL</code> for no buffer. (We recommend not
changing <code>buffer</code> unless you know what you're doing. Instead, to reduce
the number of boundary voxels, adjust <code>nbhd_order</code>).</dd>

</dl>

buffer

buffer_Param: buffer

Description

Arguments