nbhd_order_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

nbhd_order_Param function

<dl><dt>nbhd_order</dt>
<dd>For volumetric model. What order neighborhood around data
locations to keep? <code>0</code> for no neighbors, <code>1</code> for 1st-order
neighbors, <code>2</code> for 1st- and 2nd-order neighbors, etc. Smaller values
will provide greater computational efficiency at the cost of higher variance
around the edge of the data.</dd></dl>

Arguments

nbhd_order — nbhd_order_Param

<dl>

<dt>nbhd_order</dt>
<dd>For volumetric model. What order neighborhood around data
locations to keep? <code>0</code> for no neighbors, <code>1</code> for 1st-order
neighbors, <code>2</code> for 1st- and 2nd-order neighbors, etc. Smaller values
will provide greater computational efficiency at the cost of higher variance
around the edge of the data.</dd>

</dl>

nbhd_order

nbhd_order_Param: nbhd_order

Description

Arguments