ar_smooth_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

ar_smooth_Param function

<dl><dt>ar_smooth</dt>
<dd>(For prewhitening) The FWHM parameter for spatially
smoothing the coefficient estimates for the AR model to use for
prewhitening. Recall that
\(\sigma = \frac{FWHM}{2*sqrt(2*log(2)}\). Set to <code>0</code> to not smooth
the estimates. Default: <code>5</code>.</dd></dl>

Arguments

ar_smooth — ar_smooth_Param

<dl>

<dt>ar_smooth</dt>
<dd>(For prewhitening) The FWHM parameter for spatially
smoothing the coefficient estimates for the AR model to use for
prewhitening. Recall that
\(\sigma = \frac{FWHM}{2*sqrt(2*log(2)}\). Set to <code>0</code> to not smooth
the estimates. Default: <code>5</code>.</dd>

</dl>

ar_smooth

ar_smooth_Param: ar_smooth

Description

Arguments