make_mask

Mask out data locations that are invalid (missing data, low mean, or low
variance) for any session.

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

make_mask function

<dl><dt>data</dt>
<dd>A list of sessions, where each session is a list with elements
<code>BOLD</code>, <code>design</code>, and optionally <code>nuisance</code>. See
<code>?is.BfMRI.sess</code> for details.</dd>
<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.
Defaults: <code>1e-6</code>.</dd>
<dt>verbose</dt>
<dd>Print messages counting how many locations are removed?
Default: <code>TRUE</code>.</dd></dl>

Arguments

Mask out invalid data — make_mask

<dl>

<dt>data</dt>
<dd>A list of sessions, where each session is a list with elements
<code>BOLD</code>, <code>design</code>, and optionally <code>nuisance</code>. See
<code>?is.BfMRI.sess</code> for details.</dd>


<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.
Defaults: <code>1e-6</code>.</dd>


<dt>verbose</dt>
<dd>Print messages counting how many locations are removed?
Default: <code>TRUE</code>.</dd>

</dl>

make_mask: Mask out invalid data

Description

Usage

Value

Arguments

Examples