id_activations.classical

Identification of areas of activation in a General Linear Model using classical methods

internal

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

id_activations.classical function

<dl><dt>model_obj</dt>
<dd>A <code>BayesGLM</code> object</dd>
<dt>tasks, session, alpha, gamma</dt>
<dd>See <code>id_activations</code>.</dd>
<dt>correction</dt>
<dd>(character) Either 'FWER' or 'FDR'. 'FWER' corresponds to the
family-wise error rate with Bonferroni correction, and 'FDR' refers to the
false discovery rate using Benjamini-Hochberg.</dd>
<dt>mesh</dt>
<dd>(Optional) An <code>"inla.mesh"</code> object (see <code>make_mesh</code> for
surface data). Only necessary for computing surface areas of identified activations.</dd></dl>

Arguments

Identification of areas of activation in a General Linear Model using classical methods — id_activations.classical

<dl>

<dt>model_obj</dt>
<dd>A <code>BayesGLM</code> object</dd>


<dt>tasks, session, alpha, gamma</dt>
<dd>See <code>id_activations</code>.</dd>


<dt>correction</dt>
<dd>(character) Either 'FWER' or 'FDR'. 'FWER' corresponds to the
family-wise error rate with Bonferroni correction, and 'FDR' refers to the
false discovery rate using Benjamini-Hochberg.</dd>


<dt>mesh</dt>
<dd>(Optional) An <code>"inla.mesh"</code> object (see <code>make_mesh</code> for
surface data). Only necessary for computing surface areas of identified activations.</dd>

</dl>

id_activations.classical: Identification of areas of activation in a General Linear Model using classical methods

Description

Usage

Value

Arguments