organize_data_pw

Transforms the usual TxV BOLD data matrix Y into vector form, and
the usual TxK design matrix X into big sparse matrix form for use in
Bayesian GLM.

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

organize_data_pw function

<dl><dt>y</dt>
<dd>the TxV data matrix containing the fMRI timeseries</dd>
<dt>X</dt>
<dd>the TxK design matrix with K task-related columns</dd>
<dt>transpose</dt>
<dd>Check orientation of data, which, if <code>TRUE</code>, will transpose
the data when the number of time points is greater than the number of voxels.
Note: this is not always true for subcortical regions.</dd></dl>

Arguments

Organize prewhitened data for Bayesian GLM — organize_data_pw

<dl>

<dt>y</dt>
<dd>the TxV data matrix containing the fMRI timeseries</dd>


<dt>X</dt>
<dd>the TxK design matrix with K task-related columns</dd>


<dt>transpose</dt>
<dd>Check orientation of data, which, if <code>TRUE</code>, will transpose
the data when the number of time points is greater than the number of voxels.
Note: this is not always true for subcortical regions.</dd>

</dl>

organize_data_pw: Organize prewhitened data for Bayesian GLM

Description

Usage

Value

Arguments

Details