The <file>fmri_mask.nii.gz</file> dataset defines the mask used in the fMRI analysis for <file>fmri_filtered_data.nii.gz</file>.
	The mask used here is an all-brain mask; it just removes non-brain regions, as the result of applying a brain extraction tool to the <file>fmri.nii.gz</file> dataset.
	However, other masks may be defined to select regions of interest (ROIs).

datasets

mask

Compute Unified Device Architecture (CUDA) is a software
        platform for massively parallel high-performance computing on
        NVIDIA GPUs. This package provides a CUDA implementation of a
        Bayesian multilevel model for the analysis of brain fMRI data.
        A fMRI data set consists of time series of volume data in 4D
        space. Typically, volumes are collected as slices of 64 x 64
        "voxels". Analysis of fMRI data often relies on fitting linear
        regression models at each voxel of the brain. The volume of the
        data to be processed, and the type of statistical analysis to
        perform in fMRI analysis, call for high-performance computing
        strategies. In this package, the CUDA programming model uses a
        separate thread for fitting a linear regression model at each
        voxel in parallel. The global statistical model implements a
        Gibbs Sampler for hierarchical linear models with a normal
        prior. This model has been proposed by Rossi, Allenby and
        McCulloch in "Bayesian Statistics and Marketing", Chapter 3,
        and is referred to as "rhierLinearModel" in the R-package
        "bayesm". A notebook equipped with a NVIDIA "GeForce 8400M GS"
        card having Compute Capability 1.1 has been used in the tests.

Adelino da Silva

cudaBayesreg

CUDA Parallel Implementation of a Bayesian Multilevel Model for
        fMRI Data Analysis

mask function

docType

The file <file>fmri_mask.nii.gz</file> is in ungzipped NIFTI format.
	The R-package <pkg>oro.nifti</pkg> is required by <pkg>cudaBayesreg</pkg> to read gunzipped NIFTI files.
	This file may be obtained from <file>fmri.nii.gz</file> by applying FSL/FEAT of FSL/BET pre-processing tools.
	Similar preparation procedures for fMRI datasets are available in the SPM toolbox (<url>http://www.fil.ion.ucl.ac.uk/spm/</url>).

mask: Example of mask file used in processing the visual-auditory test dataset

Description

Arguments

docType

format

References