fmri: Example of a real visual-auditory dataset

In cudaBayesregData: Data sets for the examples used in the package "cudaBayesreg"

Description

The ‘fmri.nii.gz’ dataset is included in the FSL & FreeSurfer Course available form the Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), University of Oxford. The dataset has been used as a demonstration of the FEAT fMRI Analysis tool, provided by the FMRIB Software Library (FSL) (www.fmrib.ox.ac.uk/fsl). This dataset is from an auditory-visual experiment. Auditory stimulation was applied as an alternating "boxcar" with 45s-on-45s-off and visual stimulation was applied as an alternating "boxcar" with 30s-on-30s-off. The TR is 3 seconds. The dataset includes just 45 timepoints and 5 slices from the original 4D data. The file ‘fmri.nii.gz’ is provided as reference only, since it is not used directly by cudaBayesreg. The file actually used in the package is the file ‘fmri_filtered_func_data.nii’. This file may be obtained from ‘fmri.nii.gz’ by applying pre-preprocessing tools, such as pre-filtering and motion correction. These pre-processing tools are readily available in the FSL/FEAT package. Similar preparation procedures for fMRI datasets are available in the SPM toolbox (http://www.fil.ion.ucl.ac.uk/spm/).

Format

The file ‘fmri.nii.gz’ is in gzipped NIFTI format. The R-package oro.nifti is required by cudaBayesreg to read NIFTI files.

References

Brandon Whitcher, Volker Schmid and Andrew Thornton (2011), R package oro.nifti: Rigorous - NIfTI Input / Output, R package version 0.2.5,
http://CRAN.R-project.org/package=oro.nifti.

S.M. Smith et.al.(2004), Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23(S1):208-219.

FSL & FreeSurfer Course, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), University of Oxford. (www.fmrib.ox.ac.uk/fsl).

cudaBayesregData documentation built on May 29, 2017, 9:19 p.m.