Title: | All-Resolution Inference |
---|---|
Description: | It performs All-Resolutions Inference (ARI) on functional Magnetic Resonance Image (fMRI) data. As a main feature, it estimates lower bounds for the proportion of active voxels in a set of clusters as, for example, given by a cluster-wise analysis. The method is described in Rosenblatt, Finos, Weeda, Solari, Goeman (2018) <doi:10.1016/j.neuroimage.2018.07.060>. |
Authors: | Livio Finos, Jelle Goeman, Wouter Weeda, Jonathan Rosenblatt, Aldo Solari |
Maintainer: | Livio Finos <[email protected]> |
License: | GPL (>= 2) |
Version: | 0.2 |
Built: | 2024-12-03 06:36:58 UTC |
Source: | CRAN |
It performs All-Resolutions Inference on fMRI data. As a main feature, it estimates lower bounds for the proportion of active voxels in a set of clusters as, for example, given by a cluster-wise analysis.
all of us
pvalue_name <- system.file("extdata", "pvalue.nii.gz", package="ARIbrain") cluster_name <- system.file("extdata", "cluster_th_3.2.nii.gz", package="ARIbrain") zstat_name <- system.file("extdata", "zstat.nii.gz", package="ARIbrain") mask_name <- system.file("extdata", "mask.nii.gz", package="ARIbrain") ARI(Pmap = pvalue_name, clusters= cluster_name, mask=mask_name, Statmap = zstat_name)
pvalue_name <- system.file("extdata", "pvalue.nii.gz", package="ARIbrain") cluster_name <- system.file("extdata", "cluster_th_3.2.nii.gz", package="ARIbrain") zstat_name <- system.file("extdata", "zstat.nii.gz", package="ARIbrain") mask_name <- system.file("extdata", "mask.nii.gz", package="ARIbrain") ARI(Pmap = pvalue_name, clusters= cluster_name, mask=mask_name, Statmap = zstat_name)
Valid Circular Inference (ARI) for Brain Imaging
ARI(Pmap, clusters, mask = NULL, alpha = 0.05, Statmap = function(ix) -qnorm(Pmap[ix]), summary_stat = c("max", "center-of-mass"), silent = FALSE)
ARI(Pmap, clusters, mask = NULL, alpha = 0.05, Statmap = function(ix) -qnorm(Pmap[ix]), summary_stat = c("max", "center-of-mass"), silent = FALSE)
Pmap |
3D array of p-values or a (character) nifti file name. |
clusters |
3D array of cluster ids (0 when voxel does not belong to any cluster) or a (character) nifti file name. |
mask |
3D array of locicals (i.e. |
alpha |
Significance level. |
Statmap |
Statistics (usually t-values) on which the summaries are based. Can be either
a 3D array, a (character) nifti file name or a function with argument |
summary_stat |
Choose among |
silent |
|
A matrix
reporting Size, FalseNull, TrueNull, ActiveProp and other statistics for each cluster.
pvalue_name <- system.file("extdata", "pvalue.nii.gz", package="ARIbrain") cluster_name <- system.file("extdata", "cluster_th_3.2.nii.gz", package="ARIbrain") zstat_name <- system.file("extdata", "zstat.nii.gz", package="ARIbrain") mask_name <- system.file("extdata", "mask.nii.gz", package="ARIbrain") print(mask_name) print(pvalue_name) print(cluster_name) print(zstat_name) ARI(Pmap = pvalue_name, clusters= cluster_name, mask=mask_name, Statmap = zstat_name)
pvalue_name <- system.file("extdata", "pvalue.nii.gz", package="ARIbrain") cluster_name <- system.file("extdata", "cluster_th_3.2.nii.gz", package="ARIbrain") zstat_name <- system.file("extdata", "zstat.nii.gz", package="ARIbrain") mask_name <- system.file("extdata", "mask.nii.gz", package="ARIbrain") print(mask_name) print(pvalue_name) print(cluster_name) print(zstat_name) ARI(Pmap = pvalue_name, clusters= cluster_name, mask=mask_name, Statmap = zstat_name)
Get spatially-connected clusters starting from a 3D map of logical values
cluster_threshold(map, max_dist = sqrt(3))
cluster_threshold(map, max_dist = sqrt(3))
map |
3D map of logical values. |
max_dist |
maximum distance allowed to in the same cluster. By default:
|
a 3D map (same size of map
) with integer values identifying the cluster and 0 elsewhere.
## Not run: Tmap = RNifti::readNifti(system.file("extdata", "zstat.nii.gz", package="ARIbrain")) clstr=cluster_threshold(Tmap>3.2) table(clstr) ## End(Not run)
## Not run: Tmap = RNifti::readNifti(system.file("extdata", "zstat.nii.gz", package="ARIbrain")) clstr=cluster_threshold(Tmap>3.2) table(clstr) ## End(Not run)