This function processes the input data and prepares the regions for MVPA analysis by extracting voxel indices for each region of interest (ROI) specified in the region_mask.
Value
A list containing information about the regions for further processing: * allrois: A vector of unique ROI labels. * region_vec: A vector representation of the region_mask. * region_set: A sorted vector of unique ROI labels in the region_mask. * vox_iter: A list containing voxel indices for each ROI. * lens: A vector containing the number of voxels in each ROI. * keep: A logical vector indicating if an ROI should be kept for analysis (those with more than one voxel).
Examples
# Create example data
sample_data <- gen_sample_dataset(c(5, 5, 5), nobs = 100, blocks = 4)
# Create a simple region mask with 3 ROIs
mask_vol <- sample_data$dataset$mask
region_mask <- neuroim2::NeuroVol(
sample(1:3, size = sum(mask_vol > 0), replace = TRUE),
space = neuroim2::space(mask_vol),
indices = which(mask_vol > 0)
)
# Create a basic model spec
model_spec <- list(dataset = sample_data$dataset)
# Prepare regional data
regional_data <- prep_regional(model_spec, region_mask)