Create a Surface-Based MVPA Dataset Object

Creates a dataset object for surface-based MVPA analysis that encapsulates a training dataset, an optional test dataset, and a vertex mask.

Usage

mvpa_surface_dataset(train_data, test_data = NULL, mask = NULL, name = "")

Arguments

train_data

The training data set: must inherit from NeuroSurfaceVector

test_data

Optional test data set: must inherit from NeuroSurfaceVector (default: NULL)

mask

Optional binary mask for vertices. If NULL, creates mask from training data indices

name

Optional label to identify the dataset (e.g., "lh" or "rh" to indicate hemisphere)

Value

An mvpa_surface_dataset object (S3 class) containing:

train_data

The training data as a NeuroSurfaceVector instance

test_data

The test data as a NeuroSurfaceVector instance (if provided)

mask

A numeric vector indicating valid vertices (1) and excluded vertices (0)

name

Character string identifier for the dataset

Details

If no mask is provided, one will be created automatically using the indices from the training data. The mask will be a numeric vector with length equal to the number of nodes in the surface geometry.

See also

mvpa_dataset for creating volume-based MVPA datasets

mvpa_design for creating the corresponding design object

Examples

if (FALSE) { # \dontrun{
# Create surface dataset with automatic mask
train_surf <- NeuroSurfaceVector(geometry, data)
dataset <- mvpa_surface_dataset(train_surf, name="lh")

# Create dataset with test data and custom mask
test_surf <- NeuroSurfaceVector(geometry, test_data)
mask <- numeric(length(nodes(geometry)))
mask[roi_indices] <- 1
dataset <- mvpa_surface_dataset(train_surf, test_surf, mask, name="rh")
} # }