Run regional MVPA analysis on a specified MVPA model — run_regional.mvpa

This function runs a regional MVPA analysis using a specified MVPA model and region mask. The analysis can be customized to return model fits, predictions, and performance measures.

Usage

# S3 method for mvpa_model
run_regional(
  model_spec,
  region_mask,
  return_fits = FALSE,
  return_predictions = TRUE,
  compute_performance = TRUE,
  coalesce_design_vars = FALSE,
  ...
)

Arguments

model_spec: An object of type mvpa_model specifying the MVPA model to be used.
region_mask: A mask representing different regions in the brain image.
return_fits: Whether to return model fit for every ROI (default is FALSE to save memory).
return_predictions: Whether to return full prediction table with per trial probabilities (can be a large table, set FALSE to limit memory use).
compute_performance: logical indicating whether to compute performance measures (e.g. Accuracy, AUC).
coalesce_design_vars: Concatenate additional design variables with output stored in `prediction_table`.
...: Additional arguments to be passed to the function.

Value

A list of type regional_mvpa_result containing a named list of NeuroVol objects, where each element contains a performance metric and is labeled according to the metric used (e.g. Accuracy, AUC).