run_regional.mvpa_model: Run regional MVPA analysis on a specified MVPA model

In bbuchsbaum/rMVPA: Multivoxel Pattern Analysis in R

Run regional MVPA analysis on a specified MVPA model

Description

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 class '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).

bbuchsbaum/rMVPA documentation built on April 28, 2024, 6:30 a.m.