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Run Searchlight Analysis

run_searchlight.Rd

Execute a searchlight analysis using multivariate pattern analysis.

Usage

run_searchlight(
  model_spec,
  radius,
  method = c("standard", "randomized"),
  niter = NULL,
  ...
)

Arguments

model_spec

A mvpa_model instance containing the model specifications

radius

The searchlight radius in millimeters

method

The type of searchlight, either 'randomized' or 'standard'

niter

The number of searchlight iterations (used only for 'randomized' method)

...

Extra arguments passed to specific searchlight methods. Currently supported:

  • batch_size: Integer specifying the number of searchlights to process per batch. Default is 10% of total searchlights. Lower values reduce memory usage but may impact performance. This controls how searchlights are grouped for processing - each batch is processed sequentially, while searchlights within a batch are processed in parallel.

Value

A named list of NeuroVol objects containing performance metrics (e.g., AUC) at each voxel location

Examples

# \donttest{
  # Generate sample dataset with categorical response
  dataset <- gen_sample_dataset(
    D = c(8,8,8),           # 8x8x8 volume
    nobs = 100,             # 100 observations
    response_type = "categorical",
    data_mode = "image",
    blocks = 3,             # 3 blocks for cross-validation
    nlevels = 2             # binary classification
  )
  
  # Create cross-validation specification using blocks
  cval <- blocked_cross_validation(dataset$design$block_var)
  
  # Load the SDA classifier (Shrinkage Discriminant Analysis)
  model <- load_model("sda_notune")
  
  # Create MVPA model
  mspec <- mvpa_model(
    model = model,
    dataset = dataset$dataset,
    design = dataset$design,
    model_type = "classification",
    crossval = cval
  )
  
  # Run searchlight analysis
  results <- run_searchlight(
    mspec,
    radius = 8,            # 8mm radius
    method = "standard"    # Use standard searchlight
  )
#> INFO [2025-09-28 22:01:18] Running standard searchlight with radius = 8
#> INFO [2025-09-28 22:01:18] creating standard searchlight
#> INFO [2025-09-28 22:01:18] running standard searchlight iterator
#> INFO [2025-09-28 22:01:18] Processing batch 1/11 (24 ROIs in this batch)
#> INFO [2025-09-28 22:01:26] Processing batch 2/11 (23 ROIs in this batch)
#> INFO [2025-09-28 22:01:33] Processing batch 3/11 (23 ROIs in this batch)
#> INFO [2025-09-28 22:01:40] Processing batch 4/11 (23 ROIs in this batch)
#> INFO [2025-09-28 22:01:47] Processing batch 5/11 (23 ROIs in this batch)
#> INFO [2025-09-28 22:01:54] Processing batch 6/11 (23 ROIs in this batch)
#> INFO [2025-09-28 22:02:01] Processing batch 7/11 (23 ROIs in this batch)
#> INFO [2025-09-28 22:02:08] Processing batch 8/11 (23 ROIs in this batch)
#> INFO [2025-09-28 22:02:15] Processing batch 9/11 (23 ROIs in this batch)
#> INFO [2025-09-28 22:02:22] Processing batch 10/11 (23 ROIs in this batch)
#> INFO [2025-09-28 22:02:28] Processing batch 11/11 (23 ROIs in this batch)
#> INFO [2025-09-28 22:02:35] 
#> MVPA Iteration Complete
#> - Total ROIs: 254
#> - Processed: 254
#> - Skipped: 0
#> WARN [2025-09-28 22:02:35] Observed probabilities map skipped: expected 512 rows but found 100.
  
  # Run with custom batch size for memory management
  # results <- run_searchlight(
  #   mspec,
  #   radius = 8,
  #   method = "standard",
  #   batch_size = 500      # Process 500 searchlights per batch
  # )
  
  # Results contain performance metrics
  # Access them with results$performance
# }