clusters_default_params.yml

# NOTE: commented parameters are set dynamically
PrepareClustersDataset:
  detection_sfreq: 200. # Hz
  evoked_length: 1. # seconds

ClustersLocalization:
  inv_method: MNE
  epochs_window: [-0.5, 0.5]
  spacing: ico5 # the number of sources in the forward model
  # case: CaseManager
  # sensors: True

PredictIZClusters:
  smoothing_steps_one_cluster: 3 # amount of smoothing for the individual clusters binary map
  smoothing_steps_final: 10 # amount of smoothing for the final prediction
  amplitude_threshold: 0.5 # amplitude threshold for the SourceEstimate binarization; Note that the amplitude values are between 0 and 1 because data are normalized.
  min_sources: 10 # select at least min_sources sources it there is less sources above the amplitude_threshold
  normalize_using_peak: yes # normalize clusters source estimate using peak amplitude; if False then slope and baseline predictions are normalized according slope and baseline maximum values respectively
  spacing: ico5 # the number of sources in the forward model
  # case: CaseManager
  # sensors: True