pipeline_config_default-deprecated.yml

%YAML 1.1
---
# CPAC Pipeline Configuration YAML file
# Version 1.8.8.dev2
#
# http://fcp-indi.github.io for more info.
#
# Tip: This file can be edited manually with a text editor for quick modifications.
FROM: blank

pipeline_setup:

  # Name for this pipeline configuration - useful for identification.
  # This string will be sanitized and used in filepaths
  pipeline_name: cpac-default-deprecated-pipeline
  output_directory:

    # Quality control outputs
    quality_control:

      # Generate quality control pages containing preprocessing and derivative outputs.
      generate_quality_control_images: On

anatomical_preproc:
  run: On
  acpc_alignment:
    T1w_brain_ACPC_template: $FSLDIR/data/standard/MNI152_T1_1mm_brain.nii.gz

  brain_extraction:
    run: On

segmentation:

  # Automatically segment anatomical images into white matter, gray matter,
  # and CSF based on prior probability maps.
  run: On

registration_workflows:
  anatomical_registration:
    run: On

  functional_registration:
    coregistration:

      # functional (BOLD/EPI) registration to anatomical (structural/T1)
      run: On
      boundary_based_registration:

        # this is a fork point
        #   run: [On, Off] - this will run both and fork the pipeline
        run: [On]

    func_registration_to_template:

      # these options modify the application (to the functional data), not the calculation, of the
      # T1-to-template and EPI-to-template transforms calculated earlier during registration
      # apply the functional-to-template (T1 template) registration transform to the functional data
      run: On

functional_preproc:
  run: On
  slice_timing_correction:

    # Interpolate voxel time courses so they are sampled at the same time points.
    # this is a fork point
    #   run: [On, Off] - this will run both and fork the pipeline
    run: [On]

  motion_estimates_and_correction:
    run: On
    motion_correction:

      # using: ['3dvolreg', 'mcflirt']
      # Forking is currently broken for this option.
      # Please use separate configs if you want to use each of 3dvolreg and mcflirt.
      # Follow https://github.com/FCP-INDI/C-PAC/issues/1935 to see when this issue is resolved.
      using: [3dvolreg]

  distortion_correction:

    # this is a fork point
    #   run: [On, Off] - this will run both and fork the pipeline
    run: [On]

  func_masking:
    run: On

  generate_func_mean:

    # Generate mean functional image
    run: On

  normalize_func:

    # Normalize functional image
    run: On

  coreg_prep:

    # Generate sbref
    run: On

nuisance_corrections:
  2-nuisance_regression:

    # this is a fork point
    #   run: [On, Off] - this will run both and fork the pipeline
    run: [On]

    # Select which nuisance signal corrections to apply
    Regressors:
      - Name: default
        Motion:
          include_delayed: On
          include_squared: On
          include_delayed_squared: On
        aCompCor:
          summary:
            method: DetrendPC
            components: 5
          tissues:
          - WhiteMatter
          - CerebrospinalFluid
          extraction_resolution: 2
        CerebrospinalFluid:
          summary: Mean
          extraction_resolution: 2
          erode_mask: On
        GlobalSignal:
          summary: Mean
        PolyOrt:
          degree: 2
        Bandpass:
          bottom_frequency: 0.01
          top_frequency: 0.1
          method: default
      - Name: defaultNoGSR
        Motion:
          include_delayed: On
          include_squared: On
          include_delayed_squared: On
        aCompCor:
          summary:
            method: DetrendPC
            components: 5
          tissues:
          - WhiteMatter
          - CerebrospinalFluid
          extraction_resolution: 2
        CerebrospinalFluid:
          summary: Mean
          extraction_resolution: 2
          erode_mask: On
        PolyOrt:
          degree: 2
        Bandpass:
          bottom_frequency: 0.01
          top_frequency: 0.1
          method: default

    # Process and refine masks used to produce regressors and time series for
    # regression.
    regressor_masks:
      erode_anatomical_brain_mask:

        # Erode brain mask in millimeters, default for brain mask is 30 mm
        # Brain erosion default is using millimeters.
        brain_mask_erosion_mm: 30

      erode_csf:

        # Erode cerebrospinal fluid mask in millimeters, default for cerebrospinal fluid is 30mm
        # Cerebrospinal fluid erosion default is using millimeters.
        csf_mask_erosion_mm: 30

      erode_wm:

        # Target volume ratio, if using erosion.
        # Default proportion is 0.6 for white matter mask.
        # If using erosion, using both proportion and millimeters is not recommended.
        # White matter erosion default is using proportion erosion method when use erosion for white matter.
        wm_erosion_prop: 0.6

      erode_gm:

        # Target volume ratio, if using erosion.
        # If using erosion, using both proportion and millimeters is not recommended.
        gm_erosion_prop: 0.6

timeseries_extraction:
  run: On
  connectivity_matrix:

    # Create a connectivity matrix from timeseries data
    # Options:
    #  ['AFNI', 'Nilearn', 'ndmg']
    using: [Nilearn, ndmg]

    # Options:
    #  ['Pearson', 'Partial']
    # Note: These options are not configurable for ndmg, which will ignore these options
    measure: [Pearson, Partial]

amplitude_low_frequency_fluctuation:

  # ALFF & f/ALFF
  # Calculate Amplitude of Low Frequency Fluctuations (ALFF) and fractional ALFF (f/ALFF) for all voxels.
  run: On

regional_homogeneity:

  # ReHo
  # Calculate Regional Homogeneity (ReHo) for all voxels.
  run: On

voxel_mirrored_homotopic_connectivity:

  # VMHC
  # Calculate Voxel-mirrored Homotopic Connectivity (VMHC) for all voxels.
  run: On

network_centrality:

  # Calculate Degree, Eigenvector Centrality, or Functional Connectivity Density.
  run: On