%YAML 1.1
---
# CPAC Pipeline Configuration YAML file
# Version 1.8.8.dev1
#
# http://fcp-indi.github.io for more info.
#
# Tip: This file can be edited manually with a text editor for quick modifications.
FROM: default
pipeline_setup:
# Name for this pipeline configuration - useful for identification.
# This string will be sanitized and used in filepaths
pipeline_name: cpac_preproc
system_config:
# Select Off if you intend to run CPAC on a single machine.
# If set to On, CPAC will attempt to submit jobs through the job scheduler / resource manager selected below.
on_grid:
SGE:
# SGE Parallel Environment to use when running CPAC.
# Only applies when you are running on a grid or compute cluster using SGE.
parallel_environment: cpac
# The maximum amount of memory each participant's workflow can allocate.
# Use this to place an upper bound of memory usage.
# - Warning: 'Memory Per Participant' multiplied by 'Number of Participants to Run Simultaneously'
# must not be more than the total amount of RAM.
# - Conversely, using too little RAM can impede the speed of a pipeline run.
# - It is recommended that you set this to a value that when multiplied by
# 'Number of Participants to Run Simultaneously' is as much RAM you can safely allocate.
maximum_memory_per_participant: 3
working_directory:
# Deletes the contents of the Working Directory after running.
# This saves disk space, but any additional preprocessing or analysis will have to be completely re-run.
remove_working_dir: Off
Amazon-AWS:
# Enable server-side 256-AES encryption on data to the S3 bucket
s3_encryption: On
segmentation:
tissue_segmentation:
Template_Based:
# These masks should be in the same space of your registration template, e.g. if
# you choose 'EPI Template' , below tissue masks should also be EPI template tissue masks.
#
# Options: ['T1_Template', 'EPI_Template']
template_for_segmentation: []
registration_workflows:
functional_registration:
EPI_registration:
ANTs:
# EPI registration configuration - synonymous with T1_registration
# parameters under anatomical registration above
parameters:
nuisance_corrections:
2-nuisance_regression:
# Select which nuisance signal corrections to apply
Regressors:
- Name: Regressor_1
Bandpass:
bottom_frequency: 0.01
top_frequency: 0.1
CerebrospinalFluid:
erode_mask: On
extraction_resolution: 2
summary: Mean
GlobalSignal:
summary: Mean
Motion:
include_delayed: On
include_delayed_squared: On
include_squared: On
PolyOrt:
degree: 2
aCompCor:
extraction_resolution: 2
summary:
components: 5
method: DetrendPC
tissues:
- WhiteMatter
- CerebrospinalFluid
- Name: Regressor_2
Bandpass:
bottom_frequency: 0.01
top_frequency: 0.1
CerebrospinalFluid:
erode_mask: On
extraction_resolution: 2
summary: Mean
Motion:
include_delayed: On
include_delayed_squared: On
include_squared: On
PolyOrt:
degree: 2
aCompCor:
extraction_resolution: 2
summary:
components: 5
method: DetrendPC
tissues:
- WhiteMatter
- CerebrospinalFluid
timeseries_extraction:
run: Off
amplitude_low_frequency_fluctuation:
# ALFF & f/ALFF
# Calculate Amplitude of Low Frequency Fluctuations (ALFF) and fractional ALFF (f/ALFF) for all voxels.
run: Off
regional_homogeneity:
# ReHo
# Calculate Regional Homogeneity (ReHo) for all voxels.
run: Off
voxel_mirrored_homotopic_connectivity:
# VMHC
# Calculate Voxel-mirrored Homotopic Connectivity (VMHC) for all voxels.
run: Off
network_centrality:
# Calculate Degree, Eigenvector Centrality, or Functional Connectivity Density.
run: Off