second part:
# EPI template mask.
EPI_template_mask: None
ANTs:
# EPI registration configuration - synonymous with T1_registration
# parameters under anatomical registration above
parameters:
- collapse-output-transforms: 0
- dimensionality: 3
- initial-moving-transform :
initializationFeature: 0
- transforms:
- Rigid:
gradientStep : 0.1
metric :
type : MI
metricWeight: 1
numberOfBins : 32
samplingStrategy : Regular
samplingPercentage : 0.25
convergence:
iteration : 1000x500x250x100
convergenceThreshold : 1e-08
convergenceWindowSize : 10
smoothing-sigmas : 3.0x2.0x1.0x0.0
shrink-factors : 8x4x2x1
use-histogram-matching : True
- Affine:
gradientStep : 0.1
metric :
type : MI
metricWeight: 1
numberOfBins : 32
samplingStrategy : Regular
samplingPercentage : 0.25
convergence:
iteration : 1000x500x250x100
convergenceThreshold : 1e-08
convergenceWindowSize : 10
smoothing-sigmas : 3.0x2.0x1.0x0.0
shrink-factors : 8x4x2x1
use-histogram-matching : True
- SyN:
gradientStep : 0.1
updateFieldVarianceInVoxelSpace : 3.0
totalFieldVarianceInVoxelSpace : 0.0
metric:
type : CC
metricWeight: 1
radius : 4
convergence:
iteration : 100x100x70x20
convergenceThreshold : 1e-09
convergenceWindowSize : 15
smoothing-sigmas : 3.0x2.0x1.0x0.0
shrink-factors : 6x4x2x1
use-histogram-matching : True
winsorize-image-intensities :
lowerQuantile : 0.01
upperQuantile : 0.99
# Interpolation method for writing out transformed EPI images.
# Possible values: Linear, BSpline, LanczosWindowedSinc
interpolation: LanczosWindowedSinc
FSL-FNIRT:
# Configuration file to be used by FSL to set FNIRT parameters.
# It is not necessary to change this path unless you intend to use custom FNIRT parameters or a non-standard template.
fnirt_config: T1_2_MNI152_2mm
# Interpolation method for writing out transformed EPI images.
# Possible values: trilinear, sinc, spline
interpolation: sinc
# Identity matrix used during FSL-based resampling of BOLD-space data throughout the pipeline.
# It is not necessary to change this path unless you intend to use a different template.
identity_matrix: /usr/share/fsl/5.0/etc/flirtsch/ident.mat
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
# apply the functional-to-template (EPI template) registration transform to the functional data
run_EPI: Off
output_resolution:
# The resolution (in mm) to which the preprocessed, registered functional timeseries outputs are written into.
# NOTE:
# selecting a 1 mm or 2 mm resolution might substantially increase your RAM needs- these resolutions should be selected with caution.
# for most cases, 3 mm or 4 mm resolutions are suggested.
# NOTE:
# this also includes the single-volume 3D preprocessed functional data,
# such as the mean functional (mean EPI) in template space
func_preproc_outputs: 3mm
# The resolution (in mm) to which the registered derivative outputs are written into.
# NOTE:
# this is for the single-volume functional-space outputs (i.e. derivatives)
# thus, a higher resolution may not result in a large increase in RAM needs as above
func_derivative_outputs: 3mm
target_template:
# choose which template space to transform derivatives towards
# using: ['T1_template', 'EPI_template']
# this is a fork point
# NOTE:
# this will determine which registration transform to use to warp the functional
# outputs and derivatives to template space
using: ['T1_template']
T1_template:
# Standard Skull Stripped Template. Used as a reference image for functional registration.
# This can be different than the template used as the reference/fixed for T1-to-template registration.
T1w_brain_template_funcreg: /usr/share/fsl/5.0/data/standard/MNI152_T1_${func_resolution}_brain.nii.gz
# Standard Anatomical Brain Image with Skull.
# This can be different than the template used as the reference/fixed for T1-to-template registration.
T1w_template_funcreg: /usr/share/fsl/5.0/data/standard/MNI152_T1_${func_resolution}.nii.gz
# Template to be used during registration.
# It is not necessary to change this path unless you intend to use a non-standard template.
T1w_brain_template_mask_funcreg: /usr/share/fsl/5.0/data/standard/MNI152_T1_${func_resolution}_brain_mask.nii.gz
# a standard template for resampling if using float resolution
T1w_template_for_resample: $FSLDIR/data/standard/MNI152_T1_1mm_brain.nii.gz
EPI_template:
# EPI template for direct functional-to-template registration
# (bypassing coregistration and the anatomical-to-template transforms)
EPI_template_funcreg: s3://fcp-indi/resources/cpac/resources/epi_hbn.nii.gz
# EPI template mask.
EPI_template_mask_funcreg: None
# a standard template for resampling if using float resolution
EPI_template_for_resample: $FSLDIR/data/standard/MNI152_T1_1mm_brain.nii.gz
ANTs_pipelines:
# Interpolation method for writing out transformed functional images.
# Possible values: Linear, BSpline, LanczosWindowedSinc
interpolation: LanczosWindowedSinc
FNIRT_pipelines:
# Interpolation method for writing out transformed functional images.
# Possible values: trilinear, sinc, spline
interpolation: sinc
# Identity matrix used during FSL-based resampling of functional-space data throughout the pipeline.
# It is not necessary to change this path unless you intend to use a different template.
identity_matrix: /usr/share/fsl/5.0/etc/flirtsch/ident.mat
apply_transform:
# options: 'default', 'abcd', 'single_step_resampling', 'dcan_nhp'
# 'default': apply func-to-anat and anat-to-template transforms on motion corrected functional image.
# 'abcd': apply motion correction, func-to-anat and anat-to-template transforms on each of raw functional volume using FSL applywarp based on ABCD-HCP pipeline.
# 'single_step_resampling': apply motion correction, func-to-anat and anat-to-template transforms on each of raw functional volume using ANTs antsApplyTransform based on fMRIPrep pipeline.
using: 'default'
functional_preproc:
run: On
truncation:
# First timepoint to include in analysis.
# Default is 0 (beginning of timeseries).
# First timepoint selection in the scan parameters in the data configuration file, if present, will over-ride this selection.
# Note: the selection here applies to all scans of all participants.
start_tr: 0
# Last timepoint to include in analysis.
# Default is None or End (end of timeseries).
# Last timepoint selection in the scan parameters in the data configuration file, if present, will over-ride this selection.
# Note: the selection here applies to all scans of all participants.
stop_tr: None
scaling:
# Scale functional raw data, usually used in rodent pipeline
run: Off
# Scale the size of the dataset voxels by the factor.
scaling_factor: 10
despiking:
# Run AFNI 3dDespike
# this is a fork point
# run: [On, Off] - this will run both and fork the pipeline
run: [Off]
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]
# use specified slice time pattern rather than one in header
tpattern: None
# align each slice to given time offset
# The default alignment time is the average of the 'tpattern' values (either from the dataset header or from the tpattern option).
tzero: None
motion_estimates_and_correction:
motion_estimates:
# calculate motion statistics BEFORE slice-timing correction
calculate_motion_first: Off
# calculate motion statistics AFTER motion correction
calculate_motion_after: On
motion_correction:
# using: ['3dvolreg', 'mcflirt']
# this is a fork point
using: ['3dvolreg']
# option parameters
AFNI-3dvolreg:
# This option is useful when aligning high-resolution datasets that may need more alignment than a few voxels.
functional_volreg_twopass: On
# Choose motion correction reference. Options: mean, median, selected_volume, fmriprep_reference
motion_correction_reference: ['mean']
# Choose motion correction reference volume
motion_correction_reference_volume: 0
motion_estimate_filter:
# Filter physiological (respiration) artifacts from the head motion estimates.
# Adapted from DCAN Labs filter.
# https://www.ohsu.edu/school-of-medicine/developmental-cognition-and-neuroimaging-lab
# https://www.biorxiv.org/content/10.1101/337360v1.full.pdf
# this is a fork point
# run: [On, Off] - this will run both and fork the pipeline
run: [Off]
# options: "notch", "lowpass"
filter_type: "notch"
# Number of filter coefficients.
filter_order: 4
# Dataset-wide respiratory rate data from breathing belt.
# Notch filter requires either:
# "breathing_rate_min" and "breathing_rate_max"
# or
# "center_frequency" and "filter_bandwitdh".
# Lowpass filter requires either:
# "breathing_rate_min"
# or
# "lowpass_cutoff".
# If "breathing_rate_min" (for lowpass and notch filter)
# and "breathing_rate_max" (for notch filter) are set,
# the values set in "lowpass_cutoff" (for lowpass filter),
# "center_frequency" and "filter_bandwidth" (for notch filter)
# options are ignored.
# Lowest Breaths-Per-Minute in dataset.
# For both notch and lowpass filters.
breathing_rate_min:
# Highest Breaths-Per-Minute in dataset.
# For notch filter.
breathing_rate_max:
# notch filter direct customization parameters
# mutually exclusive with breathing_rate options above.
# If breathing_rate_min and breathing_rate_max are provided,
# the following parameters will be ignored.
# the center frequency of the notch filter
center_frequency:
# the width of the notch filter
filter_bandwidth:
# lowpass filter direct customization parameter
# mutually exclusive with breathing_rate options above.
# If breathing_rate_min is provided, the following
# parameter will be ignored.
# the frequency cutoff of the filter
lowpass_cutoff:
distortion_correction:
# this is a fork point
# run: [On, Off] - this will run both and fork the pipeline
run: [On]
# using: ['PhaseDiff', 'Blip']
# PhaseDiff - Perform field map correction using a single phase difference image, a subtraction of the two phase images from each echo. Default scanner for this method is SIEMENS.
# Blip - Uses AFNI 3dQWarp to calculate the distortion unwarp for EPI field maps of opposite/same phase encoding direction.
# NOTE:
# this is NOT a fork point - instead, the technique used will depend on what type of distortion correction field data accompanies the dataset
# for example, phase-difference field maps will lead to phase-difference distortion correction, and phase-encoding direction field maps will lead to blip-up/blip-down
using: ['PhaseDiff', 'Blip']
# option parameters
PhaseDiff:
# Since the quality of the distortion heavily relies on the skull-stripping step, we provide a choice of method ('AFNI' for AFNI 3dSkullStrip or 'BET' for FSL BET).
# Options: 'BET' or 'AFNI'
fmap_skullstrip_option: 'BET'
# Set the fraction value for the skull-stripping of the magnitude file. Depending on the data, a tighter extraction may be necessary in order to prevent noisy voxels from interfering with preparing the field map.
# The default value is 0.5.
fmap_skullstrip_BET_frac: 0.5
# Set the threshold value for the skull-stripping of the magnitude file. Depending on the data, a tighter extraction may be necessary in order to prevent noisy voxels from interfering with preparing the field map.
# The default value is 0.6.
fmap_skullstrip_AFNI_threshold: 0.6
func_masking:
# using: ['AFNI', 'FSL', 'FSL_AFNI', 'Anatomical_Refined', 'Anatomical_Based', 'Anatomical_Resampled', 'CCS_Anatomical_Refined']
# this is a fork point
using: ['AFNI']
FSL-BET:
# Apply to 4D FMRI data, if bold_bet_functional_mean_boolean : Off.
# Mutually exclusive with functional, reduce_bias, robust, padding, remove_eyes, surfaces
# It must be 'on' if select 'reduce_bias', 'robust', 'padding', 'remove_eyes', or 'bet_surfaces' on
functional_mean_boolean: Off
# Set an intensity threshold to improve skull stripping performances of FSL BET on rodent scans.
functional_mean_thr:
run: Off
threshold_value: 98
# Bias correct the functional mean image to improve skull stripping performances of FSL BET on rodent scans
functional_mean_bias_correction: Off
# Set the threshold value controling the brain vs non-brain voxels.
frac: 0.3
# Mesh created along with skull stripping
mesh_boolean: Off
# Create a surface outline image
outline: Off
# Add padding to the end of the image, improving BET.Mutually exclusive with functional,reduce_bias,robust,padding,remove_eyes,surfaces
padding: Off
# Integer value of head radius
radius: 0
# Reduce bias and cleanup neck. Mutually exclusive with functional,reduce_bias,robust,padding,remove_eyes,surfaces
reduce_bias: Off
# Eyes and optic nerve cleanup. Mutually exclusive with functional,reduce_bias,robust,padding,remove_eyes,surfaces
remove_eyes: Off
# Robust brain center estimation. Mutually exclusive with functional,reduce_bias,robust,padding,remove_eyes,surfaces
robust: Off
# Create a skull image
skull: Off
# Gets additional skull and scalp surfaces by running bet2 and betsurf. This is mutually exclusive with reduce_bias, robust, padding, remove_eyes
surfaces: Off
# Apply thresholding to segmented brain image and mask
threshold: Off
# Vertical gradient in fractional intensity threshold (-1,1)
vertical_gradient: 0.0
FSL_AFNI:
bold_ref: /code/CPAC/resources/templates/tpl-MNI152NLin2009cAsym_res-02_desc-fMRIPrep_boldref.nii.gz
brain_mask: /code/CPAC/resources/templates/tpl-MNI152NLin2009cAsym_res-02_desc-brain_mask.nii.gz
brain_probseg: /code/CPAC/resources/templates/tpl-MNI152NLin2009cAsym_res-01_label-brain_probseg.nii.gz
Anatomical_Refined:
# Choose whether or not to dilate the anatomical mask if you choose 'Anatomical_Refined' as the functional masking option. It will dilate one voxel if enabled.
anatomical_mask_dilation: False
# Apply functional mask in native space
apply_func_mask_in_native_space: On
generate_func_mean:
# Generate mean functional image
run: On
normalize_func:
# Normalize functional image
run: On
nuisance_corrections:
1-ICA-AROMA:
# this is a fork point
# run: [On, Off] - this will run both and fork the pipeline
run: [Off]
# Types of denoising strategy:
# nonaggr: nonaggressive-partial component regression
# aggr: aggressive denoising
denoising_type: nonaggr
2-nuisance_regression:
# this is a fork point
# run: [On, Off] - this will run both and fork the pipeline
run: [On]
# switch to Off if nuisance regression is off and you don't want to write out the regressors
create_regressors: On
# Select which nuisance signal corrections to apply
Regressors:
- Name: 'default'
Motion:
include_delayed: true
include_squared: true
include_delayed_squared: true
aCompCor:
summary:
method: DetrendPC
components: 5
tissues:
- WhiteMatter
- CerebrospinalFluid
extraction_resolution: 2
CerebrospinalFluid:
summary: Mean
extraction_resolution: 2
erode_mask: true
GlobalSignal:
summary: Mean
PolyOrt:
degree: 2
Bandpass:
bottom_frequency: 0.01
top_frequency: 0.1
method: default
- Name: 'defaultNoGSR'
Motion:
include_delayed: true
include_squared: true
include_delayed_squared: true
aCompCor:
summary:
method: DetrendPC
components: 5
tissues:
- WhiteMatter
- CerebrospinalFluid
extraction_resolution: 2
CerebrospinalFluid:
summary: Mean
extraction_resolution: 2
erode_mask: true
PolyOrt:
degree: 2
Bandpass:
bottom_frequency: 0.01
top_frequency: 0.1
method: default
# Standard Lateral Ventricles Binary Mask
# used in CSF mask refinement for CSF signal-related regressions
lateral_ventricles_mask: $FSLDIR/data/atlases/HarvardOxford/HarvardOxford-lateral-ventricles-thr25-2mm.nii.gz
# Whether to run frequency filtering before or after nuisance regression.
# Options: 'After' or 'Before'
bandpass_filtering_order: 'After'
# Process and refine masks used to produce regressors and time series for
# regression.
regressor_masks:
erode_anatomical_brain_mask:
# Erode binarized anatomical brain mask. If choosing True, please also set seg_csf_use_erosion: True; regOption: niworkflows-ants.
run: Off
# Erosion proportion, if using erosion.
# Default proportion is 0 for anatomical brain mask.
# Recommend that do not use erosion in both proportion and millimeter method.
brain_mask_erosion_prop : 0
# Erode brain mask in millimeter, default of brain is 30 mm
# brain erosion default is using millimeter erosion method when use erosion for brain.
brain_mask_erosion_mm : 30
# Erode binarized brain mask in millimeter
brain_erosion_mm: 0
erode_csf:
# Erode binarized csf tissue mask.
run: Off
# Erosion proportion, if use erosion.
# Default proportion is 0 for CSF (cerebrospinal fluid) mask.
# Recommend to do not use erosion in both proportion and millimeter method.
csf_erosion_prop : 0
# Erode brain mask in millimeter, default of csf is 30 mm
# CSF erosion default is using millimeter erosion method when use erosion for CSF.
csf_mask_erosion_mm: 30
# Erode binarized CSF (cerebrospinal fluid) mask in millimeter
csf_erosion_mm: 0
erode_wm:
# Erode WM binarized tissue mask.
run: Off
# Erosion proportion, if use erosion.
# Default proportion is 0.6 for White Matter mask.
# Recommend to do not use erosion in both proportion and millimeter method.
# White Matter erosion default is using proportion erosion method when use erosion for White Matter.
wm_erosion_prop : 0.6
# Erode brain mask in millimeter, default of White Matter is 0 mm
wm_mask_erosion_mm: 0
# Erode binarized White Matter mask in millimeter
wm_erosion_mm: 0
erode_gm:
# Erode GM binarized tissue mask.
run: Off
# Erosion proportion, if use erosion.
# Recommend to do not use erosion in both proportion and millimeter method.
gm_erosion_prop : 0.6
# Erode brain mask in millimeter, default of csf is 30 mm
gm_mask_erosion_mm: 30
# Erode binarized White Matter mask in millimeter
gm_erosion_mm: 0
# OUTPUTS AND DERIVATIVES
# -----------------------
post_processing:
spatial_smoothing:
# Smooth the derivative outputs.
# Set as ['nonsmoothed'] to disable smoothing. Set as both to get both.
#
# Options:
# ['smoothed', 'nonsmoothed']
output: ['smoothed']
# Tool to use for smoothing.
# 'FSL' for FSL MultiImageMaths for FWHM provided
# 'AFNI' for AFNI 3dBlurToFWHM for FWHM provided
smoothing_method: ['FSL']
# Full Width at Half Maximum of the Gaussian kernel used during spatial smoothing.
# this is a fork point
# i.e. multiple kernels - fwhm: [4,6,8]
fwhm: [6]
z-scoring:
# z-score standardize the derivatives. This may be needed for group-level analysis.
# Set as ['raw'] to disable z-scoring. Set as both to get both.
#
# Options:
# ['z-scored', 'raw']
output: ['z-scored']
timeseries_extraction:
run: On
# Enter paths to region-of-interest (ROI) NIFTI files (.nii or .nii.gz) to be used for time-series extraction, and then select which types of analyses to run.
# Denote which analyses to run for each ROI path by listing the names below. For example, if you wish to run Avg and SpatialReg, you would enter: '/path/to/ROI.nii.gz': Avg, SpatialReg
# available analyses:
# /path/to/atlas.nii.gz: Avg, Voxel, SpatialReg, PearsonCorr, PartialCorr
tse_roi_paths:
#/cpac_templates/CC400.nii.gz: Avg
#/cpac_templates/aal_mask_pad.nii.gz: Avg
#/cpac_templates/CC200.nii.gz: Avg
#/cpac_templates/tt_mask_pad.nii.gz: Avg
#/cpac_templates/PNAS_Smith09_rsn10.nii.gz: SpatialReg
/cpac_templates/ho_mask_pad.nii.gz: Avg
/cpac_templates/rois_3mm.nii.gz: Avg
#/ndmg_atlases/label/Human/AAL_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/CAPRSC_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/DKT_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/DesikanKlein_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
/ndmg_atlases/label/Human/HarvardOxfordcort-maxprob-thr25_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
/ndmg_atlases/label/Human/HarvardOxfordsub-maxprob-thr25_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/Juelich_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/MICCAI_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/Schaefer1000_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/Schaefer200_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/Schaefer300_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/Schaefer400_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/Talairach_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
/ndmg_atlases/label/Human/Brodmann_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/Desikan_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/Glasser_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
#/ndmg_atlases/label/Human/Slab907_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
/ndmg_atlases/label/Human/Yeo-17-liberal_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
/ndmg_atlases/label/Human/Yeo-17_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
/ndmg_atlases/label/Human/Yeo-7-liberal_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
/ndmg_atlases/label/Human/Yeo-7_space-MNI152NLin6_res-1x1x1.nii.gz: Avg
# Functional time-series and ROI realignment method: ['ROI_to_func'] or ['func_to_ROI']
# 'ROI_to_func' will realign the atlas/ROI to functional space (fast)
# 'func_to_ROI' will realign the functional time series to the atlas/ROI space
#
# NOTE: in rare cases, realigning the ROI to the functional space may
# result in small misalignments for very small ROIs - please double
# check your data if you see issues
realignment: 'ROI_to_func'
seed_based_correlation_analysis:
# SCA - Seed-Based Correlation Analysis
# For each extracted ROI Average time series, CPAC will generate a whole-brain correlation map.
# It should be noted that for a given seed/ROI, SCA maps for ROI Average time series will be the same.
run: Off
# Enter paths to region-of-interest (ROI) NIFTI files (.nii or .nii.gz) to be used for seed-based correlation analysis, and then select which types of analyses to run.
# Denote which analyses to run for each ROI path by listing the names below. For example, if you wish to run Avg and MultReg, you would enter: '/path/to/ROI.nii.gz': Avg, MultReg
# available analyses:
# /path/to/atlas.nii.gz: Avg, DualReg, MultReg
sca_roi_paths:
/cpac_templates/PNAS_Smith09_rsn10.nii.gz: DualReg
/cpac_templates/CC400.nii.gz: Avg, MultReg
/cpac_templates/ez_mask_pad.nii.gz: Avg, MultReg
/cpac_templates/aal_mask_pad.nii.gz: Avg, MultReg
/cpac_templates/CC200.nii.gz: Avg, MultReg
/cpac_templates/tt_mask_pad.nii.gz: Avg, MultReg
/cpac_templates/ho_mask_pad.nii.gz: Avg, MultReg
/cpac_templates/rois_3mm.nii.gz: Avg, MultReg
# Normalize each time series before running Dual Regression SCA.
norm_timeseries_for_DR: True
amplitude_low_frequency_fluctuation:
# ALFF & f/ALFF
# Calculate Amplitude of Low Frequency Fluctuations (ALFF) and and fractional ALFF (f/ALFF) for all voxels.
run: On
# Frequency cutoff (in Hz) for the high-pass filter used when calculating f/ALFF.
highpass_cutoff: [0.01]
# Frequency cutoff (in Hz) for the low-pass filter used when calculating f/ALFF
lowpass_cutoff: [0.1]
regional_homogeneity:
# ReHo
# Calculate Regional Homogeneity (ReHo) for all voxels.
run: On
# Number of neighboring voxels used when calculating ReHo
# 7 (Faces)
# 19 (Faces + Edges)
# 27 (Faces + Edges + Corners)
cluster_size: 27
voxel_mirrored_homotopic_connectivity:
# VMHC
# Calculate Voxel-mirrored Homotopic Connectivity (VMHC) for all voxels.
run: On
symmetric_registration:
# Included as part of the 'Image Resource Files' package available on the Install page of the User Guide.
# It is not necessary to change this path unless you intend to use a non-standard symmetric template.
T1w_brain_template_symmetric: $FSLDIR/data/standard/MNI152_T1_${resolution_for_anat}_brain_symmetric.nii.gz
# A reference symmetric brain template for resampling
T1w_brain_template_symmetric_for_resample: $FSLDIR/data/standard/MNI152_T1_1mm_brain_symmetric.nii.gz
# Included as part of the 'Image Resource Files' package available on the Install page of the User Guide.
# It is not necessary to change this path unless you intend to use a non-standard symmetric template.
T1w_template_symmetric: $FSLDIR/data/standard/MNI152_T1_${resolution_for_anat}_symmetric.nii.gz
# A reference symmetric skull template for resampling
T1w_template_symmetric_for_resample: $FSLDIR/data/standard/MNI152_T1_1mm_symmetric.nii.gz
# Included as part of the 'Image Resource Files' package available on the Install page of the User Guide.
# It is not necessary to change this path unless you intend to use a non-standard symmetric template.
dilated_symmetric_brain_mask: $FSLDIR/data/standard/MNI152_T1_${resolution_for_anat}_brain_mask_symmetric_dil.nii.gz
# A reference symmetric brain mask template for resampling
dilated_symmetric_brain_mask_for_resample: $FSLDIR/data/standard/MNI152_T1_1mm_brain_mask_symmetric_dil.nii.gz