10. Steps for reproducing results in the paper

If you would like to reproduce the results that we have written in our paper (Kim, et al. (2023)), please follow the instructions below. All TSV and JSON files shown below are available in our repo in the reproducePaperResults directory.

  1. Download the datasets from OpenNeuro

    1. AOMIC-PIOP1 (v2.0.0 https://openneuro.org/datasets/ds002785/versions/2.0.0)

    2. AOMIC-PIOP2 (v2.0.0 https://openneuro.org/datasets/ds002790/versions/2.0.0)

  2. Rescale all T1w images (both PIOP1 and PIOP2 datasets) using (1) rescale.m within Matlab or (2) rescale.sh which is a wrapper shell script that runs matlab standalone executable nii2int16.
    1. Running rescale.m in Matlab

      1. rescale.m runs nii2int16.m, which uses Matlab functions from the SVREG library, which you can download from here. The path to the functions in this folder have to be visible in Matlab to run the rescale.sh script.

      2. Modify the paths to the following variables in the rescale.m matlab script:

        • dataDir : path to the study directory (i.e. path to the AOMIC-PIOP1 directory)

      3. Execute the rescale.m script

    dataDir= '/path/to/studyDir';
demog = tdfread(strcat(dataDir,'/participants.tsv'), '\t');

ids = string(demog.participant_id);
for i = 1:length(demog.participant_id)
    nifti = strcat(dataDir, ids(i), '/anat/', ids(i), '_T1w.nii.gz');
    nii2int16(char(nifti),char(nifti));
end
    1. Running the nii2int16 standalone executable:

      1. nii2int16 was compiled using MATLAB 2019b and, thus, requires the MATLAB Compiler Runtime (MCR) 2019b library, which can be downloaded from here. Make sure to download the 2019b version.

      2. Once downloaded, set the BrainSuiteMCR environment variable to your MCR2019b library path. For example, BrainSuiteMCR="/usr/local/MATLAB/MATLAB_Runtime/v97".

      3. Modify the paths to the following variables in the rescale.sh shell script:

      • dataDir : path to the study directory (i.e. path to the AOMIC-PIOP1 directory)

      • rescale : path to the nii2int16.sh file

      1. Execute the rescale.sh script

    #!/bin/bash

## Modify paths below
dataDir=/path/to/studyDir
rescale=/path/to/nii2int16.sh

subjListTSV=${dataDir}/participants.tsv
subjList=( $(cut -f1 $subjListTSV) )

for subj in ${subjList[@]:1}; do
	 $rescale $dataDir/${subj}/anat/${subj}_T1w.nii.gz $dataDir/${subj}/anat/${subj}_T1w.nii.gz
done

  3. Run BrainSuite QC and Dashboard:

    singularity run $singImg $data $output participant --QCdir $qcdir --stages DASHBOARD

    ## $singImg is your Singularity-compatible BrainSuite BIDS App
    ## $data is the AOMIC-PIOP1 or AOMIC-PIOP1 directory
    ## $output is the output directory you would like to write out to
    ## $qcdir is the QC directory where you would like to write out the QC snapshot images
    ## *Note*: Since there are two datasets (PIOP1 and PIOP2), you will have run this command again twice

  4. Create or download the preprocessing parameter configuration file for AOMIC-PIOP1:

    Pre-processing configuration file for AOMIC-PIOP1
    {
	"BrainSuite": {
		"Global Settings":{
		"cacheFolder": ""
		},
		"Anatomical": {
			"autoParameters": 1,
			"diffusionIterations": 3,
			"diffusionConstant": 25,
			"edgeDetectionConstant": 0.64,
			"skipBSE": 0,
			"iterativeMode": 0,
			"spatialPrior": 0.1,
			"costFunction": 0,
			"useCentroids": 1,
			"linearConvergence": 0.01,
			"warpConvergence": 100,
			"warpLevel": 3,
			"tissueFractionThreshold": 50.0,
			"atlas": "BCI",
			"singleThread": 1
		},
		"Diffusion": {
			"skipDistortionCorr": 0,
			"phaseEncodingDirection": "y",
			"echoSpacing": "",
			"fieldmapCorrection": "",
			"estimateODF_3DShore": 0,
			"diffusion_time_ms": "",
			"estimateODF_GQI": 0,
			"sigma_GQI": "",
			"estimateODF_ERFO": 0,
			"ERFO_SNR": ""
		},
		"PostProc": {
			"smoothSurf": 2.0,
			"smoothVol": 3.0
		},
		"Functional": {
			"task-name": [
				"restingstate"
			],
			"TR": 2,
			"EnabletNLMPdfFiltering": 1,
			"fpr": 0.001,
			"FSLOUTPUTTYPE": "NIFTI_GZ",
			"FWHM": 6,
			"HIGHPASS":0.005,
			"LOWPASS": 0.1,
			"MultiThreading": 1,
			"memory": 16,
			"FSLRigid": 0,
			"BPoption": 1,
			"RunDetrend": 1,
			"RunNSR": 1,
			"uscrigid_similarity": "inversion",
			"scbPath": "/output/SCB.mat",
			"T1mask": 1,
			"SimRef": 1
		}
	}
}

  5. Run participant-level processing on AOMIC-PIOP1 using aomic-piop1_preprocspec.json:

    singularity run $singImg $data $output participant --preprocspec aomic-piop1_preprocspec.json --QCdir $qcdir

  6. Create or download the preprocessing parameter configuration file for AOMIC-PIOP2:

    Pre-processing configuration file for AOMIC-PIOP2
    {
	"BrainSuite": {
		"Global Settings":{
		"cacheFolder": ""
		},
		"Anatomical": {
			"autoParameters": 1,
			"diffusionIterations": 3,
			"diffusionConstant": 25,
			"edgeDetectionConstant": 0.64,
			"skipBSE": 0,
			"iterativeMode": 0,
			"spatialPrior": 0.1,
			"costFunction": 0,
			"useCentroids": 1,
			"linearConvergence": 0.01,
			"warpConvergence": 100,
			"warpLevel": 3,
			"tissueFractionThreshold": 50.0,
			"atlas": "BCI",
			"singleThread": 1
		},
		"Diffusion": {
			"skipDistortionCorr": 0,
			"phaseEncodingDirection": "y",
			"echoSpacing": "",
			"fieldmapCorrection": "",
			"estimateODF_3DShore": 0,
			"diffusion_time_ms": "",
			"estimateODF_GQI": 0,
			"sigma_GQI": "",
			"estimateODF_ERFO": 0,
			"ERFO_SNR": ""
		},
		"PostProc": {
			"smoothSurf": 2.0,
			"smoothVol": 3.0
		},
		"Functional": {
			"task-name": [
				"restingstate"
			],
			"TR": 2,
			"EnabletNLMPdfFiltering": 1,
			"fpr": 0.001,
			"FSLOUTPUTTYPE": "NIFTI_GZ",
			"FWHM": 6,
			"HIGHPASS":0.005,
			"LOWPASS": 0.1,
			"MultiThreading": 1,
			"memory": 16,
			"FSLRigid": 0,
			"BPoption": 1,
			"RunDetrend": 1,
			"RunNSR": 1,
			"uscrigid_similarity": "inversion",
			"scbPath": "/output/SCB.mat",
			"T1mask": 1,
			"SimRef": 1
		}
	}
}

  7. Run participant-level processing on AOMIC-PIOP2 using aomic-piop2_preprocspec.json:

    singularity run $singImg $data $output participant --preprocspec aomic-piop2_preprocspec.json --QCdir $qcdir
  8. Running the 13 subjects with special cases

    1. AOMIC-PIOP1: Re-run 5 subjects in AOMIC-PIOP1 (0106, 0157, 0179, 0185, and 0186). These cases required modifications in the BrainSuite Anatomical Pipeline.

      Re-run AOMIC-PIOP1 subject 0106 with initializing with centroids off during cerebrum labeling
      {
  "BrainSuite": {
    "Global Settings": {
      "cacheFolder": ""
    },
    "Structural": {
      "autoParameters": 1,
      "diffusionIterations": 3,
      "diffusionConstant": 25,
      "edgeDetectionConstant": 0.64,
      "skipBSE": 0,
      "iterativeMode": 0,
      "spatialPrior": 0.1,
      "costFunction": 2,
      "useCentroids": 0,
      "linearConvergence": 0.1,
      "warpConvergence": 100,
      "warpLevel": 3,
      "tissueFractionThreshold": 50.0,
      "atlas": "BCI",
      "singleThread": 1
    },
    "Diffusion": {
      "skipDistortionCorr": 0,
      "phaseEncodingDirection": "y",
      "echoSpacing": "",
      "fieldmapCorrection": "",
      "estimateODF_3DShore": 0,
      "diffusion_time_ms": "",
      "estimateODF_GQI": 0,
      "sigma_GQI": "",
      "estimateODF_ERFO": 0,
      "ERFO_SNR": ""
    },
    "PostProc": {
      "smoothSurf": 2.0,
      "smoothVol": 3.0
    },
    "Functional": {
      "task-name": [
        "restingstate"
      ],
      "TR": 2,
      "EnabletNLMPdfFiltering": 1,
      "fpr": 0.001,
      "FSLOUTPUTTYPE": "NIFTI_GZ",
      "FWHM": 6,
      "HIGHPASS": 0.005,
      "LOWPASS": 0.1,
      "MultiThreading": 1,
      "memory": 16,
      "FSLRigid": 0,
      "BPoption": 1,
      "RunDetrend": 1,
      "RunNSR": 1,
      "uscrigid_similarity": "inversion",
      "scbPath": "/output/SCB.mat",
      "T1mask": 1,
      "SimRef": 1
    }
  }
}
      Re-run AOMIC-PIOP1 subject 0157 with modified skull-stripping parameters
      {
	"BrainSuite": {
		"Global Settings":{
		"cacheFolder": ""
		},
		"Anatomical": {
			"autoParameters": 0,
			"diffusionIterations": 3,
			"diffusionConstant": 30,
			"edgeDetectionConstant": 0.57,
			"skipBSE": 0,
			"iterativeMode": 0,
			"spatialPrior": 0.1,
			"costFunction": 0,
			"useCentroids": 1,
			"linearConvergence": 0.01,
			"warpConvergence": 100,
			"warpLevel": 3,
			"tissueFractionThreshold": 50.0,
			"atlas": "BCI",
			"singleThread": 1
		},
		"Diffusion": {
			"skipDistortionCorr": 0,
			"phaseEncodingDirection": "y",
			"echoSpacing": "",
			"fieldmapCorrection": "",
			"estimateODF_3DShore": 0,
			"diffusion_time_ms": "",
			"estimateODF_GQI": 0,
			"sigma_GQI": "",
			"estimateODF_ERFO": 0,
			"ERFO_SNR": ""
		},
		"PostProc": {
			"smoothSurf": 2.0,
			"smoothVol": 3.0
		},
		"Functional": {
			"task-name": [
				"restingstate"
			],
			"TR": 2,
			"EnabletNLMPdfFiltering": 1,
			"fpr": 0.001,
			"FSLOUTPUTTYPE": "NIFTI_GZ",
			"FWHM": 6,
			"HIGHPASS":0.005,
			"LOWPASS": 0.1,
			"MultiThreading": 1,
			"memory": 16,
			"FSLRigid": 0,
			"BPoption": 1,
			"RunDetrend": 1,
			"RunNSR": 1,
			"uscrigid_similarity": "inversion",
			"scbPath": "/output/SCB.mat",
			"T1mask": 1,
			"SimRef": 1
		}
	}
}
      Re-run AOMIC-PIOP1 subject 0179 with modified skull-stripping parameters
      {
	"BrainSuite": {
		"Global Settings":{
		"cacheFolder": ""
		},
		"Anatomical": {
			"autoParameters": 0,
			"diffusionIterations": 1,
			"diffusionConstant": 30,
			"edgeDetectionConstant": 0.58,
			"skipBSE": 0,
			"iterativeMode": 0,
			"spatialPrior": 0.1,
			"costFunction": 0,
			"useCentroids": 1,
			"linearConvergence": 0.1,
			"warpConvergence": 100,
			"warpLevel": 3,
			"tissueFractionThreshold": 50.0,
			"atlas": "BCI",
			"singleThread": 1
		},
		"Diffusion": {
			"skipDistortionCorr": 0,
			"phaseEncodingDirection": "y",
			"echoSpacing": "",
			"fieldmapCorrection": "",
			"estimateODF_3DShore": 0,
			"diffusion_time_ms": "",
			"estimateODF_GQI": 0,
			"sigma_GQI": "",
			"estimateODF_ERFO": 0,
			"ERFO_SNR": ""
		},
		"PostProc": {
			"smoothSurf": 2.0,
			"smoothVol": 3.0
		},
		"Functional": {
			"task-name": [
				"restingstate"
			],
			"TR": 2,
			"EnabletNLMPdfFiltering": 1,
			"fpr": 0.001,
			"FSLOUTPUTTYPE": "NIFTI_GZ",
			"FWHM": 6,
			"HIGHPASS":0.005,
			"LOWPASS": 0.1,
			"MultiThreading": 1,
			"memory": 16,
			"FSLRigid": 0,
			"BPoption": 1,
			"RunDetrend": 1,
			"RunNSR": 1,
			"uscrigid_similarity": "inversion",
			"scbPath": "/output/SCB.mat",
			"T1mask": 1,
			"SimRef": 1
		}
	}
}
      Re-run AOMIC-PIOP1 subject 0185 with a different cost function for cerebrum labeling
      {
  "BrainSuite": {
    "Global Settings": {
      "cacheFolder": ""
    },
    "Structural": {
      "autoParameters": 1,
      "diffusionIterations": 3,
      "diffusionConstant": 25,
      "edgeDetectionConstant": 0.64,
      "skipBSE": 0,
      "iterativeMode": 0,
      "spatialPrior": 0.1,
      "costFunction": 0,
      "useCentroids": 0,
      "linearConvergence": 0.1,
      "warpConvergence": 100,
      "warpLevel": 3,
      "tissueFractionThreshold": 50.0,
      "atlas": "BCI",
      "singleThread": 1
    },
    "Diffusion": {
      "skipDistortionCorr": 0,
      "phaseEncodingDirection": "y",
      "echoSpacing": "",
      "fieldmapCorrection": "",
      "estimateODF_3DShore": 0,
      "diffusion_time_ms": "",
      "estimateODF_GQI": 0,
      "sigma_GQI": "",
      "estimateODF_ERFO": 0,
      "ERFO_SNR": ""
    },
    "PostProc": {
      "smoothSurf": 2.0,
      "smoothVol": 3.0
    },
    "Functional": {
      "task-name": [
        "restingstate"
      ],
      "TR": 2,
      "EnabletNLMPdfFiltering": 1,
      "fpr": 0.001,
      "FSLOUTPUTTYPE": "NIFTI_GZ",
      "FWHM": 6,
      "HIGHPASS": 0.005,
      "LOWPASS": 0.1,
      "MultiThreading": 1,
      "memory": 16,
      "FSLRigid": 0,
      "BPoption": 1,
      "RunDetrend": 1,
      "RunNSR": 1,
      "uscrigid_similarity": "inversion",
      "scbPath": "/output/SCB.mat",
      "T1mask": 1,
      "SimRef": 1
    }
  }
}
      Re-run AOMIC-PIOP1 subject 0186 with a different cost function for cerebrum labeling
      {
  "BrainSuite": {
    "Global Settings": {
      "cacheFolder": ""
    },
    "Structural": {
      "autoParameters": 1,
      "diffusionIterations": 3,
      "diffusionConstant": 25,
      "edgeDetectionConstant": 0.64,
      "skipBSE": 0,
      "iterativeMode": 0,
      "spatialPrior": 0.1,
      "costFunction": 0,
      "useCentroids": 0,
      "linearConvergence": 0.1,
      "warpConvergence": 100,
      "warpLevel": 3,
      "tissueFractionThreshold": 50.0,
      "atlas": "BCI",
      "singleThread": 1
    },
    "Diffusion": {
      "skipDistortionCorr": 0,
      "phaseEncodingDirection": "y",
      "echoSpacing": "",
      "fieldmapCorrection": "",
      "estimateODF_3DShore": 0,
      "diffusion_time_ms": "",
      "estimateODF_GQI": 0,
      "sigma_GQI": "",
      "estimateODF_ERFO": 0,
      "ERFO_SNR": ""
    },
    "PostProc": {
      "smoothSurf": 2.0,
      "smoothVol": 3.0
    },
    "Functional": {
      "task-name": [
        "restingstate"
      ],
      "TR": 2,
      "EnabletNLMPdfFiltering": 1,
      "fpr": 0.001,
      "FSLOUTPUTTYPE": "NIFTI_GZ",
      "FWHM": 6,
      "HIGHPASS": 0.005,
      "LOWPASS": 0.1,
      "MultiThreading": 1,
      "memory": 16,
      "FSLRigid": 0,
      "BPoption": 1,
      "RunDetrend": 1,
      "RunNSR": 1,
      "uscrigid_similarity": "inversion",
      "scbPath": "/output/SCB.mat",
      "T1mask": 1,
      "SimRef": 1
    }
  }
}

    2. AOMIC-PIOP2: Re-run 2 subjects in AOMIC-PIOP2 (0041 and 0189). These cases required modifications in the BrainSuite Anatomical Pipeline.

      Re-run AOMIC-PIOP2 subject 0041 with with modified skull-stripping parameters
      {
	"BrainSuite": {
		"Global Settings":{
		"cacheFolder": ""
		},
		"Anatomical": {
			"autoParameters": 0,
			"diffusionIterations": 3,
			"diffusionConstant": 22,
			"edgeDetectionConstant": 0.70,
			"skipBSE": 0,
			"iterativeMode": 0,
			"spatialPrior": 0.1,
			"costFunction": 0,
			"useCentroids": 1,
			"linearConvergence": 0.01,
			"warpConvergence": 100,
			"warpLevel": 3,
			"tissueFractionThreshold": 50.0,
			"atlas": "BCI",
			"singleThread": 1
		},
		"Diffusion": {
			"skipDistortionCorr": 0,
			"phaseEncodingDirection": "y",
			"echoSpacing": "",
			"fieldmapCorrection": "",
			"estimateODF_3DShore": 0,
			"diffusion_time_ms": "",
			"estimateODF_GQI": 0,
			"sigma_GQI": "",
			"estimateODF_ERFO": 0,
			"ERFO_SNR": ""
		},
		"PostProc": {
			"smoothSurf": 2.0,
			"smoothVol": 3.0
		},
		"Functional": {
			"task-name": [
				"restingstate"
			],
			"TR": 2,
			"EnabletNLMPdfFiltering": 1,
			"fpr": 0.001,
			"FSLOUTPUTTYPE": "NIFTI_GZ",
			"FWHM": 6,
			"HIGHPASS":0.005,
			"LOWPASS": 0.1,
			"MultiThreading": 1,
			"memory": 16,
			"FSLRigid": 0,
			"BPoption": 1,
			"RunDetrend": 1,
			"RunNSR": 1,
			"uscrigid_similarity": "inversion",
			"scbPath": "/output/SCB.mat",
			"T1mask": 1,
			"SimRef": 1
		}
	}
}
      Re-run AOMIC-PIOP2 subject 0189 with a different cost function for cerebrum labeling
      {
	"BrainSuite": {
		"Global Settings":{
		"cacheFolder": ""
		},
		"Anatomical": {
			"autoParameters": 1,
			"diffusionIterations": 3,
			"diffusionConstant": 25,
			"edgeDetectionConstant": 0.64,
			"skipBSE": 0,
			"iterativeMode": 0,
			"spatialPrior": 0.1,
			"costFunction": 0,
			"useCentroids": 1,
			"linearConvergence": 0.1,
			"warpConvergence": 100,
			"warpLevel": 5,
			"tissueFractionThreshold": 50.0,
			"atlas": "BCI",
			"singleThread": 1
		},
		"Diffusion": {
			"skipDistortionCorr": 0,
			"phaseEncodingDirection": "y",
			"echoSpacing": "",
			"fieldmapCorrection": "",
			"estimateODF_3DShore": 0,
			"diffusion_time_ms": "",
			"estimateODF_GQI": 0,
			"sigma_GQI": "",
			"estimateODF_ERFO": 0,
			"ERFO_SNR": ""
		},
		"PostProc": {
			"smoothSurf": 2.0,
			"smoothVol": 3.0
		},
		"Functional": {
			"task-name": [
				"restingstate"
			],
			"TR": 2,
			"EnabletNLMPdfFiltering": 1,
			"fpr": 0.001,
			"FSLOUTPUTTYPE": "NIFTI_GZ",
			"FWHM": 6,
			"HIGHPASS":0.005,
			"LOWPASS": 0.1,
			"MultiThreading": 1,
			"memory": 16,
			"FSLRigid": 0,
			"BPoption": 1,
			"RunDetrend": 1,
			"RunNSR": 1,
			"uscrigid_similarity": "inversion",
			"scbPath": "/output/SCB.mat",
			"T1mask": 1,
			"SimRef": 1
		}
	}
}

    3. AOMIC-PIOP1 and AOMIC-PIOP2. Re-run 6 subjects in both PIOP1 (0129) and PIOP2 (0040, 0116, 0141, 0198, and 0217). These cases required a different type of cost function for the USC rigid registration in the BrainSuite Functional Pipeline.

      Re-run subject 0129 from AOMIC-PIOP1 and subjects 0040, 0116, 0141, 0198, 0217 from AOMIC-PIOP2 using a different cost function for USC rigid registration
      {
	"BrainSuite": {
		"Global Settings":{
		"cacheFolder": ""
		},
		"Anatomical": {
			"autoParameters": 1,
			"diffusionIterations": 3,
			"diffusionConstant": 25,
			"edgeDetectionConstant": 0.64,
			"skipBSE": 0,
			"iterativeMode": 0,
			"spatialPrior": 0.1,
			"costFunction": 0,
			"useCentroids": 1,
			"linearConvergence": 0.01,
			"warpConvergence": 100,
			"warpLevel": 3,
			"tissueFractionThreshold": 50.0,
			"atlas": "BCI",
			"singleThread": 1
		},
		"Diffusion": {
			"skipDistortionCorr": 0,
			"phaseEncodingDirection": "y",
			"echoSpacing": "",
			"fieldmapCorrection": "",
			"estimateODF_3DShore": 0,
			"diffusion_time_ms": "",
			"estimateODF_GQI": 0,
			"sigma_GQI": "",
			"estimateODF_ERFO": 0,
			"ERFO_SNR": ""
		},
		"PostProc": {
			"smoothSurf": 2.0,
			"smoothVol": 3.0
		},
		"Functional": {
			"task-name": [
				"restingstate"
			],
			"TR": 2,
			"EnabletNLMPdfFiltering": 1,
			"fpr": 0.001,
			"FSLOUTPUTTYPE": "NIFTI_GZ",
			"FWHM": 6,
			"HIGHPASS":0.005,
			"LOWPASS": 0.1,
			"MultiThreading": 1,
			"memory": 16,
			"FSLRigid": 0,
			"BPoption": 1,
			"RunDetrend": 1,
			"RunNSR": 1,
			"uscrigid_similarity": "cr",
			"scbPath": "/output/SCB.mat",
			"T1mask": 1,
			"SimRef": 1
		}
	}
}

  9. After all datasets have finished processing, combine both outputs into one directory, with PIOP1 and PIOP2 as sessions (e.g., sub-0001_ses-PIOP1, sub-0001_ses-PIOP2)

  10. Run group analyses. Copy or download the demographics files below. Then create or copy the following model specification JSON files for the individual types of group-level analyses

    1. Run group analyses using the aomic-piop_10192021.tsv demographics file.

      participant_id	age	sex	ravenscore	scanner	Exclude	AtlasF	AtlasM	Fonly	Monly
sub-0001_ses-PIOP1	26.25	F	29	1	0	0	0	0	1
sub-0002_ses-PIOP1	21	F	27	1	0	0	0	0	1
sub-0004_ses-PIOP1	23.5	F	21	1	0	0	0	0	1
sub-0009_ses-PIOP1	21.75	F	19	1	0	0	0	0	1
sub-0010_ses-PIOP1	22	F	15	1	0	0	0	0	1
sub-0012_ses-PIOP1	22.75	F	30	1	0	0	0	0	1
sub-0014_ses-PIOP1	23	F	26	1	0	0	0	0	1
sub-0015_ses-PIOP1	19.5	F	26	1	0	0	0	0	1
sub-0018_ses-PIOP1	23.5	F	25	1	0	0	0	0	1
sub-0019_ses-PIOP1	21.75	F	24	1	0	0	0	0	1
sub-0020_ses-PIOP1	22	F	22	1	0	0	0	0	1
sub-0023_ses-PIOP1	21	F	25	1	0	0	0	0	1
sub-0025_ses-PIOP1	22.5	F	24	1	0	0	0	0	1
sub-0027_ses-PIOP1	20.25	F	14	1	0	0	0	0	1
sub-0029_ses-PIOP1	22	F	26	1	0	0	0	0	1
sub-0033_ses-PIOP1	23.25	F	18	1	0	0	0	0	1
sub-0034_ses-PIOP1	21.25	F	19	1	0	0	0	0	1
sub-0035_ses-PIOP1	22.5	F	23	1	0	0	0	0	1
sub-0036_ses-PIOP1	23.75	F	28	1	0	0	0	0	1
sub-0037_ses-PIOP1	25.75	F	33	1	0	1	0	0	1
sub-0038_ses-PIOP1	20.25	F	29	1	0	0	0	0	1
sub-0039_ses-PIOP1	22.25	F	32	1	0	1	0	0	1
sub-0046_ses-PIOP1	20.5	F	31	1	0	0	0	0	1
sub-0047_ses-PIOP1	21.25	F	18	1	0	0	0	0	1
sub-0048_ses-PIOP1	23	F	22	1	0	0	0	0	1
sub-0049_ses-PIOP1	24.5	F	27	1	0	0	0	0	1
sub-0050_ses-PIOP1	23.5	F	19	1	0	0	0	0	1
sub-0051_ses-PIOP1	23	F	22	1	0	0	0	0	1
sub-0056_ses-PIOP1	24.25	F	18	1	0	0	0	0	1
sub-0059_ses-PIOP1	22.25	F	23	1	0	0	0	0	1
sub-0061_ses-PIOP1	19.5	F	26	1	0	0	0	0	1
sub-0062_ses-PIOP1	25.5	F	23	1	0	0	0	0	1
sub-0063_ses-PIOP1	23	F	19	1	0	0	0	0	1
sub-0064_ses-PIOP1	21.5	F	15	1	0	0	0	0	1
sub-0065_ses-PIOP1	21	F	32	1	0	1	0	0	1
sub-0068_ses-PIOP1	21	F	22	1	0	0	0	0	1
sub-0069_ses-PIOP1	23.25	F	25	1	0	0	0	0	1
sub-0072_ses-PIOP1	24.75	F	26	1	0	0	0	0	1
sub-0073_ses-PIOP1	22.75	F	17	1	0	0	0	0	1
sub-0076_ses-PIOP1	25.75	F	23	1	0	0	0	0	1
sub-0080_ses-PIOP1	19.75	F	30	1	0	0	0	0	1
sub-0083_ses-PIOP1	19.75	F	24	1	0	0	0	0	1
sub-0084_ses-PIOP1	24	F	27	1	0	0	0	0	1
sub-0085_ses-PIOP1	24.5	F	26	1	0	0	0	0	1
sub-0087_ses-PIOP1	22.5	F	22	1	0	0	0	0	1
sub-0089_ses-PIOP1	23.5	F	23	1	0	0	0	0	1
sub-0090_ses-PIOP1	19.5	F	20	1	0	0	0	0	1
sub-0095_ses-PIOP1	21.75	F	33	1	0	1	0	0	1
sub-0096_ses-PIOP1	19.25	F	31	1	0	0	0	0	1
sub-0101_ses-PIOP1	24.75	F	26	1	0	0	0	0	1
sub-0103_ses-PIOP1	22.5	F	25	1	0	0	0	0	1
sub-0104_ses-PIOP1	21.25	F	24	1	0	0	0	0	1
sub-0105_ses-PIOP1	24.5	F	25	1	0	0	0	0	1
sub-0106_ses-PIOP1	22.75	F	24	1	0	0	0	0	1
sub-0107_ses-PIOP1	19.75	F	31	1	0	0	0	0	1
sub-0111_ses-PIOP1	22	F	25	1	0	0	0	0	1
sub-0112_ses-PIOP1	22	F	18	1	0	0	0	0	1
sub-0113_ses-PIOP1	20.25	F	19	1	0	0	0	0	1
sub-0114_ses-PIOP1	20.75	F	28	1	0	0	0	0	1
sub-0115_ses-PIOP1	21.75	F	27	1	0	0	0	0	1
sub-0116_ses-PIOP1	23.5	F	26	1	0	0	0	0	1
sub-0117_ses-PIOP1	23	F	23	1	0	0	0	0	1
sub-0118_ses-PIOP1	20.75	F	25	1	0	0	0	0	1
sub-0120_ses-PIOP1	21.75	F	16	1	0	0	0	0	1
sub-0122_ses-PIOP1	20	F	22	1	0	0	0	0	1
sub-0124_ses-PIOP1	20.5	F	24	1	0	0	0	0	1
sub-0126_ses-PIOP1	24.75	F	29	1	0	0	0	0	1
sub-0127_ses-PIOP1	20	F	30	1	0	0	0	0	1
sub-0129_ses-PIOP1	24.5	F	26	1	0	0	0	0	1
sub-0130_ses-PIOP1	22.25	F	28	1	0	0	0	0	1
sub-0132_ses-PIOP1	21.75	F	27	1	0	0	0	0	1
sub-0133_ses-PIOP1	22.75	F	27	1	0	0	0	0	1
sub-0134_ses-PIOP1	23	F	26	1	0	0	0	0	1
sub-0135_ses-PIOP1	25	F	23	1	0	0	0	0	1
sub-0136_ses-PIOP1	22.75	F	24	1	0	0	0	0	1
sub-0138_ses-PIOP1	22	F	28	1	0	0	0	0	1
sub-0139_ses-PIOP1	24	F	14	1	0	0	0	0	1
sub-0142_ses-PIOP1	23	F	14	1	0	0	0	0	1
sub-0145_ses-PIOP1	23	F	25	1	0	0	0	0	1
sub-0150_ses-PIOP1	23.25	F	34	1	0	1	0	0	1
sub-0155_ses-PIOP1	25.25	F	24	1	0	0	0	0	1
sub-0159_ses-PIOP1	18.75	F	20	1	0	0	0	0	1
sub-0160_ses-PIOP1	21.75	F	30	1	0	0	0	0	1
sub-0163_ses-PIOP1	22.25	F	30	1	0	0	0	0	1
sub-0164_ses-PIOP1	22	F	21	1	0	0	0	0	1
sub-0165_ses-PIOP1	21.75	F	31	1	0	0	0	0	1
sub-0170_ses-PIOP1	24.25	F	30	1	0	0	0	0	1
sub-0172_ses-PIOP1	21.75	F	25	1	0	0	0	0	1
sub-0175_ses-PIOP1	22.5	F	28	1	0	0	0	0	1
sub-0177_ses-PIOP1	24.5	F	25	1	0	0	0	0	1
sub-0180_ses-PIOP1	23.25	F	31	1	0	0	0	0	1
sub-0181_ses-PIOP1	23.25	F	27	1	0	0	0	0	1
sub-0182_ses-PIOP1	26	F	24	1	0	0	0	0	1
sub-0184_ses-PIOP1	23.5	F	24	1	0	0	0	0	1
sub-0186_ses-PIOP1	20.75	F	31	1	0	0	0	0	1
sub-0189_ses-PIOP1	19.5	F	23	1	0	0	0	0	1
sub-0190_ses-PIOP1	20	F	24	1	0	0	0	0	1
sub-0194_ses-PIOP1	22.5	F	24	1	0	0	0	0	1
sub-0195_ses-PIOP1	23.25	F	24	1	0	0	0	0	1
sub-0196_ses-PIOP1	22.75	F	8	1	0	0	0	0	1
sub-0197_ses-PIOP1	21	F	18	1	0	0	0	0	1
sub-0198_ses-PIOP1	21.25	F	23	1	0	0	0	0	1
sub-0199_ses-PIOP1	23	F	25	1	0	0	0	0	1
sub-0200_ses-PIOP1	24.25	F	19	1	0	0	0	0	1
sub-0203_ses-PIOP1	21.5	F	24	1	0	0	0	0	1
sub-0205_ses-PIOP1	22.5	F	25	1	0	0	0	0	1
sub-0206_ses-PIOP1	23	F	17	1	0	0	0	0	1
sub-0207_ses-PIOP1	23.5	F	28	1	0	0	0	0	1
sub-0209_ses-PIOP1	23	F	28	1	0	0	0	0	1
sub-0210_ses-PIOP1	21.5	F	23	1	0	0	0	0	1
sub-0212_ses-PIOP1	20.5	F	19	1	0	0	0	0	1
sub-0215_ses-PIOP1	18.25	F	24	1	0	0	0	0	1
sub-0216_ses-PIOP1	20.5	F	21	1	0	0	0	0	1
sub-0002_ses-PIOP2	23.25	F	19	2	0	0	0	0	1
sub-0003_ses-PIOP2	25	F	29	2	0	0	0	0	1
sub-0004_ses-PIOP2	20	F	24	2	0	0	0	0	1
sub-0007_ses-PIOP2	19.25	F	24	2	0	0	0	0	1
sub-0009_ses-PIOP2	24.75	F	33	2	0	1	0	0	1
sub-0011_ses-PIOP2	22.75	F	24	2	0	0	0	0	1
sub-0012_ses-PIOP2	22.75	F	15	2	0	0	0	0	1
sub-0015_ses-PIOP2	23	F	28	2	0	0	0	0	1
sub-0016_ses-PIOP2	20.25	F	23	2	0	0	0	0	1
sub-0017_ses-PIOP2	20.5	F	20	2	0	0	0	0	1
sub-0019_ses-PIOP2	21.25	F	22	2	0	0	0	0	1
sub-0020_ses-PIOP2	20	F	19	2	0	0	0	0	1
sub-0021_ses-PIOP2	23.25	F	24	2	0	0	0	0	1
sub-0022_ses-PIOP2	21.5	F	28	2	0	0	0	0	1
sub-0026_ses-PIOP2	20.25	F	25	2	0	0	0	0	1
sub-0027_ses-PIOP2	22	F	26	2	0	0	0	0	1
sub-0033_ses-PIOP2	20.25	F	21	2	0	0	0	0	1
sub-0034_ses-PIOP2	24.75	F	24	2	0	0	0	0	1
sub-0036_ses-PIOP2	24	F	29	2	0	0	0	0	1
sub-0037_ses-PIOP2	22	F	17	2	0	0	0	0	1
sub-0038_ses-PIOP2	21	F	20	2	0	0	0	0	1
sub-0039_ses-PIOP2	22.25	F	32	2	0	1	0	0	1
sub-0040_ses-PIOP2	19.75	F	24	2	0	0	0	0	1
sub-0042_ses-PIOP2	22	F	24	2	0	0	0	0	1
sub-0043_ses-PIOP2	22.5	F	32	2	0	1	0	0	1
sub-0044_ses-PIOP2	19	F	24	2	0	0	0	0	1
sub-0045_ses-PIOP2	25	F	27	2	0	0	0	0	1
sub-0047_ses-PIOP2	22.75	F	31	2	0	0	0	0	1
sub-0048_ses-PIOP2	20.25	F	16	2	0	0	0	0	1
sub-0049_ses-PIOP2	24.25	F	29	2	0	0	0	0	1
sub-0051_ses-PIOP2	23.25	F	26	2	0	0	0	0	1
sub-0052_ses-PIOP2	19	F	26	2	0	0	0	0	1
sub-0053_ses-PIOP2	21.25	F	31	2	0	0	0	0	1
sub-0055_ses-PIOP2	20.5	F	25	2	0	0	0	0	1
sub-0058_ses-PIOP2	21.75	F	22	2	0	0	0	0	1
sub-0060_ses-PIOP2	22.25	F	15	2	0	0	0	0	1
sub-0061_ses-PIOP2	21.75	F	16	2	0	0	0	0	1
sub-0062_ses-PIOP2	19.75	F	28	2	0	0	0	0	1
sub-0067_ses-PIOP2	19	F	19	2	0	0	0	0	1
sub-0068_ses-PIOP2	22.25	F	31	2	0	0	0	0	1
sub-0069_ses-PIOP2	23.75	F	20	2	0	0	0	0	1
sub-0071_ses-PIOP2	23.75	F	32	2	0	1	0	0	1
sub-0072_ses-PIOP2	24.25	F	17	2	0	0	0	0	1
sub-0073_ses-PIOP2	22	F	23	2	0	0	0	0	1
sub-0075_ses-PIOP2	19.75	F	23	2	0	0	0	0	1
sub-0076_ses-PIOP2	22.75	F	24	2	0	0	0	0	1
sub-0077_ses-PIOP2	21.25	F	21	2	0	0	0	0	1
sub-0080_ses-PIOP2	21	F	32	2	0	1	0	0	1
sub-0082_ses-PIOP2	21.5	F	24	2	0	0	0	0	1
sub-0083_ses-PIOP2	22.75	F	29	2	0	0	0	0	1
sub-0084_ses-PIOP2	23.25	F	28	2	0	0	0	0	1
sub-0085_ses-PIOP2	23	F	22	2	0	0	0	0	1
sub-0089_ses-PIOP2	20	F	24	2	0	0	0	0	1
sub-0090_ses-PIOP2	22.75	F	27	2	0	0	0	0	1
sub-0091_ses-PIOP2	22.25	F	25	2	0	0	0	0	1
sub-0092_ses-PIOP2	21.5	F	26	2	0	0	0	0	1
sub-0094_ses-PIOP2	20.25	F	23	2	0	0	0	0	1
sub-0095_ses-PIOP2	21	F	23	2	0	0	0	0	1
sub-0097_ses-PIOP2	23	F	15	2	0	0	0	0	1
sub-0098_ses-PIOP2	21.5	F	31	2	0	0	0	0	1
sub-0099_ses-PIOP2	20	F	20	2	0	0	0	0	1
sub-0100_ses-PIOP2	23.75	F	29	2	0	0	0	0	1
sub-0101_ses-PIOP2	22.75	F	25	2	0	0	0	0	1
sub-0102_ses-PIOP2	23	F	22	2	0	0	0	0	1
sub-0103_ses-PIOP2	21.5	F	34	2	0	1	0	0	1
sub-0104_ses-PIOP2	24	F	23	2	0	0	0	0	1
sub-0106_ses-PIOP2	24.25	F	26	2	0	0	0	0	1
sub-0109_ses-PIOP2	19.75	F	19	2	0	0	0	0	1
sub-0112_ses-PIOP2	19	F	22	2	0	0	0	0	1
sub-0114_ses-PIOP2	18.25	F	18	2	0	0	0	0	1
sub-0116_ses-PIOP2	21.75	F	14	2	0	0	0	0	1
sub-0119_ses-PIOP2	21	F	23	2	0	0	0	0	1
sub-0123_ses-PIOP2	24.5	F	28	2	0	0	0	0	1
sub-0125_ses-PIOP2	23	F	26	2	0	0	0	0	1
sub-0127_ses-PIOP2	20.5	F	24	2	0	0	0	0	1
sub-0130_ses-PIOP2	19.75	F	18	2	0	0	0	0	1
sub-0132_ses-PIOP2	22.25	F	23	2	0	0	0	0	1
sub-0134_ses-PIOP2	19.25	F	23	2	0	0	0	0	1
sub-0137_ses-PIOP2	23	F	21	2	0	0	0	0	1
sub-0139_ses-PIOP2	22.5	F	24	2	0	0	0	0	1
sub-0140_ses-PIOP2	22	F	25	2	0	0	0	0	1
sub-0142_ses-PIOP2	19	F	26	2	0	0	0	0	1
sub-0143_ses-PIOP2	18.25	F	15	2	0	0	0	0	1
sub-0145_ses-PIOP2	18.75	F	21	2	0	0	0	0	1
sub-0146_ses-PIOP2	20.75	F	30	2	0	0	0	0	1
sub-0147_ses-PIOP2	23	F	28	2	0	0	0	0	1
sub-0148_ses-PIOP2	21	F	14	2	0	0	0	0	1
sub-0149_ses-PIOP2	23	F	27	2	0	0	0	0	1
sub-0150_ses-PIOP2	22	F	23	2	0	0	0	0	1
sub-0152_ses-PIOP2	23.75	F	30	2	0	0	0	0	1
sub-0153_ses-PIOP2	19	F	28	2	0	0	0	0	1
sub-0154_ses-PIOP2	25.5	F	32	2	0	1	0	0	1
sub-0157_ses-PIOP2	20.25	F	21	2	0	0	0	0	1
sub-0166_ses-PIOP2	21	F	30	2	0	0	0	0	1
sub-0168_ses-PIOP2	25.5	F	21	2	0	0	0	0	1
sub-0169_ses-PIOP2	25	F	28	2	0	0	0	0	1
sub-0170_ses-PIOP2	25.25	F	29	2	0	0	0	0	1
sub-0171_ses-PIOP2	22.5	F	24	2	0	0	0	0	1
sub-0172_ses-PIOP2	20.5	F	28	2	0	0	0	0	1
sub-0174_ses-PIOP2	23.5	F	28	2	0	0	0	0	1
sub-0176_ses-PIOP2	22.5	F	19	2	0	0	0	0	1
sub-0179_ses-PIOP2	22.5	F	26	2	0	0	0	0	1
sub-0180_ses-PIOP2	19.75	F	28	2	0	0	0	0	1
sub-0181_ses-PIOP2	24.75	F	20	2	0	0	0	0	1
sub-0183_ses-PIOP2	24	F	21	2	0	0	0	0	1
sub-0186_ses-PIOP2	20.75	F	17	2	0	0	0	0	1
sub-0187_ses-PIOP2	25	F	26	2	0	0	0	0	1
sub-0190_ses-PIOP2	19.5	F	24	2	0	0	0	0	1
sub-0191_ses-PIOP2	22.25	F	20	2	0	0	0	0	1
sub-0192_ses-PIOP2	22.25	F	17	2	0	0	0	0	1
sub-0194_ses-PIOP2	20.75	F	30	2	0	0	0	0	1
sub-0197_ses-PIOP2	20.75	F	28	2	0	0	0	0	1
sub-0200_ses-PIOP2	19	F	20	2	0	0	0	0	1
sub-0201_ses-PIOP2	23	F	19	2	0	0	0	0	1
sub-0202_ses-PIOP2	22.5	F	29	2	0	0	0	0	1
sub-0204_ses-PIOP2	19.75	F	25	2	0	0	0	0	1
sub-0206_ses-PIOP2	24.25	F	26	2	0	0	0	0	1
sub-0208_ses-PIOP2	21.25	F	23	2	0	0	0	0	1
sub-0210_ses-PIOP2	20.75	F	24	2	0	0	0	0	1
sub-0214_ses-PIOP2	21.75	F	27	2	0	0	0	0	1
sub-0215_ses-PIOP2	20.5	F	32	2	0	1	0	0	1
sub-0218_ses-PIOP2	22	F	25	2	0	0	0	0	1
sub-0219_ses-PIOP2	23.5	F	27	2	0	0	0	0	1
sub-0220_ses-PIOP2	21.75	F	27	2	0	0	0	0	1
sub-0222_ses-PIOP2	22	F	30	2	0	0	0	0	1
sub-0223_ses-PIOP2	20.75	F	26	2	0	0	0	0	1
sub-0225_ses-PIOP2	20.25	F	27	2	0	0	0	0	1
sub-0003_ses-PIOP1	23	M	22	1	0	0	0	1	0
sub-0005_ses-PIOP1	21.75	M	28	1	0	0	0	1	0
sub-0006_ses-PIOP1	24.5	M	28	1	0	0	0	1	0
sub-0008_ses-PIOP1	24.25	M	29	1	0	0	0	1	0
sub-0016_ses-PIOP1	24	M	25	1	0	0	0	1	0
sub-0021_ses-PIOP1	24.75	M	28	1	0	0	0	1	0
sub-0024_ses-PIOP1	19.25	M	23	1	0	0	0	1	0
sub-0026_ses-PIOP1	26.25	M	20	1	0	0	0	1	0
sub-0028_ses-PIOP1	21	M	18	1	0	0	0	1	0
sub-0030_ses-PIOP1	21	M	20	1	0	0	0	1	0
sub-0032_ses-PIOP1	24.75	M	24	1	0	0	0	1	0
sub-0040_ses-PIOP1	20.5	M	24	1	0	0	0	1	0
sub-0042_ses-PIOP1	24.75	M	33	1	0	0	1	1	0
sub-0043_ses-PIOP1	22.75	M	32	1	0	0	1	1	0
sub-0044_ses-PIOP1	19	M	33	1	0	0	1	1	0
sub-0045_ses-PIOP1	20.75	M	24	1	0	0	0	1	0
sub-0052_ses-PIOP1	23.25	M	29	1	0	0	0	1	0
sub-0053_ses-PIOP1	24.75	M	28	1	0	0	0	1	0
sub-0054_ses-PIOP1	23	M	25	1	0	0	0	1	0
sub-0055_ses-PIOP1	21.5	M	24	1	0	0	0	1	0
sub-0058_ses-PIOP1	21.75	M	26	1	0	0	0	1	0
sub-0060_ses-PIOP1	22	M	26	1	0	0	0	1	0
sub-0066_ses-PIOP1	19.75	M	15	1	0	0	0	1	0
sub-0067_ses-PIOP1	23.25	M	29	1	0	0	0	1	0
sub-0070_ses-PIOP1	22	M	24	1	0	0	0	1	0
sub-0071_ses-PIOP1	20.5	M	21	1	0	0	0	1	0
sub-0074_ses-PIOP1	21.25	M	35	1	0	0	1	1	0
sub-0075_ses-PIOP1	20.5	M	25	1	0	0	0	1	0
sub-0077_ses-PIOP1	22.25	M	14	1	0	0	0	1	0
sub-0078_ses-PIOP1	22	M	24	1	0	0	0	1	0
sub-0079_ses-PIOP1	24.25	M	24	1	0	0	0	1	0
sub-0081_ses-PIOP1	21	M	34	1	0	0	1	1	0
sub-0082_ses-PIOP1	23.25	M	17	1	0	0	0	1	0
sub-0086_ses-PIOP1	22.75	M	24	1	0	0	0	1	0
sub-0088_ses-PIOP1	18.25	M	29	1	0	0	0	1	0
sub-0091_ses-PIOP1	22.25	M	23	1	0	0	0	1	0
sub-0092_ses-PIOP1	19.25	M	30	1	0	0	0	1	0
sub-0093_ses-PIOP1	24.5	M	30	1	0	0	0	1	0
sub-0094_ses-PIOP1	23.25	M	19	1	0	0	0	1	0
sub-0097_ses-PIOP1	21.25	M	32	1	0	0	1	1	0
sub-0098_ses-PIOP1	22.75	M	27	1	0	0	0	1	0
sub-0099_ses-PIOP1	24.25	M	32	1	0	0	1	1	0
sub-0100_ses-PIOP1	18.25	M	30	1	0	0	0	1	0
sub-0102_ses-PIOP1	19.25	M	27	1	0	0	0	1	0
sub-0108_ses-PIOP1	23	M	28	1	0	0	0	1	0
sub-0109_ses-PIOP1	22.25	M	18	1	0	0	0	1	0
sub-0110_ses-PIOP1	21.25	M	27	1	0	0	0	1	0
sub-0119_ses-PIOP1	22.25	M	25	1	0	0	0	1	0
sub-0125_ses-PIOP1	20.75	M	27	1	0	0	0	1	0
sub-0128_ses-PIOP1	22.75	M	23	1	0	0	0	1	0
sub-0131_ses-PIOP1	25	M	32	1	0	0	1	1	0
sub-0137_ses-PIOP1	19.75	M	23	1	0	0	0	1	0
sub-0141_ses-PIOP1	20	M	25	1	0	0	0	1	0
sub-0143_ses-PIOP1	19.75	M	27	1	0	0	0	1	0
sub-0146_ses-PIOP1	18.25	M	29	1	0	0	0	1	0
sub-0148_ses-PIOP1	19.75	M	27	1	0	0	0	1	0
sub-0149_ses-PIOP1	22.75	M	19	1	0	0	0	1	0
sub-0151_ses-PIOP1	20.75	M	28	1	0	0	0	1	0
sub-0152_ses-PIOP1	21.5	M	26	1	0	0	0	1	0
sub-0153_ses-PIOP1	22.75	M	24	1	0	0	0	1	0
sub-0154_ses-PIOP1	25.5	M	29	1	0	0	0	1	0
sub-0157_ses-PIOP1	20.5	M	23	1	0	0	0	1	0
sub-0158_ses-PIOP1	21.5	M	25	1	0	0	0	1	0
sub-0161_ses-PIOP1	18.5	M	33	1	0	0	1	1	0
sub-0166_ses-PIOP1	22.5	M	26	1	0	0	0	1	0
sub-0167_ses-PIOP1	23.25	M	23	1	0	0	0	1	0
sub-0168_ses-PIOP1	23.75	M	21	1	0	0	0	1	0
sub-0169_ses-PIOP1	23.5	M	20	1	0	0	0	1	0
sub-0171_ses-PIOP1	23.25	M	32	1	0	0	1	1	0
sub-0173_ses-PIOP1	20.5	M	26	1	0	0	0	1	0
sub-0174_ses-PIOP1	19.25	M	24	1	0	0	0	1	0
sub-0176_ses-PIOP1	24.5	M	34	1	0	0	1	1	0
sub-0179_ses-PIOP1	22	M	25	1	0	0	0	1	0
sub-0185_ses-PIOP1	23.25	M	20	1	0	0	0	1	0
sub-0187_ses-PIOP1	21.5	M	15	1	0	0	0	1	0
sub-0188_ses-PIOP1	25.5	M	24	1	0	0	0	1	0
sub-0191_ses-PIOP1	21.75	M	25	1	0	0	0	1	0
sub-0193_ses-PIOP1	19.5	M	20	1	0	0	0	1	0
sub-0201_ses-PIOP1	22.25	M	26	1	0	0	0	1	0
sub-0202_ses-PIOP1	23.5	M	12	1	0	0	0	1	0
sub-0208_ses-PIOP1	20.5	M	20	1	0	0	0	1	0
sub-0211_ses-PIOP1	22.5	M	35	1	0	0	1	1	0
sub-0213_ses-PIOP1	19.75	M	18	1	0	0	0	1	0
sub-0214_ses-PIOP1	19.5	M	19	1	0	0	0	1	0
sub-0001_ses-PIOP2	25.5	M	33	2	0	0	1	1	0
sub-0005_ses-PIOP2	24.75	M	24	2	0	0	0	1	0
sub-0006_ses-PIOP2	23.75	M	27	2	0	0	0	1	0
sub-0008_ses-PIOP2	21	M	22	2	0	0	0	1	0
sub-0013_ses-PIOP2	20.25	M	33	2	0	0	1	1	0
sub-0014_ses-PIOP2	23.25	M	18	2	0	0	0	1	0
sub-0018_ses-PIOP2	20.5	M	26	2	0	0	0	1	0
sub-0023_ses-PIOP2	22.75	M	27	2	0	0	0	1	0
sub-0024_ses-PIOP2	21	M	30	2	0	0	0	1	0
sub-0025_ses-PIOP2	25	M	24	2	0	0	0	1	0
sub-0028_ses-PIOP2	21.5	M	21	2	0	0	0	1	0
sub-0029_ses-PIOP2	21.75	M	25	2	0	0	0	1	0
sub-0030_ses-PIOP2	20.5	M	21	2	0	0	0	1	0
sub-0031_ses-PIOP2	20.75	M	30	2	0	0	0	1	0
sub-0032_ses-PIOP2	20.5	M	24	2	0	0	0	1	0
sub-0035_ses-PIOP2	23.25	M	20	2	0	0	0	1	0
sub-0041_ses-PIOP2	21	M	25	2	0	0	0	1	0
sub-0046_ses-PIOP2	24.25	M	24	2	0	0	0	1	0
sub-0050_ses-PIOP2	19.75	M	21	2	0	0	0	1	0
sub-0054_ses-PIOP2	23	M	21	2	0	0	0	1	0
sub-0056_ses-PIOP2	20.5	M	14	2	0	0	0	1	0
sub-0057_ses-PIOP2	25.75	M	17	2	0	0	0	1	0
sub-0059_ses-PIOP2	23.25	M	19	2	0	0	0	1	0
sub-0063_ses-PIOP2	25.25	M	26	2	0	0	0	1	0
sub-0065_ses-PIOP2	23.5	M	19	2	0	0	0	1	0
sub-0066_ses-PIOP2	19.5	M	27	2	0	0	0	1	0
sub-0070_ses-PIOP2	18.75	M	26	2	0	0	0	1	0
sub-0074_ses-PIOP2	20.25	M	34	2	0	0	1	1	0
sub-0078_ses-PIOP2	22.5	M	19	2	0	0	0	1	0
sub-0079_ses-PIOP2	20.25	M	23	2	0	0	0	1	0
sub-0081_ses-PIOP2	24.25	M	19	2	0	0	0	1	0
sub-0086_ses-PIOP2	21	M	20	2	0	0	0	1	0
sub-0087_ses-PIOP2	22.5	M	20	2	0	0	0	1	0
sub-0088_ses-PIOP2	23.5	M	26	2	0	0	0	1	0
sub-0093_ses-PIOP2	22	M	30	2	0	0	0	1	0
sub-0096_ses-PIOP2	21	M	25	2	0	0	0	1	0
sub-0107_ses-PIOP2	19.25	M	21	2	0	0	0	1	0
sub-0108_ses-PIOP2	21.25	M	18	2	0	0	0	1	0
sub-0110_ses-PIOP2	24.25	M	27	2	0	0	0	1	0
sub-0111_ses-PIOP2	22	M	30	2	0	0	0	1	0
sub-0113_ses-PIOP2	21.75	M	23	2	0	0	0	1	0
sub-0115_ses-PIOP2	22	M	32	2	0	0	1	1	0
sub-0117_ses-PIOP2	20.75	M	21	2	0	0	0	1	0
sub-0118_ses-PIOP2	20.5	M	25	2	0	0	0	1	0
sub-0120_ses-PIOP2	22.75	M	18	2	0	0	0	1	0
sub-0121_ses-PIOP2	21.75	M	21	2	0	0	0	1	0
sub-0122_ses-PIOP2	25	M	30	2	0	0	0	1	0
sub-0124_ses-PIOP2	22	M	26	2	0	0	0	1	0
sub-0126_ses-PIOP2	21	M	26	2	0	0	0	1	0
sub-0128_ses-PIOP2	22.75	M	27	2	0	0	0	1	0
sub-0129_ses-PIOP2	23.75	M	31	2	0	0	0	1	0
sub-0131_ses-PIOP2	22.5	M	34	2	0	0	1	1	0
sub-0133_ses-PIOP2	21.75	M	17	2	0	0	0	1	0
sub-0135_ses-PIOP2	21	M	16	2	0	0	0	1	0
sub-0136_ses-PIOP2	24.25	M	23	2	0	0	0	1	0
sub-0138_ses-PIOP2	23.75	M	26	2	0	0	0	1	0
sub-0141_ses-PIOP2	20.75	M	22	2	0	0	0	1	0
sub-0144_ses-PIOP2	20.25	M	26	2	0	0	0	1	0
sub-0151_ses-PIOP2	21.5	M	13	2	0	0	0	1	0
sub-0155_ses-PIOP2	19	M	27	2	0	0	0	1	0
sub-0156_ses-PIOP2	20.75	M	31	2	0	0	0	1	0
sub-0158_ses-PIOP2	20.75	M	19	2	0	0	0	1	0
sub-0159_ses-PIOP2	23	M	29	2	0	0	0	1	0
sub-0160_ses-PIOP2	20.75	M	24	2	0	0	0	1	0
sub-0161_ses-PIOP2	23.5	M	30	2	0	0	0	1	0
sub-0162_ses-PIOP2	18.75	M	29	2	0	0	0	1	0
sub-0163_ses-PIOP2	22.25	M	26	2	0	0	0	1	0
sub-0164_ses-PIOP2	21.75	M	20	2	0	0	0	1	0
sub-0165_ses-PIOP2	23.75	M	28	2	0	0	0	1	0
sub-0167_ses-PIOP2	24.75	M	22	2	0	0	0	1	0
sub-0173_ses-PIOP2	24	M	35	2	0	0	1	1	0
sub-0175_ses-PIOP2	24.25	M	15	2	0	0	0	1	0
sub-0177_ses-PIOP2	20.75	M	17	2	0	0	0	1	0
sub-0178_ses-PIOP2	22.25	M	27	2	0	0	0	1	0
sub-0182_ses-PIOP2	23.5	M	32	2	0	0	1	1	0
sub-0184_ses-PIOP2	21.5	M	17	2	0	0	0	1	0
sub-0185_ses-PIOP2	21	M	23	2	0	0	0	1	0
sub-0188_ses-PIOP2	23.75	M	26	2	0	0	0	1	0
sub-0189_ses-PIOP2	20.5	M	28	2	0	0	0	1	1
sub-0193_ses-PIOP2	24.75	M	29	2	0	0	0	1	0
sub-0195_ses-PIOP2	23.25	M	22	2	0	0	0	1	0
sub-0196_ses-PIOP2	19.25	M	19	2	0	0	0	1	0
sub-0198_ses-PIOP2	25	M	26	2	0	0	0	1	0
sub-0203_ses-PIOP2	20	M	29	2	0	0	0	1	0
sub-0205_ses-PIOP2	18.25	M	27	2	0	0	0	1	0
sub-0207_ses-PIOP2	24.25	M	19	2	0	0	0	1	0
sub-0209_ses-PIOP2	19.25	M	19	2	0	0	0	1	0
sub-0211_ses-PIOP2	24	M	22	2	0	0	0	1	0
sub-0212_ses-PIOP2	25	M	27	2	0	0	0	1	0
sub-0213_ses-PIOP2	22.5	M	13	2	0	0	0	1	0
sub-0216_ses-PIOP2	24.5	M	30	2	0	0	0	1	0
sub-0217_ses-PIOP2	22.25	M	22	2	0	0	0	1	0
sub-0221_ses-PIOP2	20.75	M	27	2	0	0	0	1	0
sub-0224_ses-PIOP2	21.75	M	34	2	0	0	1	1	0
sub-0226_ses-PIOP2	20	M	19	2	0	0	0	1	0
    2. Run cortical thickness analysis using modelspec_cbm.json
      Test the main effect of Raven’s score on cortical thickness while controlling for age and scanner using ANOVA on female subjects
      {
	"BrainSuite": {
	  "Structural":{
        "tsv_fname": "aomic-piop_10192021.tsv",
        "measure": "cbm",
		"test": "anova",
		"main_effect": "ravenscore",
		"covariates": [
			"age","scanner"
		],
		"corr_var": "",
		"group_var": "",
		"paired": 0,
		"smooth": 2.0,
		"mult_comp": "fdr",
		"pvalue":"parametric",
		"niter": 0,
		"roiid": [],
		"hemi": "both",
		"maskfile": "",
		"atlas": "",
		"roimeas": "",
		"dbmmeas": "" ,
		"exclude_col": "Fonly",
	  	"out_dir": "cbm_anova_F"},

	"Functional":{
        "tsv_fname": "",
		"file_ext": "-rest_bold.32k.GOrd.filt.mat",
		"lentime": 240,
		"matchT": 0,
		"stat_test": "atlas-linear" ,
		"pw_pairs": 2000,
		"pw_fdr": 0,
		"pw_perm": 2000,
		"outname": "BFPtest",
        "sig_alpha" : 0.05,
		"smooth_iter": 100,
		"save_surfaces": 1,
		"save_figures": 0,
		"atlas_groupsync": 1,
		"atlas_fname": "/data/atlas.mat",
		"test_all": 1,
		"colvar_main": "LogAge",
		"colvar_reg1": "Age",
		"colvar_reg2": "Sex",
		"colvar_exclude": "Exclude",
        "colvar_atlas": "Atlas",
        "out_dir": ""
      }
	}
}
    3. Run ROI-based analysis using modelspec_roi.json
      Test the main effect of Raven’s score on left pars opercularis while controlling for age and scanner using ANOVA on female subjects
      {
	"BrainSuite": {
	"Structural":{
        "tsv_fname": "aomic-piop_10192021.tsv",
        "measure": "roi",
        "test": "anova",
        "main_effect": "ravenscore",
        "covariates": [
            "age","scanner"
        ],
        "corr_var": "",
        "group_var": "",
        "paired": 0,
        "smooth": 2.0,
        "mult_comp": "fdr",
        "pvalue":"parametric",
        "niter": 0,
        "roiid": [143],
        "hemi": "both",
        "maskfile": "",
        "atlas": "",
        "roimeas": "gmthickness",
        "dbmmeas": "" ,
        "exclude_col": "Fonly",
        "out_dir": "roi_anova_F"},
	"Functional":{
        "tsv_fname": "",
		"file_ext": "-rest_bold.32k.GOrd.filt.mat",
		"lentime": 240,
		"matchT": 0,
		"stat_test": "atlas-linear" ,
		"pw_pairs": 2000,
		"pw_fdr": 0,
		"pw_perm": 2000,
		"outname": "BFPtest",
        "sig_alpha" : 0.05,
		"smooth_iter": 100,
		"save_surfaces": 1,
		"save_figures": 0,
		"atlas_groupsync": 1,
		"atlas_fname": "/data/atlas.mat",
		"test_all": 1,
		"colvar_main": "LogAge",
		"colvar_reg1": "Age",
		"colvar_reg2": "Sex",
		"colvar_exclude": "Exclude",
        "colvar_atlas": "Atlas",
        "out_dir": ""
      }
	}
}
    4. Run tensor-based morphometry analysis using modelspec_tbm.json
      TestingTest the main effect of Raven’s score on tensor-based morphometry analysis while controlling for age and scanner using ANOVA on female subjects
      {
	"BrainSuite": {

	  "Structural":{
        "tsv_fname": "aomic-piop_10192021.tsv",
        "measure": "tbm",
        "test": "anova",
        "main_effect": "ravenscore",
        "covariates": [
            "age","scanner"
        ],
        "corr_var": "",
        "group_var": "",
        "paired": 0,
        "smooth": 3.0,
        "mult_comp": "fdr",
        "pvalue":"parametric",
        "niter": 0,
        "roiid": [],
        "hemi": "both",
        "maskfile": "",
        "atlas": "",
        "roimeas": "",
        "dbmmeas": "" ,
        "exclude_col": "Fonly",
        "out_dir": "tbm_anova_F"},
	"Functional":{
        "tsv_fname": "",
		"file_ext": "-rest_bold.32k.GOrd.filt.mat",
		"lentime": 240,
		"matchT": 0,
		"stat_test": "atlas-linear" ,
		"pw_pairs": 2000,
		"pw_fdr": 0,
		"pw_perm": 2000,
		"outname": "BFPtest",
        "sig_alpha" : 0.05,
		"smooth_iter": 100,
		"save_surfaces": 1,
		"save_figures": 0,
		"atlas_groupsync": 1,
		"atlas_fname": "/data/atlas.mat",
		"test_all": 1,
		"colvar_main": "LogAge",
		"colvar_reg1": "Age",
		"colvar_reg2": "Sex",
		"colvar_exclude": "Exclude",
        "colvar_atlas": "Atlas",
        "out_dir": ""
      }
	}
}
    5. Run fractional anisotropy analysis using modelspec_dbm.json
      Test the difference in fractional anisotropy values across males and females using a t-test
      {
	"BrainSuite": {
	  "Structural":{
        "tsv_fname": "aomic-piop_10192021.tsv",
        "measure": "dbm",
		"test": "ttest",
		"main_effect": "sex",
		"covariates": [ "age", "scanner" ],
		"corr_var": "age",
		"group_var": "sex",
		"paired": 0,
		"smooth": 3.0,
		"mult_comp": "fdr",
		"pvalue":"parametric",
		"niter": 2000,
		"roiid": [],
		"hemi": "both",
		"maskfile": "",
		"atlas": "",
		"roimeas": "",
		"dbmmeas": "FA" ,
		"exclude_col": "Exclude",
	  	"out_dir": "dbm_ttest_F"},

	"Functional":{
        "tsv_fname": "",
		"file_ext": "-rest_bold.32k.GOrd.filt.mat",
		"lentime": 240,
		"matchT": 0,
		"stat_test": "atlas-linear" ,
		"pw_pairs": 2000,
		"pw_fdr": 0,
		"pw_perm": 2000,
		"outname": "BFPtest",
        "sig_alpha" : 0.05,
		"smooth_iter": 100,
		"save_surfaces": 1,
		"save_figures": 0,
		"atlas_groupsync": 1,
		"atlas_fname": "/data/atlas.mat",
		"test_all": 1,
		"colvar_main": "LogAge",
		"colvar_reg1": "Age",
		"colvar_reg2": "Sex",
		"colvar_exclude": "Exclude",
        "colvar_atlas": "Atlas",
        "out_dir": ""
      }
	}
}
    6. Run functional connectivity analysis using modelspec_fmri.json
      Test the main effect of Raven’s score on functional connectivity while controlling for age and scanner using atlas-based linear regression on female subjects
      {
	"BrainSuite": {
      "Structural":{
        "tsv_fname": "",
        "measure": "",
        "test": "anova",
        "main_effect": "",
        "covariates": [],
        "corr_var": "",
        "group_var": "",
        "paired": 0,
        "smooth": 2.0,
        "mult_comp": "fdr",
        "pvalue":"parametric",
        "niter": 0,
        "roiid": [],
        "hemi": "both",
        "maskfile": "",
        "atlas": "",
        "roimeas": "",
        "dbmmeas": "" ,
        "exclude_col": "",
        "out_dir": ""},

	"Functional":{
        "tsv_fname": "aomic-piop_10192021.tsv",
		"file_ext": "_task-restingstate_bold.32k.GOrd.filt.mat",
		"lentime": 480,
		"matchT": 1,
		"stat_test": "atlas-linear" ,
		"pw_pairs": 10000,
		"pw_fdr": 0,
		"pw_perm": 10000,
		"outname": "fmri_atlas_linear_F",
        "sig_alpha" : 0.05,
		"smooth_iter": 10,
		"save_surfaces": 1,
		"save_figures": 0,
		"atlas_groupsync": 1,
		"atlas_fname": "",
		"test_all": 1,
		"colvar_main": "ravenscore",
		"colvar_reg1": "age",
		"colvar_reg2": "scanner",
		"colvar_exclude": "Fonly",
        "colvar_atlas": "AtlasF",
        "out_dir": "fmri_atlas_linear_F"
      }
	}
}

  11. To run group-level mode, run the following commands:

    singularity run --bind /nafs/sjoshi,/nafs/shattuck $singImg $data $output group --modelspec modelspec_cbm.json --analysistype STRUCT
singularity run --bind /nafs/sjoshi,/nafs/shattuck $singImg $data $output group --modelspec modelspec_roi.json --analysistype STRUCT
singularity run --bind /nafs/sjoshi,/nafs/shattuck $singImg $data $output group --modelspec modelspec_tbm.json --analysistype STRUCT
singularity run --bind /nafs/sjoshi,/nafs/shattuck $singImg $data $output group --modelspec modelspec_dbm.json --analysistype STRUCT
singularity run --bind /nafs/sjoshi,/nafs/shattuck $singImg $data $output group --modelspec modelspec_fmri.json --analysistype FUNC