About the ABCC
Introduction
The ABCD-BIDS Community Collection (ABCC) provides processed, analysis-ready neuroimaging derivatives from the ABCD Study, updated alongside central ABCD data releases. The collection leverages state-of-the-art, community-standard pipelines, including fMRIPrep, XCP-D, and QSIPrep/QSIRecon, to generate harmonized structural, functional, and diffusion MRI derivatives, along with downstream outputs for connectivity and advanced analyses.
To date, ABCC has supported over 100 publications spanning brain development, cognition, mental health, and methodological innovation. A full list of publications and formatted citation files are available here. Highlights include:
- Meisler et al. (2026): Highly replicable multisite patterns of adolescent white matter maturation
- Marek et al. (2019): Identifying reproducible individual differences in childhood functional brain networks: An ABCD study (Developmental Cognitive Neuroscience)
- Chaarani et al. (2021): Task activation patterns in 9-10 year old youths
- Cieslak et al. (2021): QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data (Nature Methods)
- Bethlehem et al. (2022): Brain Charts for the human lifespan
- Marek et al. (2022): Reproducible brain behavior associations require thousands of samples
- Gordon et al. (2023): Identification of the human SCAN network, revolutionizing our understanding of the human motor system.
- Keller et al. (2023): Functional topography is associated with youth cognition
- Hermosillo et al. (2024): Individualized functional network mapping in adolescents (Nature Neuroscience)
- Keller et al. (2024): Environmental exposures mediate the association between functional topography and cognition
- Mehta et al. (2024): XCP-D: an extensible pipeline for rs-fMRI connectivity preprocessing
Key Features
- Data are compliant with the Brain Imaging Data Structure (BIDS) standard for reproducible, cross-study analyses.
- Data are processed using state-of-the-art, publicly available pipelines developed within the NMIND framework for reproducible neuroimaging software (see details).
- All ABCC release data have passed DAIRC raw MR data quality control (QC). In addition, QC is performed post-processing via BrainSwipes, a community-driven visual QC platform (to be available in a future release).
- Each release includes detailed version tracking and change logs.
Processing & Data Standards
Processing pipelines used to generate the ABCC derivatives follow community standards for reproducible neuroimaging software laid out by the NMIND consortium (Kiar et al., 2023). Pipelines must be publicly available, containerized, and published with a DOI. Pipelines are peer-reviewed via the NMIND Coding Standards Checklist to ensure they meet community-driven scientific software standards for documentation, infrastructure, and testability. This process assigns badge ratings to reviewed tools, which are published on the NMIND website under Evaluated Tools.
Release Notes (v4.0.0)
Core Data
The ABCC includes data processed through the following pipelines:
- Structural & Functional MRI [NEW]
- fMRIPrep v25.1.4: Minimal functional pre-processing
- XCP-D v0.13.0: Functional post-processing, including denoising & connectivity
- ReproTM: Individualized functional network maps via template matching
- Diffusion MRI
- ModelArrayIO [NEW]
- ModelArrayIO outputs (HDF/CSV) for efficient voxel- and/or vertex-wise statistical modeling with the ModelArray R package, including:
- QSIRecon-ModelArray multi-model diffusion metrics
- XCP-D-ModelArray connectivity, ALFF, ReHo, and morphometrics
- ModelArrayIO outputs (HDF/CSV) for efficient voxel- and/or vertex-wise statistical modeling with the ModelArray R package, including:
ABCC no longer includes ABCD-HCP BIDS derivatives: see release notes for details.
This minimal release excludes preprocessed BOLD timeseries, confounds, and surface-projected functional data. Users who require full outputs can follow the instructions provided under How to Generate Full Derivatives.
Participant Counts
| Year | fMRIPrep | XCP-D | QSIPrep | ReproTM |
|---|---|---|---|---|
| Baseline | 11,685 | 10,396 | 9,163 | 6,035 |
| 2 | 8,043 | 7,654 | 7,276 | 5,767 |
| 4 | 6,303 | 6,147 | 6,063 | 5,380 |
| 6 | 3,797 | 3,756 | 3,675 | 3,492 |
Available raw BIDS counts are shown below for each pipeline by study year. Differences reflect modality requirements (sMRI, sMRI+fMRI, or dMRI). Overall processing success rates were high across pipelines (96.6–99.8%).
| Year | fMRIPrep | XCP-D | QSIPrep |
|---|---|---|---|
| sMRI present | sMRI+fMRI present | dMRI present | |
| Baseline | 11,706 | 10,416 | 9,561 |
| 2 | 8,061 | 7,672 | 7,666 |
| 4 | 6,325 | 6,166 | 6,203 |
| 6 | 3,806 | 3,765 | 3,747 |
Key Revisions
Starting with Release 7.0, ABCC distributions include the following updates. Documentation for prior releases remains available via the Version dropdown menu located in the upper right-hand corner of the ABCD Data Documentation site.
Raw BIDS Consolidation
In Releases 6.0–6.1, BIDS raw data were distributed separately under dairc/ and abcc/. As of Release 7.0, all raw BIDS data are consolidated under a single dairc/ collection.
Legacy documentation: Raw BIDS
ABCD-HCP Pipeline Deprecation
Beginning with Release 7.0, ABCD-HCP pipeline derivatives are no longer included in ABCC releases. Moving forward, ABCC will focus on fMRIPrep- and XCP-D–based derivatives for structural and functional MRI to align with current community standards. Legacy ABCD-HCP outputs remain available in Release 6.1 via the NBDC Data Hub, including:
- ABCD-HCP BIDS v0.1.4: HCP-style MRI processing pipeline in volume & surface space
- FreeSurfer 5.3.0-HCP: Segmentation statistics & surface morphometrics
Associated documentation is available in the 6.1.3 legacy documentation: see Processing and Derivatives.
Known Issues
During reprocessing of duplicate functional runs, four cases failed due to out-of-memory errors and are not included in the current release. Derivatives for these cases remain available in previous releases and can be accessed if needed. (View affected cases)
Coming Soon
- Imaging derivatives for remaining subjects: fMRIPrep v25.1.4 minimal preprocessing outputs, along with confound estimates for all processed subjects, and XCP-D v0.13.0 post-processing outputs
- ReproTM individualized functional network maps for all functional tasks ( MID, SST, nBack)
- Task fMRI analysis results
- BrainSwipes Quality Control: structural/functional QC of XCP-D outputs generated via BrainSwipes, a gamified crowdsourcing platform for high-volume manual QC
BrainSwipes is a community-driven effort and we encourage all ABCC users to participate! No prior experience with visual QC is required. To get started, create a free account on BrainSwipes. You will then be guided through a simple tutorial that demonstrates how to evaluate derivative images and classify them as pass or fail.
Release History
NEW ADDITIONS
- QSIRecon reconstruction derivatives generated from preprocessed diffusion MRI data using the following reconstruction specifications:
- Diffusion tensor modeling: DSI Studio (all b-values), TORTOISE (b < 1200), DIPY (as part of DKI)
- Diffusion kurtosis modeling: DIPY
- Q-space imaging: DSI Studio
- NODDI models: AMICO
- Tractography: DSI Studio AutoTrack on MSMT FODs (from MRtrix3)
- QSIRecon-ModelArray - A single HDF5 (.h5) file and corresponding CSV file containing Mean Diffusivity (MD) values from all subjects in the current QSIRecon output. These files enable efficient voxelwise model fitting in R using the ModelArray package, allowing users to compute and write model-fitted parameters, p-values, and R² maps back into NIfTI files.
REVISIONS
Resolved critical issues in abcd-hcp-pipeline derivatives:
- Missing Volume-Based Resting-State Data (Runs 3–8): Restored missing data by re-executing the file-mapper across all participants
- Missing nBack Filtered Concatenated dtseries: Generated missing files using the using abcc_concat_filtered_dtseries_generator tool for all participants.
- Timepoint Mismatch Resolution: Resolved timepoint mismatches between filtered dtseries (
*_task-*_bold_desc-filtered_timeseries.dtseries.nii)and motion mask files (*_task-*_desc-filtered_motion_mask.mat)( N ~ 746 ) (View affected cases) - Duplicate Functional Runs: Reprocessed 861 cases through complete BIDS conversion and abcd-hcp-pipeline re-execution (View affected cases)
KNOWN ISSUE
Missing Cases from Duplicate Run Reprocessing: During reprocessing of duplicate functional runs, four cases failed due to out-of-memory errors and are not included in the current release. Derivatives for these cases remain available in previous releases and can be accessed if needed. (View affected cases)
REVISIONS
- Updated abcd-hcp-pipeline v0.1.4:: Enhanced BIDS compliance, streamlined directory structure, updated ExecutiveSummary QC, and improved BOLD bandpass filtering. (see changes here)
- Fixed incorrect AP/PA labeling in subset of GE dv26 subjects.
- Updated QSIPrep v0.21.4 (see changes here): Critical fixes to distortion correction and QC metric calculation.
Important Note: Users of earlier QSIPrep derivatives are encouraged to reprocess analyses to account for the distortion correction fix. In the prior release, TOPUP was given a denoised b=0 image from the DWI series and a raw b=0 image in the opposite phase encoding direction, resulting in inaccurate distortion correction for a subset of subjects. The updated version uses unprocessed b=0 images in both phase encoding directions.
NEW ADDITIONS
- Additional inputs and derivatives for Years 2, 4, and 6
- Expanded QSIPrep diffusion derivatives
- New
sessions.tsvfiles with session demographics, acquisition timestamps, scanner metadata, and automated QC metrics. Structural QA columns include BOLD brain coverage Pass/Fail indicators (bc_(task)_run-(run_num)) based on 10% threshold, coverage percentages (bc_(task)_run-(run_num)_perc_vox), and outlier counts for subcortical segmentation volumes (n=22) and cortical morphometry (n=333). Functional QA columns include Pass/Fail indicators for 5- and 10-minute connectivity matrix generation (5min_pconn_<atlas>,10min_pconn_<atlas>) and corresponding outlier counts (n=61776) across five parcellation schemes: Gordon2014, HCP2016, Markov2012, Power2011, and Yeo2011 (all with FreeSurferSubcortical). Values of 888 indicate missing or ungenerated files, except for pconn Pass/Fail columns.
KNOWN ISSUE
Missing Volume-Based Resting-State Run Files (Runs 3–8): Due to a transfer issue, some minimally processed, volume-based resting-state data are missing for runs 3–8 (mainly affecting data from Years 4 and 6). Surface-based CIFTI data — used by most researchers — are fully available and unaffected. Affected files include:
- `*_task-rest_run-{3-8}_motion.tsv`
- `*_task-rest_run-{3-8}_space-MNI_bold.nii.gz`
- `*_task-rest_run-{3-8}_desc-filteredincludingFD_motion.tsv`
These files were restored in v3.1.0 patch release. Users who required these files could also regenerate them from the concatenated motion files using the [abcd-abcc_motion_reg_generator](https://github.com/nbdc-datahub/abcd-abcc_motion_reg_generator) utility (see its documentation for details).ABCC releases through version 2.0.0 were distributed through the NIMH Data Archive (NDA). Starting with Release 3.0.0 (2025), ABCC data transitioned to the NBDC Data Hub, and release notes no longer reflect NDA repository revisions. Release notes and documentation for NDA-based releases are available in the ABCC Archival Data Release Documentation.