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On this page

  • 🧠 What is the ABCC?
  • 🚀 What Makes ABCC Special?
  • 📚 Featured In High-Impact Studies
  • 📦 What’s in Release 3.0.0 (2025-06-26)?
    • Core Data
    • At-A-Glance: Data Availability
  • 🆕 Highlights of This Release
    • New Data
    • 🔧 Key Revisions
  • 🧠 NMIND Standards for Reproducibility
  • Coming Soon in the Next Release
  • Known Issues (Temporary)
  • Release History
  1. Imaging data
  2. ABCD BIDS Community Collection (ABCC)
  3. Documentation
  4. Imaging
  5. ABCD-BIDS community collection

ABCD-BIDS community collection

🧠 What is the ABCC?

The ABCD-BIDS Community Collection (ABCC) is a rigorously curated MRI dataset derived from the ABCD Study. It leverages the Brain Imaging Data Structure (BIDS) standards and software standards grounded in the NMIND framework for reproducible neuroimaging, ABCC delivers ready-to-use MRI raw data and derivative data enabling rapid, robust scientific discovery.

All data in the collection are collated or run on data that has passed Data Analysis, Informatics & Resource Center (DAIRC) quality control and are processed using peer-reviewed, open-source pipelines.

BrainSwipes is used to perform visual inspection for quality control of derivatives generated by processing pipelines - this is an active community-driven effort - please see details and information on how to get involved here.

See Feczko et al. (2021) for details.

🚀 What Makes ABCC Special?

  • BIDS-Standardized: Harmonized formats that accelerate cross-study integration and reproducibility.
  • NMIND reviewed Pipelines: Data passed through NMIND reviewed tools including the DCAN Labs ABCD-HCP pipeline, QSIPrep, and soon to include fMRIPrep and XCP-D pipelines.
  • Surface + Volume Data: Includes both BIDS input and derived MRI data provided in BIDS validated formats (e.g. CIFTI/NIFTI/GIFTI).
  • Versioned & Transparent: Every release includes detailed change logs and version tracking for reproducibility.
  • Continually Updated: Reflects the most current ABCD data releases, with ongoing additions planned.

📚 Featured In High-Impact Studies

ABCC data has already powered impactful neuroscience research, including:

  • 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

Over 90 studies have been published referencing the ABCC. You can find a list of them and formatted reference files here.

📦 What’s in Release 3.0.0 (2025-06-26)?

Core Data

  • BIDS input data (converted from DICOM)
  • abcd-hcp-pipeline (v0.1.4) derivatives (volume + surface data, HCP-style processing with BIDS formatted derivatives)
  • FreeSurfer 5.3.0-HCP segmentation statistics + surface morphometrics
  • QSIPrep-processed diffusion-weighted MRI

At-A-Glance: Data Availability

Year BIDS Inputs abcd-hcp-pipeline Derivatives DWI Inputs QSIPrep Derivatives
Baseline 11,753 11,751 9,564 8,852
2 8,086 8,085 7,669 7,273
4 6,355 6,351 6,207 6,066
6 3,820 3,820 3,748 3,676

🆕 Highlights of This Release

New Data

  • Additional inputs and derivatives for Years 2, 4, and 6
  • Expanded QSIPrep diffusion derivatives
  • New sessions.tsv files within subject directories with:
    • Session demographics & acquisition timestamps
    • Updated scanner software metadata
    • Inclusion of QC columns described in Automated QA section

🔧 Key Revisions

  • Updated abcd-hcp-pipeline v0.1.4 (see changes here): More BIDS-compliant outputs, cleaner directory structure, an updated ExecutiveSummary for QC, and improved BOLD bandpass filtering in DCANBoldProc.
  • 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.

Details: In the prior release. TOPUP being given a denoised b=0 image from the DWI series and a raw b=0 image in the opposite phase encoding direction, resulted in inaccurate distortion correction results for a subset of subjects. The updated version uses unprocessed b=0 images in both phase encoding directions.

🧠 NMIND Standards for Reproducibility

All ABCC processing pipelines have undergone independent peer review under the NMIND infrastructure designed to maximize reproducibility and standardization across neuroimaging tools. Please see here for details.

Coming Soon in the Next Release

  • Structural & functional MRI processed through fMRIPrep and XCP-D
  • Task fMRI pipeline results
  • QSIRecon derivatives for DWI
  • Individualized network maps (Hermosillo et al. 2024)

Known Issues (Temporary)

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 will be restored in the next release. In the meantime, users who require these files can regenerate them from the concatenated motion files using the abcd-abcc_motion_reg_generator utility (see its documentation for details).

Release History

Release 3.0 changes

The below release history reflects releases previously available through the NIMH Data Archive (NDA). Starting with Release 3.0.0 (2025-06-26), the ABCC is made available through the NBDC Data Hub and does not reflect revisions made to the NDA repository. The release history for versions 2.0.0 and below are provided below for legacy purposes. Please visit the ABCC Archival Data Release Documentation for the archived release documentation associated wih the data available for prior releases via the NDA.

Release 2.0.0 (2022-06-22)

REVISIONS

  1. Uploading 144 participants with new data due to revised fast track QC: The initial release was processed prior to new updates to the fast track QC spreadsheet that affected the original inputs for 144 participants. This led to discrepancies in the number of timepoints reported for connectivity matrices (see below) relative to the inputs. The 144 participants were re-processed through the ABCD-BIDS pipeline at the Minnesota Supercomputing Institute (MSI). The participants.tsv file indicates which subjects were reprocessed. These subjects have new Gordon 10 and 5 minute connectivity matrices generated and replaced on the NDA. The old matrices remain valid, but may use different frames from the new matrices. The labels for the updated connectivity matrices were defined in Gordon et al. (2016) and generated using the DCAN Labs cifti connectivity wrapper at a frame displacement (FD) threshold of 0.2 mm to filter out high-motion frames. An outlier detection procedure was used to exclude remaining frames 2 STD from the mean.
  2. Providing Connectivity matrices for those participants with discrepancies in the number of timepoints used
  3. Uploading JSONs for the diffusion inputs in some participants.
  4. Updated version of the participants.tsv to v1.0.2 includes correction to site and sex designation for a small subset of subjects based on new information from the DAIRC.

NEW ADDITIONS

  1. Individualized Network Maps Generated with Infomap and Template Matching (Submission ID: 36448)
  2. Derivatives for the fmriprep pipeline: fMRIPrep v20.2.0 was run on all 10,038 participants whose visit one data was successfully converted to BIDS. The limited fMRIPrep processing errors were due to subjects that did not have any valid fMRI runs, but we did not do any manual quality control of outputs. 9,484 participants have at least one output. The data is available in 18 submissions (a summary, including number of files and submission size can be found here). Detailed information about the files included in each submission are on the second tab of that spreadsheet. Files with no submission name listed have not yet been uploaded.
  3. DWI sidecar JSON patch (Diffusion inputs) (Submission IDs: 36449 - 36452): The DWI acquisition parameters from subjects scanned on Philips and GE with MR Software release versions 5.3.0_5.3.0.0 and DV25.0_R02_1549.b respectively (n=423) are missing the required field, PhaseEncodingDirection. This omission is because they reported the axis and not direction; therefore we did a manual check of these images to check the phase encoding direction, so that these JSON inputs are BIDS compatible and can be processed by pipelines like QSIprep. These JSONs have been updated and uploaded.
  4. Level-2 task files from the ABCD-task-fMRI pipeline (Submission IDs: 36458 - 36630)
Release 2.0.0 (2022-06-22)

REVISIONS

  1. Uploading 144 participants with new data due to revised fast track QC: The initial release was processed prior to new updates to the fast track QC spreadsheet that affected the original inputs for 144 participants. This led to discrepancies in the number of timepoints reported for connectivity matrices (see below) relative to the inputs. The 144 participants were re-processed through the ABCD-BIDS pipeline at the Minnesota Supercomputing Institute (MSI). The participants.tsv file indicates which subjects were reprocessed. These subjects have new Gordon 10 and 5 minute connectivity matrices generated and replaced on the NDA. The old matrices remain valid, but may use different frames from the new matrices. The labels for the updated connectivity matrices were defined in Gordon et al. (2016) and generated using the DCAN Labs cifti connectivity wrapper at a frame displacement (FD) threshold of 0.2 mm to filter out high-motion frames. An outlier detection procedure was used to exclude remaining frames 2 STD from the mean.
  2. Providing Connectivity matrices for those participants with discrepancies in the number of timepoints used
  3. Uploading JSONs for the diffusion inputs in some participants.
  4. Updated version of the participants.tsv to v1.0.2 includes correction to site and sex designation for a small subset of subjects based on new information from the DAIC.

NEW ADDITIONS

  1. Individualized Network Maps Generated with Infomap and Template Matching (Submission ID: 36448)
  2. Derivatives for the fmriprep pipeline: fMRIPrep v20.2.0 was run on all 10,038 participants whose visit one data was successfully converted to BIDS. The limited fMRIPrep processing errors were due to subjects that did not have any valid fMRI runs, but we did not do any manual quality control of outputs. 9,484 participants have at least one output. The data is available in 18 submissions (a summary, including number of files and submission size can be found here). Detailed information about the files included in each submission are on the second tab of that spreadsheet. Files with no submission name listed have not yet been uploaded.
  3. DWI sidecar JSON patch (Diffusion inputs) (Submission IDs: 36449 - 36452): The DWI acquisition parameters from subjects scanned on Philips and GE with MR Software release versions 5.3.0_5.3.0.0 and DV25.0_R02_1549.b respectively (n=423) are missing the required field, PhaseEncodingDirection. This omission is because they reported the axis and not direction; therefore we did a manual check of these images to check the phase encoding direction, so that these JSON inputs are BIDS compatible and can be processed by pipelines like QSIprep. These JSONs have been updated and uploaded.
  4. Level-2 task files from the ABCD-task-fMRI pipeline (Submission IDs: 36458 - 36630)
Release 1.1.1 (2020-10-07)

This was a small version 1.0.0 release of the derivatives_qc.(json|tsv) with additional BIDS derivatives quality control data including a “brain coverage score” for the derivatives.func.runs_task-(MID|nback|rest|SST)_volume data subsets.

Release 1.1.0 (2020-07-27)

NEW ADDITIONS

  • 157 additional subjects due to updated fast track QC spreadsheet
  • participants.(json|tsv) version 1.0.0: BIDS standard participants files with matched groups
  • sourcedata.func.task_events: Task-based fMRI E-Prime files
  • inputs.dwi.dwi: DWI BIDS input data
  • derivatives.anat.stats: FreeSurfer stats files
  • derivatives.anat.(T1w|T2w): T1 and T2 volumes
  • derivatives.anat.wmparc: white-matter volume ROIs
  • derivatives.func.updated_motion_task-(MID|nback|SST|rest): Improved motion files (including outlier calculation)
  • derivatives.func.pconns: Curated parcellated connectivity files
  • derivatives.func.runs_task-(MID|nback|SST|rest)_volume: Minimally-processed fMRI volumes
Release 1.0.0 (2020-02-17)

This was the initial release of DCAN Labs ABCD-BIDS inputs and derivatives containing 10,038 MRI sessions worth of NDA imagingcollection01 data and 9,647 MRI sessions worth of NDA fmriresults01 data.

KNOWN ISSUES

  • sourcedata: Event Related Information sourcedata files can be csv files as well as txt files, but this release only includes the txt files
  • task-rest_bold.json: Discovered in the middle of June 2020, the modality-specific BIDS inherited task-rest_bold.json file at the top of the directory tree which is nested in almost every task-rest associated record in the NDA database has a typo in it. The "TaskDescription" key has a value of "See http://www.cognitiveatlas.org/task/id/tsk_4a57abb949e1a/". However, this link goes to the stop signal task page on the Cognitive Atlas website. Instead you should refer to the Cognitive Atlas website for “rest eyes open”. This website describes the task as: “Subjects rest passively with their eyes open. Often used as a baseline for comparison for other tasks.”
  • derivatives.func.runs_task-rest_volume: This data subset was originally uploaded in Release 1.1.0, but was missing all runs chronologically numbered 3 and up. We are uploading these missing data in Release 1.1.2.
  • updated_dwi_input_json: The DWI acquisition parameters from all subjects scanned on GE with MR Software release DV25.0_R02_1549.b (n=281) are missing the required field, PhaseEncodingDirection. This omission is because they reported the axis and not direction.

References

Bethlehem, R. a. I., J. Seidlitz, S. R. White, J. W. Vogel, K. M. Anderson, C. Adamson, S. Adler, et al. 2022. Nature 604 (7906). Nature Publishing Group: 525–33. doi:10.1038/s41586-022-04554-y.
Chaarani, B., S. Hahn, N. Allgaier, S. Adise, M. M. Owens, A. C. Juliano, D. K. Yuan, et al. 2021. Nature Neuroscience 24 (8). Nature Publishing Group: 1176–86. doi:10.1038/s41593-021-00867-9.
Cieslak, Matthew, Philip A. Cook, Xiaosong He, Fang-Cheng Yeh, Thijs Dhollander, Azeez Adebimpe, Geoffrey K. Aguirre, et al. 2021. Nature Methods 18 (7). Nature Publishing Group: 775–78. doi:10.1038/s41592-021-01185-5.
Feczko, Eric, Greg Conan, Scott Marek, Brenden Tervo-Clemmens, Michaela Cordova, Olivia Doyle, Eric Earl, et al. 2021. doi:10.1101/2021.07.09.451638.
Gordon, Evan M., Roselyne J. Chauvin, Andrew N. Van, Aishwarya Rajesh, Ashley Nielsen, Dillan J. Newbold, Charles J. Lynch, et al. 2023. Nature 617 (7960). Nature Publishing Group: 351–59. doi:10.1038/s41586-023-05964-2.
Gordon, Evan M., Timothy O. Laumann, Babatunde Adeyemo, Jeremy F. Huckins, William M. Kelley, and Steven E. Petersen. 2016. Cerebral Cortex 26 (1): 288–303. doi:10.1093/cercor/bhu239.
Hermosillo, Robert J. M., Lucille A. Moore, Eric Feczko, Óscar Miranda-Domínguez, Adam Pines, Ally Dworetsky, Gregory Conan, et al. 2024. Nature Neuroscience 27 (5): 1000–1013. doi:10.1038/s41593-024-01596-5.
Keller, Arielle S., Tyler M. Moore, Audrey Luo, Elina Visoki, Mārtiņš M. Gataviņš, Alisha Shetty, Zaixu Cui, et al. 2024. Developmental Cognitive Neuroscience 66 (April): 101370. doi:10.1016/j.dcn.2024.101370.
Keller, Arielle S., Adam R. Pines, Sheila Shanmugan, Valerie J. Sydnor, Zaixu Cui, Maxwell A. Bertolero, Ran Barzilay, et al. 2023. Nature Communications 14 (1). Nature Publishing Group: 8411. doi:10.1038/s41467-023-44087-0.
Marek, Scott, Brenden Tervo-Clemmens, Finnegan J. Calabro, David F. Montez, Benjamin P. Kay, Alexander S. Hatoum, Meghan Rose Donohue, et al. 2022. Nature 603 (7902). Nature Publishing Group: 654–60. doi:10.1038/s41586-022-04492-9.
Marek, Scott, Brenden Tervo-Clemmens, Ashley N. Nielsen, Muriah D. Wheelock, Ryland L. Miller, Timothy O. Laumann, Eric Earl, et al. 2019. Developmental Cognitive Neuroscience 40 (December): 100706. doi:10.1016/j.dcn.2019.100706.
Mehta, Kahini, Taylor Salo, Thomas J. Madison, Azeez Adebimpe, Danielle S. Bassett, Max Bertolero, Matthew Cieslak, et al. 2024. Imaging Neuroscience 2 (August): 1–26. doi:10.1162/imag_a_00257.
 

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