Download Abcd Data

All data access information is documented on the NDA ABCD Featured Dataset page and includes pointers to an external ABCD Study wiki where data release notes and general information about the data resource are provided. All users should review the release notes for detailed information on the released data. Note that with the change to how release notes are made available, they will be updated regularly and thus users are advised to check -notes/start-page.html for the most up-to-date information. Release notes for qualified users only (i.e., non-public) are available at =2147. The 5.0 data ontology and dictionary can be viewed at -dict.abcdstudy.org/.

The table below highlights key differences between the 4.0 and 5.0 data releases. Note that the Data Exploration and Analysis Portal (DEAP) has been decommissioned as of June 1, 2023. In addition, study creation no longer works with how the data are shared this year. We anticipate reinstating it with the 6.0 data release.

Download Abcd Data

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This special issue of ChildArt introduces the intersection of the arts and neuroscience through an overview of the ABCD Study. It presents some of the data from the study, as well as other research looking at the impact of the arts on child development. The issue combines the work of experts in neuroscience, world renowned artists, specialists in child development, and others. Topics covered include the juncture between the arts and human culture, the developing adolescent brain, the interaction between cultural and biological processes and artistic creation, the interface of the arts and science as a multisensory experience, insights from the neuroscience of dance and music, and more. We hope that this special issue will stimulate creativity and innovation in research on the impact of the arts on child development as well as encourage researchers to leverage the ABCD Study data to advance research on a wide range of other topics.

All applicants planning research (funded or conducted in whole or in part by NIH) that results in the generation of scientific data are required to comply with the instructions for the Data Management and Sharing Plan. All applications, regardless of the amount of direct costs requested for any one year, must address a Data Management and Sharing Plan.

Consistent with the NIH Policy for Data Management and Sharing, when data management and sharing is applicable to the award, recipients will be required to adhere to the Data Management and Sharing requirements as outlined in the NIH Grants Policy Statement. Upon the approval of a Data Management and Sharing Plan, it is required for recipients to implement the plan as described.

Hey, I getting ready to do some analyses on ABCD data. I was wondering if anyone had preprocessed the data into bids format and used fMRIprep/open neuro on it already using AWS/ developed a pipeline? I am a noob on AWS and if someone has already figured this out I would be pretty excited.

Grace

Hi, I have been working to download data from NDAR- I was wondering if you have any tips on selecting and downloading only the rsfMRI or DTI files? Currently I have to open one page at a time and select them individually to download them.

Description: This data collection from the Developmental Cognition and Neuroimaging (DCAN) Labs contains a regularly updated dataset of ABCD Brain Imaging Data Structure (BIDS) version 1.2.0 pipeline inputs and derivatives. Source data are currently comprised of all the ABCD Study participants baseline year 1 arm 1 DICOM imaging data that passed initial acquisition quality control from the ABCD Data Analysis and Informatics Center (DAIC) and were processed by DCAN Labs. The input DICOM data to this BIDS version 1.2.0 ( ) data collection were retrieved from the NIMH Data Archive (NDA) share of ABCD fast-track data ( _collection.html?id=2573) and were last accessed on May 1, 2019. BIDS input data were converted from DICOMs using Dcm2Bids ( ). BIDS derivatives data were derived from the DCAN Labs ABCD-BIDS MRI processing pipeline which outputs Human Connectome Project (HCP) Minimal Preprocessing Pipelines-style data in both volume and surface spaces ( , ). This collection is independent from ABCD Data Collection 2573. Users may access ABCD DICOM files via the ABCD fast-track imaging data release in Collection 2573.

The Access to Biological Collections Data (ABCD) Schema is an evolving comprehensive standard for the access to and exchange of data about specimens and observations (a.k.a. primary biodiversity data).

As the largest longitudinal study of adolescent brain development and behavior to date, the Adolescent Brain Cognitive Development (ABCD) Study has provided immense opportunities for researchers across disciplines since its first data release in 2018. The size and scope of the study also present a number of hurdles, which range from becoming familiar with the study design and data structure to employing rigorous and reproducible analyses. The current paper is intended as a guide for researchers and reviewers working with ABCD data, highlighting the features of the data (and the strengths and limitations therein) as well as relevant analytical and methodological considerations. Additionally, we explore justice, equity, diversity, and inclusion efforts as they pertain to the ABCD Study and other large-scale datasets. In doing so, we hope to increase both accessibility of the ABCD Study and transparency within the field of developmental cognitive neuroscience.

Trait stability of measures is an essential requirement for individual differences research. Functional MRI has been increasingly used in studies that rely on the assumption of trait stability, such as attempts to relate task related brain activation to individual differences in behavior and psychopathology. However, recent research using adult samples has questioned the trait stability of task-fMRI measures, as assessed by test-retest correlations. To date, little is known about trait stability of task fMRI in children. Here, we examined within-session reliability and long-term stability of individual differences in task-fMRI measures using fMRI measures of brain activation provided by the adolescent brain cognitive development (ABCD) Study Release v4.0 as an individual's average regional activity, using its tasks focused on reward processing, response inhibition, and working memory. We also evaluated the effects of factors potentially affecting reliability and stability. Reliability and stability (quantified as the ratio of non-scanner related stable variance to all variances) was poor in virtually all brain regions, with an average value of 0.088 and 0.072 for short term (within-session) reliability and long-term (between-session) stability, respectively, in regions of interest (ROIs) historically-recruited by the tasks. Only one reliability or stability value in ROIs exceeded the 'poor' cut-off of 0.4, and in fact rarely exceeded 0.2 (only 4.9%). Motion had a pronounced effect on estimated reliability/stability, with the lowest motion quartile of participants having a mean reliability/stability 2.5 times higher (albeit still 'poor') than the highest motion quartile. Poor reliability and stability of task-fMRI, particularly in children, diminishes potential utility of fMRI data due to a drastic reduction of effect sizes and, consequently, statistical power for the detection of brain-behavior associations. This essential issue urgently needs to be addressed through optimization of task design, scanning parameters, data acquisition protocols, preprocessing pipelines, and data denoising methods.

Selections in the tree automatically filter the data dictionary displayed in the table on the right-hand side, i.e., the more fine-grained the selection of nodes in the tree on the left-hand side, the fewer variables will be displayed in the table. Users can use this to drill down into one or several domains, sub-domains, etc. For example, the following figure shows three selection states

The tree hierarchy and selection of nodes can also be specified by appending one or several URL parameters to the base URL like https//data-dict.abcdstudy.org?parameter_1=valueA,valueB&parameter_2=valueC. This is a good option if one would like to open the application with a certain predefined selection, for example, to send a colleague the data dictionary of a specific table or a domain.

As described above, the table can be used in combination with the tree selector on the left hand side to display only variables that are part of the selected nodes in the tree. But the table provides additional features to filter and search the data dictionary.

Note: The data dictionary explorer can only be used to explore and download the ABCD data dictionary. It cannot be used to download the actual data. Users with a valid data use certificate can download the data through NDA (see also the release note Start Page).

The National Institutes of Health announced today that enrollment for the Adolescent Brain Cognitive Development (ABCD) Study is now complete and, in early 2019, scientists will have access to baseline data from all ABCD Study participants.

Anonymized study data are being made available to the broad research community on a regular basis. This will allow scientists to analyze data and ask novel questions that were not even anticipated in the original study planning. Offering these data while the study is in progress means that both ABCD investigators and non-ABCD researchers will have access to the datasets to pursue their own research interests.

Similarly, researchers can look at risk and resilience factors for mental illness and substance use, including genetics, family history, traits such as impulsivity, and exposure to positive and negative environmental events. With longitudinal data, the developmental trajectories of the participants can be tracked to better understand these complex relationships, and eventually to improve prevention or mitigate risks for adverse outcomes. ff782bc1db