NDA Help Center

Collection - General Tab

Fields available for edit on the top portion of the page include:

  • Collection Title
  • Investigators
  • Collection Description
  • Collection Phase
  • Funding Source
  • Clinical Trials

Collection Status: The visibility status of an NDA Collection.  Collection Status can be Shared or Private.  Collections in Shared status are visible to all users and can be searched in the NDA Query Tool. Private Collections are not visible to NDA users.  The Status of an NDA Collection only affects the visibility of information about the Collection (metadata) and does not relate to the status of the record-level research data in the NDA Collection.

Collection Phase: The current status of a research project submitting data to an NDA Collection, based on the timing of the award and/or the data that have been submitted.
 

  • Pre-Enrollment: The default entry made when the NDA Collection is created.
     
  • Enrolling: Data have been submitted to the NDA Collection or the NDA Data Expected initial submission date has been reached for at least one data structure category in the NDA Collection.
     
  • Data Analysis: Subject level data collection for the research project is completed and has been submitted to the NDA Collection.  The NDA Collection owner or the NDA Help Desk may set this phase when they’ve confirmed data submission is complete and submitted subject counts match at least 90% of the target enrollment numbers in the NDA Data Expected. Data submission reminders will be turned off for the NDA Collection.
     
  • Funding Completed: The NIH grant award (or awards) associated with the NDA Collection has reached its end date. NDA Collections in Funding Completed phase are assigned a subphase to indicate the status of data submission.
     
    • The Data Expected Subphase indicates that NDA expects more data will be submitted
    • The Closeout Subphase indicates the data submission is complete.
    • The Sharing Not Met Subphase indicates that data submission was not completed as expected. 

Blinded Clinical Trial Status:

  • This status is set by a Collection Owner and indicates the research project is a double blinded clinical trial.  When selected, the public view of Data Expected will show the Data Expected items and the Submission Dates, but the targeted enrollment and subjects submitted counts will not be displayed.
     
  • Targeted enrollment and subjects submitted counts are visible only to NDA Administrators and to the NDA Collection or as the NDA Collection Owner.
     
  • When an NDA Collection that is flagged Blinded Clinical Trial reaches the maximum data sharing date for that Data Repository (see https://nda.nih.gov/about/sharing-regimen.html), the embargo on Data Expected information is released.
     

Funding Source

The organization(s) responsible for providing the funding is listed here. 

Supporting Documentation

Users with Submission privileges, as well as Collection Owners, Program  Officers, and those with Administrator privileges, may upload and attach supporting documentation. By default, supporting documentation is shared to the general public, however, the option is also available to limit this information to qualified researchers only. 

Grant Information 

Identifiable details are displayed about the Project of which the Collection was derived from. You may click in the Project Number to view a full report of the Project captured by the NIH. 

Clinical Trials

Any data that is collected to support or further the research of clinical studies will be available here. Collection Owners and those with Administrator privileges may add new clinical trials. 

Frequently Asked Questions

  • When a Collection is created by NDA staff and marked as Shared, an email notification will automatically be sent to the PI(s) of the grant(s) associated with the Collection to notify them.

  • During Collection creation, NDA staff determine the appropriate Permission Group based on the type of data to be submitted, the type of access that will be available to data access users, and the information provided by the Program Officer during grant award.

  • The NDA system does not allow for a single grant to be associated with more than one Collection; therefore, a single grant will not be listed in the Grant Information section of a Collection for more than one Collection.

  • In general, each Collection is associated with only one grant; however, multiple grants may be associated if the grant has multiple competing segments for the same grant number or if multiple different grants are all working on the same project and it makes sense to hold the data in one Collection (e.g., Cooperative Agreements).

Glossary

  • Number of human subjects enrolled in an NIH-funded clinical research study. The data is provided in annual progress reports.

  • A privilege provided to a user associated with an NDA Collection or NDA Study whereby that user can perform a full range of actions including providing privileges to other users. 

  • Generally, the Collection Owner is the contact PI listed on a grant. Only one NDA user is listed as the Collection owner. Most automated emails are primarily sent to the Collection Owner.

  • The Collection Phase provides information on data submission as opposed to grant/project completion so while the Collection phase and grant/project phase may be closely related they are often different.  Collection users with Administrative Privileges are encouraged to edit the Collection Phase.  The Program Officer as listed in eRA (for NIH funded grants) may also edit this field. Changes must be saved by clicking the Save button at the bottom of the page.  This field is sortable alphabetically in ascending or descending order. Collection Phase options include: 

    • Pre-Enrollment:  A grant/project has started, but has not yet enrolled subjects.
    • Enrolling:  A grant/project has begun enrolling subjects.  Data submission is likely ongoing at this point.
    • Data Analysis:  A grant/project has completed enrolling subjects and has completed all data submissions.
    • Funding Completed:  A grant/project has reached the project end date.
  • The Collection State indicates whether the Collection is viewable and searchable.  Collections can be either Private, Shared, or an Ongoing Study.  A Collection that is shared does not necessarily have shared data as the Collection State and state of data are independent of each other.  This field can be edited by Collection users with Administrative Privileges and the Program Officer as listed in eRA (for NIH funded grants). Changes must be saved by clicking the Save button at the bottom of the page.

  • An editable field with the title of the Collection, which is often the title of the grant associated with the Collection.

  • Data Use Limitations (DULs) describe the appropriate secondary use of a dataset and are based on the original informed consent of a research participant. NDA only accepts consent-based data use limitations defined by the NIH Office of Science Policy.

  • Provides the grant number(s) for the grant(s) associated with the Collection.  The field is a hyperlink so clicking on the Grant number will direct the user to the grant information in the NIH Research Portfolio Online Reporting Tools (RePORT) page.

  • A virtual container and organization structure for data and associated documentation from one grant or one large project/consortium. It contains tools for tracking data submission and allows investigators to define a wide array of other elements that provide context for the data, including all general information regarding the data and source project, experimental parameters used to collect any event-based data contained in the Collection, methods, and other supporting documentation. They also allow investigators to link underlying data to an NDA Study, defining populations and subpopulations specific to research aims. 

  • NDA Collections may be organized by scientific similarity into NIH Research Initiatives, to facilitate query tool user experience. NIH Research Initiatives map to one or multiple Funding Opportunity Announcements. 

  • Access to shared record-level data in NDA is provisioned at the level of a Permission Group. NDA Permission Groups consist of one or multiple NDA Collections that contain data with the same subject consents.

  • Number of human subject participants to be enrolled in an NIH-funded clinical research study. The data is provided in competing applications and annual progress reports.

  • Various documents and materials to enable efficient use of the data by investigators unfamiliar with the project and may include the research protocol, questionnaires, and study manuals.  

  • The total number of unique subjects for whom data have been shared and are available for users with permission to access data.

NDA Help Center

Collection - Shared Data Tab

This tab provides a quick overview of the Data Structure title, Data Type, and Number of Subjects that are currently Shared for the Collection. The information presented in this tab is automatically generated by NDA and cannot be edited. If no information is visible on this tab, this would indicate the Collection does not have shared data or the data is private.

The shared data is available to other researchers who have permission to access data in the Collection's designated Permission Group(s). Use the Download button to get all shared data from the Collection to the Filter Cart.

 

Frequently Asked Questions

  • To see what data your project have submitted are being used by a study, simply go the Associated Studies tab of your collection.  Alternatively, you may review an NDA Study Attribution Report available on the General tab.  

  • Often it becomes more difficult to organize and format data electronically after the project has been completed and the information needed to create a GUID may not be available; however, you may still contact a program staff member at the appropriate funding institution for more information.

  • Unlike completed projects where researchers may not have the information needed to create a GUID and/or where the effort needed to organize and format data becomes prohibitive, ongoing projects have more of an opportunity to overcome these challenges.  Please contact a program staff member at the appropriate funding institution for more information.

Glossary

  • A defined organization and group of Data Elements to represent an electronic definition of a measure, assessment, questionnaire, or collection of data points.  Data structures that have been defined in the NDA Data Dictionary are available at https://ndar.nih.gov/data_dictionary.html. 

  • A grouping of data by similar characteristics such as Clinical Assessments, Omics, or Neurosignal data.

  • The term 'Shared' generally means available to others; however, there are some slightly different meanings based on what is Shared.  A Shared NDA Collection or NDA Study is viewable and searchable publicly regardless of the user's role or whether the user has an NDA account.  A Shared Collection or NDA Study does not necessarily mean that data submitted to the Collection or used in the NDA Study have been shared as this is independently determined.  Data are shared according the schedule defined in a Collection's Data Expected Tab and/or in accordance with data sharing expectations in the NDA Data Sharing Terms and Conditions.  Additionally, Supporting Documentation uploaded to a Collection may be shared independent of whether data are shared, but will only be viewable and accessible if the Collection is Shared.

NDA Help Center

fMRi

fMRI stands for functional magnetic resonance imaging. fMRI tests measure blood flow, providing detailed functional images of the brain or body. 

Acquisition
The Acquisition parameters needed for an experiment include the following:

The name of the experiment is required. Please be concise and specific as possible.
Following experiment name, selection boxes are provided for the Equipment, Software, or other items specific to the experiment type. At least one selection is required for each. If NDAR does not have the appropriate listing, select Add New to add the information provided. Following the selection boxes, provide additional information may be required depending on the experiment type. Any required items are denoted by an asterisk (*).

Block/Event Design
At least one block/event is required. Note that any fields denoted with an asterisk (*) are required. All data must be devoid of personally identifiable data, including the contents of any files attached to the experiment.

Note: To simplify the definition of multiple events, we provide an Import from XML function. This function supports importing data from all three experiment sections (Acquisition, Block/Event Design, and Post Processing), at this time files cannot be uploaded from XML A test format is provided here and our XML Schema Definition (xsd) can be found here.

Post Processing
If you have completed any post-processing on your data, please choose 'Yes' for Has Postprocessing? If not, select 'No'. Depending on this selection the remaining post-processing fields will be enabled (some of which will be required). If you are initially providing data you can select 'No', then return to the experiment to add post-processing steps at a later date when the data are being provided.

Please provide information about post-processing manipulations, i.e. artifact detection algorithms, segmentation used for post data collection, items denoted with an asterisk (*) are required.

Frequently Asked Questions

Glossary

  • This button will add all selections to the Filter Cart. 

  • This button will allow you to copy all of the Experiment details as a template for a new experiment. 

  • Adds all data from the current selections in a Collection or NDA Study to the Filter Cart.

  • This button will allow you to return to the Experiments tab. 

NDA Help Center

Collection - Submissions Tab

Users with permission to access Shared data in the Collection’s assigned Permission Group may use this tab. 

Here, you can:

  • Review your uploads to your Collection, monitor their status, and download them individually to verify their contents.
  • Download individual datasets as a secondary user of the data approved for access.
  • Identify and download datasets containing errors identified by NDA's QA/QC process for review and resolution.
  • Report suspected or discovered Personally Identifiable Information in a submission via the Actions column.

Frequently Asked Questions

Glossary

  • The default view of Datasets within a Collection's Submission tab.

  • A Submission Loading Status on a Collection's Submission Tab that indicates that an issue has prevented the successful loading of the submission.  Users should contact the NDA Help Desk for assistance at NDAHelp@mail.nih.gov.

  • The NDA has two Submission Cycles per year - January 15 and July 15.

  • An interface to notify NDA that data may not be submitted during the upcoming/current submission cycle.  

  • The unique and sequentially assigned ID for a submission (e.g. a discrete upload via the Validation and Upload Tool), which may contain any number of datafiles, Data Structures and/or Data Types, regardless of the Submission Loading Status. A single submission may be divided into multiple Datasets, which are based on Data Type.

  • The total number of unique subjects for whom data have been shared and are available for users with permission to access data.

  • The total number of unique subjects for whom data have been submitted, which includes data in both a Private State and a Shared State.

NDA Help Center

Collection - Publications Tab

The number of Publications is displayed in parentheses next to the tab name. Clicking on any of the Publication Titles will open the Publication in a new internet browsing tab. 

Collection Owners, Program Officers, and users with Submission or Administrative Privileges for the Collection may mark a publication as either Relevant or Not Relevant in the Status column. 

 

Frequently Asked Questions

  • Publications are considered relevant to a collection when the data shared is directly related to the project or collection.

  • PubMed, an online library containing journals, articles, and medical research. Sponsored by NiH and National Library of Medicine (NLM). 

Glossary

  • A link to the Create an NDA Study page that can be clicked to start creating an NDA Study with information such as the title, journal and authors automatically populated.

  • Indicates that the publication has not yet been reviewed and/or marked as Relevant or Not Relevant so it has not been determined whether an NDA Study is expected.

  • A publication that is not based on data related to the aims of the grant/project associated with the Collection or not based on any data such as a review article and, therefore, an NDA Study is not expected to be created.

  • PubMed provides citation information for biomedical and life sciences publications and is managed by the U.S. National Institutes of Health's National Library of Medicine.

  • The PUBMed ID is the unique ID number for the publication as recorded in the PubMed database.  

  • A publication that is based on data related to the aims of the grant/project associated with the Collection and, therefore, an NDA Study is expected to be created.

NDA Help Center

EEG

EEG stands for electroencencephalogram and is a test used to measure electrical activity in the brain.

Acquisition
The Acquisition parameters needed for an experiment include the following:

Name of the experiment is required. Please be concise and specific as possible.
Following experiment name, selection boxes are provided for the Equipment, Software, or other items specific to experiment type. At least one selection is required for each. If NDAR does not have the appropriate listing, select Add New to add the information provided. Following the selection boxes, provide additional information may be required depending on experiment type. Any required items are denoted by an asterisk (*).

Block/Event Design
At least one block/event is required. Note that any fields denoted with an asterisk (*) are required. All data must be devoid of personally identifiable data, including the contents of any files attached to the experiment.

Note: To simplify definition of multiple events, we provide an Import from XML function. This function supports importing data from all three experiment sections (Acquisition, Block/Event Design, and Post Processing), at this time files cannot be uploaded from XML A test format is provided here and our XML Schema Definition (xsd) can be found here.

Post Processing
If you have completed any post processing on your data, please choose 'Yes' for Has Postprocessing? If not, select 'No'. Depending on this selection the remaining post processing fields will be enabled (some of which will be required). If you are initially providing data you can select 'No', then return to the experiment to add post processing steps at a later date when the data are being provided.

Please provide information about post-processing manipulations, i.e. artifact detection algorithms, segmentation used for post data collection, items denoted with an asterisk (*) are required.

Frequently Asked Questions

Glossary

  • This button will add all selections to the Filter Cart. 

  • This button will allow you to copy all of the Experiment details as a template for a new experiment. 

  • Adds all data from the current selections in a Collection or NDA Study to the Filter Cart.

  • This button will allow you to return to the Experiments tab. 

NDA Help Center

Collection - Data Expected

The Data Expected tab displays the list of all data that NDA expects to receive in association with the Collection as defined by the contributing researcher, as well as the dates for the expected initial upload of the data, and when it is first expected to be shared, or with the research community. Above the primary table of Data Expected, any publications determined to be relevant to the data within the Collection are also displayed - members of the contributing research group can use these to define NDA Studies, connecting those papers to underlying data in NDA.

The tab is used both as a reference for those accessing shared data, providing information on what is expected and when it will be shared, and as the primary tracking mechanism for contributing projects. It is used by both contributing primary researchers, secondary researchers, and NIH Program and Grants Management staff.

Contributing researchers just getting started on their project will need to define this list by adding all of the items they are collecting under their grant and setting their schedule according to the NDA Data Sharing Regimen. If you fall into this category, you can begin by clicking "add new Data Expected" and selecting which data structures you will be using, saving the page after each change, or requesting new structures by adding and naming a new item, providing any materials NDA Data Dictionary Curators can use to help define your structure. For more information see the tutorial on creating Data Expected.

If you are a contributing researcher creating this list for the first time, or making changes to the list as your project progress, please note the following:

  • Although items you add to the list and changes you make are displayed, they are not committed to the system until you Save the entire page using the "Save" button at the bottom of your screen. Please Save after every change to ensure none of your work is lost.
  • If you attempt to add a new structure, the title you provide must be unique - if another structure exists with the same name your change will fail.
  • Adding a new structure to this list is the only way to request the creation of a new Data Dictionary definition.

 

Frequently Asked Questions

  • An NDA Data Structure is comprised of multiple Data Elements to make up an electronic definition of an assessment, measure, questionnaire, etc will have a corresponding Data Structure.

  • The NDA Data Dictionary is comprised of electronic definitions known as Data Structures.

Glossary

  • Data specific to the primary aims of the research being conducted (e.g. outcome measures, other dependent variables, observations, laboratory results, analyzed images, volumetric data, etc.) including processed images.

  • Items listed on the Data Expected list in the Collection which may be an individual and discrete Data Structure, Data Structure Category, or Data Structure Group.

  • A defined organization and group of Data Elements to represent an electronic definition of a measure, assessment, questionnaire, or collection of data points.  Data structures that have been defined in the NDA Data Dictionary are available at https://ndar.nih.gov/data_dictionary.html. 

  • An NDA term describing the affiliation of a Data Structure to a Category, which may be disease/disorder or diagnosis related (Depression, ADHD, Psychosis), specific to data type (MRI, eye tracking, omics), or type of data (physical exam, IQ).

  • A Data Item listed on the Data Expected tab of a Collection that indicates a group of Data Structures (e.g., ADOS or SCID) for which data may be submitted instead of a specific Data Structure identified by version, module, edition, etc. For example, the ADOS Data Structure Category includes every ADOS Data Structure such as ADOS Module 1, ADOS Module 2, ADOS Module 1 - 2nd Edition, etc. The SCID Data Structure Group includes every SCID Data Structure such as SCID Mania, SCID V Mania, SCID PTSD, SCID-V Diagnosis, and more. 

  • A new Data Structure category, Evaluated Data is analyzed data resulting from the use of computational pipelines in the Cloud and can be uploaded directly back to a miNDAR database.  Evaluated Data is expected to be listed as a Data Item in the Collection's Data Expected Tab.

  • Imaging+ is an NDA term which encompasses all imaging related data including, but not limited to, images (DTI, MRI, PET, Structural, Spectroscopy, etc.) as well as neurosignal data (EEG, fMRI, MEG, EGG, eye tracking, etc.) and Evaluated Data.

  • Initial Submission and Initial Share dates should be populated according to the NDA Data Sharing Terms and Conditions. Any modifications to these will go through the approval processes outlined above. Data will be shared with authorized users upon publication (via an NDA Study) or 1-2 years after the grant end date specified on the first Notice of Award, as defined in the applicable Data Sharing Terms and Conditions.

  • Initial Submission and Initial Share dates should be populated according to these NDA Data Sharing Terms and Conditions. Any modifications to these will go through the approval processes outlined above. Data for all subjects is not expected on the Initial Submission Date and modifications may be made as necessary based on the project's conduct.

  • An NDA created Data Structure used to convey basic information about the subject such as demographics, pedigree (links family GUIDs), diagnosis/phenotype, and sample location that are critical to allow for easier querying of shared data.

  • The NDA has two Submission Cycles per year - January 15 and July 15.

  • An interface to notify NDA that data may not be submitted during the upcoming/current submission cycle.  

NDA Help Center

Collection - Permissions Tab

Collection Owners, Program Officers, and users with Administrator privileges may view this tab.

The available permission groups include:

  • Query: This read-only access is generally for NIH Program Officers
  • Submission: This will grant read access and allow the user to upload data and create experiment definitions. This is for the typical contributing personnel member.
  • Administrator: In addition to the access provided to Query and Submission users, Admins can also edit the Collection itself, create or edit the Data Expected list, and edit user permissions. This access is for the PI, data managers, and anyone they wish to delegate this to.

The PI has a special designation as the Collection Owner in addition to administrator access.

Frequently Asked Questions

  • Collection Owners and Admins may assign Collection Privileges to anyone.

  • Yes, you can assign various Privileges to other users with an NDA account.

  • If you are the Collection Owner or have Admin privileges, you can view and make changes to the list of individuals who have access to the Collection on the Collection's Permissions tab.  Information on users who have access to data Shared in your Collection because they were granted access to a Permission Group is not available.

  • Staff/collaborators who are working submitting data to the Collection, checking the quality of the data, and/or analyzing data should have access for the duration of the project until all data have been submitted, NDA Studies have been created for data used in publications, and/or a collaborative relationship with the user exists.  

  • The individual listed as an Investigator on the General tab of the NDA Collection will generally be able to provide a user access to the NDA Collection.  Additional users may also have this ability if granted Administrator access to an NDA Collection; however, these users are not viewable unless your account has access to the NDA Collection.  Given this, it is best to contact the Investigator to request access to the Collection.

  • Privileges that can be assigned to a user include:
    Submission allows a user to submit data to Collection
    Query allows the user to download data from Collection even when in a Private state
    Admin is both the Submission and Query Privilege + the ability to give privileges to other users.

  • You may have staff who are working on the submission of data or other activities associated with data sharing such as the definition of the Data Expected list or NDA Experiment creation.  Also, many projects have multiple performance sites and wish to share data among the site PIs.  Submitting to the NDA facilitates access by all investigators working on a project even before data have been shared with other users.  You can control who gets access to data while in a Private state.

Glossary

  • A privilege provided to a user associated with an NDA Collection or NDA Study whereby that user can perform a full range of actions including providing privileges to other users. 

  • Access to shared record-level data in NDA is provisioned at the level of a Permission Group. NDA Permission Groups consist of one or multiple NDA Collections that contain data with the same subject consents.

NDA Help Center

Eye Tracking

EyeTracking tests follow the movement of the eye. The visual trajectory or focus can help determine predictions and assist in diagnoses. 

Acquisition
The Acquisition parameters needed for an experiment include the following:

The name of the experiment is required. Please be concise and specific as possible.
Following experiment name, selection boxes are provided for the Equipment, Software, or other items specific to the experiment type. At least one selection is required for each. If NDAR does not have the appropriate listing, select Add New to add the information provided. Following the selection boxes, provide additional information may be required depending on the experiment type. Any required items are denoted by an asterisk (*).

Block/Event Design
At least one block/event is required. Note that any fields denoted with an asterisk (*) are required. All data must be devoid of personally identifiable data, including the contents of any files attached to the experiment.

Note: To simplify the definition of multiple events, we provide an Import from XML function. This function supports importing data from all three experiment sections (Acquisition, Block/Event Design, and Post Processing), at this time files cannot be uploaded from XML A test format is provided here and our XML Schema Definition (xsd) can be found here.

Post Processing
If you have completed any post-processing on your data, please choose 'Yes' for Has Postprocessing? If not, select 'No'. Depending on this selection the remaining post-processing fields will be enabled (some of which will be required). If you are initially providing data you can select 'No', then return to the experiment to add post-processing steps at a later date when the data are being provided.

Please provide information about post-processing manipulations, i.e. artifact detection algorithms, segmentation used for post data collection, items denoted with an asterisk (*) are required.

Frequently Asked Questions

Glossary

  • This button will add all selections to the Filter Cart. 

  • This button will allow you to copy all of the Experiment details as a template for a new experiment. 

  • Adds all data from the current selections in a Collection or NDA Study to the Filter Cart.

  • This button will allow you to return to the Experiments tab. 

NDA Help Center

Collection - Experiments Tab

The number of Experiments included is displayed in parentheses next to the tab name. You may download all experiments associated with the Collection via the Download button. You may view individual experiments by clicking the Experiment Name and add them to the Filter Cart via the Add to Cart button.

Collection Owners, Program Officers, and users with Submission or Administrative Privileges for the Collection may create or edit an Experiment.

Please note: The creation of an NDA Experiment does not necessarily mean that data collected, according to the defined Experiment, has been submitted or shared.

Frequently Asked Questions

  • Yes -see the “Copy” button in the bottom left when viewing an experiment. There are two actions that can be performed via this button:

    1. Copy the experiment with intent for modifications.  
    2. Associate the experiment to the collection. No modifications can be made to the experiment.

     

Glossary

  • An Experiment must be Approved before data using the associated Experiment_ID may be uploaded.

  • The ID number automatically generated by NDA which must be included in the appropriate file when uploading data to link the Experiment Definition to the subject record.

NDA Help Center

Omics

Omics is a collective group of technologies, related to a field of study in Biology such as Genomics or proteomics. 

Experiment Parameters

To define an Omics experiment, provide a meaningful name and select a single molecule. The standard molecules are listed. However, if you are doing proteomic or environmental experiments, simply “Add New” and the new selection will be created. Only one value for molecule is permitted.

Next the technology (box 2) associated with the molecule will be presented along with its application. Again, only one selection is possible. If you wish to see all of NDAR’s options for any one box, Select “Show All”.

Platform

Continue to select the Platform (box 3).

Extraction

Next, the Extraction Protocol (box 4) and Kits (box 5) are presented based upon the Molecule selected and the Processing Protocol (box 6) and Kits (box 7) are presented based upon the Molecule and Technology Application (Box 1 and 2)

Processing

Note that for each of these (boxes 4, 5, 6, and 7) multiple selections are possible.

Additional Information

Lastly, the Software (box 8) and Equipment (box 9) is expected.

 

Once saved, the experiment will be associated with the Collection and by using the returned Experiment_ID, the NDA makes it possible to associate the experiment meta data directly with the data from the experiment.

Frequently Asked Questions

Glossary

  • This button will add all selections to the Filter Cart. 

  • This button will allow you to copy all of the Experiment details as a template for a new experiment. 

  • Adds all data from the current selections in a Collection or NDA Study to the Filter Cart.

  • This button will allow you to return to the Experiments tab. 

NDA Help Center

Filter Cart

Viewable at the top right of NDA pages, the Filter Cart is a temporary holder for filters and data they select. Filters are added to the Workspace first, before being submitted to The Filter Cart. Data selected by filters in the Filter Cart can be added to a Data Package or an NDA Study from the Data Packaging Page, by clicking the 'Create Data Package / Add Data to Study' button.

The filter cart supports combining multiple filters together, and depending on filter type will use "AND" or "OR"  when combining filters.

Multiple selections from the same filter type will result in those selections being applied with an ‘OR’ condition. For example, if you add an NDA Collection Filter with selections for both collections 2112 and 2563 to an empty Workspace, the subjects from NDA Collection 2112 ‘OR’ NDA Collection 2563 will be added to your Workspace even if a subject is in both NDA Collections. You can then add other NDA Collections to your Workspace which further extends the ‘OR’ condition.

If a different filter type is added to your Workspace, or a filter has already been submitted to the Filter Cart, the operation then performs a logical ‘AND’ operation. This means that given the subjects returned from the first filter, only those subjects that matched the first filter are returned by the second filter (i.e., subjects that satisfied both filters).

When combining other filters with the GUID filter, please note the GUID filter should be added last. Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets may select a subset of data available for a subject. When combined with a GUID filter for the same subject, the filter cart will contain all data available from that subject, data structure, and dataset; this may be more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the subjects, data structures, and datasets already included in your filter cart.

Note that only the subjects specific to your filter will be added to your Filter Cart and only on data shared with the research community. Other data for those same subjects may exist (i.e., within another NDA Collection, associated with a data structure that was not requested in the query, etc.). So, users should select ‘Find all Subjects Data’ to identify all data for those specific subjects. 

Additional Tips:

  • You may query the data without an account, but to gain access you will need to create an NDA user account and apply for access.  Most data access requires that you or your lab are sponsored by an NIH recognized institution with Federal Wide Assurance (FWA).  Without access, you will not be able to obtain individual-level data. 

    Once you have selected data of interest you can:
  • Create a data package - This allows you to specify format for access/download
  • Assign to Study Cohort - Associate the data to an NDA Study allowing for a DOI to be generated and the data to be linked directly to a finding, publication, or data release. 
  • Find All Subject Data - Depending on filter types being used, not all data associated with a subject will be selected.  Data may be restricted by data structure, NDA Collection, or outcome variables (e.g., NDA Study). ‘Find All Data’ expands the fliter criteria by replacing all filters in your Filter Cart with a single Query by GUID filter for all subjects selected by those filters.

    Please Note:
  • When running a query, it may take a moment to populate the Filter Cart. Queries happen in the background so you can define other queries during this time. 
  • When you add your first filter, all data associated with your query will be added to the Filter Cart (e.g., a Concept, an NDA Collection, a Data Structure/Element, etc.). As you add additional filters, they will also display in the Filter Cart. Only the name of filter will be shown in the Filter Cart, not the underlying structures. 
  • Information about the contents of the Filter Cart can be seen by clicking "Edit”.
  • Once your results appear in the Filter Cart, you can create a data package or assign subjects to a study by selecting the 'Package/Assign to Study' option. You can also 'Edit' or 'Clear' filters.
     

Frequently Asked Questions

  • The Filter Cart currently employs basic AND/OR Boolean logic. A single filter may contain multiple selections for that filter type, e.g., a single NDA Study filter might contain NDA Study 1 and NDA Study 2. A subject that is in EITHER 1 OR 2 will be returned.  Adding multiple filters to the cart, regardless of type, will AND the result of each filter.  If NDA Study 1 and NDA Study 2 are added as individual filters, data for a subject will only be selected if the subject is included in  BOTH 1 AND 2.

    When combining other filters with the GUID filter, please note the GUID filter should be added last. Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets may select a subset of data available for a subject. When combined with a GUID filter for the same subject, the filter cart will contain all data available from that subject, data structure, and dataset; this may be more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the subjects, data structures, and datasets already included in your filter cart.

  • Viewable at the top right of NDA pages, the Filter Cart is a temporary holder of data identified by the user, through querying or browsing, as being of some potential interest. The Filter Cart is where you send the data from your Workspace after it has been filtered.

  • After filters are added to the Filter Cart, users have options to ‘Create a Package’ for download, ‘Associate to Study Cohort’, or ‘Find All Subject Data’. Selecting ‘Find All Subject Data’ identifies and pulls all data for the subjects into the Filter Cart. Choosing ‘Create a Package’ allows users to package and name their query information for download. Choosing ‘Associate to Study Cohort’ gives users the opportunity to choose the Study Cohort they wish to associate this data.

Glossary

  • Once your filter cart contains the subjects of interest, select Create Data Package/Assign to Data Study which will provide options for accessing item level data and/or assigning to a study.  

  • Once queries have been added to your workspace, the next step is to Submit the Filters in the workspace to the Filter Cart.  This process runs the queries selected, saving the results within a filter cart attached to your account.  

  • The Workspace within the General Query Tool is a holding area where you can review your pending filters prior to adding them to Filter Cart. Therefore, the first step in accessing data is to select one or more items and move it into the Workspace. 

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Collection - Associated Studies

Clicking on the Study Title will open the study details in a new internet browser tab. The Abstract is available for viewing, providing the background explanation of the study, as provided by the Collection Owner. 

Primary v. Secondary Analysis: The Data Usage column will have one of these two choices. An associated study that is listed as being used for Primary Analysis indicates at least some and potentially all of the data used was originally collected by the creator of the NDA Study. Secondary Analysis indicates the Study owner was not involved in the collection of data, and may be used as supporting data. 

Private v. Shared State: Studies that remain private indicate the associated study is only available to users who are able to access the collection. A shared study is accessible to the general public. 

Frequently Asked Questions

  • Studies are associated to the Collection automatically when the data is defined in the Study. 

Glossary

  • A tab in a Collection that lists the NDA Studies that have been created using data from that Collection including both Primary and Secondary Analysis NDA Studies.

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1 Numbers reported are subjects by age
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New Project

Format should be in the following format: Activity Code, Institute Abbreviation, and Serial Number. Grant Type, Support Year, and Suffix should be excluded. For example, grant 1R01MH123456-01A1 should be entered R01MH123456

Please select an experiment type below

Collection - Use Existing Experiment

To associate an experiment to the current collection, just select an axperiment from the table below then click the associate experiment button to persist your changes (saving the collection is not required). Note that once an experiment has been associated to two or more collections, the experiment will not longer be editable.

The table search feature is case insensitive and targets the experiment id, experiment name and experiment type columns. The experiment id is searched only when the search term entered is a number, and filtered using a startsWith comparison. When the search term is not numeric the experiment name is used to filter the results.

SelectExperiment IdExperiment NameExperiment Type
  • Select One
  • EEG
  • EGG
  • Eye Tracking
  • Omics
  • fMRI
Created On
1943EEG Acquisition R21EEG01/21/2022
1941Social CognitionfMRI01/20/2022
1940Dot Pattern ExpectancyfMRI01/20/2022
1938Resting StatefMRI01/20/2022
1937NN107 Emotional FacesEye Tracking01/20/2022
1936RESTfMRI01/20/2022
1934Scene Processing Task (SPT)fMRI01/14/2022
1933finger tappingfMRI01/14/2022
1932Resting StatefMRI01/14/2022
1931Emotion Reappraisal fMRI ParadigmfMRI01/14/2022
1930Understanding Sarcasm fMRI ParadigmfMRI01/14/2022
1929Complex Social GeoPref 600 HzEye Tracking01/13/2022
1926Outdoor Peer Play GeoPref 600 HzEye Tracking01/13/2022
1925Original GeoPref 600 HzEye Tracking01/13/2022
1924fBIRN_AuditoryOddballfMRI01/12/2022
1923HCP_WorkingMemory_fMRIfMRI01/12/2022
1922SPTfMRI01/12/2022
1921Long Term Passive Recording 2EEG01/12/2022
1920EmoStroopfMRI01/12/2022
1919Resting State Visit 2fMRI01/12/2022
1918Emotional N-back Visit 2fMRI01/12/2022
1917CARDS Task Visit 2fMRI01/12/2022
19162-back Visit 2fMRI01/12/2022
19151-back Visit 2fMRI01/12/2022
19140-back Visit 2fMRI01/12/2022
1913IBIS Eye-Tracking Substudy Eye Tracking01/12/2022
1906Resting statefMRI01/10/2022
1905ASL resting statefMRI01/10/2022
1904Using fMRI to Measure Neural-level Signals Underlying Visual Memory Behavior-continuationfMRI01/09/2022
1900Resting statefMRI01/07/2022
1899Resting StatefMRI01/06/2022
1898NetFlexfMRI01/04/2022
1897Pavlovian Fear Conditioning with Avoidance - Fear RenewalfMRI01/03/2022
1896Pavlovian Fear Conditioning with Avoidance - Extinction RecallfMRI01/03/2022
1895Pavlovian Fear Conditioning with Avoidance - Fear Extinction LearningfMRI01/03/2022
1894Pavlovian Fear Conditioning with Avoidance - Fear AcquisitionfMRI01/03/2022
1893Whole Genome Sequencing in Irish Multiplex Schizophrenia FamiliesOmics12/30/2021
1892AHKJ Task Episode CfMRI12/21/2021
1891AHKJ Task Episode BfMRI12/21/2021
1890AHKJ Task Episode AfMRI12/21/2021
1889VEP v2EEG12/21/2021
1888Offset Response v2EEG12/21/2021
1887DTIfMRI12/17/2021
1885Resting StatefMRI12/17/2021
1884Emotional_SSTfMRI12/15/2021
1883IBIS-EP EEG SubstudyEEG12/14/2021
1882Picture Viewing (neg, neut, pos)fMRI12/13/2021
1881EEfRT_NYSPIfMRI12/13/2021
1880ChatroomTask_NYSPIfMRI12/13/2021
1879iCereMotorPilot_RestfMRI12/13/2021
Collection - Add Experiment
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Please enter the name of the data structure to search or if your definition does not exist, please upload that definition so that it can be appropriately defined for submission. Multiple data structures may be associated with a single Data Expected entry. Please add only one data structure per assessment.

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Your Collection is now in Data Analysis phase and exempt from biannual submissions. Data is still expected prior to publication or no later than the project end date.

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Shared
Collection Summary Collection Charts
Collection Title Collection Investigators Collection Description
Adolescent Brain Cognitive Development Study (ABCD)
Terry L. Jernigan 
The ABCD Study is designed to permit the scientific community to answer important questions about the relationships among physical and mental health, cognition, substance use (SU), culture and environment, genetics, environmental exposures and brain development of adolescents. The ABCD Study is a nationwide study of more than 10,000 9-10 year-olds conducted at 21 sites (29% of the US population lives within 50 miles of our geographically spread sites), that, uniquely, can provide a representative sample and a large twin sample that together can help distinguish environmental, sociocultural, and genetic factors relevant to adolescent health and brain development. We ensure cohesion and standardization with a recruitment strategy designed by a professional survey company (experience with Monitoring the Future), standardized environmental, neurocognitive and mental health assessments, MRI assessments with scanners using modified harmonized Human Connectome Project procedures, and computerized data collection with real-time quality control. Developmentally tailored assessments will have stable sensitivity and construct validity across childhood and adolescence, capture even subtle changes in SU, mental health, neurocognition, development, and environment, and employ novel bioassays and passive data collection from mobile devices. The retention plan builds on the experience of our investigators to ensure success.
Adolescent Brain Cognitive Development
Adolescent Brain Cognitive Development (ABCD) / Connectome Coordination Facility (CCF)
Adolescent Brain Cognitive Development (ABCD)
Enrolling
Shared
No
$135,149,332.00
11,892
Loading Chart...
NIH - Extramural None

3a. NDA 2.0.1 Changes and Known Issues Fix Release 2.0.1.pdf Background 3a. NDA 2.0.1 Changes and Known Issues Fix Release 2.0.1 Qualified Researchers
ABCD_Diffusion_Tables.zip Background Diffusion tables for Fast Track dMRI Qualified Researchers
22. ABCD_Release_2.0_mapping_r.csv Background Mapping of ABCD instruments to NDA structures for Release 2.0 Qualified Researchers
ABCD Release 3.0 release notes_public.zip Background Please Read - Release Notes: Adolescent Brain Cognitive Development (ABCD) Release 3.0 General Public
ABCD Release 3.0 release notes_non-public.zip Background Please Read - Release Notes: Adolescent Brain Cognitive Development (ABCD) Release 3.0 Qualified Researchers
111.incorrect.genetic.subjectid.csv Background 111.incorrect.genetic.subjectid Qualified Researchers
ABCD_dMRI_fMRI_Slicetiming.pdf Background MRI image acquisition parameters for dMRI and fMRI slice timing Qualified Researchers
ABCD Release 2.0 Release Notes_Non_public.zip Background Please Read - Updated Release 2.0 Notes (June 2019 Update) Qualified Researchers
ABCD Release 2.0 Release Notes_public.zip Background Please Read - Updated Release 2.0 Notes (June 2019 Update) General Public
Fix Release Notes 2.0.1_Not_Public.zip Background Please Read - Release Notes: Adolescent Brain Cognitive Development (ABCD) Fix Release 2.0.1 Qualified Researchers
Fix Release Notes 2.0.1_Public.zip Background Please Read - Release Notes: Adolescent Brain Cognitive Development (ABCD) Fix Release 2.0.1 General Public
3a. NDA 2.0 Changes between Release 1.1 and 2.0_Known Issues Release 2.0.pdf Background Release 2.0 Known Issues and changes between Releases 1.1 and 2.0 (June 2019 Update) Qualified Researchers
3b. ABCD Release 2.0 Family History_issues.pdf Background Release 2.0 Family History Issues Qualified Researchers
ABCD Fast Track DICOM Sharing.pdf Background ABCD Fast Track DICOM Sharing (Jan 2020) Qualified Researchers
ABCD NDA 4.0 - Release Notes - public.zip Background ABCD 4.0 Release Notes - public General Public
ABCD NDA 4.0 - Release Notes - non-public.zip Background ABCD 4.0 Release Notes - private Qualified Researchers

U01DA041089-01 ABCD-USA Consortium: Research Project 09/30/2015 05/31/2020 0 13696 UNIVERSITY OF CALIFORNIA, SAN DIEGO $12,358,765.00
U24DA041123-01 ABCD-USA Consortium: Data Analysis Center 09/30/2015 05/31/2020 0 0 UNIVERSITY OF CALIFORNIA, SAN DIEGO $4,468,619.00
U01DA041117-01 Adolescent Brain Cognitive Development (ABCD) Prospective Research in Studies of Maturation (PRISM) Consortium 09/30/2015 05/31/2020 1535 1210 UNIVERSITY OF MARYLAND BALTIMORE $5,434,585.00
U01DA041022-01 ABCD-USA Consortium: Research Project 09/30/2015 03/31/2027 350 356 SRI INTERNATIONAL $5,211,982.00
U01DA041148-01 ABCD-USA Consortium: Research Project 09/30/2015 05/31/2020 2362 1160 OREGON HEALTH & SCIENCE UNIVERSITY $8,316,307.00
U01DA041106-01 ABCD-USA Consortium: Research Project 09/30/2015 05/31/2020 2150 2352 UNIVERSITY OF MICHIGAN AT ANN ARBOR $7,896,592.00
U01DA041028-01 ABCD-USA Consortium:Research Project 09/30/2015 03/31/2027 450 455 UNIVERSITY OF PITTSBURGH AT PITTSBURGH $5,908,888.00
U01DA041048-01 ABCD-USA Consortium: Research Project 09/30/2015 05/31/2020 11961 5365 CHILDRENS HOSPITAL OF LOS ANGELES $6,767,468.00
U24DA041147-01 ABCD-USA Consortium: Coordinating Center 09/30/2015 05/31/2020 0 0 UNIVERSITY OF CALIFORNIA, SAN DIEGO $5,753,586.00
U01DA041156-01 FIU-ABCD: Pathways and Mechanisms to Addiction in the Latino Youth of South Florida 09/30/2015 05/31/2020 600 631 FLORIDA INTERNATIONAL UNIVERSITY $6,991,660.00
U01DA041134-01 Prospective Research Studies of Maturation (PRISM)- Research Project 09/30/2015 05/31/2020 950 1000 UNIVERSITY OF UTAH $7,859,943.00
U01DA041174-01 ABCD-USA: NYC Research Project 09/30/2015 03/31/2027 1725 635 YALE UNIVERSITY $9,301,963.00
U01DA041120-01 ABCD-USA Consortium: Twin Research Project 09/30/2015 05/31/2020 2380 2429 UNIVERSITY OF MINNESOTA $17,094,329.00
U01DA041093-01 13/13 ABCD-USA Consortium: Research Project 07/01/2017 05/31/2020 340 383 MEDICAL UNIVERSITY OF SOUTH CAROLINA $1,736,945.00
U01DA041025-01 ABCD-USA Consortium: UWM SIte 07/15/2017 03/31/2027 508 387 UNIVERSITY OF WISCONSIN MILWAUKEE $4,100,427.00
U01DA050989-01 15/21 ABCD-USA Consortium: Research Project Site at LIBR 04/15/2020 03/31/2027 743 737 LAUREATE INSTITUTE FOR BRAIN RESEARCH $4,252,568.00
U01DA051039-01 19/21 ABCD-USA CONSORTIUM: RESEARCH PROJECT SITE AT UVM 04/15/2020 03/31/2027 575 575 UNIVERSITY OF VERMONT & ST AGRIC COLLEGE $3,696,938.00
U01DA051016-01 18/21 ABCD-USA CONSORTIUM: RESEARCH PROJECT SITE AT THE UNIVERSITY OF FLORIDA 04/15/2020 03/31/2027 452 457 UNIVERSITY OF FLORIDA $2,686,249.00
U01DA051037-01 20/21 ABCD-USA CONSORTIUM: RESEARCH PROJECT SITE AT VCU 04/15/2020 03/31/2027 554 552 VIRGINIA COMMONWEALTH UNIVERSITY $3,323,433.00
U01DA050987-01 17/21 ABCD-USA CONSORTIUM: RESEARCH PROJECT SITE AT UCLA 04/15/2020 03/31/2027 435 435 UNIVERSITY OF CALIFORNIA LOS ANGELES $2,616,658.00
U01DA051018-01 14/21 ABCD-USA Consortium: Research Project Site at CU Boulder 04/15/2020 03/31/2027 565 565 UNIVERSITY OF COLORADO $3,252,372.00
U01DA051038-01 21/21 ABCD-USA CONSORTIUM: RESEARCH PROJECT SITE AT WUSTL 04/15/2020 03/31/2027 704 701 WASHINGTON UNIVERSITY $3,966,837.00
U01DA050988-01 16/21 ABCD-USA CONSORTIUM: RESEARCH PROJECT SITE AT UNIVERSITY OF ROCHESTER 04/15/2020 03/31/2027 340 337 UNIVERSITY OF ROCHESTER $2,152,218.00

IDNameCreated DateStatusType
648ABCD MID 04/17/2017ApprovedfMRI
649ABCD REST04/18/2017ApprovedfMRI
650ABCD SST 04/18/2017ApprovedfMRI
651ABCD NBACK 04/18/2017ApprovedfMRI
1194ABCD Smokescreen genotyping01/17/2019ApprovedOmics

Collection Owners and those with Collection Administrator permission, may edit a collection. The following is currently available for Edit on this page:

Shared Data

Data structures with the number of subjects submitted and shared are provided.

ABCD dMRI Post Processing QC Imaging 11610
ABCD dMRI RSI Part 1 Imaging 11811
ABCD dMRI RSI Part 2 Imaging 11811
ABCD dMRI RSI Part 3 Imaging 11811
ABCD dMRI RSI Part 4 Imaging 11811
ABCD dMRI RSI Part 7 Imaging 11811
ABCD sMRI Destrieux Parcellation Part 1 Imaging 11811
ABCD sMRI Destrieux Parcellation Part 2 Imaging 11811
ABCD sMRI Part 1 Imaging 11811
ABCD sMRI Part 2 Imaging 11811
ABCD ABCL Scores Clinical Assessments 10522
ABCD ACS Post Stratification Weights Clinical Assessments 11876
ABCD Adult Behavior Checklist Clinical Assessments 10414
ABCD Barkley Deficits in Executive Functioning Scale Clinical Assessments 6251
ABCD Breastfeeding Questionnaire Clinical Assessments 6251
ABCD Brief Problem Monitor-Teacher Form For Ages 6-18 (BPMT) Clinical Assessments 11876
ABCD Cash Choice Task Clinical Assessments 11876
ABCD Child Nutrition Assessment Clinical Assessments 11225
ABCD Children's Report of Parental Behavioral Inventory Clinical Assessments 11876
ABCD Cyber Bully Clinical Assessments 10522
ABCD Delay Discounting Trial Level Behavior Clinical Assessments 10406
ABCD Developmental History Questionnaire Clinical Assessments 11876
ABCD Difficulty in Emotion Regulation Clinical Assessments 6251
ABCD Early Adolescent Temperament Questionnaire Parent Clinical Assessments 10414
ABCD Emotion Regulation Questionnaire Clinical Assessments 6251
ABCD Emotional Stroop Task Trial Level Behavior Clinical Assessments 10399
ABCD Family History Assessment Part 1 Clinical Assessments 11876
ABCD Family History Assessment Part 2 Clinical Assessments 11876
ABCD Fasttrack QC Instrument Imaging 11836
ABCD Follow-Up Scheduling Screener Clinical Assessments 10414
ABCD FreeSurfer QC Imaging 11816
ABCD Game of Dice Summary Scores Clinical Assessments 10414
ABCD Game of Dice Trial Level Behavior Clinical Assessments 9593
ABCD Hormone Saliva Salimetric Scores Clinical Assessments 11876
ABCD International Physical Activity Questionnaire Clinical Assessments 6251
ABCD Irma Substudy Child Clinical Assessments 408
ABCD Irma Substudy Parent Clinical Assessments 466
ABCD Kiddie Schedule for Affective Disorders and Schizophrenia 5 Parent Clinical Assessments 6251
ABCD Kiddie Schedule for Affective Disorders and Schizophrenia 5 Youth Clinical Assessments 6251
ABCD Little Man Task Summary Scores Clinical Assessments 11876
ABCD Little Man Task Trial Level Behavior Clinical Assessments 11826
ABCD Longitudinal Parent Demographics Survey Clinical Assessments 11876
ABCD Longitudinal Parent Diagnostic Interview for DSM-5 Background Items Full (KSAD) Clinical Assessments 11488
ABCD Longitudinal Parent Medical History Questionnaire Clinical Assessments 11488
ABCD Longitudinal Parent Ohio State Traumatic Brain Injury Screen-Short Modified (OTBI) Clinical Assessments 11488
ABCD Longitudinal Parent Sports and Activities Involvement Questionnaire (SAIQ) Clinical Assessments 11488
ABCD Longitudinal Summary Scores Medical History Clinical Assessments 11488
ABCD Longitudinal Summary Scores Sports Activity Clinical Assessments 11488
ABCD Longitudinal Summary Scores Traumatic Brain Injury Clinical Assessments 11488
ABCD Longitudinal Tracking Clinical Assessments 11876
ABCD MR Findings Clinical Assessments 11876
ABCD MRI Info Imaging 11832
ABCD Mobil Tech from EARS Company Clinical Assessments 67
ABCD Mobil Tech from EARS Raw Data Imaging 68
ABCD Mobil Tech from Vibrent Company Clinical Assessments 59
ABCD Multi-Group Ethnic Identity-Revised (MEIM-R) Clinical Assessments 6251
ABCD Multidimensional Neglectful Behavior Scale Clinical Assessments 6251
ABCD NIH Toolbox Trial Level Behavior Clinical Assessments 11876
ABCD Occupation Survey Parent Clinical Assessments 10522
ABCD Other Resilience Clinical Assessments 11876
ABCD Pain Questionnaire Clinical Assessments 10522
ABCD Parent Acculturation Survey Modified from PhenX (ACC) Clinical Assessments 11876
ABCD Parent Adult Self Report Raw Scores Aseba (ASR) Clinical Assessments 11876
ABCD Parent Adult Self Report Scores Aseba (ASR) Clinical Assessments 11876
ABCD Parent Child Behavior Checklist Raw Scores Aseba (CBCL) Clinical Assessments 11876
ABCD Parent Child Behavior Checklist Scores Aseba (CBCL) Clinical Assessments 11876
ABCD Parent Community Risk and Protective Factors (CRPF) Clinical Assessments 11876
ABCD Parent Demographics Survey Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) ADHD Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Agoraphobia Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Alcohol Use Disorder Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Autism Spectrum Disorders Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Bipolar Disorders Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) DMDD Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Depressive Disorders Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Drug Use Disorder Individual Questions Clinical Assessments 3189
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Eating Disorders Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Generalized Anxiety Disorder Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Homicidality Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) ODD Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Panic Disorder Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Psychotic Disorders Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Separation Anxiety Disorder Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Sleep Problems Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Specific Anxiety Disorder Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Specific Phobia Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Suicidality Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Tic Disorder Individual Questions Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Traumatic Events Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 Background Items Full (KSADS-5) Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5 Full (KSADS-5) Clinical Assessments 11876
ABCD Parent Diagnostic Interview for DSM-5(KSADS) Obsessive Compulsive Disorder Individual Questions Clinical Assessments 11876
ABCD Parent Family Environment Scale-Family Conflict Subscale Modified from PhenX (FES) Clinical Assessments 11876
ABCD Parent Family History Summary Scores Clinical Assessments 11876
ABCD Parent Fitbit Baseline Clinical Assessments 164
ABCD Parent Fitbit Followup Clinical Assessments 11876
ABCD Parent Gender Identity Clinical Assessments 11488
ABCD Parent KSADS Conduct Disorder Clinical Assessments 11876
ABCD Parent Life Events Clinical Assessments 11488
ABCD Parent Medical History Questionnaire (MHX) Clinical Assessments 11876
ABCD Parent Medications Survey Inventory Modified from PhenX (PMP) Clinical Assessments 11876
ABCD Parent Mexican American Cultural Values Scale Modified (MACV) Clinical Assessments 11876
ABCD Parent Mobil Tech Postassessment Clinical Assessments 10414
ABCD Parent Mobil Tech Preassessment Clinical Assessments 10414
ABCD Parent Multi-Group Ethnic Identity-Revised Survey (MEIM) Clinical Assessments 11876
ABCD Parent Neighborhood Safety/Crime Survey Modified from PhenX (NSC) Clinical Assessments 11876
ABCD Parent Ohio State Traumatic Brain Injury Screen-Short Modified (OTBI) Clinical Assessments 11876
ABCD Parent Parent General Behavior Inventory-Mania (PGBI) Clinical Assessments 11876
ABCD Parent Participant Last Use Survey Day 2 3 4 (PLUS) Clinical Assessments 11876
ABCD Parent PhenX Community Cohesion Clinical Assessments 10414
ABCD Parent Pubertal Development Scale and Menstrual Cycle Survey History (PDMS) Clinical Assessments 11876
ABCD Parent School Attendance and Grades Clinical Assessments 10522
ABCD Parent Screen Time Survey (STQ) Clinical Assessments 11876
ABCD Parent Screentime Questionnaire Clinical Assessments 6251
ABCD Parent Short Social Responsiveness Scale Clinical Assessments 11225
ABCD Parent Sleep Disturbance Scale for Children (SDS) Clinical Assessments 11876
ABCD Parent Sports and Activities Involvement Questionnaire (SAIQ) Clinical Assessments 11876
ABCD Parent Survey of Substance Use Density, Storage, and Exposure Clinical Assessments 10522
ABCD Parent Vancouver Index of Acculturation-Short Survey (VIA) Clinical Assessments 11876
ABCD Parental Monitoring Survey Clinical Assessments 11876
ABCD Parental Rules on Substance Use Clinical Assessments 11876
ABCD Pearson Scores Clinical Assessments 11876
ABCD Peer Experiences Questionnaire Clinical Assessments 10522
ABCD Perceived Stress Scale Clinical Assessments 6251
ABCD Pet Ownership Clinical Assessments 6251
ABCD Post-assessment Parent Survey for Fitbit Protocol Clinical Assessments 10414
ABCD Post-assessment Youth Survey for Fitbit Protocol Clinical Assessments 10414
ABCD Pre-assessment Parent Survey for Fitbit Protocol Clinical Assessments 10414
ABCD Pre-assessment Youth Survey for Fitbit Protocol Clinical Assessments 10414
ABCD Prodromal Psychosis Scale Clinical Assessments 11876
ABCD Pubertal Hormone Saliva Clinical Assessments 11876
ABCD RA Scanning Checklist and Notes Clinical Assessments 11876
ABCD RECMEM Task Trial Level Behavior Clinical Assessments 10858
ABCD Recommended Imaging Inclusion Imaging 11832
ABCD SMARTE Task Trial Level Behavior Clinical Assessments 1478
ABCD School Risk and Protective Factors Survey Clinical Assessments 11876
ABCD Screener Clinical Assessments 11876
ABCD Social Development Follow Up Alabama Parenting Clinical Assessments 1606
ABCD Social Development Follow Up Child Difficulties in Emotion Regulation Clinical Assessments 1606
ABCD Social Development Follow Up Child Feedback Clinical Assessments 1606
ABCD Social Development Follow Up Child Firearms Clinical Assessments 1606
ABCD Social Development Follow Up Child Peer Behavior Clinical Assessments 1606
ABCD Social Development Follow Up Child Personality Disposition Clinical Assessments 1606
ABCD Social Development Follow Up Child Victimization Clinical Assessments 1606
ABCD Social Development Follow Up Parent Alabama Parenting Clinical Assessments 1606
ABCD Social Development Follow Up Parent Emotion Regulation Clinical Assessments 1606
ABCD Social Development Follow Up Parent Feedback Clinical Assessments 1606
ABCD Social Development Follow Up Parent Firearms Clinical Assessments 1606
ABCD Social Development Follow Up Parent Neighborhood Clinical Assessments 1606
ABCD Social Development Follow Up Parent Personality Disposition Clinical Assessments 1606
ABCD Social Development Follow Up Parent Reported Delinquency Clinical Assessments 1606
ABCD Social Development Follow Up Parent Victimization Clinical Assessments 1606
ABCD Social Development Follow Up Reported Delinquency Clinical Assessments 1606
ABCD Social Development Follow Up Visit Type Clinical Assessments 1606
ABCD Social Influence Summary Scores Clinical Assessments 10414
ABCD Social Influence Task Trial Level Behavior Clinical Assessments 9511
ABCD Specialty Summary Score Clinical Assessments 11876
ABCD Sports Activities Read/Music – Parent Clinical Assessments 6251
ABCD Sports Activities Read/Music – Youth Clinical Assessments 6251
ABCD Stanford Mental Arithmetic Response Time Evaluation Clinical Assessments 6251
ABCD Sum Scores Culture & Environment Parent Clinical Assessments 11876
ABCD Sum Scores Culture & Environment Youth Clinical Assessments 11876
ABCD Sum Scores Mobil Tech Youth Clinical Assessments 11876
ABCD Sum Scores Physical Health Parent Clinical Assessments 11876
ABCD Sum Scores Physical Health Youth Clinical Assessments 11876
ABCD Sum Scores Traumatic Brain Injury Clinical Assessments 11876
ABCD Summary Scores Brief Problem Monitor-Teacher Form for Ages 6-18 Clinical Assessments 11876
ABCD Summary Scores Developmental History Clinical Assessments 11876
ABCD Summary Scores Medical History Clinical Assessments 11876
ABCD Summary Scores Sports Activity Clinical Assessments 11876
ABCD Summary Scores Substance Use Clinical Assessments 11876
ABCD Task fMRI MID Average Beta Weights Destrieux Parcellations Part 1 Imaging 10982
ABCD Task fMRI MID Average Beta Weights Destrieux Parcellations Part 2 Imaging 10982
ABCD Task fMRI MID Average Beta Weights Part 1 Imaging 10982
ABCD Task fMRI MID Average Beta Weights Part 2 Imaging 10982
ABCD Task fMRI MID Average SEM Destrieux Parcellations Part 1 Imaging 10982
ABCD Task fMRI MID Average SEM Destrieux Parcellations Part 2 Imaging 10982
ABCD Task fMRI MID Average Standard Error of the Mean Part 1 Imaging 10982
ABCD Task fMRI MID Average Standard Error of the Mean Part 2 Imaging 10982
ABCD Task fMRI MID Behavior Clinical Assessments 11876
ABCD Task fMRI MID Run 1 Beta Weights Destrieux Parcellations Part 1 Imaging 10979
ABCD Task fMRI MID Run 1 Beta Weights Destrieux Parcellations Part 2 Imaging 10979
ABCD Task fMRI MID Run 1 Beta Weights Part 1 Imaging 10979
ABCD Task fMRI MID Run 1 Beta Weights Part 2 Imaging 10979
ABCD Task fMRI MID Run 1 SEM Destrieux Parcellations Part 1 Imaging 10979
ABCD Task fMRI MID Run 1 SEM Destrieux Parcellations Part 2 Imaging 10979
ABCD Task fMRI MID Run 1 Standard Error of the Mean Part 1 Imaging 10979
ABCD Task fMRI MID Run 1 Standard Error of the Mean Part 2 Imaging 10979
ABCD Task fMRI MID Run 2 Beta Weights Destrieux Parcellations Part 1 Imaging 10736
ABCD Task fMRI MID Run 2 Beta Weights Destrieux Parcellations Part 2 Imaging 10736
ABCD Task fMRI MID Run 2 Beta Weights Part 1 Imaging 10736
ABCD Task fMRI MID Run 2 Beta Weights Part 2 Imaging 10736
ABCD Task fMRI MID Run 2 SEM Destrieux Parcellations Part 1 Imaging 10736
ABCD Task fMRI MID Run 2 SEM Destrieux Parcellations Part 2 Imaging 10736
ABCD Task fMRI MID Run 2 Standard Error of the Mean Part 1 Imaging 10736
ABCD Task fMRI MID Run 2 Standard Error of the Mean Part 2 Imaging 10736
ABCD Task fMRI MID Trial Level Behavior Imaging 11101
ABCD Task fMRI REC Behavior Clinical Assessments 11876
ABCD Task fMRI SST Average Beta Weights Imaging 10898
ABCD Task fMRI SST Average Beta Weights Destrieux Parcellations Part 1 Imaging 10898
ABCD Task fMRI SST Average Beta Weights Destrieux Parcellations Part 2 Imaging 10898
ABCD Task fMRI SST Average SEM Destrieux Parcellations Part 1 Imaging 10898
ABCD Task fMRI SST Average SEM Destrieux Parcellations Part 2 Imaging 10898
ABCD Task fMRI SST Average Standard Error of the Mean Imaging 10898
ABCD Task fMRI SST Behavior Clinical Assessments 11876
ABCD Task fMRI SST Run 1 Beta Weights Imaging 10897
ABCD Task fMRI SST Run 1 Beta Weights Destrieux Parcellations Part 1 Imaging 10897
ABCD Task fMRI SST Run 1 Beta Weights Destrieux Parcellations Part 2 Imaging 10897
ABCD Task fMRI SST Run 1 SEM Destrieux Parcellations Part 1 Imaging 10897
ABCD Task fMRI SST Run 1 SEM Destrieux Parcellations Part 2 Imaging 10897
ABCD Task fMRI SST Run 1 Standard Error of the Mean Imaging 10897
ABCD Task fMRI SST Run 2 Beta Weights Imaging 10646
ABCD Task fMRI SST Run 2 Beta Weights Destrieux Parcellations Part 1 Imaging 10646
ABCD Task fMRI SST Run 2 Beta Weights Destrieux Parcellations Part 2 Imaging 10646
ABCD Task fMRI SST Run 2 SEM Destrieux Parcellations Part 1 Imaging 10646
ABCD Task fMRI SST Run 2 SEM Destrieux Parcellations Part 2 Imaging 10646
ABCD Task fMRI SST Run 2 Standard Error of the Mean Imaging 10646
ABCD Task fMRI SST Trial Level Behavior Imaging 11028
ABCD Task fMRI nBack Average Beta Weights Imaging 10830
ABCD Task fMRI nBack Average Beta Weights Destrieux Parcellations Part 1 Imaging 10830
ABCD Task fMRI nBack Average Beta Weights Destrieux Parcellations Part 2 Imaging 10830
ABCD Task fMRI nBack Average SEM Destrieux Parcellations Part 1 Imaging 10830
ABCD Task fMRI nBack Average SEM Destrieux Parcellations Part 2 Imaging 10830
ABCD Task fMRI nBack Average Standard Error of the Mean Imaging 10830
ABCD Task fMRI nBack Behavior Clinical Assessments 11693
ABCD Task fMRI nBack Run 1 Beta Weights Imaging 10826
ABCD Task fMRI nBack Run 1 Beta Weights Destrieux Parcellations Part 1 Imaging 10826
ABCD Task fMRI nBack Run 1 Beta Weights Destrieux Parcellations Part 2 Imaging 10826
ABCD Task fMRI nBack Run 1 SEM Destrieux Parcellations Part 1 Imaging 10826
ABCD Task fMRI nBack Run 1 SEM Destrieux Parcellations Part 2 Imaging 10826
ABCD Task fMRI nBack Run 1 Standard Error of the Mean Imaging 10826
ABCD Task fMRI nBack Run 2 Beta Weights Imaging 10629
ABCD Task fMRI nBack Run 2 Beta Weights Destrieux Parcellations Part 1 Imaging 10629
ABCD Task fMRI nBack Run 2 Beta Weights Destrieux Parcellations Part 2 Imaging 10629
ABCD Task fMRI nBack Run 2 SEM Destrieux Parcellations Part 1 Imaging 10629
ABCD Task fMRI nBack Run 2 SEM Destrieux Parcellations Part 2 Imaging 10629
ABCD Task fMRI nBack Run 2 Standard Error of the Mean Imaging 10629
ABCD Task fMRI nBack Trial Level Behavior Imaging 9891
ABCD The Stanford Education Data Archive (SEDA) part 2 Clinical Assessments 10153
ABCD The Stanford Education Data Archive (SEDA) part 3 Clinical Assessments 10527
ABCD The Stanford Education Data Archive (SEDA) part 4 Clinical Assessments 10527
ABCD The Stanford Education Data Archive (SEDA) part 5 Clinical Assessments 10416
ABCD The Stanford Education Data Archive(SEDA) Part 1 Clinical Assessments 10561
ABCD Timeline Follow-back Survey Calendar Scores (TLFB) Clinical Assessments 11876
ABCD Twin Zygosity Rating Clinical Assessments 11876
ABCD Youth 7-Up Mania Items Clinical Assessments 11368
ABCD Youth Acculturation Survey Modified from PhenX (ACC) Clinical Assessments 11876
ABCD Youth Alcohol Measures Clinical Assessments 11488
ABCD Youth Alcohol Screen Clinical Assessments 11876
ABCD Youth Anthropometrics Modified From PhenX (ANT) Clinical Assessments 11876
ABCD Youth Behavioral Inhibition/Behavioral Approach System Scales Modified from PhenX (BIS/BAS) Clinical Assessments 11876
ABCD Youth Block Food Screen Clinical Assessments 10522
ABCD Youth Blood Analysis Clinical Assessments 10414
ABCD Youth Blood Pressure Clinical Assessments 10414
ABCD Youth Brief Problem Monitor Clinical Assessments 11733
ABCD Youth Community Risk and Protective Factors Clinical Assessments 10522
ABCD Youth Delay Discounting Sum Scores Clinical Assessments 11368
ABCD Youth Diagnostic Interview for DSM-5 (KSADS) Alcohol Use Disorder Individual Questions Clinical Assessments 11876
ABCD Youth Diagnostic Interview for DSM-5 (KSADS) Bipolar Disorders Individual Questions Clinical Assessments 11876
ABCD Youth Diagnostic Interview for DSM-5 (KSADS) Conduct Disorder Individual Questions Clinical Assessments 11876
ABCD Youth Diagnostic Interview for DSM-5 (KSADS) DMDD Individual Questions Clinical Assessments 11876
ABCD Youth Diagnostic Interview for DSM-5 (KSADS) Depressive Disorders Individual Questions Clinical Assessments 11876
ABCD Youth Diagnostic Interview for DSM-5 (KSADS) Drug Use Disorder Individual Questions Clinical Assessments 7808
ABCD Youth Diagnostic Interview for DSM-5 (KSADS) Eating Disorders Individual Questions Clinical Assessments 11876
ABCD Youth Diagnostic Interview for DSM-5 (KSADS) Generalized Anxiety Disorder Individual Questions Clinical Assessments 11876
ABCD Youth Diagnostic Interview for DSM-5 (KSADS) Sleep Problems Individual Questions Clinical Assessments 11876
ABCD Youth Diagnostic Interview for DSM-5 (KSADS) Specific Anxiety Disorder Individual Questions Clinical Assessments 11876
ABCD Youth Diagnostic Interview for DSM-5 (KSADS) Suicidality Individual Questions Clinical Assessments 11876
ABCD Youth Diagnostic Interview for DSM-5 5 (KSADS-5) Clinical Assessments 11876
ABCD Youth Diagnostic Interview for DSM-5 Background Items 5 (KSADS-5) Clinical Assessments 11876
ABCD Youth Discrimination Measure Clinical Assessments 11453
ABCD Youth Edinburgh Handedness Inventory Short Form (EHIS) Clinical Assessments 11876
ABCD Youth Emotional Stroop Task Clinical Assessments 11368
ABCD Youth Family Environment Scale-Family Conflict Subscale Modified from PhenX (FES) Clinical Assessments 11876
ABCD Youth Fitbit Baseline Clinical Assessments 162
ABCD Youth Fitbit Daily Physical Activity Summaries Clinical Assessments 7439
ABCD Youth Fitbit Daily Sleep Summaries Clinical Assessments 5950
ABCD Youth Fitbit Followup Clinical Assessments 150
ABCD Youth Fitbit Weekly Physical Activity Summaries Clinical Assessments 7076
ABCD Youth Fitbit Weekly Sleep Summaries Clinical Assessments 4709
ABCD Youth Gender Identity Clinical Assessments 11488
ABCD Youth Genetic Blood (RUCDR) Clinical Assessments 11876
ABCD Youth Genetic Saliva (RUCDR) Clinical Assessments 11876
ABCD Youth Gish2 Clinical Assessments 10522
ABCD Youth Hair Results Clinical Assessments 1262
ABCD Youth Hair Sample Clinical Assessments 11876
ABCD Youth Life Events Clinical Assessments 11488
ABCD Youth Marijuana Illicit Drug Measures Clinical Assessments 11488
ABCD Youth Mexican American Cultural Values Scale Clinical Assessments 10522
ABCD Youth Mid Year Phone Interview Substance Use Clinical Assessments 11672
ABCD Youth Mobil Tech Postassessment Clinical Assessments 10414
ABCD Youth Mobil Tech Preassessment Clinical Assessments 10414
ABCD Youth Monetary Incentive Delay Task Survey Post Scan Questionnaire Clinical Assessments 11876
ABCD Youth Munich Chronotype Questionnaire Clinical Assessments 10522
ABCD Youth NIH TB Summary Scores Clinical Assessments 11876
ABCD Youth NIH Toolbox Positive Affect Items Clinical Assessments 11716
ABCD Youth Neighborhood Safety/Crime Survey Modified from PhenX (NSC) Clinical Assessments 11876
ABCD Youth Neurognition Survey Session Clinical Assessments 11876
ABCD Youth Nicalert Clinical Assessments 11488
ABCD Youth Nicotine Measures Clinical Assessments 11488
ABCD Youth Participant Last Use Survey Day 1 2 3 4 (PLUS) Clinical Assessments 11876
ABCD Youth Peer Behavior Profile Clinical Assessments 10522
ABCD Youth Peer Network Health Protective Scaler Clinical Assessments 10522
ABCD Youth Post Scan Questionnaire 2 Clinical Assessments 11876
ABCD Youth Post Scan Questionnaire 1 Clinical Assessments 11876
ABCD Youth Pre Scan Questionnaire 1 Clinical Assessments 11876
ABCD Youth Pre Scan Questionnaire 2 Clinical Assessments 11876
ABCD Youth Pubertal Development Scale and Menstrual Cycle Survey History (PDMS) Clinical Assessments 11876
ABCD Youth Rescan Monetary Incentive Delay Task Survey Post Scan Questionnaire Clinical Assessments 11876
ABCD Youth School Attendance and Grades Clinical Assessments 10522
ABCD Youth Screen Time Survey (STQ) Clinical Assessments 11876
ABCD Youth Snellen Vision Screener (SVS) Clinical Assessments 11876
ABCD Youth Substance Use Attitudes Clinical Assessments 11488
ABCD Youth Substance Use Interview Clinical Assessments 11876
ABCD Youth Substance Use Introduction and Patterns Clinical Assessments 11488
ABCD Youth Summary Scores BPM and POA Clinical Assessments 11733
ABCD Youth Teeth Collection Clinical Assessments 11876
ABCD Youth Toxicology Test Clinical Assessments 11876
ABCD Youth Vancouver Index of Acculturation Clinical Assessments 6251
ABCD Youth Wills Problem Solving Scale Clinical Assessments 11368
ABCD Youth Youth Risk Behavior Survey Exercise Physical Activity (YRB) Clinical Assessments 11876
ABCD dMRI DTI Destrieux Parcellations Part 1 Imaging 11811
ABCD dMRI DTI Destrieux Parcellations Part 2 Imaging 11811
ABCD dMRI DTI Full Destrieux Parcellation Part 1 Imaging 11811
ABCD dMRI DTI Full Destrieux Parcellation Part 2 Imaging 11811
ABCD dMRI DTI Full Part 1 Imaging 11811
ABCD dMRI DTI Full Part 2 Imaging 11811
ABCD dMRI DTI Part 1 Imaging 11811
ABCD dMRI DTI Part 2 Imaging 11811
ABCD dMRI RSI Part 5 Imaging 11811
ABCD dMRI RSI Part 6 Imaging 11811
ABCD rsfMRI Destrieux Imaging 11614
ABCD rsfMRI Gordon Network Correlations Imaging 11614
ABCD rsfMRI Network to Subcortical ROI Correlations Imaging 11614
ABCD rsfMRI Temporal Variance Imaging 11614
ABCD sMRI Destrieux Parcellation Part 3 Imaging 11811
ABCD sMRI Part 3 Imaging 11811
ABCD sMRI T2w Post Processing QC Imaging 11488
Automated Post-Processing QC Metrics Imaging 11811
Genomics Sample Genomics 10217
Image Imaging 11819
MRI QC Raw Part 1 Imaging 11841
MRI QC Raw Part 2 Imaging 11841
MRI QC Raw Part 3 Imaging 11841
Manual fMRI Post-Processing QC Imaging 11738
Mobile Data Imaging 7032
Parent ABCD COVID-19 Questionnaire Clinical Assessments 6010
Parent Prosocial Behavior Survey Clinical Assessments 11876
Processed MRI Data Imaging 11821
Residential History Derived Scores Clinical Assessments 11876
Social Development Child Alabama Parenting Questionnaire Clinical Assessments 2300
Social Development Child Difficulties in Emotion Regulation Clinical Assessments 2300
Social Development Child Feedback Clinical Assessments 2300
Social Development Child Firearms Clinical Assessments 2300
Social Development Child Peer Behavior Clinical Assessments 2300
Social Development Child Personality Disposition Clinical Assessments 2300
Social Development Child Reported Delinquency Clinical Assessments 2300
Social Development Child Victimization Clinical Assessments 2300
Social Development Contact Track Clinical Assessments 11876
Social Development Parent Alabama Parenting Questionnaire Clinical Assessments 2300
Social Development Parent Difficulties in Emotion Regulation Clinical Assessments 2300
Social Development Parent Feedback Clinical Assessments 2300
Social Development Parent Firearms Clinical Assessments 2300
Social Development Parent Neighborhood Clinical Assessments 2300
Social Development Parent Personality Disposition Clinical Assessments 2300
Social Development Parent Reported Delinquency Clinical Assessments 2300
Social Development Parent Victimization Clinical Assessments 2300
Social Development Visit Type Clinical Assessments 2300
Sum Scores Mental Health Parent Clinical Assessments 11876
Sum Scores Mental Health Youth Clinical Assessments 11876
UPPS-P for Children Short Form (ABCD-version) Clinical Assessments 11876
Youth ABCD COVID-19 Questionnaire Clinical Assessments 6010
Youth Prosocial Behavior Survey Clinical Assessments 11876

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Publications

Publications relevant to NDA data are listed below. Most displayed publications have been associated with the grant within Pubmed. Use the "+ New Publication" button to add new publications. Publications relevant/not relevant to data expected are categorized. Relevant publications are then linked to the underlying data by selecting the Create Study link. Study provides the ability to define cohorts, assign subjects, define outcome measures and lists the study type, data analysis and results. Analyzed data and results are expected in this way.

PubMed IDStudyTitleJournalAuthorsDateStatus
34954668Create StudyThe Emotional Word-Emotional Face Stroop task in the ABCD study: Psychometric validation and associations with measures of cognition and psychopathology.Developmental cognitive neuroscienceSmolker, Harry R; Wang, Kai; Luciana, Monica; Bjork, James M; Gonzalez, Raul; Barch, Deanna M; McGlade, Erin C; Kaiser, Roselinde H; Friedman, Naomi P; Hewitt, John K; Banich, Marie TDecember 21, 2021Not Determined
34923146Create StudyParent-adolescent discrepancies in adolescent recreational screen time reporting during the COVID-19 pandemic.Academic pediatricsNagata, Jason M; Cortez, Catherine A; Iyer, Puja; Ganson, Kyle T; Chu, Jonathan; Conroy, Amy ADecember 16, 2021Not Determined
34860306Create StudyAssociations Between Traumatic Stress, Brain Volumes and Post-traumatic Stress Disorder Symptoms in Children: Data from the ABCD Study.Behavior geneticsBustamante, Daniel; Amstadter, Ananda B; Pritikin, Joshua N; Brick, Timothy R; Neale, Michael CDecember 3, 2021Not Determined
34845019Create StudyPredicting multilingual effects on executive function and individual connectomes in children: An ABCD study.Proceedings of the National Academy of Sciences of the United States of AmericaKwon, Young Hye; Yoo, Kwangsun; Nguyen, Hillary; Jeong, Yong; Chun, Marvin MDecember 7, 2021Not Determined
34820951Create StudyWe Know Even More Things: A Decade Review of Parenting Research.Journal of research on adolescence : the official journal of the Society for Research on AdolescenceMorris, Amanda Sheffield; Ratliff, Erin L; Cosgrove, Kelly T; Steinberg, LaurenceDecember 1, 2021Not Determined
34818623Create StudyStress and adolescence: vulnerability and opportunity during a sensitive window of development.Current opinion in psychologySisk, Lucinda M; Gee, Dylan GOctober 23, 2021Not Determined
34798853Create StudyMethylphenidate augmentation of escitalopram to enhance adherence to antidepressant treatment: a pilot randomized controlled trial.BMC psychiatryPaulus, Martin P; Kuplicki, Rayus; Victor, Teresa A; Yeh, Hung-Wen; Khalsa, Sahib SNovember 19, 2021Not Determined
34795422Create StudyNeural vulnerability and hurricane-related media are associated with post-traumatic stress in youth.Nature human behaviourDick, Anthony Steven; Silva, Karina; Gonzalez, Raul; Sutherland, Matthew T; Laird, Angela R; Thompson, Wesley K; Tapert, Susan F; Squeglia, Lindsay M; Gray, Kevin M; Nixon, Sara Jo; Cottler, Linda B; La Greca, Annette M; Gurwitch, Robin H; Comer, Jonathan SNovember 1, 2021Not Determined
34782711Create StudyPersistent and distressing psychotic-like experiences using adolescent brain cognitive development℠ study data.Molecular psychiatryKarcher, Nicole R; Loewy, Rachel L; Savill, Mark; Avenevoli, Shelli; Huber, Rebekah S; Makowski, Carolina; Sher, Kenneth J; Barch, Deanna MNovember 16, 2021Not Determined
34753911Create StudyWidespread attenuating changes in brain connectivity associated with the general factor of psychopathology in 9- and 10-year olds.Translational psychiatrySripada, Chandra; Angstadt, Mike; Taxali, Aman; Kessler, Daniel; Greathouse, Tristan; Rutherford, Saige; Clark, D Angus; Hyde, Luke W; Weigard, Alex; Brislin, Sarah J; Hicks, Brian; Heitzeg, MaryNovember 9, 2021Not Determined
34750359Create StudyBrain-wide functional connectivity patterns support general cognitive ability and mediate effects of socioeconomic status in youth.Translational psychiatrySripada, Chandra; Angstadt, Mike; Taxali, Aman; Clark, D Angus; Greathouse, Tristan; Rutherford, Saige; Dickens, Joseph R; Shedden, Kerby; Gard, Arianna M; Hyde, Luke W; Weigard, Alexander; Heitzeg, MaryNovember 8, 2021Not Determined
34742018Create StudyDemographic and mental health assessments in the adolescent brain and cognitive development study: Updates and age-related trajectories.Developmental cognitive neuroscienceBarch, Deanna M; Albaugh, Matthew D; Baskin-Sommers, Arielle; Bryant, Brittany E; Clark, Duncan B; Dick, Anthony Steven; Feczko, Eric; Foxe, John J; Gee, Dylan G; Giedd, Jay; Glantz, Meyer D; Hudziak, James J; Karcher, Nicole R; LeBlanc, Kimberly; Maddox, Melanie; McGlade, Erin C; Mulford, Carrie; Nagel, Bonnie J; Neigh, Gretchen; Palmer, Clare E; Potter, Alexandra S; Sher, Kenneth J; Tapert, Susan F; Thompson, Wesley K; Xie, LailiDecember 1, 2021Not Determined
34734493Create StudyGreater radiologic evidence of hypothalamic gliosis predicts adiposity gain in children at risk for obesity.Obesity (Silver Spring, Md.)Sewaybricker, Leticia E; Kee, Sarah; Melhorn, Susan J; Schur, Ellen ANovember 1, 2021Not Determined
34734154Create StudyCingulo-opercular and Cingulo-parietal Brain Networks Functional Connectivity in Pre-adolescents: Multiplicative Effects of Race, Ethnicity, and Parental Education.Research in health scienceAssari, ShervinJanuary 1, 2021Not Determined
34724543Create StudyScreen Time Use Among US Adolescents During the COVID-19 Pandemic: Findings From the Adolescent Brain Cognitive Development (ABCD) Study.JAMA pediatricsNagata, Jason M; Cortez, Catherine A; Cattle, Chloe J; Ganson, Kyle T; Iyer, Puja; Bibbins-Domingo, Kirsten; Baker, Fiona CJanuary 1, 2022Not Determined
34710799Create StudyAssociations among negative life events, changes in cortico-limbic connectivity, and psychopathology in the ABCD Study.Developmental cognitive neuroscienceBrieant, Alexis E; Sisk, Lucinda M; Gee, Dylan GDecember 1, 2021Not Determined
34706458Create StudyP300 amplitude during a monetary incentive delay task predicts future therapy completion in individuals with major depressive disorder.Journal of affective disordersWhite, Evan J; Nacke, Mariah; Akeman, Elisabeth; Cannon, Mallory J; Mayeli, Ahmad; Touthang, James; Zoubi, Obada Al; McDermott, Timothy J; Kirlic, Namik; Santiago, Jessica; Kuplicki, Rayus; Bodurka, Jerzy; Paulus, Martin P; Craske, Michelle G; Wolitzky-Taylor, Kate; Abelson, James; Martell, Christopher; Clausen, Ashley; Stewart, Jennifer L; Aupperle, Robin LDecember 1, 2021Not Determined
34706304Create StudyMulti-label, multi-domain learning identifies compounding effects of HIV and cognitive impairment.Medical image analysisZhang, Jiequan; Zhao, Qingyu; Adeli, Ehsan; Pfefferbaum, Adolf; Sullivan, Edith V; Paul, Robert; Valcour, Victor; Pohl, Kilian MJanuary 1, 2022Not Determined
34695448Create StudyOpportunities for Early Identification: Implementing Universal Depression Screening with a Pathway to Suicide Risk Screening in a Pediatric Health Care System.The Journal of pediatricsCrandal, Brent R; Aguinaldo, Laika D; Carter, Chelsea; Billman, Glenn F; Sanderson, Kendall; Kuelbs, CynthiaOctober 22, 2021Not Determined
34677743Create StudyInvestigating the Link Between Depression, Cognition, and Motivation in Late Childhood.Child psychiatry and human developmentSteinberger, David C; Barch, Deanna MOctober 22, 2021Not Determined
34661541Create StudyPassive Sensing of Preteens'' Smartphone Use: An Adolescent Brain Cognitive Development (ABCD) Cohort Substudy.JMIR mental healthWade, Natasha E; Ortigara, Joseph M; Sullivan, Ryan M; Tomko, Rachel L; Breslin, Florence J; Baker, Fiona C; Fuemmeler, Bernard F; Delrahim Howlett, Katia; Lisdahl, Krista M; Marshall, Andrew T; Mason, Michael J; Neale, Michael C; Squeglia, Lindsay M; Wolff-Hughes, Dana L; Tapert, Susan F; Bagot, Kara S; ABCD Novel Technologies WorkgroupOctober 18, 2021Not Determined
34648580Create StudyRisk of lead exposure, subcortical brain structure, and cognition in a large cohort of 9- to 10-year-old children.PloS oneMarshall, Andrew T; McConnell, Rob; Lanphear, Bruce P; Thompson, Wesley K; Herting, Megan M; Sowell, Elizabeth RJanuary 1, 2021Not Determined
34632309Create StudyEmotional, Behavioral, and Cognitive Correlates of Attention Deficit and Hyperactive Disorder (ADHD) Screening and Diagnosis History: Sex/Gender Differences.Journal of neurology & neuromedicineAssari, ShervinJanuary 1, 2021Not Determined
34621600Create StudyThe General Factor of Psychopathology in the Adolescent Brain Cognitive Development (ABCD) Study: A Comparison of Alternative Modeling Approaches.Clinical psychological science : a journal of the Association for Psychological ScienceClark, D Angus; Hicks, Brian M; Angstadt, Mike; Rutherford, Saige; Taxali, Aman; Hyde, Luke; Weigard, Alexander; Heitzeg, Mary M; Sripada, ChandraMarch 1, 2021Not Determined
34608463Create StudyLongitudinal Impact of Childhood Adversity on Early Adolescent Mental Health During the COVID-19 Pandemic in the ABCD Study® Cohort: Does Race or Ethnicity Moderate Findings?Biological psychiatry global open scienceStinson, Elizabeth A; Sullivan, Ryan M; Peteet, Bridgette J; Tapert, Susan F; Baker, Fiona C; Breslin, Florence J; Dick, Anthony S; Gonzalez, Marybel Robledo; Guillaume, Mathieu; Marshall, Andrew T; McCabe, Connor J; Pelham 3rd, William E; Van Rinsveld, Amandine M; Sheth, Chandni S; Sowell, Elizabeth R; Wade, Natasha E; Wallace, Alexander L; Lisdahl, Krista MSeptember 29, 2021Not Determined
34607958Create StudyAdolescent civic engagement: Lessons from Black Lives Matter.Proceedings of the National Academy of Sciences of the United States of AmericaBaskin-Sommers, Arielle; Simmons, Cortney; Conley, May; Chang, Shou-An; Estrada, Suzanne; Collins, Meghan; Pelham, William; Beckford, Emil; Mitchell-Adams, Haley; Berrian, Nia; Tapert, Susan F; Gee, Dylan G; Casey, B JOctober 12, 2021Not Determined
34599145Create StudyCortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group.Translational psychiatryHarrewijn, Anita; Cardinale, Elise M; Groenewold, Nynke A; Bas-Hoogendam, Janna Marie; Aghajani, Moji; Hilbert, Kevin; Cardoner, Narcis; Porta-Casteràs, Daniel; Gosnell, Savannah; Salas, Ramiro; Jackowski, Andrea P; Pan, Pedro M; Salum, Giovanni A; Blair, Karina S; Blair, James R; Hammoud, Mira Z; Milad, Mohammed R; Burkhouse, Katie L; Phan, K Luan; Schroeder, Heidi K; Strawn, Jeffrey R; Beesdo-Baum, Katja; Jahanshad, Neda; Thomopoulos, Sophia I; Buckner, Randy; Nielsen, Jared A; Smoller, Jordan W; Soares, Jair C; Mwangi, Benson; Wu, Mon-Ju; Zunta-Soares, Giovana B; Assaf, Michal; Diefenbach, Gretchen J; Brambilla, Paolo; Maggioni, Eleonora; Hofmann, David; Straube, Thomas; Andreescu, Carmen; Berta, Rachel; Tamburo, Erica; Price, Rebecca B; Manfro, Gisele G; Agosta, Federica; Canu, Elisa; Cividini, Camilla; Filippi, Massimo; Kostić, Milutin; Munjiza Jovanovic, Ana; Alberton, Bianca A V; Benson, Brenda; Freitag, Gabrielle F; Filippi, Courtney A; Gold, Andrea L; Leibenluft, Ellen; Ringlein, Grace V; Werwath, Kathryn E; Zwiebel, Hannah; Zugman, André; Grabe, Hans J; Van der Auwera, Sandra; Wittfeld, Katharina; Völzke, Henry; Bülow, Robin; Balderston, Nicholas L; Ernst, Monique; Grillon, Christian; Mujica-Parodi, Lilianne R; van Nieuwenhuizen, Helena; Critchley, Hugo D; Makovac, Elena; Mancini, Matteo; Meeten, Frances; Ottaviani, Cristina; Ball, Tali M; Fonzo, Gregory A; Paulus, Martin P; Stein, Murray B; Gur, Raquel E; Gur, Ruben C; Kaczkurkin, Antonia N; Larsen, Bart; Satterthwaite, Theodore D; Harper, Jennifer; Myers, Michael; Perino, Michael T; Sylvester, Chad M; Yu, Qiongru; Lueken, Ulrike; Veltman, Dick J; Thompson, Paul M; Stein, Dan J; Van der Wee, Nic J A; Winkler, Anderson M; Pine, Daniel SOctober 1, 2021Not Determined
34571161Create StudyA deep learning toolbox for automatic segmentation of subcortical limbic structures from MRI images.NeuroImageGreve, Douglas N; Billot, Benjamin; Cordero, Devani; Hoopes, Andrew; Hoffmann, Malte; Dalca, Adrian V; Fischl, Bruce; Iglesias, Juan Eugenio; Augustinack, Jean CDecember 1, 2021Not Determined
34567915Create StudyAlcohol and Cannabis Use and the Developing Brain.Alcohol research : current reviewsLees, Briana; Debenham, Jennifer; Squeglia, Lindsay MJanuary 1, 2021Not Determined
34560273Create StudyVertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology.NeuroImageShadrin, Alexey A; Kaufmann, Tobias; van der Meer, Dennis; Palmer, Clare E; Makowski, Carolina; Loughnan, Robert; Jernigan, Terry L; Seibert, Tyler M; Hagler, Donald J; Smeland, Olav B; Motazedi, Ehsan; Chu, Yunhan; Lin, Aihua; Cheng, Weiqiu; Hindley, Guy; Thompson, Wesley K; Fan, Chun C; Holland, Dominic; Westlye, Lars T; Frei, Oleksandr; Andreassen, Ole A; Dale, Anders MDecember 1, 2021Not Determined
34555784Create StudyIdentifying profiles of brain structure and associations with current and future psychopathology in youth.Developmental cognitive neuroscienceMattoni, Matthew; Wilson, Sylia; Olino, Thomas MOctober 1, 2021Not Determined
34555056Create StudyRecalibrating expectations about effect size: A multi-method survey of effect sizes in the ABCD study.PloS oneOwens, Max M; Potter, Alexandra; Hyatt, Courtland S; Albaugh, Matthew; Thompson, Wesley K; Jernigan, Terry; Yuan, Dekang; Hahn, Sage; Allgaier, Nicholas; Garavan, HughJanuary 1, 2021Not Determined
34536537Create StudyLarge, open datasets for human connectomics research: Considerations for reproducible and responsible data use.NeuroImageLaird, Angela RDecember 1, 2021Not Determined
34530359Create StudyNeural response to monetary loss among youth with disruptive behavior disorders and callous-unemotional traits in the ABCD study.NeuroImage. ClinicalByrd, Amy L; Hawes, Samuel W; Waller, Rebecca; Delgado, Mauricio R; Sutherland, Matthew T; Dick, Anthony S; Trucco, Elisa M; Riedel, Michael C; Pacheco-Colón, Ileana; Laird, Angela R; Gonzalez, RaulSeptember 1, 2021Not Determined
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33731234Create StudyUsing multivariate endophenotypes to identify psychophysiological mechanisms associated with polygenic scores for substance use, schizophrenia, and education attainment.Psychological medicineHarper, Jeremy; Liu, Mengzhen; Malone, Stephen M; McGue, Matt; Iacono, William G; Vrieze, Scott IMarch 18, 2021Not Determined
33713937Create StudyPreliminary analysis of low-level alcohol use and suicidality with children in the adolescent brain and cognitive development (ABCD) baseline cohort.Psychiatry researchAguinaldo, Laika D; Goldstone, Aimee; Hasler, Brant P; Brent, David A; Coronado, Clarisa; Jacobus, JoannaMay 1, 2021Not Determined
33679599Create StudyCorrespondence Between Perceived Pubertal Development and Hormone Levels in 9-10 Year-Olds From the Adolescent Brain Cognitive Development Study.Frontiers in endocrinologyHerting, Megan M; Uban, Kristina A; Gonzalez, Marybel Robledo; Baker, Fiona C; Kan, Eric C; Thompson, Wesley K; Granger, Douglas A; Albaugh, Matthew D; Anokhin, Andrey P; Bagot, Kara S; Banich, Marie T; Barch, Deanna M; Baskin-Sommers, Arielle; Breslin, Florence J; Casey, B J; Chaarani, Bader; Chang, Linda; Clark, Duncan B; Cloak, Christine C; Constable, R Todd; Cottler, Linda B; Dagher, Rada K; Dapretto, Mirella; Dick, Anthony S; Dosenbach, Nico; Dowling, Gayathri J; Dumas, Julie A; Edwards, Sarah; Ernst, Thomas; Fair, Damien A; Feldstein-Ewing, Sarah W; Freedman, Edward G; Fuemmeler, Bernard F; Garavan, Hugh; Gee, Dylan G; Giedd, Jay N; Glaser, Paul E A; Goldstone, Aimee; Gray, Kevin M; Hawes, Samuel W; Heath, Andrew C; Heitzeg, Mary M; Hewitt, John K; Heyser, Charles J; Hoffman, Elizabeth A; Huber, Rebekah S; Huestis, Marilyn A; Hyde, Luke W; Infante, M Alejandra; Ivanova, Masha Y; Jacobus, Joanna; Jernigan, Terry L; Karcher, Nicole R; Laird, Angela R; LeBlanc, Kimberly H; Lisdahl, Krista; Luciana, Monica; Luna, Beatriz; Maes, Hermine H; Marshall, Andrew T; Mason, Michael J; McGlade, Erin C; Morris, Amanda S; Nagel, Bonnie J; Neigh, Gretchen N; Palmer, Clare E; Paulus, Martin P; Potter, Alexandra S; Puttler, Leon I; Rajapakse, Nishadi; Rapuano, Kristina; Reeves, Gloria; Renshaw, Perry F; Schirda, Claudiu; Sher, Kenneth J; Sheth, Chandni; Shilling, Paul D; Squeglia, Lindsay M; Sutherland, Matthew T; Tapert, Susan F; Tomko, Rachel L; Yurgelun-Todd, Deborah; Wade, Natasha E; Weiss, Susan R B; Zucker, Robert A; Sowell, Elizabeth RJanuary 1, 2020Not Determined
33676919Create StudyFailure to Identify Robust Latent Variables of Positive or Negative Valence Processing Across Units of Analysis.Biological psychiatry. Cognitive neuroscience and neuroimagingPeng, Yujia; Knotts, Jeffrey D; Taylor, Charles T; Craske, Michelle G; Stein, Murray B; Bookheimer, Susan; Young, Katherine S; Simmons, Alan N; Yeh, Hung-Wen; Ruiz, Julian; Paulus, Martin PMay 1, 2021Not Determined
33630070Create StudyAssociation Between Habitual Snoring and Cognitive Performance Among a Large Sample of Preadolescent Children.JAMA otolaryngology-- head & neck surgeryIsaiah, Amal; Ernst, Thomas; Cloak, Christine C; Clark, Duncan B; Chang, LindaMay 1, 2021Not Determined
33615640Create StudyEffects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs.Human brain mappingSønderby, Ida E; Ching, Christopher R K; Thomopoulos, Sophia I; van der Meer, Dennis; Sun, Daqiang; Villalon-Reina, Julio E; Agartz, Ingrid; Amunts, Katrin; Arango, Celso; Armstrong, Nicola J; Ayesa-Arriola, Rosa; Bakker, Geor; Bassett, Anne S; Boomsma, Dorret I; Bülow, Robin; Butcher, Nancy J; Calhoun, Vince D; Caspers, Svenja; Chow, Eva W C; Cichon, Sven; Ciufolini, Simone; Craig, Michael C; Crespo-Facorro, Benedicto; Cunningham, Adam C; Dale, Anders M; Dazzan, Paola; de Zubicaray, Greig I; Djurovic, Srdjan; Doherty, Joanne L; Donohoe, Gary; Draganski, Bogdan; Durdle, Courtney A; Ehrlich, Stefan; Emanuel, Beverly S; Espeseth, Thomas; Fisher, Simon E; Ge, Tian; Glahn, David C; Grabe, Hans J; Gur, Raquel E; Gutman, Boris A; Haavik, Jan; Håberg, Asta K; Hansen, Laura A; Hashimoto, Ryota; Hibar, Derrek P; Holmes, Avram J; Hottenga, Jouke-Jan; Hulshoff Pol, Hilleke E; Jalbrzikowski, Maria; Knowles, Emma E M; Kushan, Leila; Linden, David E J; Liu, Jingyu; Lundervold, Astri J; Martin-Brevet, Sandra; Martínez, Kenia; Mather, Karen A; Mathias, Samuel R; McDonald-McGinn, Donna M; McRae, Allan F; Medland, Sarah E; Moberget, Torgeir; Modenato, Claudia; Monereo Sánchez, Jennifer; Moreau, Clara A; Mühleisen, Thomas W; Paus, Tomas; Pausova, Zdenka; Prieto, Carlos; Ragothaman, Anjanibhargavi; Reinbold, Céline S; Reis Marques, Tiago; Repetto, Gabriela M; Reymond, Alexandre; Roalf, David R; Rodriguez-Herreros, Borja; Rucker, James J; Sachdev, Perminder S; Schmitt, James E; Schofield, Peter R; Silva, Ana I; Stefansson, Hreinn; Stein, Dan J; Tamnes, Christian K; Tordesillas-Gutiérrez, Diana; Ulfarsson, Magnus O; Vajdi, Ariana; van 't Ent, Dennis; van den Bree, Marianne B M; Vassos, Evangelos; Vázquez-Bourgon, Javier; Vila-Rodriguez, Fidel; Walters, G Bragi; Wen, Wei; Westlye, Lars T; Wittfeld, Katharina; Zackai, Elaine H; Stefánsson, Kári; Jacquemont, Sebastien; Thompson, Paul M; Bearden, Carrie E; Andreassen, Ole A; ENIGMA-CNV Working Group; ENIGMA 22q11.2 Deletion Syndrome Working GroupJanuary 1, 2022Not Determined
33607147Create StudyPromising vulnerability markers of substance use and misuse: A review of human neurobehavioral studies.NeuropharmacologyLees, Briana; Garcia, Alexis M; Debenham, Jennifer; Kirkland, Anna E; Bryant, Brittany E; Mewton, Louise; Squeglia, Lindsay MApril 1, 2021Not Determined
33585160Create StudyThe ups and downs of relating nondrug reward activation to substance use risk in adolescents.Current addiction reportsBjork, James MSeptember 1, 2020Not Determined
33556882Create StudyDecomposing complex links between the childhood environment and brain structure in school-aged youth.Developmental cognitive neuroscienceHong, Seok-Jun; Sisk, Lucinda M; Caballero, Camila; Mekhanik, Anthony; Roy, Amy K; Milham, Michael P; Gee, Dylan GApril 1, 2021Not Determined
33536880Create StudyRetaining Adolescent and Young Adult Participants in Research During a Pandemic: Best Practices From Two Large-Scale Developmental Neuroimaging Studies (NCANDA and ABCD).Frontiers in behavioral neuroscienceNooner, Kate B; Chung, Tammy; Feldstein Ewing, Sarah W; Brumback, Ty; Arwood, Zjanya; Tapert, Susan F; Brown, Sandra A; Cottler, LindaJanuary 1, 2020Not Determined
33529676Create StudyCaffeine exposure in utero is associated with structural brain alterations and deleterious neurocognitive outcomes in 9-10 year old children.NeuropharmacologyChristensen, Zachary P; Freedman, Edward G; Foxe, John JMarch 15, 2021Not Determined
33523708Create StudyInterpreting Interaction Effects in Generalized Linear Models of Nonlinear Probabilities and Counts.Multivariate behavioral researchMcCabe, Connor J; Halvorson, Max A; King, Kevin M; Cao, Xiaolin; Kim, Dale SFebruary 1, 2021Not Determined
33518499Create StudyDirect and Indirect Associations of Widespread Individual Differences in Brain White Matter Microstructure With Executive Functioning and General and Specific Dimensions of Psychopathology in Children.Biological psychiatry. Cognitive neuroscience and neuroimagingCardenas-Iniguez, Carlos; Moore, Tyler M; Kaczkurkin, Antonia N; Meyer, Francisco A C; Satterthwaite, Theodore D; Fair, Damien A; White, Tonya; Blok, Elisabet; Applegate, Brooks; Thompson, Lauren M; Rosenberg, Monica D; Hedeker, Donald; Berman, Marc G; Lahey, Benjamin BNovember 25, 2020Not Determined
33510046Create StudyBrain microstructure mediates sex-specific patterns of cognitive aging.AgingReas, Emilie T; Hagler, Donald J; Zhong, Allison J; Lee, Roland R; Dale, Anders M; McEvoy, Linda KJanuary 28, 2021Not Determined
33503481Create StudyLatent variables for region of interest activation during the monetary incentive delay task.NeuroImageWhite, Evan J; Kuplicki, Rayus; Stewart, Jennifer L; Kirlic, Namik; Yeh, Hung-Wen; T1000 Investigators; Paulus, Martin P; Aupperle, Robin LApril 15, 2021Not Determined
33495121Create StudyObsessive-Compulsive Symptoms Among Children in the Adolescent Brain and Cognitive Development Study: Clinical, Cognitive, and Brain Connectivity Correlates.Biological psychiatry. Cognitive neuroscience and neuroimagingPagliaccio, David; Durham, Katherine; Fitzgerald, Kate D; Marsh, RachelApril 1, 2021Not Determined
33479512Create StudyAssociation of gray matter volumes with general and specific dimensions of psychopathology in children.Neuropsychopharmacology : official publication of the American College of NeuropsychopharmacologyDurham, E Leighton; Jeong, Hee Jung; Moore, Tyler M; Dupont, Randolph M; Cardenas-Iniguez, Carlos; Cui, Zaixu; Stone, Farrah E; Berman, Marc G; Lahey, Benjamin B; Kaczkurkin, Antonia NJune 1, 2021Not Determined
33472387Create StudyMultimodal Neuroimaging of Suicidal Thoughts and Behaviors in a U.S. Population-Based Sample of School-Age Children.The American journal of psychiatryVidal-Ribas, Pablo; Janiri, Delfina; Doucet, Gaelle E; Pornpattananangkul, Narun; Nielson, Dylan M; Frangou, Sophia; Stringaris, ArgyrisApril 1, 2021Not Determined
33467473Create StudyTypologies of Family Functioning and 24-h Movement Behaviors.International journal of environmental research and public healthGuerrero, Michelle D; Barnes, Joel D; Tremblay, Mark S; Pulkki-Råback, LauraJanuary 15, 2021Not Determined
33462446Create StudyState-dependent responses to intracranial brain stimulation in a patient with depression.Nature medicineScangos, Katherine W; Makhoul, Ghassan S; Sugrue, Leo P; Chang, Edward F; Krystal, Andrew DFebruary 1, 2021Not Determined
33462190Create StudyMultimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study.Translational psychiatryOwens, Max M; Allgaier, Nicholas; Hahn, Sage; Yuan, DeKang; Albaugh, Matthew; Adise, Shana; Chaarani, Bader; Ortigara, Joseph; Juliano, Anthony; Potter, Alexandra; Garavan, HughJanuary 18, 2021Not Determined
33461315Create StudyAge and Sex Differences in the Associations of Pulse Pressure With White Matter and Subcortical Microstructure.Hypertension (Dallas, Tex. : 1979)Reas, Emilie T; Laughlin, Gail A; Hagler Jr, Donald J; Lee, Roland R; Dale, Anders M; McEvoy, Linda KMarch 3, 2021Not Determined
33447841Create StudyBoost in Test-Retest Reliability in Resting State fMRI with Predictive Modeling.Cerebral cortex (New York, N.Y. : 1991)Taxali, Aman; Angstadt, Mike; Rutherford, Saige; Sripada, ChandraMay 10, 2021Not Determined
33434614Create StudyRisk factors associated with curiosity about alcohol use in the ABCD cohort.Alcohol (Fayetteville, N.Y.)Wade, Natasha E; Palmer, Clare E; Gonzalez, Marybel R; Wallace, Alexander L; Infante, M Alejandra; Tapert, Susan F; Jacobus, Joanna; Bagot, Kara SMay 1, 2021Not Determined
33425663Create StudyNeurocognitive Correlates of Adolescent Cannabis Use: An Overview of Neural Activation Patterns in Task-Based Functional MRI Studies.Journal of pediatric neuropsychologyCoronado, Clarisa; Wade, Natasha E; Aguinaldo, Laika D; Mejia, Margie Hernandez; Jacobus, JoannaMarch 1, 2020Not Determined
33410532Create StudyTuber Locations Associated with Infantile Spasms Map to a Common Brain Network.Annals of neurologyCohen, Alexander L; Mulder, Brechtje P F; Prohl, Anna K; Soussand, Louis; Davis, Peter; Kroeck, Mallory R; McManus, Peter; Gholipour, Ali; Scherrer, Benoit; Bebin, E Martina; Wu, Joyce Y; Northrup, Hope; Krueger, Darcy A; Sahin, Mustafa; Warfield, Simon K; Fox, Michael D; Peters, Jurriaan M; Tuberous Sclerosis Complex Autism Center of Excellence Network Study GroupApril 1, 2021Not Determined
33369616Create StudyObesity and Eating Disorder Disparities Among Sexual and Gender Minority Youth.JAMA pediatricsSchvey, Natasha A; Pearlman, Arielle T; Klein, David A; Murphy, Mikela A; Gray, Joshua CApril 1, 2021Not Determined
33359407Create StudyRacial Disparities in Elementary School Disciplinary Actions: Findings From the ABCD Study.Journal of the American Academy of Child and Adolescent PsychiatryFadus, Matthew C; Valadez, Emilio A; Bryant, Brittany E; Garcia, Alexis M; Neelon, Brian; Tomko, Rachel L; Squeglia, Lindsay MAugust 1, 2021Not Determined
33335310Create StudyThe effects of FAAH inhibition on the neural basis of anxiety-related processing in healthy male subjects: a randomized clinical trial.Neuropsychopharmacology : official publication of the American College of NeuropsychopharmacologyPaulus, Martin P; Stein, Murray B; Simmons, Alan N; Risbrough, Victoria B; Halter, Robin; Chaplan, Sandra RApril 1, 2021Not Determined
33334432Create StudyThe Influence of Cannabis and Nicotine Co-use on Neuromaturation: A Systematic Review of Adolescent and Young Adult Studies.Biological psychiatryHernandez Mejia, Margie; Wade, Natasha E; Baca, Rachel; Diaz, Vanessa G; Jacobus, JoannaJanuary 15, 2021Not Determined
33325561Create StudyAltered hippocampal microstructure and function in children who experienced Hurricane Irma.Developmental psychobiologyConley, May I; Skalaban, Lena J; Rapuano, Kristina M; Gonzalez, Raul; Laird, Angela R; Dick, Anthony Steven; Sutherland, Matthew T; Watts, Richard; Casey, B JJuly 1, 2021Not Determined
33317053Create StudyParental Education, Household Income, and Cortical Surface Area among 9-10 Years Old Children: Minorities'' Diminished Returns.Brain sciencesAssari, ShervinDecember 9, 2020Not Determined
33309003Create StudyCorrigendum to "Behavioral and brain signatures of substance use vulnerability in childhood" [Developmental Cognitive Neuroscience 46 (December) (2020) 100878].Developmental cognitive neuroscienceRapuano, Kristina M; Rosenberg, Monica D; Maza, Maria T; Dennis, Nicholas J; Dorji, Mila; Greene, Abigail S; Horien, Corey; Scheinost, Dustin; Todd Constable, R; Casey, B JFebruary 1, 2021Not Determined
33299967Create StudyDimensional Change Card Sorting of American Children: Marginalization-Related Diminished Returns of Age.Children and teenagersAssari, ShervinJanuary 1, 2020Not Determined
33299959Create StudyFamily''s Subjective Economic Status and Children''s Matrix Reasoning: Blacks'' Diminished Returns.Research in health scienceAssari, Shervin; Boyce, ShanikaNovember 29, 2021Not Determined
33297546Create StudyParental Education, Household Income, Race, and Children''s Working Memory: Complexity of the Effects.Brain sciencesAkhlaghipour, Golnoush; Assari, ShervinDecember 7, 2020Not Determined
33294964Create StudyPsychotic Like Experiences are Associated with Suicide Ideation and Behavior in 9 to 10 Year Old Children in the United States.Research on child and adolescent psychopathologyGrattan, Rebecca E; Karcher, Nicole R; Maguire, Adrienne M; Hatch, Burt; Barch, Deanna M; Niendam, Tara AFebruary 1, 2021Not Determined
33294757Create StudyStronger Association between Nucleus Accumbens Density and Body Mass Index in Low-Income and African American Children.Research in health scienceAssari, ShervinJanuary 1, 2020Not Determined
33283124Create StudyRacial Variation in the Association between Childhood Depression and Frontal Pole Volume among American Children.Research in health scienceAssari, ShervinJanuary 1, 2020Not Determined
33282611Create StudyBrain Structure and Function in Recovery.Alcohol research : current reviewsNixon, Sara Jo; Lewis, BenJanuary 1, 2020Not Determined
33282415Create StudyAmerican Children''s Screen Time: Diminished Returns of Household Income in Black Families.Information (Basel)Assari, ShervinNovember 1, 2020Not Determined
33281105Create StudyAltered Neurocognitive Functional Connectivity and Activation Patterns Underlie Psychopathology in Preadolescence.Biological psychiatry. Cognitive neuroscience and neuroimagingLees, Briana; Squeglia, Lindsay M; McTeague, Lisa M; Forbes, Miriam K; Krueger, Robert F; Sunderland, Matthew; Baillie, Andrew J; Koch, Forrest; Teesson, Maree; Mewton, LouiseApril 1, 2021Not Determined
33274304Create StudyAge-Related Decline in Children''s Reward Sensitivity: Blacks'' Diminished Returns.Research in health scienceAssari, ShervinJanuary 1, 2020Not Determined
33259511Create StudyAssociation between brain morphometry and aerobic fitness level and sex in healthy emerging adults.PloS oneWade, Natasha E; Wallace, Alexander L; Sullivan, Ryan M; Swartz, Ann M; Lisdahl, Krista MJanuary 1, 2020Not Determined
33251336Create StudyParental Human Capital and Adolescents'' Executive Function: Immigrants'' Diminished Returns.Medical research archivesAssari, Shervin; Akhlaghipour, Golnoush; Boyce, Shanika; Bazargan, Mohsen; Caldwell, Cleopatra HOctober 1, 2020Not Determined
33241770Create StudyFalse positive rates in positron emission tomography (PET) voxelwise analyses.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and MetabolismGanz, Melanie; Nørgaard, Martin; Beliveau, Vincent; Svarer, Claus; Knudsen, Gitte M; Greve, Douglas NJuly 1, 2021Not Determined
33241232Create StudyPrefrontal Cortex Response to Threat: Race by Age Variation in 9-10 Year Old Children.Journal of mental health & clinical psychologyAssari, Shervin; Akhlaghipour, Golnoush; Saqib, Mohammed; Boyce, Shanika; Bazargan, MohsenJanuary 1, 2020Not Determined
33241230Create StudyDiminished Protective Effects of Household Income on Internalizing Symptoms among African American than European American Pre-Adolescents.Journal of economics, trade and marketing managementAssari, Shervin; Islam, SondosJanuary 1, 2020Not Determined
33241229Create StudySex Differences in the Association between Cortical Thickness and Children''s Behavioral Inhibition.Journal of psychology & behavior researchAssari, ShervinJanuary 1, 2020Not Determined
33238925Create StudyScreen media activity does not displace other recreational activities among 9-10 year-old youth: a cross-sectional ABCD study®.BMC public healthLees, Briana; Squeglia, Lindsay M; Breslin, Florence J; Thompson, Wesley K; Tapert, Susan F; Paulus, Martin PNovember 25, 2020Not Determined
33233814Create StudyMental Rotation in American Children: Diminished Returns of Parental Education in Black Families.Pediatric reportsAssari, ShervinNovember 20, 2020Not Determined
33229246Create StudyAssociations Between Resting-State Functional Connectivity and a Hierarchical Dimensional Structure of Psychopathology in Middle Childhood.Biological psychiatry. Cognitive neuroscience and neuroimagingKarcher, Nicole R; Michelini, Giorgia; Kotov, Roman; Barch, Deanna MMay 1, 2021Not Determined
33229052Create StudyProblems experienced by children from families with histories of substance misuse: An ABCD study®.Drug and alcohol dependenceLees, Briana; Stapinski, Lexine A; Teesson, Maree; Squeglia, Lindsay M; Jacobus, Joanna; Mewton, LouiseJanuary 1, 2021Not Determined
33215166Create StudySocioeconomic Status Inequalities Partially Mediate Racial and Ethnic Differences in Children''s Amygdala Volume.Studies in social science researchAssari, ShervinJanuary 1, 2020Not Determined
33215045Create StudySocial Determinants of Delayed Gratification among American Children.Caspian journal of neurological sciencesAssari, ShervinJanuary 1, 2020Not Determined
33192411Create StudyPositive Economic, Psychosocial, and Physiological Ecologies Predict Brain Structure and Cognitive Performance in 9-10-Year-Old Children.Frontiers in human neuroscienceGonzalez, Marybel Robledo; Palmer, Clare E; Uban, Kristina A; Jernigan, Terry L; Thompson, Wesley K; Sowell, Elizabeth RJanuary 1, 2020Not Determined
33181393Create StudyBehavioral and brain signatures of substance use vulnerability in childhood.Developmental cognitive neuroscienceRapuano, Kristina M; Rosenberg, Monica D; Maza, Maria T; Dennis, Nicholas J; Dorji, Mila; Greene, Abigail S; Horien, Corey; Scheinost, Dustin; Todd Constable, R; Casey, B JDecember 1, 2020Not Determined
33176359Create StudyDisentangling vulnerability, state and trait features of neurocognitive impairments in depression.Brain : a journal of neurologyAng, Yuen-Siang; Frontero, Nicole; Belleau, Emily; Pizzagalli, Diego ADecember 1, 2020Not Determined
33163908Create StudyRacial Variation in the Association between Suicidal History and Positive and Negative Urgency among American Children.Journal of education and culture studiesAssari, ShervinJanuary 1, 2020Not Determined
33163684Create StudySex Differences in the Association between Household Income and Children''s Executive Function.SexesAssari, Shervin; Boyce, Shanika; Bazargan, Mohsen; Caldwell, Cleopatra HowardDecember 1, 2020Not Determined
33152602Create StudyDetect and correct bias in multi-site neuroimaging datasets.Medical image analysisWachinger, Christian; Rieckmann, Anna; Pölsterl, Sebastian; Alzheimer’s Disease Neuroimaging Initiative and the Australian Imaging Biomarkers and Lifestyle flagship study of ageingJanuary 1, 2021Not Determined
33150523Create StudyUsing Multimodel Inference/Model Averaging to Model Causes of Covariation Between Variables in Twins.Behavior geneticsMaes, Hermine H; Neale, Michael C; Kirkpatrick, Robert M; Kendler, Kenneth SJanuary 1, 2021Not Determined
33145600Create StudyIndividual Differences in Cognitive Performance Are Better Predicted by Global Rather Than Localized BOLD Activity Patterns Across the Cortex.Cerebral cortex (New York, N.Y. : 1991)Zhao, Weiqi; Palmer, Clare E; Thompson, Wesley K; Chaarani, Bader; Garavan, Hugh P; Casey, B J; Jernigan, Terry L; Dale, Anders M; Fan, Chun ChiehFebruary 5, 2021Not Determined
33141160Create StudyAssessment of Neighborhood Poverty, Cognitive Function, and Prefrontal and Hippocampal Volumes in Children.JAMA network openTaylor, Rita L; Cooper, Shelly R; Jackson, Joshua J; Barch, Deanna MNovember 2, 2020Not Determined
33127479Create StudyLearning Clique Subgraphs in Structural Brain Network Classification with Application to Crystallized Cognition.NeuroImageWang, Lu; Lin, Feng Vankee; Cole, Martin; Zhang, ZhengwuJanuary 15, 2021Not Determined
33123624Create StudyYouth Social, Emotional, and Behavioral Problems in the ABCD Study: Minorities'' Diminished Returns of Family Income.Journal of economics and public financeAssari, ShervinJanuary 1, 2020Not Determined
33109338Create StudyMultivariate Patterns of Brain-Behavior-Environment Associations in the Adolescent Brain and Cognitive Development Study.Biological psychiatryModabbernia, Amirhossein; Janiri, Delfina; Doucet, Gaelle E; Reichenberg, Abraham; Frangou, SophiaMarch 1, 2021Not Determined
33103279Create StudyUsing the MoBI motion capture system to rapidly and accurately localize EEG electrodes in anatomic space.The European journal of neuroscienceMazurek, Kevin A; Patelaki, Eleni; Foxe, John J; Freedman, Edward GDecember 1, 2021Not Determined
33103157Create StudySubjective Socioeconomic Status and Children''s Amygdala Volume: Minorities'' Diminish Returns.NeuroSciAssari, Shervin; Boyce, Shanika; Bazargan, MohsenDecember 1, 2020Not Determined
33103023Create StudyRace, Ethnicity, Family Socioeconomic Status, and Children''s Hippocampus Volume.Research in health scienceAssari, ShervinJanuary 1, 2020Not Determined
33096046Create StudyA large-scale genome-wide association study meta-analysis of cannabis use disorder.The lancet. PsychiatryJohnson, Emma C; Demontis, Ditte; Thorgeirsson, Thorgeir E; Walters, Raymond K; Polimanti, Renato; Hatoum, Alexander S; Sanchez-Roige, Sandra; Paul, Sarah E; Wendt, Frank R; Clarke, Toni-Kim; Lai, Dongbing; Reginsson, Gunnar W; Zhou, Hang; He, June; Baranger, David A A; Gudbjartsson, Daniel F; Wedow, Robbee; Adkins, Daniel E; Adkins, Amy E; Alexander, Jeffry; Bacanu, Silviu-Alin; Bigdeli, Tim B; Boden, Joseph; Brown, Sandra A; Bucholz, Kathleen K; Bybjerg-Grauholm, Jonas; Corley, Robin P; Degenhardt, Louisa; Dick, Danielle M; Domingue, Benjamin W; Fox, Louis; Goate, Alison M; Gordon, Scott D; Hack, Laura M; Hancock, Dana B; Hartz, Sarah M; Hickie, Ian B; Hougaard, David M; Krauter, Kenneth; Lind, Penelope A; McClintick, Jeanette N; McQueen, Matthew B; Meyers, Jacquelyn L; Montgomery, Grant W; Mors, Ole; Mortensen, Preben B; Nordentoft, Merete; Pearson, John F; Peterson, Roseann E; Reynolds, Maureen D; Rice, John P; Runarsdottir, Valgerdur; Saccone, Nancy L; Sherva, Richard; Silberg, Judy L; Tarter, Ralph E; Tyrfingsson, Thorarinn; Wall, Tamara L; Webb, Bradley T; Werge, Thomas; Wetherill, Leah; Wright, Margaret J; Zellers, Stephanie; Adams, Mark J; Bierut, Laura J; Boardman, Jason D; Copeland, William E; Farrer, Lindsay A; Foroud, Tatiana M; Gillespie, Nathan A; Grucza, Richard A; Harris, Kathleen Mullan; Heath, Andrew C; Hesselbrock, Victor; Hewitt, John K; Hopfer, Christian J; Horwood, John; Iacono, William G; Johnson, Eric O; Kendler, Kenneth S; Kennedy, Martin A; Kranzler, Henry R; Madden, Pamela A F; Maes, Hermine H; Maher, Brion S; Martin, Nicholas G; McGue, Matthew; McIntosh, Andrew M; Medland, Sarah E; Nelson, Elliot C; Porjesz, Bernice; Riley, Brien P; Stallings, Michael C; Vanyukov, Michael M; Vrieze, Scott; Psychiatric Genomics Consortium Substance Use Disorders Workgroup; Davis, Lea K; Bogdan, Ryan; Gelernter, Joel; Edenberg, Howard J; Stefansson, Kari; Børglum, Anders D; Agrawal, ArpanaDecember 1, 2020Not Determined
33046629Create StudyNucleus accumbens cytoarchitecture predicts weight gain in children.Proceedings of the National Academy of Sciences of the United States of AmericaRapuano, Kristina M; Laurent, Jennifer S; Hagler Jr, Donald J; Hatton, Sean N; Thompson, Wesley K; Jernigan, Terry L; Dale, Anders M; Casey, B J; Watts, RichardOctober 27, 2020Not Determined
33043878Create StudyIncipient Alcohol Use in Childhood: Early Alcohol Sipping and its Relations with Psychopathology and Personality - Corrigendum.Development and psychopathologyWatts, Ashley L; Wood, Phillip K; Jackson, Kristina M; Lisdahl, Krista M; Heitzeg, Mary M; Gonzalez, Raul; Tapert, Susan F; Barch, Deanna M; Sher, Kenneth JAugust 1, 2021Not Determined
32985363Create StudySuicide Ideation and Neurocognition Among 9- and 10-Year Old Children in the Adolescent Brain Cognitive Development (ABCD) Study.Archives of suicide research : official journal of the International Academy for Suicide ResearchHuber, Rebekah S; Sheth, Chandni; Renshaw, Perry F; Yurgelun-Todd, Deborah A; McGlade, Erin CSeptember 28, 2020Not Determined
32976083Create StudyEffective Velopharyngeal Ratio: A More Clinically Relevant Measure of Velopharyngeal Function.Journal of speech, language, and hearing research : JSLHRHaenssler, Abigail E; Fang, Xiangming; Perry, Jamie LNovember 13, 2020Not Determined
32972200Create StudyAssociation of Prenatal Alcohol Exposure With Psychological, Behavioral, and Neurodevelopmental Outcomes in Children From the Adolescent Brain Cognitive Development Study.The American journal of psychiatryLees, Briana; Mewton, Louise; Jacobus, Joanna; Valadez, Emilio A; Stapinski, Lexine A; Teesson, Maree; Tapert, Susan F; Squeglia, Lindsay MNovember 1, 2020Not Determined
32971390Create StudyMarital status, partner acknowledgment of paternity, and neighborhood influences on smoking during first pregnancy: findings across race/ethnicity in linked administrative and census data.Drug and alcohol dependenceHouston-Ludlam, Alexandra N; Waldron, Mary; Lian, Min; Cahill, Alison G; McCutcheon, Vivia V; Madden, Pamela A F; Bucholz, Kathleen K; Heath, Andrew CDecember 1, 2020Not Determined
32965490Create StudyAssociations Between Prenatal Cannabis Exposure and Childhood Outcomes: Results From the ABCD Study.JAMA psychiatryPaul, Sarah E; Hatoum, Alexander S; Fine, Jeremy D; Johnson, Emma C; Hansen, Isabella; Karcher, Nicole R; Moreau, Allison L; Bondy, Erin; Qu, Yueyue; Carter, Ebony B; Rogers, Cynthia E; Agrawal, Arpana; Barch, Deanna M; Bogdan, RyanJanuary 1, 2021Not Determined
32897083Create StudyNeuroanatomical correlates of impulsive traits in children aged 9 to 10.Journal of abnormal psychologyOwens, Max M; Hyatt, Courtland S; Gray, Joshua C; Miller, Joshua D; Lynam, Donald R; Hahn, Sage; Allgaier, Nicholas; Potter, Alexandra; Garavan, HughNovember 1, 2020Not Determined
32886714Create StudyPerformance of a commercial multi-sensor wearable (Fitbit Charge HR) in measuring physical activity and sleep in healthy children.PloS oneGodino, Job G; Wing, David; de Zambotti, Massimiliano; Baker, Fiona C; Bagot, Kara; Inkelis, Sarah; Pautz, Carina; Higgins, Michael; Nichols, Jeanne; Brumback, Ty; Chevance, Guillaume; Colrain, Ian M; Patrick, Kevin; Tapert, Susan FJanuary 1, 2020Not Determined
32861729Create StudyScreen media use and sleep disturbance symptom severity in children.Sleep healthHisler, Garrett C; Hasler, Brant P; Franzen, Peter L; Clark, Duncan B; Twenge, Jean MDecember 1, 2020Not Determined
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31648682Create StudyErratum.Biological psychiatryNovember 15, 2019Not Determined
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31634568Study (868)Brain Volume Abnormalities in Youth at High Risk for Depression: Adolescent Brain and Cognitive Development Study.Journal of the American Academy of Child and Adolescent PsychiatryPagliaccio, David; Alqueza, Kira L; Marsh, Rachel; Auerbach, Randy POctober 2020Not Determined
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29311006Create StudyThe adolescent brain cognitive development study external advisory board.Developmental cognitive neuroscienceCharness, Michael EAugust 2018Not Determined
29198276Create StudyDoes Cannabis Use Cause Declines in Neuropsychological Functioning? A Review of Longitudinal Studies.Journal of the International Neuropsychological Society : JINSGonzalez, Raul; Pacheco-Colón, Ileana; Duperrouzel, Jacqueline C; Hawes, Samuel WOctober 2017Not Determined
29197573Create StudyDevelopment of the emotional brain.Neuroscience lettersCasey BJ, Heller AS, Gee DG, Cohen AODecember 2017Not Determined
29182012Create StudyValidating Online Measures of Cognitive Ability in Genes for Good, a Genetic Study of Health and Behavior.AssessmentLiu, MengZhen; Rea-Sandin, Gianna; Foerster, Johanna; Fritsche, Lars; Brieger, Katharine; Clark, Christopher; Li, Kevin; Pandit, Anita; Zajac, Gregory; Abecasis, Gonçalo R; Vrieze, ScottJanuary 2020Not Determined
29150307Create StudyApproaching Retention within the ABCD Study.Developmental cognitive neuroscienceFeldstein Ewing, Sarah W; Chang, Linda; Cottler, Linda B; Tapert, Susan F; Dowling, Gayathri J; Brown, Sandra AAugust 2018Not Determined
29113758Create StudyDemographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description.Developmental cognitive neuroscienceBarch, Deanna M; Albaugh, Matthew D; Avenevoli, Shelli; Chang, Linda; Clark, Duncan B; Glantz, Meyer D; Hudziak, James J; Jernigan, Terry L; Tapert, Susan F; Yurgelun-Todd, Debbie; Alia-Klein, Nelly; Potter, Alexandra S; Paulus, Martin P; Prouty, Devin; Zucker, Robert A; Sher, Kenneth JAugust 2018Not Determined
29107609Create StudyThe utility of twins in developmental cognitive neuroscience research: How twins strengthen the ABCD research design.Developmental cognitive neuroscienceIacono, William G; Heath, Andrew C; Hewitt, John K; Neale, Michael C; Banich, Marie T; Luciana, Monica M; Madden, Pamela A; Barch, Deanna M; Bjork, James MAugust 2018Not Determined
29051027Create StudyThe conception of the ABCD study: From substance use to a broad NIH collaboration.Developmental cognitive neuroscienceVolkow, Nora D; Koob, George F; Croyle, Robert T; Bianchi, Diana W; Gordon, Joshua A; Koroshetz, Walter J; Pérez-Stable, Eliseo J; Riley, William T; Bloch, Michele H; Conway, Kevin; Deeds, Bethany G; Dowling, Gayathri J; Grant, Steven; Howlett, Katia D; Matochik, John A; Morgan, Glen D; Murray, Margaret M; Noronha, Antonio; Spong, Catherine Y; Wargo, Eric M; Warren, Kenneth R; Weiss, Susan R BAugust 2018Not Determined
29038777Create StudyThe ABCD study of neurodevelopment: Identifying neurocircuit targets for prevention and treatment of adolescent substance abuse.Current treatment options in psychiatryBjork, James M; Straub, Lisa K; Provost, Rosellen G; Neale, Michael CJune 2017Not Determined
28935096Create StudyThe Effect of Acute Stress on the Calculus of Reward and Punishment.Biological psychiatryPaulus MPOctober 2017Not Determined
28900686Create StudyChanges in marijuana use symptoms and emotional functioning over 28-days of monitored abstinence in adolescent marijuana users.PsychopharmacologyJacobus, Joanna; Squeglia, Lindsay M; Escobar, Silvia; McKenna, Benjamin M; Hernandez, Margie Mejia; Bagot, Kara S; Taylor, Charles T; Huestis, Marilyn ADecember 2017Not Determined
28868337Create StudyThe adolescent brain at risk for substance use disorders: a review of functional MRI research on motor response inhibition.Current opinion in behavioral sciencesKoyama, Maki S; Parvaz, Muhammad A; Goldstein, Rita ZFebruary 2017Not Relevant
28838468Create StudyComputational Dysfunctions in Anxiety: Failure to Differentiate Signal From Noise.Biological psychiatryHuang H, Thompson W, Paulus MPSeptember 2017Not Determined
28828560Create StudyLinking tuberous sclerosis complex, excessive mTOR signaling, and age-related neurodegeneration: a new association between TSC1 mutation and frontotemporal dementia.Acta neuropathologicaOlney, Nicholas T; Alquezar, Carolina; Ramos, Eliana Marisa; Nana, Alissa L; Fong, Jamie C; Karydas, Anna M; Taylor, Joanne B; Stephens, Melanie L; Argouarch, Andrea R; Van Berlo, Victoria A; Dokuru, Deepika R; Sherr, Elliott H; Jicha, Gregory A; Dillon, William P; Desikan, Rahul S; De May, Mary; Seeley, William W; Coppola, Giovanni; Miller, Bruce L; Kao, Aimee WNovember 2017Not Relevant
28803940Create StudyReal-time motion analytics during brain MRI improve data quality and reduce costs.NeuroImageDosenbach NUF, Koller JM, Earl EA, Miranda-Dominguez O, Klein RL, Van AN, Snyder AZ, Nagel BJ, Nigg JT, Nguyen AL, Wesevich V, Greene DJ, Fair DANovember 2017Not Determined
28779616Create StudyPhenotypic and familial associations between childhood maltreatment and cannabis initiation and problems in young adult European-American and African-American women.Drug and alcohol dependenceGrant, Julia D; Agrawal, Arpana; Werner, Kimberly B; McCutcheon, Vivia V; Nelson, Elliot C; Madden, Pamela A F; Bucholz, Kathleen K; Heath, Andrew C; Sartor, Carolyn EOctober 2017Not Relevant
28716389Create StudyBiomedical ethics and clinical oversight in multisite observational neuroimaging studies with children and adolescents: The ABCD experience.Developmental cognitive neuroscienceClark, Duncan B; Fisher, Celia B; Bookheimer, Susan; Brown, Sandra A; Evans, John H; Hopfer, Christian; Hudziak, James; Montoya, Ivan; Murray, Margaret; Pfefferbaum, Adolf; Yurgelun-Todd, DeborahAugust 2018Not Determined
28714184Create StudyResearch Review: What have we learned about adolescent substance use?Journal of child psychology and psychiatry, and allied disciplinesGray KM, Squeglia LMJuly 2017Not Determined
28641131Create StudyChildren's brain activation during risky decision-making: A contributor to substance problems?Drug and alcohol dependenceCrowley TJ, Dalwani MS, Sakai JT, Raymond KM, Mcwilliams SK, Banich MT, Mikulich-Gilbertson SKJune 2017Not Relevant
28438513Create StudyRapid-Response Impulsivity Predicts Depression and Posttraumatic Stress Disorder Symptomatology at 1-Year Follow-Up in Blast-Exposed Service Members.Archives of physical medicine and rehabilitationBjork JM, Burroughs TK, Franke LM, Pickett TC, Johns SE, Moeller FG, Walker WCAugust 2017Not Determined
28279988Create StudyEntorhinal Cortex: Antemortem Cortical Thickness and Postmortem Neurofibrillary Tangles and Amyloid Pathology.AJNR. American journal of neuroradiologyThaker, A A; Weinberg, B D; Dillon, W P; Hess, C P; Cabral, H J; Fleischman, D A; Leurgans, S E; Bennett, D A; Hyman, B T; Albert, M S; Killiany, R J; Fischl, B; Dale, A M; Desikan, R SMay 2017Not Determined
28271184Create StudyShared genetic risk between corticobasal degeneration, progressive supranuclear palsy, and frontotemporal dementia.Acta neuropathologicaYokoyama JS, Karch CM, Fan CC, Bonham LW, Kouri N, Ross OA, Rademakers R, Kim J, Wang Y, Höglinger GU, Müller U, Ferrari R, Hardy J, Momeni P, Sugrue LP, Hess CP, James Barkovich A, Boxer AL, Seeley WW, Rabinovici GD, Rosen HJ, Miller BL, Schmansky NJ, Fischl B, et al.March 2017Not Relevant
28161313Create StudyDevelopment of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature.NeuroImageGrayson, David S; Fair, Damien AOctober 2017Not Determined
28018986Create StudyA Roadmap for the Development of Applied Computational Psychiatry.Biological psychiatry : cognitive neuroscience and neuroimagingPaulus MP, Huys QJ, Maia TVSeptember 2016Not Relevant
27995817Create StudyPsychophysiological endophenotypes to characterize mechanisms of known schizophrenia genetic loci.Psychological medicineLiu M, Malone SM, Vaidyanathan U, Keller MC, Abecasis G, Mcgue M, Iacono WG, Vrieze SIDecember 2016Not Relevant
27899424Create StudyGenetic architecture of sporadic frontotemporal dementia and overlap with Alzheimer''s and Parkinson''s diseases.Journal of neurology, neurosurgery, and psychiatryFerrari, Raffaele; Wang, Yunpeng; Vandrovcova, Jana; Guelfi, Sebastian; Witeolar, Aree; Karch, Celeste M; Schork, Andrew J; Fan, Chun C; Brewer, James B; International FTD-Genomics Consortium (IFGC),; International Parkinson's Disease Genomics Consortium (IPDGC),; International Genomics of Alzheimer's Project (IGAP),; Momeni, Parastoo; Schellenberg, Gerard D; Dillon, William P; Sugrue, Leo P; Hess, Christopher P; Yokoyama, Jennifer S; Bonham, Luke W; Rabinovici, Gil D; Miller, Bruce L; Andreassen, Ole A; Dale, Anders M; Hardy, John; Desikan, Rahul SFebruary 2017Not Relevant
27862206Create StudyMalformations of cortical development.Annals of neurologyDesikan RS, Barkovich AJDecember 2016Not Relevant
27774503Create StudyIs biological aging accelerated in drug addiction?Current opinion in behavioral sciencesBachi, Keren; Sierra, Salvador; Volkow, Nora D; Goldstein, Rita Z; Alia-Klein, NellyFebruary 2017Not Relevant
27739397Create StudyNeural predictors of alcohol use and psychopathology symptoms in adolescents.Development and psychopathologyBrumback TY, Worley M, Nguyen-Louie TT, Squeglia LM, Jacobus J, Tapert SFNovember 2016Not Determined
27539487Create StudyNeural Predictors of Initiating Alcohol Use During Adolescence.The American journal of psychiatrySqueglia LM, Ball TM, Jacobus J, Brumback T, Mckenna BS, Nguyen-Louie TT, Sorg SF, Paulus MP, Tapert SFAugust 2016Not Determined
27503447Create StudyEffects of Marijuana Use on Brain Structure and Function: Neuroimaging Findings from a Neurodevelopmental Perspective.International review of neurobiologyBrumback T, Castro N, Jacobus J, Tapert SJanuary 2016Not Relevant
27408790Create StudyRecreational marijuana use impacts white matter integrity and subcortical (but not cortical) morphometry.NeuroImage. ClinicalOrr JM, Paschall CJ, Banich MTJanuary 2016Not Determined
27288319Create StudyNeuroimaging cognitive reappraisal in clinical populations to define neural targets for enhancing emotion regulation. A systematic review.NeuroImageZilverstand A, Parvaz MA, Goldstein RZJune 2016Not Relevant
27175326Create StudyComorbid Cannabis and Tobacco Use in Adolescents and Adults.Current addiction reportsSubramaniam, Punitha; McGlade, Erin; Yurgelun-Todd, DeborahJune 2016Not Relevant
27001846Create StudyIndividual differences in frontolimbic circuitry and anxiety emerge with adolescent changes in endocannabinoid signaling across species.Proceedings of the National Academy of Sciences of the United States of AmericaGee DG, Fetcho RN, Jing D, Li A, Glatt CE, Drysdale AT, Cohen AO, Dellarco DV, Yang RR, Dale AM, Jernigan TL, Lee FS, Casey BJ, April 2016Not Determined

Relevant Publications
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You can use "Add New Data Expected" to add exsiting structures and create your project's list. However, this is also the method you can use to request new structures be created for your project. When adding the Data Expected item, if the structure already exists you can locate it and specify your dates and enrollment. To add a new structure and request it be defined in the Data Dictionary, select Upload Definition and attach the definition or material needed to create it, including manual, codebooks, forms, etc. If you have multiple files, please upload a zipped archive containing them all.

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Data Expected
Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
Genomics/omics info icon
10,69904/24/2017
10,217
Approved
Processed MRI Data info icon
11,50001/15/2018
11,821
Approved
Evaluated Data info icon
11,50001/15/2018
11,857
Approved
Imaging (Structural, fMRI, DTI, PET, microscopy) info icon
11,50004/24/2017
11,819
Approved
Wearable Data info icon
15004/24/2017
7,032
Approved
Task Based info icon
4,52401/15/2018
0
Approved
ABCD Med History Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Questionnaire Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Task Based Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Substance Use Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Social Adjustment Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Phys Exam Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Diagnostic Measures info icon
11,50001/15/2018
11,876
Approved
ABCD PTSD Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Sleep Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Activity Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Socioeconomic Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Personality Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Behavior Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Parenting Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Trauma Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Phys Characteristics Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Demographics Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Cognitive Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Summary Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Treatment Measures info icon
11,50001/15/2018
11,876
Approved
ABCD Psychosis Measures info icon
11,50001/15/2018
11,876
Approved
Structure not yet defined
No Status history for this Data Expected has been recorded yet

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Associated Studies

Studies that have been defined using data from a Collection are important criteria to determine the value of data shared. The number of subjects column displays the counts from this Collection that are included in a Study, out of the total number of subjects in that study. The Data Use column represents whether or not the study is a primary analysis of the data or a secondary analysis. State indicates whether the study is private or shared with the research community.

Study NameAbstractCollection/Study SubjectsData UsageState
Diffusion Basis Spectrum Imaging Neuroinflammation Metrics in AdolescentsHuman obesity is related to alterations in brain structure and function. Rodent models of obesity show that diet-induced obesity causes neuroinflammation and impairment in learning and memory. In humans, non-invasive measurement of putative neuroinflammation is accomplished with diffusion-based magnetic resonance (MR) imaging. We have shown that, relative to normal-weight, obese adults have greater putative neuroinflammation, including indicators of cellularity and vasogenic edema, using diffusion basis spectrum imaging (DBSI) to model anisotropic and isotropic water diffusion in white matter tracts and regions of interest including hippocampus. Characterization of relationships between adiposity and brain structure and function in adolescents may provide insight into mechanisms underlying development of chronic overfeeding and obesity. Recently, Rapuano et al. (2020) used diffusion-based restricted spectrum imaging (RSI) to quantify putative neuroinflammation in reward-related brain regions in a large sample of 9 and 10 year old children enrolled in the Adolescent Brain Cognitive Development (ABCD) multi-site study and found that greater cellular density in the nucleus accumbens related to higher body mass index (BMI) and waist circumference at baseline and 1 year after MR imaging. We compared DBSI-measured putative neuroinflammation to those of RSI by selecting a sample of 9 and 10 year old children enrolled in the ABCD study representing a wide range of BMI categories (n=200 normal-weight; 50 overweight; 50 obese) and based on effect sizes and inclusion and exclusion criteria in the Rapuano et al. (2020) study. We hypothesize that greater neuroinflammation, as measured by DBSI, in white matter tracts and reward-related brain regions will relate to higher BMI and waist circumference at baseline and 1 year after MR imaging. Findings from the current study will provide insight into whether two different diffusion-based models yield convergent evidence regarding neuroinflammation and its relationship to adiposity in adolescents. 11848/13751Secondary AnalysisPrivate
Associations Between Resting State Functional Connectivity and a Hierarchical Dimensional Structure of Psychopathology in Middle ChildhoodBackground: Previous research from the Adolescent Brain Cognitive Development℠ (ABCD) study delineated and validated a hierarchical 5-factor structure with a general psychopathology (‘p’) factor at the apex and five specific factors (internalizing, somatoform, detachment, neurodevelopmental, externalizing) using parent-reported child symptoms. The current study is the first examining associations between dimensions from a hierarchical structure and resting state functional connectivity (RSFC) networks. Methods: Using 9-11-year-old children from the ABCD Study® baseline sample, we examined the variance explained by each hierarchical structure level (p-factor, 2-factor, 3-factor, 4-factor, and 5-factor models) in associations with RSFC. Analyses were first conducted in a discovery dataset (n=3790) with significant associations examined in a replication dataset (n=3791). Results: The current study found robust associations between p-factor and lower connectivity within default mode network (DMN), although stronger effects emerged for the neurodevelopmental factor. Neurodevelopmental impairments were also related to variation in RSFC networks associated with attention to internal states and external stimuli. Analyses revealed robust associations within DMN, DMN with cingulo-opercular (CON) and ‘Other’ (Unassigned) networks, and dorsal attention with ‘Other’ network. Conclusion: The hierarchical structure of psychopathology showed replicable links to RSFC alterations in middle childhood. The specific neurodevelopmental dimension showed robust associations with multiple RSFC impairments. Results show the utility of examining associations between intrinsic brain architecture and specific dimensions of psychopathology, revealing associations especially with neurodevelopmental impairments. 11878/11898Secondary AnalysisPrivate
Environmental Risk Factors and Psychotic-like Symptoms in Children Aged 9-11Objective: Research implicates environmental risk factors, including correlates of urbanicity, deprivation, and environmental toxins, in psychotic-like experiences (PLEs). The current study examined associations between several types of environmental risk factors and PLEs in school-age children, whether these associations were specific to PLEs or generalized to other psychopathology, and examined possible neural mechanisms for significant associations. Method: The current study used data from 10,328 9-11-year-olds from the Adolescent Brain Cognitive Development (ABCD) study. Hierarchical linear models examined associations between PLEs and geocoded environmental risk factors, and whether associations generalized to internalizing/externalizing symptoms. Mediation models examined whether structural MRI abnormalities (e.g., intracranial volume) mediated associations between PLEs and environmental risk factors. Results: The results found specific types of environmental risk factors, namely measures of urbanicity (i.e., drug offense exposure, less perception of neighborhood safety), deprivation (including overall deprivation, rate of poverty, fewer years at residence), and lead exposure risk, were associated with PLEs. These associations showed evidence of stronger associations with PLEs than internalizing/externalizing symptoms (especially overall deprivation, poverty, drug offense exposure, and lead exposure risk). There was evidence that brain volume mediated between 11-25% of the associations between poverty, perception of neighborhood safety, and lead exposure risk with PLEs. Conclusions: These results are the first to find support for neural measures partially mediating the association between PLEs and environmental exposures. Furthermore, the current study replicated and extended recent findings of the association between PLEs and environmental exposures, finding evidence for specific associations with correlates of urbanicity, deprivation, and lead exposure risk. 11879/11898Secondary AnalysisPrivate
Morphometry of the lateral orbitofrontal cortex is associated with eating dispositions in early adolescence: findings from a large population-based studyEarly adolescence is a critical period for eating behaviors as children gain autonomy around food choice and peer influences increase in potency. From a neurodevelopmental perspective, significant structural changes take place in the prefrontal cortex during this time, including the orbitofrontal cortex (OFC), which is involved in socially contextualized decision-making. We examined the morphological features of the OFC in relation to food choice in a sample of 10 309 early adolescent children from the Adolescent Brain and Cognitive Development Study. Structural parameters of the OFC and insula were examined for relationships with two important aspects of food choice: limiting the consumption of fast/fried food and maximizing the consumption of nutritious foods. Raw, partially adjusted and fully adjusted models were evaluated. Findings revealed that a larger surface area of the lateral OFC was associated with higher odds of limiting fast/fried food consumption in raw [odds ratio (OR) = 1.07, confidence interval (CI): 1.02, 1.12, P = 0.002, PFDR = 0.012], partially adjusted (OR = 1.11, CI: 1.03, 1.19, P = 0.004, PFDR = 0.024) and fully adjusted models (OR = 1.11, CI: 1.03, 1.19, P = 0.006, PFDR = 0.036). In contrast, a larger insula volume was associated with lower odds of maximizing healthy foods in raw (OR = 0.94, CI: 0.91, 0.97, P <0.001, PFDR = 0.003) and partially adjusted (OR = 0.93, CI: 0.88, 0.98, P = 0.008, PFDR = 0.048) models. These findings refine our understanding of the OFC as a network node implicated in socially mediated eating behaviors.11892/11892Secondary AnalysisShared
Relationships between apparent cortical thickness and working memory across the lifespan - effects of genetics and socioeconomic statusWorking memory (WM) supports several higher-level cognitive abilities, yet we know less about factors associated with development and decline in WM compared to other cognitive processes. Here, we investigated lifespan changes in WM capacity and their structural brain correlates, using a longitudinal sample including 2358 magnetic resonance imaging (MRI) scans and WM scores from 1656 participants (4.4-86.4 years, mean follow-up interval 4.3 years). 8764 participants (9.0-10.9 years) with MRI, WM scores and genetic information from the Adolescent Brain Cognitive Development study were used for follow-up analyses. Results showed that both the information manipulation component and the storage component of WM improved during childhood and adolescence, but the age-decline could be fully explained by reductions in passive storage capacity alone. Greater WM function in development was related to apparent thinner cortex in both samples, also when general cognitive function was accounted for. The same WM-apparent thickness relationship was found for young adults. The WM-thickness relationships could not be explained by SNP-based co-heritability or by socioeconomic status. A larger sample with genetic information may be necessary to disentangle the true gene-environment effects. In conclusion, WM capacity changes greatly through life and has anatomically extended rather than function-specific structural cortical correlates. 11892/11892Secondary AnalysisPrivate
Brain associated with mental health and cognition in childrenBrain associated with mental health and cognition in children11879/11879Secondary AnalysisPrivate
Racism May Interrupt Age-related Brain Growth of African American Children in the United StatesBackground: Considerable research has documented age-related growth in brain size as a marker of normal brain development. This is particularly important because brain volume has a significant role in overall cognitive performance. However, less research is done on whether age-related changes in the global brain volume differ across diverse racial and ethnic groups. We hypothesized that age-related growth in brain size would be disrupted in African American children who are historically affected by racism. Purpose: Considering race as a proxy of racism rather than genetics, this study tested racial and ethnic differences in the effects of age on global brain volume using structural brain imaging data. Built on a sociological, rather than a biological theory, we built our study on Marginalization-related Diminished Returns (MDRs) framework, which argues that under racism, resources and assets are less effective for social groups that are historically racialized, discriminated against, marginalized, and segregated. Considering age as an asset/resource that increases the global brain volume, we expected weaker effects of age on overall brain size of African American and Hispanic children, than White and non-Hispanic children, again as a result of racism. Methods: We borrowed the structural Magnetic Resonance Imaging (sMRI) data from the Children Brain Cognitive Development (ABCD) study, which included 9,311 9-10 year old children. The independent variable was the child’s age treated as a continuous measure (in months). The primary outcome was global brain volume. Sex, parental employment, parental education, household income, and parental marital status were the covariates. Race and ethnicity, as proxies of racism, were the moderators. To analyze the data, we used linear regression models. Results: Age was positively associated with the global brain size in children. In line with the MDRs, the positive association between age and global brain volume was weaker for African American than White children, while family structure, sex, and family socioeconomic status was controlled. Conclusions: Under racism, age has unequal effects on global brain size of diverse racial groups. In line with the MDRs, we observe diminished age-related growth of the brain for African American children, which documents detrimental effects of racism. For White children who are not affected by racism, age makes a large difference regarding global brain volume. Age-related growth of global brain size is diminished in African American children, whose daily lives are shaped by racism. School and residential segregation may have a role in reducing the effect of age on children’s brain growth in African American families. The results should not be interpreted as inferiority of one group but social processes that hinder normal development of a historically oppressed group.11879/11879Secondary AnalysisPrivate
Relationship between obstructive sleep disordered breathing and childhood behavioral problems is mediated by frontal lobe structureParents frequently report behavioral problems among children who snore. Our understanding of the relationship between symptoms of obstructive sleep disordered breathing (oSDB)—e.g. snoring—and childhood behavioral problems attributable to brain structural alterations is limited. Therefore, we examined the relationships among oSDB symptoms, problem behaviors and brain morphometry in a diverse dataset comprising 10,140 preadolescents. We demonstrate that the symptoms of oSDB predicted composite and domain-specific behavioral measures. Cortical morphometric alterations demonstrating the strongest negative associations with oSDB symptoms are most pronounced within the frontal lobe. The relationships between oSDB symptoms and behavioral measures are mediated by significantly smaller volumes of multiple frontal lobe regions. These results provide population-level evidence for regional structural alterations in cortical gray matter accompanying problem behaviors in children with oSDB. 11879/11879Secondary AnalysisShared
Reward Processing in Children with Psychotic-like ExperiencesAlterations to striatal reward pathways have been identified in individuals with psychosis. They are hypothesised to be a key mechanism that generates psychotic symptoms through the production of aberrant attribution of motivational salience and are proposed to result from accumulated childhood adversity in combination with genetic risk making the striatal system hyper-responsive to stress. However, few studies have examined whether children with psychotic-like experiences (PLEs) also exhibit these alterations, limiting our understanding of how differences in reward processing relate to hallucinations and delusional ideation in childhood. Consequently, we examined whether psychotic-like experiences and psychotic-like-experience-related distress were associated with reward-related activation in the nucleus accumbens. The sample consisted of children (N = 6,676) from the Adolescent Brain Cognitive Development (ABCD) study aged 9-10 years who had participated in the Monetary Incentive Delay (MID) task in functional MRI. We used robust mixed-effects linear regression models to investigate the relationship between PLEs and nucleus accumbens activation during reward anticipation and reward outcome stages of the MID task. Analyses were adjusted for gender, household income, ethnicity, affective symptoms, movement in the scanner, pubertal development, scanner ID, subject and family ID. There was no association between PLEs and alterations to anticipation-related or outcome-related striatal reward processing. We discuss the implications for developmental models of psychosis and suggest a developmental delay model of how psychotic-like experiences may arise at this stage of development.11879/11879Secondary AnalysisShared
Widespread attenuating changes in brain connectivity associated with the general factor of psychopathology in 9- and 10-year-oldsObjective: Convergent research identifies a general factor (“P factor”) that confers transdiagnostic risk for psychopathology. Large-scale networks are key organizational units of the human brain. However, studies of altered network connectivity patterns associated with the P factor are limited, especially in early adolescence when most mental disorders are first emerging Method: The sample consisted of 11,875 9- and 10-year olds from the Adolescent Brain and Cognitive Development (ABCD) study, of whom 6,593 had high quality resting state scans. Network contingency analysis was used to identify altered interconnections associated with the P factor among 16 large-scale networks. These connectivity changes were then further characterized with quadrant analysis that quantified the directionality of P factor effects in relation to neurotypical patterns of positive versus negative connectivity across connections. Results: The P factor was associated with altered connectivity across 28 network cells (i.e., sets of connections linking pairs of networks); pPERMUTATION-values<0.05 FDR-corrected for multiple comparisons. Higher P factor scores were associated with hypoconnectivity within default network and hyperconnectivity between default network and multiple control networks. Among connections within these 28 significant cells, the P factor was predominantly associated with “attenuating” effects (67%; pPERMUTATION<0.0002), i.e., reduced connectivity at neurotypically positive connections and increased connectivity at neurotypically negative connections. Conclusion: The general factor of psychopathology produces attenuating changes across multiple networks including default network, involved in spontaneous responses, and control networks involved in cognitive control. These results clarify mechanisms of transdiagnostic risk for psychopathology and invite further research into developmental causes of distributed attenuated connectivity. 11878/11878Secondary AnalysisShared
Adolescent Brain Cognitive Development DEAP Study (ABCD) release 3.0The purpose of the RDS file is for the implementation of DEAP for the most current release of ABCD Study data (Data Release 3.0). The variable names in DEAP have been modified from the official NDA variable names to make them easier to search using the data ontology implemented in the Explore module in DEAP. These DEAP names are listed as aliases in the NDA 3.0 release files. RDS 3.0 includes 292 tables. Details are in the official Data Release 3.0 release update notes.11878/11878Secondary AnalysisShared
Adolescent Brain Cognitive Development Study (ABCD) - Annual Release 3.0The ABCD Curated Data Release 3.0 includes high quality baseline and early longitudinal data from ~11,800 research participants, including minimally processed brain image volumes and tabulated structural MRI, diffusion MRI, resting-state fMRI and task fMRI results, as well as all non-imaging assessment data from the genetics, mental health, physical health, neurocognition, substance use, mobile technology, and culture & environment domains. For neuroimaging assessments, this release contains all baseline data and half of the 2-year follow-up (second imaging timepoint). For non-imaging assessments, this release contains baseline and follow-up data for the 6-month and 1 year visits on the full participant cohort, as well as interim data for the 18-month, 2-year, and 30-month visits. For a detailed description of all the measures included in this release, download the Curated Data Release 3.0 Summary document.11878/11878Primary AnalysisShared
Brain structure is linked to the association between family environment and behavioral problems in children in the ABCD studyChildren’s behavioral problems have been associated with their family environments. Here, we investigate whether specific features of brain structures could relate to this link. Using structural magnetic resonance imaging of 8756 children aged 10 from the Adolescent Brain Cognitive Developmental study, we show that high family conflict and low parental monitoring scores are associated with children’s behavioral problems, as well as with smaller cortical areas of the orbitofrontal cortex, anterior cingulate cortex, and middle temporal gyrus. A longitudinal analysis indicates that psychiatric problems scores are associated with increased family conflict and decreased parental monitoring 1 year later, and mediate associations between the reduced cortical areas and family conflict, and parental monitoring scores. These results emphasize the relationships between the brain structure of children, their family environments, and their behavioral problems. 11878/11878Secondary AnalysisPrivate
Brain-Wide Functional Connectivity Patterns Support General Cognitive Ability and Mediate Effects of Socioeconomic Status in YouthGeneral cognitive ability (GCA) is an individual difference dimension linked to important academic, occupational, and health-related outcomes, and its development is strongly linked to differences in socioeconomic status (SES). Complex abilities of the human brain are realized through interconnections among distributed brain regions, but brain-wide connectivity patterns associated with GCA in youth, and the influence of SES on these connectivity patterns, is poorly understood. The present study examined functional connectomes from 5,937 9- and 10-year-olds in the Adolescent Brain Cognitive Development (ABCD) multi-site study. Using multivariate predictive modeling methods, we identified whole-brain functional connectivity patterns linked to GCA. In leave-one-site-out cross-validation, we found these connectivity patterns exhibited strong and statistically reliable generalization at 19 out of 19 held-out sites accounting for 18.0% of the variance in GCA scores (cross-validated partial η2). GCA-related connections were remarkably dispersed across all brain networks: Across 120 sets of connections linking pairs of large-scale networks, significantly elevated GCA-related connectivity was found in 110 of them, and differences in levels of GCA-related connectivity across the brain were modest. Consistent with prior work, socioeconomic status was a strong predictor of GCA in this sample, and we found that distributed GCA-related brain connectivity patterns significantly statistically mediated this relationship (mean proportion mediated: 15.6%, p<2x10-16). These results suggest that socioeconomic status and GCA are related to broad and diffuse differences in functional connectivity architecture during early adolescence, potentially suggesting a mechanism through which socioeconomic status influences cognitive development.11878/11878Secondary AnalysisShared
Child Reward Neurocircuitry and Parental Substance Use History: Findings from the Adolescent Brain Cognitive Development StudySubstance use research has focused on family history of alcohol use disorders but less on other addictions in biological family members. We examined how parental substance use history relates to reward system functioning, specifically nucleus accumbens (NAcc) and putamen activation at age 9-10 in the Adolescent Brain Cognitive Development (ABCD) Study. This research hopes to address limitations in prior literature by focusing analyses on a large, substance-naïve sample. We included ABCD participants with valid Monetary Incentive Delay task fMRI Baseline data and parent substance use history at project baseline from Data Release 2.0 (N =10,622). Parent-history-positive (PH+) participants had one or both biological parents with a history of two+ problems with alcohol (n = 741; PH+A) and/or other drugs (n = 638; Ph+D). Of participants who were parent-history-negative (PH-) for alcohol and/or drugs, a stratified random sample based on six sociodemographic variables was created and matched to the PH+ group (PH-A n = 699; PH-D n = 615). The contrast of interest was anticipation of a large reward vs. neutral response. PH+A youth had more activation in the right NAcc during large reward anticipation than PH-A. PH+D youth showed enhanced left putamen activation during large reward anticipation than PH-D youth. Bayesian hypothesis testing showed moderate evidence (BF > 3) in favor of the null hypothesis. These findings suggest that pre-adolescents whose biological parents had a history of substance-related problems show small differences in reward processing compared to their PH- peers. 10622/11878Secondary AnalysisShared
Daily caffeinated soda intake is associated with impaired working memory and higher impulsivity in childrenCaffeinated soda contains two addictive substances, sugar and caffeine, and is the most preferred route of caffeine consumption among children. While the negative impacts of caffeinated soda on children’s physical health have been well documented, it remains unexplored if habitual caffeinated soda intake is associated with intellectual capacities in children. Here, we investigated the behavioral and neural correlates of daily consumption of caffeinated soda on neurocognitive functions including working memory, impulsivity, and reward processing. We rigorously tested the link between caffeinated soda intake and the neurocognitive functions by applying machine learning and hierarchical linear regression to a large dataset from the Adolescent Brain Cognitive Development (ABCD) Study (N=3,966; age=9-10 years). The results showed that daily consumption of caffeinated soda in children was associated with impaired working memory and higher impulsivity, and increased amygdala activation during the emotional working memory task. The machine learning results also showed hypoactivity in the nucleus accumbens and the posterior cingulate cortex during reward processing. These results suggest that daily caffeinated soda intake in childhood is associated with impaired neurocognitive functioning, which has significant implications for public health recommendations. 11878/11878Secondary AnalysisShared
Depression and Psychosis Risk Shared Vulnerability for Motor Abnormalities Backgrounds: Motor abnormalities are a strong indicator of emerging neural network abnormalities and may provide critical early indications of psychopathology risk. In fact, motor abnormalities, such as motor slowing and agitation, are widely recognized as features of several neurodevelopmental disorders. However, our understanding of motor pathology in the course of depression remains poorly developed. Methods: 10,835 adolescents from the ABCD study were used to explore the relationship between motor abnormalities and depression. These analyses leveraged the rich data available in the ABCD dataset by examining several motor and depression metrics. Depression variables included measures of current symptom dimensions, familial risk, and current diagnoses. In a similarly expansive approach, multiple measures of motor abnormalities were assessed, including early motor delay, coordination, motor slowing, and motor agitation. Finally, motor network connectivity assessed whether current depression symptoms are associated with motor network abnormalities for 8,940 individuals. For all analyses, psychosis variables were used as a comparison. Results: Early developmental motor delays were associated with current depression diagnoses, current symptoms, and a familial risk loading for depression. Current motor abnormality symptoms were also each associated with all depression metrics, including current diagnoses, current symptoms, and familial risk loading. Motor network connectivity was also related to current depression symptom levels. Conclusions: Motor development and symptoms are critically related to depression symptoms, diagnoses, and familial risk loading. Motor function may reflect core biological vulnerability to depression as evidenced by familial risk and motor network connectivity. Finally, individuals with familial risk for psychosis and depression showed the greatest motor abnormalities. 11878/11878Secondary AnalysisPrivate
Development Over the Digital Divide: A Longitudinal Expansion of Empathy Development in AdolescentsThis study aims to expand on Vossen and Valkenberk (2016). More information to come11878/11878Primary AnalysisPrivate
Getting a good night’s sleep: Sleep duration and quality impacts DMN connectivity in youthSleep plays an integral role in healthy development. Inadequate sleep has been linked to poorer emotion regulation and increased risk of psychopathology. Alarmingly, 58% of middle school children are sleeping less than the recommended amount of 9-12 hours based on guidelines from the American Academy of Sleep Medicine. Prior neuroimaging studies in adults link poor sleep to variation within and between key neurocognitive networks, particularly connectivity of the default mode network (DMN). The DMN is implicated in self-reference and rumination, and disruptions in DMN connectivity are associated with risk of psychiatric disorders. Importantly, many psychiatric disorders begin during childhood and adolescence, and functional connectivity within and between neurocognitive networks undergo dramatic changes across childhood and adolescence. However, few studies have examined the impact of sleep on DMN connectivity in youth. This study included 3798 youth (11.9±0.6 years, 47.5% female, 78.9% White, 12.3% Black American, 4.5% Asian) from the Adolescent Brain Cognitive Development (ABCD) study, a longitudinal experiment across 21 sites in the United States. To maximize sample size with both neuroimaging and objective sleep data (Fitbit watch activity tracker), we included data from the ABCD 2-year follow-up time point. Within and between network resting state functional connectivity (rsFC) was measured between the DMN and core neurocognitive networks (i.e., dorsal attention network [DAN], frontoparietal network [FPN], and salience network [SN]). Average sleep duration was measured over 13.1±6.5 days. Pearson’s R correlations were used to test for associations between sleep duration and within and between network rsFC of the DMN.On average, youth slept 7.4±0.7 hours (range: 3-14.1 hours), which is below the recommend 9-12 hours. Total sleep duration was positively correlated with within-network DMN rsFC and negatively correlated with rsFC between the DMN and the DAN and FPN. Sleep duration was not associated with rsFC between DMN and the SN.These findings are consistent with a previous neuroimaging study of sleep deprivation in adults, showing similar patterns of altered within and between network connectivity of the DMN. Given that altered DMN connectivity has been associated with risk of psychopathology, altered DMN connectivity during development may play a role in the link between poor sleep and the development of psychiatric disorders. This study contributes to a growing body of research demonstrating the importance of healthy sleep habits in youth. Future directions will include behavioral indices and additional measures of sleep quality.11878/11878Secondary AnalysisShared
Impact of Prenatal Cannabis Exposure on the Salience Network and Other Core Neurocognitive Networks Cannabis use has become common practice among pregnant women and during the pre-conception period and around 1/3 of THC in the plasma undergoes cross-placental transfer upon cannabis smoking during pregnancy. Prenatal cannabis exposure is associated with cognitive, motor, and social deficits that last into the adulthood of offspring. Further, the eCB system is implicated in risk of anxiety disorders and other comorbid conditions, such as depression. The proposed study leveraged large-scale data from the ABCD study to examine the impact of prenatal cannabis exposure on childhood anxiety symptoms and resting-state functional connectivity within and between the salience network (SN) and other core neurocognitive networks The study includes over 11,000 participants between the ages of 9 and 10 and information on brain development is collected with the use of structural and functional neuroimaging. Prenatal cannabis use was assessed based on the parents’ retrospective report on whether they used it before and/or after their knowledge of pregnancy. Prenatal cannabis exposure on childhood anxiety which was measured by the Childhood Behavior Checklist. Neural activation within the regions of interest were examined using functional magnetic resonance data collected during the well-vetted emotional n-back task. 10,864 had no prenatal cannabis exposure. 309 used cannabis before knowledge of pregnancy, 137 used cannabis after knowledge of pregnancy. We examined the impact of prenatal cannabis exposure (before or after knowledge of pregnancy) on resting-state functional connectivity within and between the salience network (SN) and other core neurocognitive networks (i.e., default mode network [DMN], frontoparietal network [FPN], cingulo-opercular network [CON], ventral attention network [VAN], dorsal attention network [DAN]). Prenatal cannabis exposure before knowledge of pregnancy was associated with lower within network connectivity of the SN, and lower between network connectivity of the SN and VAN. Prenatal cannabis exposure was not associated with altered SN connectivity with other networks. Prenatal cannabis exposure is associated with disrupted connectivity within and between brain networks associated with attention and salience monitoring. Evidence from this study can be used to discourage pregnant women from the recreational use of cannabis. If women are informed on prenatal cannabis exposures effect on child anxiety and altered neurodevelopment, this may prevent them from continued cannabis use during this period. 11878/11878Secondary AnalysisShared
Impact of trauma exposure and endocannabinoid signaling on frontolimbic white matter pathways in childrenThe endocannabinoid system (eCB) is present and functional in early pregnancy and plays a key role in modulating pre- and post-natal brain development, including myelination processes. Recent studies in adolescents and adults link a common variant (C385A) in the gene encoding fatty acid amide hydrolase (FAAH) with higher eCB levels, lower anxiety, and altered frontolimbic development. Frontolimbic white matter pathways demonstrate a protracted maturational course across childhood and adolescence, are associated with anxiety symptoms, and shown to be sensitive to the effects of environmental stress. Here, we examined the impact of the FAAH C385A polymorphism and trauma exposure on anxiety and integrity of frontolimbic white matter pathways in children. We leveraged data collected from the ongoing large-scale NIH Adolescent Brain Cognitive Development (ABCD) study (n = 10,774; M ± SD age = 9.92 ± 0.62 years; 47.9% female; 54.3% White, 13.8% Black, 19.3% Hispanic, 2.1% Asian, 10.4% Other). Saliva samples were used for genotyping and parents reported on their child’s anxiety symptoms and trauma exposure using the Child Behavior Checklist and the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS) traumatic events screener, respectively. Fractional anisotropy (FA) was estimated from DTI data for frontolimbic white matter pathways. Overall, 43.4% of youth were FAAH A-allele carriers or homozygotes (52.1% were CC homozygotes), and 35.7% of youth were exposed to trauma (64.3% unexposed). Trauma-exposed youth demonstrated higher anxiety symptoms and higher FA of the right and left uncinate fasciculus and corpus callosum (forceps minor), as compared to trauma-naïve youth. There was no main effect of the FAAH C385A variant or trauma x FAAH interaction on anxiety symptoms. However, there was a main effect of FAAH genotype on FA in the left and right fornix and left parahippocampal cingulum, such that FA was higher in CC homozygotes as compared to A-alleles. There was also a significant trauma x FAAH interaction for FA in the left and right fornix, right uncinate fasciculus, corpus callosum, and right parahippocampal cingulum. Follow-up analyses in gene groups separately demonstrated that the effects of trauma on white matter integrity were significant in the CC (but the not A-allele) group. In particular, trauma-exposed CC homozygotes demonstrated greater FA than trauma-naïve CC homozygotes. These results highlight the role of trauma exposure and endocannabinoid signaling in modulating frontolimbic development and anxiety risk. 11787/11878Secondary AnalysisShared
Is Executive Dysfunction a Risk Marker or Consequence of Psychopathology? A Test of Executive Function as a Prospective Predictor and Outcome of General Psychopathology in the Adolescent Brain Cognitive Development Study. A general psychopathology (‘p’) factor captures shared variation across mental disorders. One hypothesis is that poor executive function (EF) contributes to p. Although EF is related to p concurrently, it is unclear whether EF predicts or is a consequence of p. For the first time, we examined prospective relations between EF and p in 9,845 preadolescents (aged 9-12) from the Adolescent Brain Cognitive Development Study® longitudinally over two years. We identified higher-order factor models of psychopathology at baseline and one- and two-year follow-up waves. Consistent with previous research, a cross-sectional inverse relationship between EF and p emerged. Using residualized-change models, baseline EF prospectively predicted p factor scores two years later, controlling for prior p, sex, age, race/ethnicity, parental education, and family income. Baseline p factor scores also prospectively predicted change in EF two years later. Tests of specificity revealed that bi-directional prospective relations between EF and p were largely generalizable across externalizing, internalizing, neurodevelopmental, somatization, and detachment symptoms. EF consistently predicted change in externalizing and neurodevelopmental symptoms. These novel results suggest that executive dysfunction is both a risk marker and consequence of general psychopathology. EF may be a promising transdiagnostic intervention target to prevent the onset and maintenance of psychopathology. 11878/11878Secondary AnalysisShared
Latent Profiles of Youth Brain Structure as Markers for PsychopathologyBrain structure is often related to psychopathology through massive univariate approaches on multiple brain regions or confirmatory approaches on a priori defined regions. However, psychopathological disorders are neurobiologically heterogenous such that a single clinical presentation may have multiple possible biological markers. Univariate approaches may not be able to detect these effects as they seek a single directional effect of a particular region across the population. Here, we use latent profile analysis to identify subgroups of youth with more homogenous brain structure in order to examine how distinct neuroanatomical profiles may relate to youth psychopathology. We included volume measures for bilateral accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus and thickness measures for four orbitofrontal regions. Results indicate that distinct profiles of youth neuroanatomy are associated with concurrent and future psychopathology, suggesting that utilizing homogenous patterns of multiple brain regions is a valid alternative to structural univariate approaches. 11878/11878Secondary AnalysisPrivate
Morphology of the prefrontal cortex predicts body composition in early adolescence: cognitive mediators and environmental moderators in the ABCD StudyMorphological features of the lateral prefrontal cortex (PFC) in late childhood and early adolescence may provide important clues as to the developmental etiology of clinical conditions such as obesity. Body composition measurements and structural brain imaging were performed on 11 226 youth at baseline (age 9 or 10 years) and follow-up (age 11 or 12 years). Baseline morphological features of the lateral PFC were examined as predictors of body composition. Findings revealed reliable associations between middle frontal gyrus volume, thickness and surface area and multiple indices of body composition. These findings were consistent across both time points and remained significant after covariate adjustment. Cortical thicknesses of the inferior frontal gyrus and lateral orbitofrontal cortex were also reliable predictors. Morphology effects on body composition were mediated by performance on a non-verbal reasoning task. Modest but reliable moderation effects were observed with respect to environmental self-regulatory demand after controlling for sex, race/ethnicity, income and methodological variables. Overall findings suggest that PFC morphology is a reliable predictor of body composition in early adolescence, as mediated through select cognitive functions and partially moderated by environmental characteristics.11878/11878Secondary AnalysisShared
Motor abnormalities, depression risk, and clinical course in adolescenceBackground: Motor abnormalities, such as psychomotor agitation and retardation, are widely recognized as core features of depression. However, it is not currently known if motor abnormalities connote risk for depression. Methods: Using data from the Adolescent Brain Cognitive Development (ABCD) Study, a nationally representative sample of youth (n=10,835, 9–11 years old), the present paper examines whether motor abnormalities are associated with (a) depression symptoms in early adolescence, (b) familial risk for depression (familial risk loading), and (c) future depression symptoms. Motor abnormalities measures included traditional (DSM) motor signs such as psychomotor agitation and retardation as well as other motor domains such as developmental motor delays and dyscoordination. Results: Traditional motor abnormalities were less prevalent (agitation=3.2%, retardation=0.3%) than non-traditional domains (delays=13.79%, coordination=35.5%) among adolescents. Motor dysfunction was associated with depression symptoms (Cohen’s Ds=0.02 to 0.12). Familial risk for depression was related to motor abnormalities (Cohen’s Ds=0.08 to 0.27), with the exception of motor retardation. Family vulnerability varied in sensitivity to depression risk (e.g., retardation: .53%; dyscoordination: 32.05%). Baseline endorsement of motor abnormalities predicted future depression symptoms at one-year follow-up. Conclusions: These findings suggest that motor abnormalities mark vulnerability to depression and may be useful clinical tools in identifying depression risk in early adolescence. 11878/11878Secondary AnalysisShared
Neighborhood safety is associated with anxiety symptoms and variation in emotion processing neurocircuitry in children While the literature has long established the relationship between the environment and mental health, less is known about the neural correlates underlying these associations. Emotion-related disorders, such as anxiety, commonly begin during childhood and adverse environments, such as living in dangerous neighborhoods, can increase risk for anxiety. Moreover, how children perceive their environment is a determinant for their overall health. This study aims to understand the relationships among perceived neighborhood safety, anxiety, and emotion processing neurocircuitry in a large, demographically diverse sample of children. The current study used cross-sectional baseline survey and functional magnetic resonance imaging (fMRI) data from 11,878 9-year-old children from the Adolescent Brain Cognitive Development study (48% female; 65% White, 15% Black). Children self-reported on their neighborhood safety using the Youth Neighborhood Safety/Crime Survey. Child anxiety was estimated using the Child Behavior Checklist. The primary neuroimaging outcome variables were blood oxygen-level dependent response in emotion processing brain regions of interest (ROIs) during an emotional n-back task: amygdala, hippocampus, dorsal anterior cingulate cortex (dACC), and the insula. We estimated neural response via mean beta weights in each ROI to (1) threatening vs. neutral faces, (2) positive vs. neutral faces, and (3) overall response to emotional faces. Regression models examined whether neighborhood safety predicted anxiety symptoms and neural response in ROIs, and if neural responses, predicted anxiety. Overall, lower neighborhood safety was associated with greater anxiety symptoms in children. Children living in less safe neighborhoods also demonstrated greater left amygdala and right hippocampus reactivity to emotional faces and to positive faces, and lower dACC and insula reactivity to emotional faces. Lower insula reactivity was also associated with higher anxiety, but insula reactivity did not mediate the association between neighborhood safety and anxiety. Given the role of the amygdala and hippocampus in emotion reactivity, and the dACC and insula in top-down emotion regulation, lower neighborhood safety may be associated with greater emotion reactivity and poorer top-down regulation. These results demonstrate that neighborhood safety predicts anxiety and variation in emotion processing neurocircuitry in children- which may also have public health implications. Future interventions aiming toward neighborhood safety may be a promising approach for improving mental health and moderating neurodevelopment in children. 11878/11878Secondary AnalysisShared
Obesogenic EnvironmentModeling environmental variables and their association with obesity.11878/11878Secondary AnalysisPrivate
Obsessive-Compulsive Symptoms among Children in the Adolescent Brain and Cognitive Development Study: Clinical, Cognitive, and Brain Connectivity CorrelatesBackground. Childhood obsessive-compulsive symptoms (OCS) are common and can be an early risk marker for Obsessive-Compulsive Disorder (OCD). The Adolescent Brain and Cognitive Development (ABCD) Study provides a unique opportunity to characterize OCS in a large, normative sample of school-age children and to explore, dimensionally, cortico-striatal and task-control circuits implicated in pediatric OCD. Method. The ABCD Study acquired data from 9-10-year-olds (N=11,876). Linear mixed-effects models probed associations between OCS (Child Behavior Checklist) and cognition (NIH Toolbox), brain structure (subcortical volume, cortical thickness), white matter (diffusion tensor imaging), and resting-state functional connectivity. Results. OCS scores showed good psychometric properties, high prevalence, and related to familial/parental factors, including family conflict. Higher OCS related to better cognitive performance (b=0.06, t(9966.60)=6.28, p<.001, n2p=0.01), particularly verbal, when controlling for ADHD, which related to worse performance. OCS did not significantly relate to brain structure but did relate to lower superior cortico-striate tract fractional anisotropy (b=-0.03, t=-3.07, p=.002, n2p=0.02). Higher OCS related to altered functional connectivity, including weaker within dorsal attention network connectivity (b=-0.04, t(7262.87)=-3.71, p<.001, n2p=0.002) and weaker dorsal attention-default mode anti-correlation (b=0.04, t(7251.95)=3.94, p<.001, n2p=0.002). Dorsal attention-default mode connectivity predicted OCS at 1-year (b=-0.04, t(2407.61)=-2.23, p=.03, n2p=0.03). Conclusions. OCS are common and may persist throughout childhood. Cortico-striatal and attention network connectivity are likely mechanisms in the subclinical-to-clinical spectrum of OCS. Understanding correlates and mechanisms of OCS may elucidate their role in childhood psychiatric risk and suggest potential utility of neuroimaging, e.g. dorsal attention-default mode connectivity, for identifying children at increased risk for OCD. 11878/11878Secondary AnalysisShared
P Factor Resting StateBACKGROUND Convergent research identifies a general factor (“P factor”) that confers transdiagnostic risk for psychopathology. However, brain functional connectivity patterns that underpin the P factor remain poorly understood, especially at the transition to adolescence when many serious mental disorders have their onset. OBJECTIVE: Identify a distributed connectome-wide neurosignature of the P factor and assess the generalizability of this neurosignature in held out samples. DESIGN, SETTING, AND PARTICIPANTS This study used data from the full baseline wave of the Adolescent Brain and Cognitive Development (ABCD) national consortium study, a prospective, population-based study of 11,875 9- and 10-year olds. Data for this study were collected from September 1, 2016 to November 15, 2018 at 21 research sites across the United States. MAIN OUTCOMES AND MEASURES We produced whole brain functional connectomes for 5,880 youth with high quality resting state scans. We then constructed a low rank basis set of 250 components that captures interindividual connectomic differences. Multi-level regression modeling was used to link these components to the P factor, and leave-one-site-out cross-validation was used to assess generalizability of P factor neurosignatures to held out subjects across 19 ABCD sites. RESULTS The set of 250 connectomic components was highly statistically significantly related to the P factor, over and above nuisance covariates alone (ANOVA nested model comparison, incremental R-squared 6.05%, χ2(250) = 412.1, p<4.6x10-10). In addition, two individual connectomic components were statistically significantly related to the P factor after Bonferroni correction for multiple comparisons (t(5511)= 4.8, p<1.4x10-06; t(5121)= 3.9, p<9.7x10-05). Functional connections linking control networks and default mode network were prominent in the P factor neurosignature. In leave-one-site-out cross-validation, the P factor neurosignature generalized to held out subjects (average correlation between actual and predicted P factor scores across 19 held out sites=0.13; pPERMUTATION<0.0001). Additionally, results remained significant after a number of robustness checks. CONCLUSIONS AND RELEVANCE: The general factor of psychopathology is associated with connectomic alterations involving control networks and default mode network. Brain imaging combined with network neuroscience can identify distributed and generalizable signatures of transdiagnostic risk for psychopathology during emerging adolescence. 11878/11878Secondary AnalysisPrivate
Participation in organized team (but not individual) sport is associated with fewer mental health difficulties: Data from over 11,000 American children and youthPurpose: The purpose of this study was to explore the association between participation in organized sport and a broad array of mental health difficulties among American children and youth. Methods: The data (cross-sectional) were from Data Release 3.0 (one-year follow-up visits on the full cohort) of the Adolescent Brain Cognitive Development (ABCD) study—a broadly representative sample of 11,235 US children and youth aged 9 to 13 years. Parents/guardians provided self-reports of their child’s mental health difficulties using the Child Behavior Checklist. To assess participation in organized sport, children and youth were categorized into one of four groups: 1) participation in team sport, 2) participation in individual sport, 3) participation in team and individual sport, and 4) non-sport participation. Several covariates were entered in the analyses, including sport volume (hours) and overall physical activity levels. Results: Participation in team sport compared to non-sport participation was associated with 10% lower anxious/depressed scores, 19% lower withdrawn/depressed scores, 17% lower social problems scores, 17% lower thought problems scores, and 12% lower attention problems scores. Participation in team sport compared to non-sport participation was also associated with 20% lower rule-breaking behavior scores for females (compared to males). Conversely, participation in individual sport compared to non-sport participation was associated with 16% higher anxious/depressed scores, 14% higher withdrawn/depressed scores, 12% higher social problems scores, and 14% higher attention problems scores. Participation in both team and individual sport compared to non-sport participation was associated with 17% lower rule-breaking behavior scores for females (compared to males). Conclusion: Team sport participation was associated with fewer mental health difficulties, whereas individual sport participation was associated with greater mental health difficulties. Findings support and extend previous work suggesting that team sport participation should be encouraged as a vehicle to support children’s and youth’s mental health. Additional research is needed to determine to what extent participation in individual sport may be problematic for younger cohorts. 11878/11878Secondary AnalysisPrivate
Psychiatric Disorders in Grandchildren with Two Previous Generations Affected: a Replication in Big Data Importance: Three-generation family studies of depression have established added risk for offspring with two, compared to one or none, previous generations affected. Rigorous in methodology, these studies are few and sample-limited. Consequently, the three-generation family risk paradigm established in family studies can be a critical neuropsychiatric tool if similar transmission patterns are reliably demonstrated with the family history method. Objective: To examine the effects of multigenerational family history of depression on lifetime depressive disorders and other psychopathology in children. Design, Setting, and Participants: Secondary analyses of the Adolescent Brain Cognitive Development (ABCD) study data. Retrospective, cross-sectional reports on psychiatric functioning among 11,200 children (G3, mean age 9.9 years; 48.8% female), and parent reports on parents’ (G2) and grandparents’ (G1) depression history. Main Outcomes and Measures: Four risk categories were created, reflecting how many prior generations were affected with depression: (1) Neither G1 nor G2, (2) only G1, (3) only G2, and (4) G1 and G2. Lifetime prevalence and relative risks for psychiatric disorders in G3 based on child and caregiver reporters, according to familial risk category derived from G1 and G2’s depression history. Results: By parent reports, G3 depressive disorder prevalence (95% CI) across risk categories 1-4 were: 3.8 (3.2-4.3), 5.5 (4.3-7.1), 10.4 (8.6-12.6), 13.3 (11.6-15.2); Cochran Armitage trend=243.77, p<.0001. G3 suicidal behavior prevalence was, respectively, 5.0 (4.5-5.6), 7.2 (5.8-8.9), 12.1(10.1-14.4), 15.0(13.2-17.0); CA=188.66, p<.0001. By child reports, G3 depressive disorder across risk categories were 4.8 (4.3-5.5), 4.3 (3.2-5.7), 6.3 (4.9-8.1), 7.0 (5.8-8.5); CA=9.01, p<.01; for suicidal behaviors, 7.4 (6.7-8.2), 7.0 (5.6-8.6), 9.8 (8.1-12.0), 13.8 (12.1-15.8), CA=46.69, p<.0001. Similar patterns were observed for other disorders for both parent and child reports, and across sex, socioeconomic status and race/ethnicity. Conclusions and Relevance: Consistent with previous family study findings, having multiple prior affected generations further increases risk for childhood psychopathology. Furthermore, these findings are detectable even at prepubertal ages, and exist in diverse racial/ethnic and socioeconomic groups. Clinically they underscore the need for screening for family history in pediatric settings, and highlight implications for biological research with homogenous subgroups using MRI or genetic analyses. 11878/11878Secondary AnalysisPrivate
Psychotic-like experiences and polygenic liability in the ABCD Study®Background: The current study examined whether psychotic-like experiences (PLEs) during childhood are associated with several psychopathology-related polygenic scores (PGS) generally associated with psychopathology (e.g., psychosis) risk, and additionally examined possible neural and behavioral mechanisms for significant associations. Methods: Adolescent Brain Cognitive Development℠ Study baseline data from children with European ancestry (n=4,650; ages 9-10; 46.8% female) were used to estimate associations between PLEs (i.e., both total and presence of significantly distressing) and PGS for psychopathology (i.e., schizophrenia, psychiatric cross-disorder risk, PLEs) and related phenotypes (i.e., educational attainment [EDU]), birth-weight, inflammation). We also assessed evidence that variability in brain structure indices (i.e., volume, cortical thickness, surface area), as well as behaviors proximal to PGS (e.g., cognition for EDU), indirectly linked PGS to PLEs using mediational models. Results: Total and significantly distressing PLEs were associated with EDU and cross-disorder PGS (all %ΔR2s=0.202-0.660%; pFDRs<0.006). Significantly distressing PLEs were also associated with higher schizophrenia and PLEs PGS (both %ΔR2=0.120-0.171%; pFDRs<0.03). There was evidence consistent with global brain volume metrics and cognitive performance indirectly linking EDU PGS to PLEs (proportion mediated:3.33-32.22%). Conclusions: Total and significantly distressing PLEs were associated with genomic risk indices associated with broad-spectrum psychopathology risk (i.e., EDU and cross-disorder PGS). Significantly distressing PLEs were associated with genomic risk for psychosis (i.e., schizophrenia, PLEs). Global brain volume metrics and PGS-proximal behaviors represent promising putative intermediary phenotypes that may contribute to genomic risk for psychopathology. Broadly, polygenic scores derived from genome-wide association studies of adult samples generalize to indices of psychopathology risk among children. 11878/11878Secondary AnalysisPrivate
Replication of Associations With Psychotic-Like Experiences in Middle Childhood From the Adolescent Brain Cognitive Development (ABCD) StudyThe fields of psychology and psychiatry are increasingly recognizing the importance of replication efforts. The current study aimed to replicate previous findings examining the construct validity and psychometric properties of a psychotic-like experiences (PLEs) measure in middle childhood using an independent subset of the baseline Adolescent Brain Cognitive Development (ABCD) sample. Using a remainder baseline sample of 7013 nine- to eleven-year-old children with complete data, we examined measurement invariance across race/ethnicity and sex, and examined the associations between the Prodromal Questionnaire Brief-Child Version (PQ-BC) and other measures of PLEs, internalizing symptoms, neuropsychological test performance, and developmental milestones, to determine whether previously obtained results replicated in this nonoverlapping baseline sample subset. The results replicated measurement invariance across ethnicity and sex, and analyses again found higher PQ-BC scores for African American (β = .364, 95% CI = 0.292, 0.435) and Hispanic (β = .255, 95% CI = 0.185, 0.324) groups. We also replicated that higher PQ-BC scores were associated with psychosis risk measures, higher rates of child-reported internalizing symptoms (Distress: β = .378, 95% CI = 0.357,0.398), neuropsychological test performance deficits (eg, working memory; Distress: β = −.069, 95% CI = −0.096, −0.042), and motor (Distress: β = .026, 95% CI = 0.003, 0.049) and speech (Distress: β = .042, 95% CI = 0.018, 0.065) developmental milestone delays. The current results replicated many findings from the original study examining the PQ-BC. We replicated evidence for mean differences in race/ethnicity, and associations with other PLE measures, greater internalizing symptoms, cognitive impairments, and developmental milestone delays. These findings indicate robust and reliable associations between PLEs and hypothesized correlates can be found in middle childhood nonclinical samples.11878/11878Secondary AnalysisPrivate
Reward Sensitivity and Executive Function in AdolescenceReward sensitivity and Executive Function are interacting processes that develop over adolescence. 11878/11878Secondary AnalysisPrivate
Sleep duration, brain structure, and psychiatric and cognitive problems in childrenLow sleep duration in adults is correlated with psychiatric and cognitive problems. We performed for the first time a large-scale analysis of sleep duration in children, and how this relates to psychiatric problems including depression, to cognition, and to brain structure. Structural MRI was analyzed in relation to sleep duration, and psychiatric and cognitive measures in 11,067 9–11-year-old children from the Adolescent Brain Cognitive Development (ABCD) Study, using a linear mixed model, mediation analysis, and structural equation methods in a longitudinal analysis. Dimensional psychopathology (including depression, anxiety, impulsive behavior) in the children was negatively correlated with sleep duration. Dimensional psychopathology in the parents was also correlated with short sleep duration in their children. The brain areas in which higher volume was correlated with longer sleep duration included the orbitofrontal cortex, prefrontal and temporal cortex, precuneus, and supramarginal gyrus. Longitudinal data analysis showed that the psychiatric problems, especially the depressive problems, were significantly associated with short sleep duration 1 year later. Further, mediation analysis showed that depressive problems significantly mediate the effect of these brain regions on sleep. Higher cognitive scores were associated with higher volume of the prefrontal cortex, temporal cortex, and medial orbitofrontal cortex. Public health implications are that psychopathology in the parents should be considered in relation to sleep problems in children. Moreover, we show that brain structure is associated with sleep problems in children, and that this is related to whether or not the child has depressive problems.11878/11878Secondary AnalysisPrivate
Sleep_ApneaSleep Disorder 11878/11878Primary AnalysisPrivate
The effects of threat versus deprivation during childhood on puberty and white matter maturationEarly childhood experiences--including threat and deprivation--have life-long effects on physiology and behavior. Threat exposure is defined as those experiences involving harm or threat of harm, such as community violence, domestic violence, physical, verbal, and sexual abuse. Deprivation exposure is defined as those experiences involving absence of expected inputs from the environment necessary for healthy development. A replication of the National Comorbidity Survey found anxiety diagnoses in the United States to be prevalent at 28.8%, with a median age of onset between ages 11 and 14--around the same age at which individuals are transitioning into puberty. Altogether, threat and deprivation experiences during sensitive periods when children's brains are developing and susceptible to the effects of experience, as well as gonadal hormones during the pubertal phase, may have profound impacts on brain structure and resultant behavior. Previous work in healthy adolescents has indicated a sensitivity of white matter integrity to gonadal hormones estradiol and testosterone. The present study aims to leverage data from the ABCD cohort to examine whether exposure to threat is associated with accelerated pubertal maturation and more adult-like patterns of white matter tractograph, compared to youth who experience deprivation and may exhibit attenuated pubertal maturation and less-developed white matter tracts. 11878/11878Secondary AnalysisPrivate
Typologies of Family Functioning and 24-h Movement BehaviorsResearch on the importance of the family environment on children’s health behaviors is ubiquitous, yet critical gaps in the literature exist. Many studies have focused on one family characteristic and have relied on variable-centered approaches as opposed to person-centered ap- proaches (e.g., latent profile analysis). The purpose of the current study was to use latent profile analysis to identify family typologies characterized by parental acceptance, parental monitoring, and family conflict, and to examine whether such typologies are associated with the number of movement behavior recommendations (i.e., physical activity, screen time, and sleep) met by children. Data for this cross-sectional observational study were part of the baseline data from the Adolescent Brain Cognitive Development (ABCD) study. Data were collected across 21 study sites in the United States. Participants included 10,712 children (female = 5143, males = 5578) aged 9 and 10 years (M = 9.91, SD = 0.62). Results showed that children were meaningfully classified into one of five family typologies. Children from families with high acceptance, medium monitoring, and medium conflict (P2; OR = 0.54; 95% CI, 0.39–0.76); high acceptance, medium monitoring, and high conflict (P3; OR = 0.28; 95% CI, 0.20, 0.40); low acceptance, low monitoring, and medium conflict (P4; OR = 0.24; 95% CI, 0.16, 0.36); and medium acceptance, low monitoring, and high conflict (P5; OR = 0.19; 95% CI, 0.12–0.29) were less likely to meet all three movement behavior recommendations compared to children from families with high acceptance, high monitoring, and low conflict (P1). These findings highlight the importance of the family environment for promoting healthy movement behaviors among children.11878/11878Secondary AnalysisPrivate
Wearable Assessment of Adolescent Mental HealthBackground: Adolescence is characterized by alterations in biobehavioral functioning, during which individuals are at heightened risk for onset of psychopathology, particularly internalizing disorders. Researchers have proposed using digital technologies to index daily biobehavioral functioning, yet there is a dearth of research examining how wearable metrics are associated with mental health. Methods: We preregistered analyses using the Adolescent Brain Cognitive Development Study dataset using wearable data collection in 5,686 adolescents (123,862 person days or 2,972,688 person hours) to determine whether wearable indices of resting heart rate (RHR), step count, and sleep duration as well as variability in these measures were cross-sectionally associated with internalizing symptomatology. All models were also run controlling for age, sex, body mass index, socioeconomic status, and race. We then performed prospective analyses on a subset of this sample (n = 143) across 25 months that had Fitbit data available at Baseline and Follow Up in order to explore directionality of effects. Results: Cross-sectional analyses revealed a small, yet significant effect size (R2=0.053) that higher RHR, lower step count and step count variability, and greater variability in sleep duration were associated with greater internalizing symptoms. Cross-lagged panel model analysis revealed that there were no prospective associations between wearable variables and internalizing symptoms (partial R2=0.026), but greater internalizing symptoms and higher RHR predicted lower step count 25 months later (partial R2=0.010), while higher RHR also predicted lower step count variability 25 months later (partial R2=0.008). Conclusions: Findings indicate that wearable indices concurrently associate with internalizing symptoms during early adolescence, while a larger sample size is likely required to accurately assess prospective or directional effects between wearable indices and mental health. Future research should capitalize on the temporal resolution provided by wearable devices to determine the intensive longitudinal relations between biobehavioral risk factors and acute changes in mental health.11878/11878Secondary AnalysisShared
Adolescent Brain Cognitive Development Study (ABCD) - Annual Release 4.0The ABCD Curated Data Release 4.0 includes high-quality baseline and early longitudinal data from ~11,800 research participants, including minimally processed brain image volumes and tabulated structural MRI, diffusion MRI, resting-state fMRI and task fMRI results, as well as all non-imaging assessment data from the genetics, mental health, physical health, neurocognition, substance use, mobile technology, and culture & environment domains. For neuroimaging assessments, this release contains all baseline data and half of the 2-year follow-up (second imaging timepoint). For non-imaging assessments, this release contains baseline and follow-up data for the 6-month, 1 year, 18-month visits on the full participant cohort, as well as interim data for the 2-year, 30-month, 3-year, and 42-month visits. For a detailed description of all the measures included in this release, download the Curated Data Release 4.0 Summary document.11877/11877Primary AnalysisShared
Adolescent Verbal Memory as a Psychosis Endophenotype: a Genome-wide Association Study in an Ancestrally Diverse SampleVerbal memory impairment is one of the most prominent cognitive deficits in psychosis. However, few studies have investigated the genetic basis of verbal memory in a neurodevelopmental context, and most genome-wide association studies (GWASs) have been conducted in European-ancestry populations. We conducted a GWAS on verbal memory in a maximum 11,017 participants aged 8.9 to 11.1 years in the Adolescent Brain Cognitive Development Study, recruited from a diverse population in the United States. Verbal memory was assessed by the Rey Auditory Verbal Learning Test, which included three measures of verbal memory: immediate recall, short-delay recall, and long-delay recall. We adopted a mixed-model approach to perform a joint GWAS of all participants, adjusting for ancestral background and familial relatedness. The inclusion of participants from all ancestries increased the power of the GWAS. Two novel genome-wide significant associations were found for short-delay and long-delay recall verbal memory. In particular, one locus (rs9896243) associated with long-delay recall was mapped to the NSF (N-Ethylmaleimide Sensitive Factor, Vesicle Fusing ATPase) gene, indicating the role of membrane fusion in adolescent verbal memory. Based on the GWAS in the European subset, we estimated the SNP-heritability to be 15% to 29% for the three verbal memory traits. We found that verbal memory was genetically correlated with schizophrenia, providing further evidence supporting verbal memory as an endophenotype for psychosis.11877/11877Secondary AnalysisShared
ABCD Dissertation StudyAssessing longitudinal trajectories of resting state functional connectivity and psychopathology, as they relate to social support. 11876/11876Secondary AnalysisPrivate
Associations Between Neighborhood Disadvantage, Resting-State Functional Connectivity, and Behavior in the Adolescent Brain Cognitive Development Study: The Moderating Role of Positive Family and School EnvironmentsBackground Neighborhood disadvantage has consistently been associated with mental health and cognitive function, in addition to alterations in brain function and connectivity. However, positive environmental influences may buffer these effects. The aim of this study was to examine the association between neighborhood disadvantage and resting-state functional connectivity (rsFC), the moderating role of positive parenting and school environment, and relationships between disadvantage-associated rsFC patterns and mental health and cognition. Methods In this preregistered study, we tested this hypothesis in a large sample of 7618 children (aged 9–10 years) from the Adolescent Brain Cognitive Development (ABCD) study. Specifically, we analyzed the relationship between neighborhood disadvantage and system-level FC. We also tested whether positive family and school environmental factors and sex moderated effects. Finally, we investigated multivariate relationships between disadvantage-associated rsFC patterns and cognition and mental health. Results Disadvantage was associated with widespread alterations in FC across both higher-order (e.g., default mode network and dorsal attention network) and sensorimotor functional systems, some of which were moderated by positive environments. Implicated connections showed multivariate associations with behavior, whereby disadvantage-associated rsFC was generally associated with worse cognition and mental health. Disadvantage-associated connections also predicted variation in cognitive scores using machine learning models. Conclusions Our findings shed light on potential mechanisms (i.e., alteration of neural circuitry) through which neighborhood disadvantage may affect youth cognition and mental well-being. This work highlights the importance of positive family and school environments in mitigating some of these effects.11876/11876Secondary AnalysisShared
Cognitive performance in children and adolescents with psychopathology traits: a cross-sectional multi-cohort study in the general populationBackground: Psychopathology and cognitive development are closely related. Assessing the relationship between multiple domains of psychopathology and cognitive performance can elucidate which cognitive tasks are related to specific domains of psychopathology. This can help build theory and improve clinical decision making in the future. Methods: The study included 13,841 children and adolescents drawn from two large population-based samples (Generation R and ABCD studies). We assessed the cross-sectional relationship between three psychopathology domains (internalizing, externalizing, dysregulation profile (DP)) and four cognitive domains (vocabulary, fluid reasoning, working memory and processing speed) and the full-scale intelligence quotient (FSIQ). Lastly, differential associations between symptoms of psychopathology and cognitive performance by sex were assessed. Results: Internalizing symptoms were related to worse performance in working memory and processing speed, but better performance in the verbal domain. Externalizing and DP symptoms were related to poorer global cognitive performance. Notably, those in the DP subgroup had a 5.0 point lower IQ than those without behavioral problems. Cognitive performance was more heavily affected in boys than in girls given comparable levels of psychopathology. Conclusions: We provide evidence for globally worse cognitive performance in children and adolescents with externalizing and DP symptoms, with those in the DP subgroup being most heavily affected. 11876/11876Secondary AnalysisPrivate
Do visual attentional blink and executive function tasks share similar brain networks, as seen from connectome based predictive modellingExecutive function and visual attention blink seems to be related. Can we validate it using CPM? We use the HCP and ABCD dataset to validate whether the vabCPM can predict the scores of n-back task and emotional stroop task.11876/11876Primary AnalysisPrivate
Learning Clique Subgraphs in Structural Brain Network Classification with Application to Crystallized CognitionStructural brain networks constructed from diffusion MRI are important biomarkers for understanding human brain structure and its relation to cognitive functioning. There is increasing interest in learning differences in structural brain networks between groups of subjects in neuroimaging studies, leading to a variable selection problem in network classification. Traditional methods often use independent edgewise tests or unstructured generalized linear model (GLM) with regularization on vectorized networks to select edges distinguishing the groups, which ignore the network structure and make the results hard to interpret. In this paper, we develop a symmetric bilinear logistic regression (SBLR) with elastic-net penalty to identify a set of small clique subgraphs in network classification. Clique subgraphs, consisting of all the interconnections among a subset of brain regions, have appealing neurological interpretations as they may correspond to some anatomical circuits in the brain related to the outcome. We apply this method to study differences in the structural connectome between adolescents with high and low crystallized cognitive ability, using the crystallized cognition composite score, picture vocabulary and oral reading recognition tests from NIH Toolbox. A few clique subgraphs containing several small sets of brain regions are identified between different levels of functioning, indicating their importance in crystallized cognition.11876/11876Secondary AnalysisShared
Parental psychological problems were associated with higher screen time and the use of mature-rated media in childrenAim: Parents' psychological problems may affect children's screen time, but research has been scarce. We examined the association between parental psychological problems and children's screen media behaviours in a nationally representative sample. Methods: The participants were from the Adolescent Brain Cognitive Development study, recruited by probability sampling from the USA population. Children reported their use of TV, videos, video games, social media, and mature-rated media. The parents (85% mothers) reported psychological problems using the Adult Self-Report questionnaire. Results: In 10,650 children (5,112 girls, 5,538 boys) aged 9.9±0.6 years, presence of parental psychological problems was associated with children spending more daily time on screen media and with meeting the recommendation of ≤2 daily hours less often than children whose parents did not have psychological problems. Parental psychological problems were associated with children's TV watching, video watching and gaming but not with using social media. Parental internalising problems were associated with children watching mature-rated movies (odds ratio [OR] =1.14, 95% confidence interval [CI]=1.00, 1.30) and playing mature-rated games (OR=1.27, 95% CI=1.11, 1.45). Conclusion: Presence of parental psychological problems is associated with higher screen time and use of mature-rated media in children. This cross-sectional study was not able to examine causal associations.11876/11876Secondary AnalysisShared
Similar but distinct - Effects of different socioeconomic indicators on resting state functional connectivity: Findings from the Adolescent Brain Cognitive Development (ABCD) Study®Early socioeconomic status (SES) has consistently been associated with child health and cognitive outcomes, in addition to alterations in brain function and connectivity. The goal of the present study was to probe the effects of different facets of SES (parent education, income, and neighborhood disadvantage), that likely represent varying aspects of the environment, on resting state functional connectivity (rsFC). We investigated this question in a large sample of 9475 children (aged 9-10 years) from the Adolescent Brain Cognitive Development (ABCD) Study. Specifically, we analyzed the association between household SES (parent education, income-to-needs ratio) and neighborhood disadvantage, and system-level rsFC using within-sample split-half replication. We then tested whether the associations were unique to each SES measure, and whether household SES and neighborhood disadvantage had interactive effects on rsFC. SES measures had both common and distinct effects on rsFC, with sensory-motor systems (e.g., sensorimotor network) and cognitive networks (e.g., front-parietal network) particularly implicated. Further, the association between neighborhood disadvantage and sensorimotor network connectivity was less pronounced in the presence of high income-to-needs. Findings demonstrate that different facets of SES have distinct and interacting effects on rsFC, highlighting the importance of considering different indicators when studying the effects of SES on the brain.11876/11876Secondary AnalysisShared
Similar but distinct – Effects of different socioeconomic indicators on resting state functional connectivity: Findings from the Adolescent Brain Cognitive Development (ABCD) StudyEarly socioeconomic status (SES) has consistently been associated with child health and cognitive outcomes, in addition to alterations in brain function and connectivity. The goal of the present study was to probe the effects of different facets of SES (parent education, income, and neighborhood disadvantage), that likely represent varying aspects of the environment, on resting state functional connectivity (rsFC). We investigated this question in a large sample of 9475 children (aged 9–10 years) from the Adolescent Brain Cognitive Development (ABCD) Study. Specifically, we analyzed the association between household SES (parent education, income-to-needs ratio) and neighborhood disadvantage, and system-level rsFC using within-sample split-half replication. We then tested whether the associations were unique to each SES measure, and whether household SES and neighborhood disadvantage had interactive effects on rsFC. SES measures had both common and distinct effects on rsFC, with sensory-motor systems (e.g., sensorimotor network) and cognitive networks (e.g., front-parietal network) particularly implicated. Further, the association between neighborhood disadvantage and sensorimotor network connectivity was less pronounced in the presence of high income-to-needs. Findings demonstrate that different facets of SES have distinct and interacting effects on rsFC, highlighting the importance of considering different indicators when studying the effects of SES on the brain.11876/11876Secondary AnalysisPrivate
Statistical causal inference approaches with the ABCD datasetResearchers studying human behavior are often interested in answering causal research questions like, what effect does a drug exposure or environmental feature have on an outcome measure related to the brain or mental health. Prior studies attempting to answer these questions have often used small samples and cross-sectional designs, which make it challenging, if not impossible, to understand the causal nature of these relationships. Furthermore, the use of experimental designs like randomized controlled trials are practically impossible to implement with illicit drugs (e.g., cannabis) and vulnerable populations (e.g., children or pregnant individuals). One way to navigate these challenges is to use statistical causal inference methods applied to large observational studies, like the Adolescent Brain and Cognitive Development study ("ABCD"; N=11,873). Broadly, statistical causal inference methods seek to leverage a dataset to approximate an experimental design. Techniques like a causal random forest (CRF) model infers an "average treatment effect" of an “exposure” or “treatment” on an outcome measure by using decision trees to compare similar subgroups of participants matched on variables that would have otherwise confounded a causal relationship. CRFs also identify "heterogeneous treatment effects" by estimating moderators between the exposure and outcome measure. Quasi-experimental methods like regression discontinuity designs (RDD) infers causality by estimating a discontinuity in an outcome measure between participants who are close to a "threshold" for their inclusion vs. exclusion from an “exposure” or “treatment”. Using a causal inference framework, this project seeks to identify modifiable factors (e.g., sleep, extracurriculars, screen media hours) that are causally related to brain and behavioral health outcome measures (e.g., internalizing disorders, brain activation measures). For example, a CRF model will test the hypothesis that there is an average treatment effect of sleep hours on internalizing symptoms, and this causal pathway might be moderated by prenatal or adolescent cannabis exposure. Moreover, an RDD model will test the hypothesis that living within 250mi. of a time-zone boundary (i.e., the discontinuity threshold) will have an effect on cognitive or other psychosocial measures. This is hypothesized due to the discrepancy between sunlight exposure and clock-time that is exaggerated near time-zone boundaries (early sunsets just west vs. late sunsets just east of a boundary), yet social responsibilities (school start times) are constant across boundaries ("social jetlag"). Similar methods will also be pursued with other exposure/treatment measures, and outcome measures, pertaining adolescent brain and behavioral health. By illuminating causal factors like these, one can begin to develop explanatory models and novel interventions aimed at promoting adolescent mental health and wellbeing. The use of a causal framework is key, as the modification of causal processes are most likely to have an effect on critical outcome measures 11876/11876Secondary AnalysisPrivate
Substance use patterns in 9-10 year olds: Baseline findings from the adolescent brain cognitive development (ABCD) studyBackground: The Adolescent Brain Cognitive Development ™ Study (ABCD Study®) is an open-science, multisite, prospective, longitudinal study following over 11,800 9- and 10-year-old youth into early adulthood. The ABCD Study aims to prospectively examine the impact of substance use (SU) on neurocognitive and health outcomes. Although SU initiation typically occurs during teen years, relatively little is known about patterns of SU in children younger than 12. Methods: This study aims to report the detailed ABCD Study® SU patterns at baseline (n = 11,875) in order to inform the greater scientific community about cohort’s early SU. Along with a detailed description of SU, we ran mixed effects regression models to examine the association between early caffeine and alcohol sipping with demographic factors, externalizing symptoms and parental history of alcohol and substance use disorders (AUD/ SUD). Primary Results: At baseline, the majority of youth had used caffeine (67.6 %) and 22.5 % reported sipping alcohol (22.5 %). There was little to no reported use of other drug categories (0.2 % full alcohol drink, 0.7 % used nicotine, <0.1 % used any other drug of abuse). Analyses revealed that total caffeine use and early alcohol sipping were associated with demographic variables (p’s<.05), externalizing symptoms (caffeine p = 0002; sipping p = .0003), and parental history of AUD (sipping p = .03). Conclusions: ABCD Study participants aged 9–10 years old reported caffeine use and alcohol sipping experimentation, but very rare other SU. Variables linked with early childhood alcohol sipping and caffeine use should be examined as contributing factors in future longitudinal analyses examining escalating trajectories of SU in the ABCD Study cohort.11876/11876Primary AnalysisShared
ABCD LPARegardless of the precise mechanism, the underlying assumption of all neurodevelopmental models of risk is that, at the population level, there exist subgroups of individuals that share similar patterns of neural function and development, and that these subgroups somehow relate to psychiatric risk. The existence of multiple neurodevelopmental subgroups at the population level has not been assessed previously. In the current study, cross-validated latent profile analysis was used to test for the presence of empirical neurodevelopmental subgroups using fMRI data from 6,758 individuals (49.4% female) in the ABCD Wave 1 release. Data were randomly split into training and testing samples and the optimal solution from the training data was validated in the testing data. Analyses in the training sample (n=3,379) identified a 7-profile solution (entropy=.880), that replicated in the held-out testing data (n=3,379, entropy=.890). Identified subgroups included a ‘majority’ group (66.8%), high reward (4.3%) and low reward (4.0%) groups, high inhibition (9.8%) and low inhibition (6.7%) groups, and high emotion regulation (4.0%) and low emotion regulation (4.3%) groups. Relative to the majority group, smaller subgroups were characterized by more males (X2=25.28, p<.0001), higher proportions of individuals from lower-income households (X2=122.17, p<.0001), poorer cognitive performance (F=14.78, p<.0001), more screen time (F=10.27, p<.0001), and heightened impulsivity (p’s<.00625). These data for the first time demonstrate the existence of multiple, distinct neurodevelopmental subgroups at the population-level. They indicate that these empirically derived, brain-based developmental profiles relate to differences in clinical features, even at a young age, and prior to the onset of significant psychopathology.11875/11875Secondary AnalysisShared
Adolescent Brain Cognitive Development DEAP Study (ABCD)The purpose of the RDS file is for the implementation of DEAP for the most current release of ABCD Study data (Data Release 2.0.1). The variable names in DEAP have been modified from the official NDA variable names to make them easier to search using the data ontology implemented in the Explore module in DEAP. These DEAP names are listed as aliases in the NDA 2.0.1 release files. RDS 2.0.1 includes 218 tables, 129 of which are from the original ABCD Data Release 2.0 and 89 are from ABCD Data Release 2.0.1. Details are in the official Data Release 2.0.1 release notes.11875/11875Secondary AnalysisShared
Adolescent Brain Cognitive Development DEAP Study (ABCD) release 2.0.1 updateThe purpose of the RDS file is for the implementation of DEAP for the most current release of ABCD Study data (Data Release 2.0.1). The variable names in DEAP have been modified from the official NDA variable names to make them easier to search using the data ontology implemented in the Explore module in DEAP. These DEAP names are listed as aliases in the NDA 2.0.1 release files. RDS 2.0.1 includes 218 tables, 129 of which are from the original ABCD Data Release 2.0 and 89 are from ABCD Data Release 2.0.1. Details are in the official Data Release 2.0.1 release update notes.11875/11875Secondary AnalysisShared
Adolescent Brain Cognitive Development Study (ABCD) - Annual Release 2.0The ABCD Curated Annual Release 2.0 includes high quality baseline data from ~11,800 research participants, including minimally processed brain image volumes and tabulated structural MRI, diffusion MRI, resting-state fMRI and task fMRI results, as well as all non-imaging assessment data from the genetics, mental health, physical health, neurocognition, substance use, mobile technology, and culture & environment domains. All personally identifiable information is removed from the data to ensure participant confidentiality and anonymity. For a detailed description of all the measures included in this release, download the Curated Annual Release 2.0 Summary document. Problems have been identified with imaging data tables and associated data dictionaries for the following instruments: abcd_dti_p101, abcd_dti_p201, abcd_ddtidp101, abcd_ddtidp201, abcd_dmdtifp201, abcd_midasemdp201, abcd_midr1bwdp201, abcd_tr2bwdp201, abcd_midabwdp201, abcd_tmidr1semdp201, abcd_tr2semdp201. Corrected files will be available soon. An error was also discovered in imaging data collected from Siemens scanners between September 2017 and December 2017 where structural images are flipped left-right. These data will be updated in a patch release later this year. 11875/11875Primary AnalysisShared
Adolescent Brain Cognitive Development Study (ABCD) 2.0.1 releaseDue to reporting compilation and processing errors in 2.0 Data Release, a 2.0.1 Fix Release has been issued. Please ensure curated data (datasheets, minimally processed data) from the original Data Release 2.0 are replaced with data from 2.0.1 Fix Release. The following release notes were updated to reflect these changes: NDA 2.0.1 Release Notes ABCD README FIRST NDA 2.0.1 Release Notes Imaging Instruments NDA 2.0.1 Changes and Known Issues Fix Release 2.0.1 NDA 2.0.1 Diffusion Magnetic Resonance Imaging NDA 2.0.1 Task-Based Functional Magnetic Resonance Imaging NDA 2.0.1 Mental Health NDA 2.0.1 Genetics Registered users can obtain more information from https://nda.nih.gov/study.html?id=721, and access updated data via Option One or Option Two using the NDA Query Tool - https://nda.nih.gov/general-query.html.. For downloading only updated minimally processed imaging data, add the Minimally Processed "Release 2.0.1" to the Workspace via Option Two. 11875/11875Primary AnalysisShared
Adverse Childhood Experiences and Psychotic-like Experiences Are Associated Above and Beyond Shared Correlates: Findings from the Adolescent Brain Cognitive Development StudyAdverse childhood experiences (ACEs) are associated with increased risk for psychotic-like experiences (PLEs). However, ACEs and PLEs are also both associated with several shared factors (e.g., internalizing symptoms, suicidality). Few studies have explicitly examined whether the association between ACEs and PLEs remains over and above shared correlates. To address this question, using 10,800 9-11-year-olds, we examined whether ACEs and school-aged PLEs were associated when accounting for shared correlates, and whether there was evidence of mediation in associations between PLEs, ACEs, and these shared factors. Greater number of ACEs were associated with greater PLEs, including several specific ACEs (e.g., bullying). Importantly, ACEs and PLEs were related even when accounting for shared correlates. Further, PLEs partially mediated the relationships between ACEs and both internalizing symptoms and suicidality, including suicidal behavior. The current study helps clarify the nature of the associations between PLEs and ACE and has important clinical implications for addressing PLEs. 11875/11875Secondary AnalysisShared
African Americans’ Diminished Returns of Parental Education on Adolescents’ Depression and Suicide in the Adolescent Brain Cognitive Development (ABCD) StudyTo investigate racial and ethnic differences in the protective effects of parental education and marital status against adolescents’ depressed mood and suicidal attempts in the U.S. As proposed by the Marginalization-related Diminished Returns (MDRs), parental education generates fewer tangible outcomes for non-White compared to White families. Our existing knowledge is very limited regarding diminished returns of parental education and marital status on adolescents’ depressed mood and suicidal attempts. To compare racial groups for the effects of parental education and marital status on adolescents’ depressed mood and suicidal attempt. This cross-sectional study included 7076 non-Hispanic White or African American 8-11 years old adolescents from the Adolescent Brain Cognitive Development (ABCD) study. The independent variables were parental education and marital status. The main outcomes were depressed mood and suicidal attempts based on parents’ reports using the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS). Age and gender were the covariates. Race was the moderator. Logistic regression was used to analyze the ABCD data. Overall, parental education was associated with lower odds of depressed mood (OR = 0.81; 95% CI = 0.67-0.99; p = 0.037) and having married parents was associated with lower odds of suicidal attempts (OR = 0.50; 95% CI = 0.28-0.91; p = 0.022). In the pooled sample, we found interaction terms between race with parental education and marital status on the outcomes, suggesting that the protective effect of having married parents against depressed mood (OR = 1.54; 95% CI = 1.00-2.37; p = 0.048) and the protective effect of having married parents against suicidal attempts (OR = 6.62; 95% CI = 2.21-19.86; p =0.001) are weaker for African Americans when compared to Whites. The protective effects of parent education and marital status against depressed mood and suicidal attempts are diminished for African American adolescents compared to White adolescents. There is a need for programs and interventions that equalize not only socioeconomic status (SES) but also the marginal returns of SES for racial minority groups. Such efforts require addressing structural and societal barriers that hinder African American families from translating their SES resources and human capital into tangible outcomes. There is a need for studies that can minimize MDRs for African American families, so that every individual and every family can benefit from their resources regardless of their skin color. To achieve such a goal, we need to help middle-class African American families secure tangible outcomes in the presence of SES resources.11875/11875Secondary AnalysisPrivate
An IRT Analysis of the Prodromal Questionnaire-Brief Child Version: Developing a Screening Form that Informs Understanding of Self-Reported Psychotic-Like Experiences in ChildhoodThe Prodromal Questionnaire-Brief Child Version (PQ-BC) has been developed as a tool for identifying psychotic-like experiences (PLEs) in school-age children. The current study examined the psychometric properties of the PQ-BC, examined how well the PQ-BC estimates the latent construct of PLEs (θ ̂), and began the process of developing a screening form informed by item response theory (IRT). Utilizing the baseline (n=11,129) sample from the Adolescent Brain Cognitive Brain (ABCD) study, we examined which PQ-BC items provide the most information and best discriminate individuals experiencing PLEs. Using hierarchical linear models (HLMs), we found that θ ̂ scores were significantly associated with several previously identified predictors of psychosis spectrum symptoms (i.e., history of psychosis, internalizing symptoms, cognitive impairments, developmental milestone delays, and resting-state functional connectivity impairments) at baseline and year 1 (n=5,532). Using item level information and discrimination parameters of the PQ-BC from the baseline sample, we created a seven-item screening form. HLMs generally found significant associations between screening form scores for both baseline and year 1 with the aforementioned predictors. The analyses provide evidence for the validity of a screening form derived from the PQ-BC using IRT derived parameters. This screening form could prove useful when the full measure is not feasible. 11875/11875Secondary AnalysisShared
An integrative approach to modelling suicidal thoughts and behaviour in youthsSuicide is a leading cause of death in young people. Research has identified biological, cognitive and social factors that reflect vulnerability to youth suicide. However, these predictors are correlated and hard to disentangle. To aid early detection of suicide, a better understanding of the mechanisms underlying both suicidal ideation and attempt is a critical first step. We will utilize multivariate statistical techniques to investigate an integrative model to differentiate between suicidal ideation and attempt for optimized prediction of future treatment by combining childhood adversity, cognitive ability and structural and functional brain data. We hypothesize that these factors connected to affective functioning will be associated with suicidal ideation. In contrast, relationships will be observed between these measures linked to altered executive cognitive function for suicidal attempt. Using longitudinal data, we will predict the progress from suicidal ideation to attempt. 11875/11875Secondary AnalysisPrivate
Association Between Habitual Snoring and Cognitive Performance in a Large Sample of Preadolescent ChildrenImportance: Previous studies have identified an association between habitual snoring and lower cognitive measures in children. However, whether and to what extent this relationship is confounded by pertinent demographic, anthropometric and socioeconomic characteristics is unknown. Objective: We assessed the extent of potential confounding in the relationship between parent-reported habitual snoring in children and their cognitive outcomes in a large diverse sample of typically developing preadolescent children. Design: Cross-sectional analysis of the Adolescent Brain Cognitive Development Study baseline dataset (v2.0.1) including children enrolled between September 2016 and October 2018. Setting: Community-based recruitment of children from 21 sites in the US that approximates the racial and socioeconomic diversity of the U.S. Participants: Children aged 9-10 years and without serious psychiatric or neurological comorbidities. Exposure: Parent-reported habitual snoring in children occurring three or more nights a week. Main outcomes and Measures: Associations between habitual snoring and cognitive performance assessed using the National Institutes of Health Toolbox® before and after adjustment for covariates including age, sex, body mass index percentile, total family income before taxes, and highest caregiver education status. The extent of confounding was assessed by the magnitude of the effect represented by Cohen’s d before and after inclusion of covariates in linear mixed effect models. Results: 11,873 children aged 9-10 years were included from 21 sites in the U.S. Habitual snoring (≥3 nights/week) was reported in 810 (6.8%) children, while non-habitual snoring (1-2 nights/week) was reported in 4,058 (34.2%). In the unadjusted models, the total cognition composite score in habitually snoring children was significantly lower compared to non-snorers (Cohen’s d, 95% confidence interval [CI]; 0.35 [0.28 to 0.42]). These differences were also identified for crystallized (0.34 [0.26 to 0.41]) and fluid composite (0.28 [0.21 to 0.35) scores. They were attenuated substantially following adjustment for covariates (total composite; 0.17 [0.07 to 0.26], crystallized composite; 0.21 [0.10 to 0.33] and fluid composite; 0.13 [0.06 to 0.21]. Similar mitigation was also observed for all domain-specific scores. Interpretation: When adjusted for baseline demographic, anthropometric and socioeconomic characteristics, the association between parent-reported habitual snoring in children and children’s cognitive performance is negligible. 11875/11875Secondary AnalysisShared
Association of Prenatal Opioid Exposure With Precentral Gyrus Volume in ChildrenThis cross-sectional study identifies structural differences of the precentral gyrus among children with reported prenatal opioid exposure compared with children with no reported exposure, controlling for present social factors.11875/11875Secondary AnalysisShared
Behavioral and brain signatures of substance use vulnerability in childhoodThe prevalence of risky behavior such as substance use increases during adolescence; however, the neurobiological precursors to adolescent substance use remain unclear. Predictive modeling may complement previous work observing associations with known risk factors or substance use outcomes by developing generalizable models that predict early susceptibility. The aims of the current study were to identify and characterize behavioral and brain models of vulnerability to future substance use. Principal components analysis (PCA) of behavioral risk factors were used together with connectome-based predictive modeling (CPM) during rest and task-based functional imaging to generate predictive models in a large cohort of nine- and ten-year-olds enrolled in the Adolescent Brain & Cognitive Development (ABCD) study (NDA release 2.0.1). Dimensionality reduction (n=9,437) of behavioral measures associated with substance use identified two latent dimensions that explained the largest amount of variance: risk-seeking (PC1; e.g., curiosity to try substances) and familial factors (PC2; e.g., family history of substance use disorder). Using cross-validated regularized regression in a subset of data (Year 1 Fast Track data; n>1,500), functional connectivity during rest and task conditions (resting-state; monetary incentive delay task; stop signal task; emotional n-back task) significantly predicted individual differences in risk-seeking (PC1) in held-out participants (partial correlations between predicted and observed scores controlling for motion and number of frames [rp]: 0.07-0.21). By contrast, functional connectivity was a weak predictor of familial risk factors associated with substance use (PC2) (rp: 0.03-0.06). These results demonstrate a novel approach to understanding substance use vulnerability, which—together with mechanistic perspectives—may inform strategies aimed at early identification of risk for addiction.11875/11875Secondary AnalysisPrivate
Brain Volume Abnormalities in Youth at High Risk for Depression: Adolescent Brain and Cognitive Development StudyObjective Children of parents with depression are two to three times more likely to develop major depressive disorder than children without parental history; however, subcortical brain volume abnormalities characterizing major depressive disorder risk remain unclear. The Adolescent Brain and Cognitive Development (ABCD) Study provides an opportunity to identify subcortical differences associated with parental depressive history. Method Structural magnetic resonance data were acquired from 9- and 10-year-old children (N = 11,876; release 1.1, n = 4,521; release 2.0.1, n = 7,355). Approximately one-third of the children had a parental depressive history, providing sufficient power to test differences in subcortical brain volume between low- and high-risk youths. Children from release 1.1 were examined as a discovery sample, and we sought to replicate effects in release 2.0.1. Secondary analyses tested group differences in the prevalence of depressive disorders and clarified whether subcortical brain differences were present in youths with a lifetime depressive disorder history. Results Parental depressive history was related to smaller right putamen volume in the discovery (release 1.1; Cohen’s d = −0.10) and replication (release 2.0.1; d = −0.10) samples. However, in release 1.1, this effect was driven by maternal depressive history (d = −0.14), whereas in release 2.0.1, paternal depressive history showed a stronger relationship with putamen volume (d = −0.09). Furthermore, high-risk children exhibited a near twofold greater occurrence of depressive disorders relative to low-risk youths (maternal history odds ratio =1.99; paternal history odds ratio = 1.45), but youths with a lifetime depressive history did not exhibit significant subcortical abnormalities. Conclusion A parental depressive history was associated with smaller putamen volume, which may affect reward learning processes that confer increased risk for major depressive disorder.11875/11875Secondary AnalysisPrivate
Correspondence Between Perceived Pubertal Development and Hormone Levels in 9-10 Year-Olds From the Adolescent Brain Cognitive Development StudyAim: To examine individual variability between perceived physical features and hormones of pubertal maturation in 9–10-year-old children as a function of sociodemographic characteristics. Methods: Cross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study—a multi-site sample of 9–10 year-olds (n = 11,875)—and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels. Results: PDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child’s weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample. Conclusions: Sociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9–10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.11875/11875Primary AnalysisShared
Extracurricular activities, sleep, and screen media activity may be modifiable factors influencing children’s cognitive functioning: evidence from the ABCD studyObjective Fluid cognitive functioning (FCF), or the capacity to learn, solve problems, and adapt to novel situations, is instrumental for academic success, psychological well-being, and adoption of healthy behaviors. Our knowledge concerning factors influencing FCF, including those that may be targeted with interventions to improve outcomes, remains limited. Methods We used a machine learning (ML) framework in conjunction with a large battery of measures from 9,718 youth from the Adolescent Brain Cognitive Development (ABCD) study to identify factors contributing to the observed variability in FCF performance. Youth age-corrected composite FCF score was derived from the National Institutes for Health Toolbox Neurocognitive Battery. A ML pipeline using a stack ensemble of multiple ML algorithms and nested cross-validation to avoid overfitting was conducted to examine factors associated with FCF. Results The identified ML algorithm explained 14.74% of variance (95%CI: 14.53-14.88%) in FCF. Among the most important factors were those that replicated previous research (e.g., socioeconomic factors), as well as novel, potentially modifiable factors, including extracurricular involvement, sleep, and screen media activity. Conclusion Pragmatic and scalable interventions targeting these behaviors may not only enhance cognitive performance but may also protect against the negative impact of socioeconomic and mental health factors on cognitive performance in at-risk youth. 11875/11875Primary AnalysisShared
Involvement in Sports, Hippocampal Volume, and Depressive Symptoms in ChildrenBackground: Recent studies have found that higher levels of exercise are associated with fewer symptoms of depression among young people. In addition, research suggests that exercise may modify hippocampal volume, a brain region that has been found to show reduced volume in depression. However, it is not clear whether this relationship emerges as early as preadolescence. Methods: We examined data from a nation-wide sample of 4191 children ages 9-11 years from the Adolescent Brain and Cognitive Development Study. The parents of the children completed the Child Behavior Checklist, providing data about the child’s depressive symptoms, and the Sports and Activities Questionnaire, which provided data about the child’s participation in 23 sports. Children also took part in a structural MRI scan, providing us with measures of bilateral hippocampal volume. Results: Sports involvement interacted with sex to predict depressive symptoms, with a negative relationship in boys only (t= -5.257, B= -0.115, p< 0.001). Sports involvement was positively correlated with hippocampal volume in both boys and girls (t= 2.810, B= 0.035, p= 0.007). Hippocampal volume also interacted with sex to predict depressive symptoms, with a negative relationship in boys (t= -2.562, B= -0.070, p= 0.010), and served as a partial mediator for the relationship between involvement in sports and depressive symptoms in boys. Conclusions: These findings help illuminate a potential neural mechanism for the impact of exercise on the developing brain and the differential effects in boys versus girls mirror findings in the animal literature. More research is needed to understand the causal relationships between these constructs. 11875/11875Primary AnalysisShared
M145: Structural and Resting State Neural Correlates of Pediatric Obsessive-Compulsive Symptoms in the Adolescent Brain and Cognitive Development StudyBackground: Subclinical Obsessive-Compulsive symptoms (OCS) in childhood increase risk for later onset of Obsessive-Compulsive Disorder (OCD) and related impairment. Studying the neural circuits underlying subclinical OCS may facilitate the identification of neural markers of risk for later OCD as well as potential targets for novel mechanism-based interventions and prevention strategies. Yet, the neural mechanisms underlying OCS and their trajectories over development are poorly understood at present, though are hypothesized to involve differential engagement of task control circuits that underlie attentional and cognitive control processes (e.g. Maia et al., 2008). Dysfunction in these circuits and processes likely contributes to the repetitive thoughts and inappropriate actions that characterize OCS. While a growing literature has probed the neural underpinnings of OCD in children, including ENIGMA mega-analytic findings suggesting larger thalamic volumes in pediatric OCD (Boedhoe et al., 2017), few studies have examined subclinical OCS. One relatively larger study noted associations between OCS and altered gray and white matter volume in healthy children (Suñol et a., 2018). The Adolescent Brain and Cognitive Development (ABCD) provides an opportunity to examine associations between OCS and brain structure in the largest sample of children to date as well as to provide novel insight into associations with resting state connectivity of task control circuits. Methods: Data from the 2.0.1 release (July 2019) of baseline data from the ABCD Study were examined. These data include clinical interviews, cognitive testing, questionnaires, and MRI assessments from a nationally representative sample of N = 11,876 9-10-year-old children. An 8-item subscale for OCS severity (Hudziak et al., 2006) was ascertained from parent report on the Child Behavior Checklist (CBCL). Diagnosis of OCD was based on parent report on the Kiddie-Schedule for Affective Disorders and Schizophrenia for School-Age Children (KSADS). Cognitive performance was assessed using the NIH Toolbox. Of these children, n = 10,585 successfully completed T1 structural imaging that were analyzed using FreeSurfer and that passed ABCD quality control procedures. Resting state data was also collected and analyzed with the ABCD pipelines; n = 8,341 children had  >5 minutes of data retained after quality control. Within and between network connectivity was extracted from regions/networks defined in the Gordon et al., 2016 atlas. Linear mixed effects models were used to examine whether CBCL OCS related to cognitive performance, subcortical volumes, cortical thickness, or resting state connectivity of default mode and task control circuits. Results: N = 5,257 children (44.30%) exhibited non-zero CBCL OCS scores and, as expected, scores were elevated among the N = 898 children who met KSADS criteria for current OCD (b = 2.30, t = 36.82, p < .001, d = 1.35). CBCL OCS associated with worse performance on NIH Toolbox measures of inhibitory control, executive function, and working memory (all t < −2.2, p < .05). No associations between CBCL OCS and brain structure passed correction for multiple comparisons. CBCL OCS associated positively with resting state connectivity between the dorsal attention and default mode networks, the dorsal and ventral attention networks, and ventral attention and cingulo-parietal networks (all t > −2.79, p < .005). CBCL OCS associated negatively with connectivity within the dorsal attention network (t = −2.95, p = .003).11534/11875Secondary AnalysisShared
Minorities' Diminished Returns of Parental Educational Attainment on Adolescents' Social, Emotional, and Behavioral ProblemsAim: To compare racial groups for the effect of parental educational attainment on adolescents' social, emotional, and behavioral problems. Methods: In this cross-sectional study, 10,762 youth from the Adolescent Brain Cognitive Development (ABCD) study were included. The independent variable was parental educational attainment. The main outcomes were 1) anxious and depressed mood, 2) withdrawn and depressed affect, 3) somatic complaints, 4) social and interpersonal problems, 5) thought problems, 6) rule-breaking behaviors, 7) attention problems, and 8) violent and aggressive behaviors. These scores were generated based on parent-reported behavioral problems measured using the Child Behavior Checklist (CBCL). Race and ethnicity were the moderators. Linear regression was used to analyze the ABCD data. Results: Overall, high parental educational attainment was associated with lower scores across all domains. Race and ethnicity showed statistically significant interactions with parental educational attainment on adolescents' fewer social, emotional, and behavioral problems (all domains), net of all confounders, indicating smaller tangible gains from their parental educational attainment for Black and Hispanic compared to non-Hispanic White adolescents. Conclusion: The protective effects of parental education against social, emotional, and behavioral problems are systematically diminished for Hispanic and Black than non-Hispanic White adolescents.11875/11875Secondary AnalysisPrivate
Neural correlates of response inhibition and executive control in children with extensive screen timePreliminary fMRI data reveals that total weekly screen-time interacts with sex in marginally predicting BOLD signal during an emotional N-Back task across frontal and parietal regions and significantly predicts stop signal failed stop performance in the right superior frontal region. However, given the few regions influenced and small effect-sizes, it appears the total screen-time is not likely an important predictor of neural functioning. Thus, fears regarding total screen-time may be overstated. Future research should focus on how screens are used, rather than total amount of time used.11875/11875Secondary AnalysisPrivate
P Factor ModelingBackground: Many contemporary structural models of psychopathology includea single general factor of psychopathology(GFP)or“pfactor”,toaccount for covariation across a wide range of psychiatric symptoms. The Adolescent BrainCognitive Development(ABCD) Studyisalarge longitudinal study of youth that provides a rich opportunity to study the development of the GFP. However, one challenge for the field concerns the variety of approaches formodeling the GFP that have emerged,raising questionsabout how different modeling choices impactestimated GFP scores.Method:We used the ABCD baseline assessment(ages 9-10 years-old; N= 11,875)of the parent-rated Child Behavior Checklist(CBCL)to examine the implicationsof differentstrategies formodeling the GFP. As a preliminary stepwe assessed the psychometric properties of the CBCL. Next, we consideredmodeling the GFP usingitems versus scales;using a prioriCBCL scalesversus data-drivendimensions; and usingbifactor, higher-order, or simple confirmatory factor analytic models. Results:CBCL scales were unidimensional and psychometrically robust. Children’s rank-ordering on the GFPwas stable across models(mean r= .92), and the different GFPscores had similar associations with other problem behavior measuresand general cognitive ability.Similar results were observed forinternalizing and externalizingsubfactorsacross GFP models.Conclusions:The parent-rated CBCL isa sound basis for GFP construction, with children’s GFP, internalizing, and externalizingscoreslargely robust tomodel choicein the ABCD study. 11875/11875Secondary AnalysisPrivate
P Factor Nomological NetworksIntroduction: Structural models of psychopathology consistently identify internalizing (INT) and externalizing (EXT) specific factors as well as a superordinate factor that captures their shared variance, the P factor. Questions remain, however, about meaning of these data-driven dimensions and the interpretability and distinguishability of the larger nomological networks in which they are embedded. Methods: The sample consisted of 11,875 youth aged 9 to 10 years participating in the multisite Adolescent Brain and Cognitive Development (ABCD) Study. P, INT, and EXT were modeled using the parent-rated Child Behavior Checklist (CBCL). Patterns of associations were examined with variables drawn from diverse domains including: demographics, psychopathology, temperament, family history of substance use and psychopathology, school and family environment, and cognitive ability, using instruments based on youth-, parent-, and teacher-report and behavioral task performance. Results: P exhibited a broad pattern of statistically significant associations with risk variables across all domains assessed, including temperament, neurocognition, and social adversity. The specific factors exhibited more domain-specific patterns of associations, with INT exhibiting greater fear/distress and EXT exhibiting greater impulsivity. Conclusions: In this largest study of hierarchical models of psychopathology to date, we found that P, INT, and EXT exhibit well differentiated nomological networks that are interpretable in terms of neurocognition, impulsivity, fear/distress, and social adversity. These networks were, in contrast, obscured when relying on the a priori internalizing and externalizing dimensions of the CBCL scales. Our findings add to the evidence for the validity of P, INT, and EXT as theoretically and empirically meaningful broad psychopathology liabilities. 11875/11875Secondary AnalysisPrivate
Parental Arrest and Youth Outcomes: Is Executive Function a Protective Factor?This study examines relations among parental arrest, youth executive function, and social and behavioral development among children who participated in the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) study (N = 11,875). Participants ranged in age from 9-10 (M = 9.91) and approximately half were girls (47.9%). Controlling for economic hardship, youth who experienced parental arrest had lower mean levels of cognitive flexibility than youth who did not experience parental arrest, but the groups did not differ in terms of mean levels of inhibitory control/attention. Structural equation analyses revealed that inhibitory control/attention served a protective function for boys, but not girls, who experienced parental arrest; higher inhibitory control/attention was associated with fewer externalizing behavior problems among boys. Findings underscore the relevance of executive function in research on parental contact with the criminal justice system, particularly for boys, and illuminate the potential value of investigating executive function-based interventions with this population of children. Findings are also relevant for criminal justice policies and practices.11875/11875Secondary AnalysisPrivate
Parental and Social Factors in relation to Child Psychopathology, Behavior, and Cognitive FunctionParental and social factors have long-term impact on the neurodevelopment of offspring, but tend to highly covary with each other. Thus, it is difficult to parse out which parental and social factor contributes most to neurodevelopmental outcomes. This study aimed to assess clusters of parental and social factors associated with child psychopathology, behavioral problems, and cognition. This study employed the data of 11,875 children (9-to-11 years) from the Adolescent Brain Cognitive Development (ABCD) study. Principal component analysis (PCA) was performed on 39 environmental measures and 30 child behavior and cognitive measures separately to identify clusters of parental and social factors and clusters of child psychopathology, behaviour, and cognition. Regression analysis was used to examine independent effects of each cluster of parental and social factors on child psychopathology, behavioral problems, and cognition. Greater Parent Psychopathology cluster was associated with greater Child Psychopathology cluster. Moreover, greater Socioeconomic Status cluster was associated with greater child General Cognition and Executive Function but less Behavioral Inhibition clusters. Greater Proximal Social Environment and Interaction cluster were associated with less child Impulsive Behavior and Behavioral Inhibition, but greater Behavioral Activation cluster. The environmental clusters related to birth outcomes, maternal tobacco, and drug use were not significantly related to child psychopathology, behavior, and cognition. Our findings suggest that socioeconomic status, parental psychopathology, and social environment and interactions are the strongest risks for behavioral problems and cognitive performance in a general child population. Intervention programs should target modifiable factors within these domains.11875/11875Secondary AnalysisPrivate
Prenatal cannabis exposure and childhood outcomes: Results from the ABCD Study®Importance: In light of increasing cannabis use among pregnant women, the Surgeon General of the United States recently issued an advisory against the use of marijuana during pregnancy. Objective: To determine whether cannabis use during pregnancy is associated with adverse outcomes among offspring. Design: Cross-sectional analysis of the baseline session of the ongoing longitudinal Adolescent Brain and Cognitive Development (ABCD) Study℠. Setting: Data were collected from 22 sites across the United States between 2016 and 2018. Participants: Children ages 9-11 (n=11,489) and their parent/caregiver. Exposure: Prenatal cannabis exposure prior to and following maternal knowledge of pregnancy. Main Outcomes and Measures: Child psychopathology symptomatology (i.e., psychotic-like experiences (PLEs) and internalizing, externalizing, attention, thought, and social problems), cognition, sleep, birth weight, gestational age at birth, body mass index (BMI), and brain structure (i.e., total intracranial volume, white matter volume, gray matter volume). Covariates included familial (e.g., income, familial psychopathology), pregnancy (e.g., prenatal exposure to alcohol and tobacco), and child (e.g., substance use) variables. Results: Among 11,489 children (age 9.9±0.6 years; 47.78% female), 655 (5.70%) were prenatally exposed to cannabis. Relative to no exposure, cannabis exposure only prior to (n=413; 3.59%) and following (n=242; 2.11%) maternal knowledge of pregnancy were associated with greater offspring psychopathology characteristics (i.e., PLEs and internalizing, externalizing, attention, thought, social, and sleep problems) and BMI as well as lower cognition and gray matter volume (all |ßs|>0.02, psfdr<0.03). Only exposure after knowledge of pregnancy was associated with lower birth weight and total intracranial and white matter volumes relative to no exposure and exposure only before knowledge (|ßs|>0.02, ps<0.002). When including potentially confounding covariates, exposure after maternal knowledge of pregnancy remained associated with greater PLEs and externalizing, attention, thought, and social problems (all |ßs|>0.02, psfdr<0.02). Exposure only prior to maternal knowledge of pregnancy did not differ from no exposure on any outcomes when considering potentially confounding variables (all |ßs|<0.02, psfdr>0.70). Conclusions and Relevance: Prenatal cannabis exposure and its correlated factors are associated with greater risk for psychopathology during middle childhood. Cannabis use during pregnancy should be discouraged. 11875/11875Secondary AnalysisShared
Rates of Incidental Findings in Brain Magnetic Resonance Imaging in ChildrenImportance Incidental findings (IFs) are unexpected abnormalities discovered during imaging and can range from normal anatomic variants to findings requiring urgent medical intervention. In the case of brain magnetic resonance imaging (MRI), reliable data about the prevalence and significance of IFs in the general population are limited, making it difficult to anticipate, communicate, and manage these findings. Objectives To determine the overall prevalence of IFs in brain MRI in the nonclinical pediatric population as well as the rates of specific findings and findings for which clinical referral is recommended. Design, Setting, and Participants This cohort study was based on the April 2019 release of baseline data from 11 810 children aged 9 to 10 years who were enrolled and completed baseline neuroimaging in the Adolescent Brain Cognitive Development (ABCD) study, the largest US population-based longitudinal observational study of brain development and child health, between September 1, 2016, and November 15, 2018. Participants were enrolled at 21 sites across the US designed to mirror the demographic characteristics of the US population. Baseline structural MRIs were centrally reviewed for IFs by board-certified neuroradiologists and findings were described and categorized (category 1, no abnormal findings; 2, no referral recommended; 3; consider referral; and 4, consider immediate referral). Children were enrolled through a broad school-based recruitment process in which all children of eligible age at selected schools were invited to participate. Exclusion criteria were severe sensory, intellectual, medical, or neurologic disorders that would preclude or interfere with study participation. During the enrollment process, demographic data were monitored to ensure that the study met targets for sex, socioeconomic, ethnic, and racial diversity. Data were analyzed from March 15, 2018, to November 20, 2020. Main Outcomes and Measures Percentage of children with IFs in each category and prevalence of specific IFs. Results A total of 11 679 children (52.1% boys, mean [SD] age, 9.9 [0.62] years) had interpretable baseline structural MRI results. Of these, 2464 participants (21.1%) had IFs, including 2013 children (17.2%) assigned to category 2, 431 (3.7%) assigned to category 3, and 20 (0.2%) assigned to category 4. Overall rates of IFs did not differ significantly between singleton and twin gestations or between monozygotic and dizygotic twins, but heritability analysis showed heritability for the presence or absence of IFs (h2 = 0.260; 95% CI, 0.135-0.387). Conclusions and Relevance Incidental findings in brain MRI and findings with potential clinical significance are both common in the general pediatric population. By assessing IFs and concurrent developmental and health measures and following these findings over the longitudinal study course, the ABCD study has the potential to determine the significance of many common IFs.11875/11875Secondary AnalysisPrivate
Risk of lead exposure, subcortical brain structure, and cognition in a large cohort of 9- to 10-year-old childrenBackground: Lead, a toxic metal, affects cognitive development at the lowest measurable concentrations found in children, but little is known about its direct impact on brain development. Recently, we reported widespread decreases in cortical surface area and volume with increased risks of lead exposure, primarily in children of low-income families. Methods and Findings: We examined associations of neighborhood-level risk of lead exposure with cognitive test performance and subcortical brain volumes. We also examined whether subcortical structure mediated associations between lead risk and cognitive performance. Our analyses employed a cross-sectional analysis of baseline data from the observational Adolescent Brain Cognitive Development (ABCD) Study. The multi-center ABCD Study used school-based enrollment to recruit a demographically diverse cohort of almost 11,900 9- and 10-year-old children from an initial 22 study sites. The analyzed sample included data from 8,524 typically developing child participants and their parents or caregivers. The primary outcomes and measures were subcortical brain structure, cognitive performance using the National Institutes of Health Toolbox, and geocoded risk of lead exposure. Children who lived in neighborhoods with greater risks of environmental lead exposure exhibited smaller volumes of the mid-anterior (partial correlation coefficient [rp] = 0.040), central (rp = 0.038), and mid-posterior corpus callosum (rp = 0.035). Smaller volumes of these three callosal regions were associated with poorer performance on cognitive tests measuring language and processing speed. The association of lead exposure risk with cognitive performance was partially mediated through callosal volume, particularly the mid-posterior corpus callosum. In contrast, neighborhood-level indicators of disadvantage were not associated with smaller volumes of these brain structures. Conclusions: Environmental factors related to the risk of lead exposure may be associated with certain aspects of cognitive functioning via diminished subcortical brain structure, including the anterior splenium (i.e., mid-posterior corpus callosum). 11875/11875Primary AnalysisShared
Screen Time and Other Determinants of Mental Health Predicting Emerging Psychotic-like Experiences in 9-10 Year Old ChildrenIMPORTANCE: Worsening child psychotic-like experiences (PLEs) are risk factors of poor future mental health including full blown psychotic illness. Identifying readily assessable indicators for worsening PLEs are therefore of great interest. OBJECTIVE: To examine relationships between a set of indicators (behaviors and stressors) previously associated with mental health (screen time, school environment, neighborhood safety, family conflict, parental (caregiver) acceptance, and sleep habits) and worsening PLE severity. DESIGN, SETTING, AND PARTICIPANTS: This prospective study included 4296 children (mean age 10 years (standard deviation = 0.7)), 52% boys) from the Adolescent Brain and Cognitive Development study. MAIN OUTCOMES AND MEASURES: The primary outcome was 12-month distress score of the Prodromal-Questionnaire Brief-Child (PQ-BC) Version, modeled after controlling for age, sex, race, ethnicity, parental marital status/education, and baseline PQ-BC severity. RESULTS: Significant baseline indicators of worsening PLE severity by 12-month follow-up included high screen time (46% increase for ≥ 4.6 hours/day (vs. 0 to 1.5 hours/day), 95% CI = 28% to 66%), living in an unsafe neighborhood (30% increase in most unsafe (vs. safest), 95% CI = 6% to 61%), high family conflict (30% increase with 2-3 and 16% increase with ≥ 4 "yes" responses to questions re: conflict (vs. none), 95% CIs = 16% to 46% and 2 to 32%, respectively), lack of parental acceptance (13% decrease in group with highest possible acceptance (vs. low group), 95% CI = -24% to -2%), and sleeping < 9 hours/night (16% increase (vs. sleeping 9-11 hours/night), 95% CI = 7% to 27%). Examining screen time variants, significant associations were observed with time watching videos (33% increase for ≥ 1.2 hours/day (vs. 0 to 0.1 hours/day), 95% CI = 16% to 52%) and time texting (29% decrease when texting 0.1-0.2 hours/day (vs. none), 95% CI = -41% to -15%). An interaction between sex and video chatting was also observed, as video chatting was a negative indicator in girls but not boys. CONCLUSIONS AND RELEVANCE: Screen time, crime, and family environment were identified as future indicators of mental health risk. These results suggest the value of prospective evaluation of behavior and stressors in identifying at risk groups. 11875/11875Primary AnalysisShared
Shared and unique features of brain network organization brain network characteristics predict individual differences in children's cognition, mental health and personalityMany psychiatric disorders emerge during adolescence, so studying behavioral risk factors in healthy children is important. Functional connectivity (FC) has emerged as a powerful tool for studying brain-behavior relationship. Here, we used rest-FC and task-FC to predict multiple behavioral measures in the Adolescent Brain Cognitive Development (ABCD) study. We also explored the existence of shared and unique network features supporting prediction across behavioral classes: cognition, personality and mental health.11875/11875Secondary AnalysisPrivate
Sleep disorders predict the one-year onset, persistence, but not remission of psychotic experiences in 10-11 year old children: a longitudinal analysis of the ABCD cohort dataSleep problems have been reliably associated with psychotic experiences in adults and have been suggested as target for intervention. However, the relationship between sleep disorder and psychotic experiences in children has not been extensively studied despite the potential for guiding intervention. The Adolescent Brain Cognitive Development (ABCD) dataset, containing baseline and one-year follow-up data of over 11,000 10-11 year olds, was utilised to investigate this relationship. More specifically, a set of pre-registered multi-level regression models were applied to test whether a) baseline sleep disorder predicts baseline psychotic experiences cross-sectionally; b) baseline sleep disorder predicts psychotic experiences one year later; c) the persistence of sleep disorder predicts the persistence psychotic experiences at one year; d) the remission of sleep disorder predicts the remission of psychotic experiences. After controlling for potential confounders, sleep disorder was associated with psychotic experiences cross-sectionally (OR=1.40, 95% CI 1.20-1.63), at one-year follow-up (OR=1.32, 95% CI 1.11-1.57), and the persistence of sleep disorder predicted the persistence of psychotic experiences (OR=1.72, 95% CI 1.44-2.04). However, remission of sleep problems did not predict remission of psychotic experiences (OR=1.041, 95% CI 0.80-1.35). In all models where an association was found, sleep was one of the two strongest predictors of psychotic experiences (with stimulant medication being the other). The results indicate that sleep problems in children are common and strongly associated with psychotic experiences but the lack of co-remission raises questions about the mechanism of association. However given existing evidence in adults, further investigation and interest in sleep as a preventative mental health intervention in this age group is warranted.11875/11875Secondary AnalysisShared
Suicide ideation and neurocognition among 9- and 10-year old children in the Adolescent Brain Cognitive Development (ABCD) StudyObjective: During the past decade, the pediatric suicide rate has nearly tripled. Yet, little is known about suicide behavior (SB) in children. Identification of risk factors associated with SB during childhood may be critical to preventing future attempts. The purpose of this study was to examine the relationship between neurocognitive performance and suicide ideation (SI) in children. Method: The present study utilized baseline data from 11,875 participants in the Adolescent Brain Cognitive Development (ABCD) study, a longitudinal study that follows nine- and ten-year-old children through late adolescence to examine factors that influence developmental trajectories. Suicidality was assessed by the Kiddie Schedule for Affective Disorder and Schizophrenia (KSADS) suicide module completed by the parent. Neurocognitive ability was assessed using the NIH Toolbox Cognition measures administered to the youth. Results: Children with a history of SI reported by their parent or concordant parent and youth report of SI demonstrated lower performance on the NIH Toolbox Picture Sequence Memory Test compared to children without SI. The difference in performance on the memory task remained significant when including demographic characteristics, family history of suicide, and internalizing symptoms in the model as covariates. Conclusions: To our knowledge, this is the first study to identify decreased episodic memory in children with SI. These findings are similar to results from adult and adolescent studies which have reported decreased memory performance among suicide attempters. Deficits in episodic memory may impact a child’s ability to problem-solve and generate potential future outcomes, which may increase the risk for SB. Early identification of memory deficits in children may inform suicide prevention and intervention efforts. 11875/11875Secondary AnalysisShared
The Associations between Religion and Impulsivity in the Adolescent Brain Cognitive Development (ABCD) StudyImpulsivity is associated with increased risk for externalizing symptoms and disorders across the lifespan. Religiosity may be a protective factor for the consequences of impulsivity. The purpose of this study was to examine in children whether (1) religion is associated with decreased impulsivity, and (2) religiosity is a protective factor in the association between impulsivity and externalizing symptoms. Data were from Wave 1 of the Adolescent Brain Cognitive Development (ABCD) study, a nationally representative longitudinal study of children (aged 9-10, N =11,875) in the United States. Impulsivity was assessed via the UPPS-P Impulsive Behavior Scale, BIS/BAS (behavioral inhibition/behavioral activation system) scale, and the Cash-Choice task. Externalizing symptoms were assessed via the Child Behavior Checklist. Structural equation models examined various dimensions of religiosity (religious affiliation, service attendance, and importance) as moderators of the relationship between impulsivity and externalizing symptoms. Results showed greater religious attendance, but not religious importance or having any religious affiliation, was significantly associated with decreased impulsivity (r = -0.03, p = .02). Differences in impulsivity were observed between certain religious affiliations: Christian religious affiliation was associated with increased impulsivity as compared to other religions (r = 0.06, p < .001). Religiosity did not moderate associations between impulsivity and externalizing symptoms. These findings suggest impulsivity and some domains of religiosity are related in children. Religiosity was not protective of the association between impulsivity and externalizing symptoms at this age. Future studies could use a longitudinal design to better understand how these relationships form across the lifespan.11875/11875Secondary AnalysisShared
White Matter Tract Integrity, Involvement in Sports, and Depressive Symptoms in ChildrenWhite matter tract integrity, measured via fractional anisotropy (FA), may serve as a mediating variable between exercise and depression. To study this, we examined data from 3973 children participating in the ABCD study. Parents of children completed the Sports and Activities questionnaire and the Child Behavior Checklist, and children completed a diffusion MRI scan, providing information about the FA of the parahippocampal cingulum and fornix. Results showed that involvement in sports was associated with reduced depression in boys. The number of activities and sports that a child was involved in was negatively related to FA of the left fornix but was unrelated to FA of other tracts. FA of these white matter tracts was also unrelated to depressive symptoms. This suggests that while white matter tract integrity is associated with exercise, it may not be part of a pathway linking exercise to depression levels in preadolescent boys.11875/11875Primary AnalysisShared
Behavioral and Neural Signatures of Working Memory in ChildhoodWorking memory is a foundational cognitive ability that changes over time and varies across individuals. Here, we analyze data from over 11,500 9- to 10-year-olds to establish relationships between working memory, other cognitive abilities, and frontoparietal brain activity during a working memory challenge, but not during other cognitive challenges. Our results lay the groundwork for assessing longitudinal changes in working memory and predicting later academic and other real-world outcomes.11874/11874Secondary AnalysisShared
Genetic and Environmental Influences on Executive Functions and Intelligence in the ABCD StudyExecutive functions (EFs) and intelligence (IQ) are phenotypically correlated and heritable; however, they show variable genetic correlations in twin studies spanning childhood to middle age. We analyzed data from over 11,000 children (9-10-year-olds, including 749 twin pairs) in the Adolescent Brain Cognitive Development (ABCD) Study to examine the phenotypic and genetic relations between EFs and IQ in childhood. We identified two EF factors – Common EF and Updating-Specific, which were both related to IQ (rs = .64-.81). Common EF and IQ were heritable (53-67%), and their genetic correlation (rG = .86) was not significantly different than 1. These results suggest that EFs and IQ are phenotypically but not genetically separable in middle childhood.11874/11874Secondary AnalysisShared
History of depression, elevated BMI, and waist-to-height ratio in pre-adolescent childrenObjective: To evaluate history of depression and self-injurious thoughts and behaviors as predictors of elevated BMI and elevated waist-to-height ratio in pre-adolescents. Methods: Baseline data were evaluated from a large, nationally representative cohort study of 9- and 10-year-old children (unweighted n = 11,875), the Adolescent Brain and Cognitive Development (ABCD) study. Results: In the weighted sample, 10.6 % of children had a history of depression, 7.0% had engaged in non-suicidal self-injury, 13.1% had experienced suicidal ideation in their lifetime, and 1.1% had a history of attempted suicide. 34.1% of children had an elevated BMI in the overweight or obese range and 31.9% of children had a waist-to-height ratio > 0.5. In multivariate analyses, history of depression was associated with elevated BMI and waist-to-height ratio. Furthermore, sex interactions were found; girls with a history of depression were more likely to have an elevated BMI (OR 1.47, 95% CI: 1.24-1.74, p < 0.001) and elevated waist-to-height ratio (OR 1.48, 95% CI: 1.18-1.86, p = 0.002) than girls without a history of depression, but no differences were observed between boys with and without a history of depression. Self-injurious thoughts and behaviors were not associated with elevated BMI or elevated waist-to-height. Conclusions: In our study, nine- and ten-year-old girls with a history of depression were more likely to have an elevated BMI and elevated waist-to-height ratio than girls with no history of depression. These results provide important clinical context in caring for pre-adolescents with a history of depression. 11874/11874Secondary AnalysisPrivate
Prenatal cannabis exposure and sleep outcomes in children 9-10 years of age in the Adolescent Brain Cognitive Development ℠ Study.Objectives: Analyze the associations between prenatal cannabis exposure and child sleep outcomes. Methods: Data from the Adolescent Brain Cognitive Development Study (ABCD Study®) study was used to determine whether maternal reports of prenatal cannabis use were associated with child sleep outcomes among 11,875 children ages 9-10 controlling for covariates including prenatal substance exposure, mother’s education, combined household income, parental marital status, race, child sex, and child age. Results: Endorsement of any prenatal cannabis use was associated with symptoms of disorders of initiating and maintaining sleep, disorders of arousal, sleep wake disorders, disorders of excessive somnolence, and a summed sleep disorder score (all β > 0.10 and p < 0.03) while frequency of prenatal daily cannabis use was significantly associated with disorders of excessive somnolence (β = 0.29, p = 0.03). Conclusions: Although causality is not established, the results suggest potential long-term effects of prenatal cannabis exposure on sleep and the prudence of abstinence from cannabis use while pregnant. 11874/11874Primary AnalysisShared
Mediating Role of the Default Mode Network on Parental Acceptance/Warmth and Psychopathology in YouthHumans are reliant on their caregivers for an extended period of time, offering numerous opportunities for environmental factors, such as parental attitudes and behaviors, to impact brain development. The default mode network (DMN) is a neural system encompassing the medial prefrontal cortex, posterior cingulate cortex, precuneus, and temporo-parietal junction, which is implicated in aspects of cognition and psychopathology. Delayed DMN maturation in children and adolescents has been associated with greater general dimensional psychopathology, and positive parenting behaviors have been suggested to serve as protective mechanisms against atypical DMN development. The current study aimed to extend the existing research by examining whether within-DMN resting-state functional connectivity (RSFC) would mediate the relation between parental acceptance/warmth and youth psychopathology. Data from the Adolescent Brain and Cognitive Development (ABCD) study, which included a community sample of 9,058 children ages 9-10.9 years, were analyzed to test this prediction. Results from the analysis demonstrated a significant mediation, where greater parental acceptance/warmth predicted greater within-DMN RSFC, which in turn predicted lower psychopathology. Our study provides preliminary support for the notion that positive parenting traits may reduce the risk for psychopathology in youth through their influence on the DMN. Due to the cross-sectional nature of this study, we can only draw correlational inference; therefore, these relationships should be tested longitudinally in future investigations.11873/11873Primary AnalysisPrivate
Towards Reproducible Brain-Wide Association StudiesMagnetic resonance imaging (MRI) continues to drive many important neuroscientific advances. However, progress in uncovering reproducible associations between individual differences in brain structure/function and behavioral phenotypes (e.g., cognition, mental health) may have been undermined by typical neuroimaging sample sizes (median N=25)1,2. Leveraging the Adolescent Brain Cognitive Development (ABCD) Study3, we estimated the effect sizes and reproducibility of these brain-wide associations studies (BWAS) as a function of sample size. The very largest, replicable brain-wide associations for univariate and multivariate methods were r=0.14 and r=0.34, respectively. In smaller samples, typical for brain-wide association studies (BWAS), irreproducible, inflated effect sizes were ubiquitous, no matter the method (univariate, multivariate). Until sample sizes started to approach consortium-levels, BWAS were underpowered and statistical errors assured. Multiple factors contribute to replication failures4–6; here, we show that the pairing of small brain-behavioral phenotype effect sizes with sampling variability is a key element in wide-spread BWAS replication failure. Brain-behavioral phenotype associations stabilize and become more reproducible with sample sizes of N⪆2,000. While investigator-initiated brain-behavior research continues to generate hypotheses and propel innovation, large consortia are needed to usher in a new era of reproducible human brain-wide association studies.11872/11872Secondary AnalysisPrivate
Functional connectome mediated the associations between Sleep disturbance and mental healthAbstract: Background: Many types of mental disorders, including mood, attention, and anxiety disorders, share common symptoms such as sleep disturbance. Although sleep disturbance typically precedes the onset of various mental disorders in youth, a bi-directional influence between sleep disturbance and mental disorder has also been reported. The goal of this study is to explore potentially shared neural mechanisms between sleep disturbance and mental disorders in pre-adolescents, which can be beneficial for early interventions. Methods In this study, we included a dataset of 9350 9-10 year-old children from Adolescent Brain and Cognitive Development (ABCD) Study. Linear mixed-effects models and mediation analysis were used to test the associations between network connectivity and sleep disturbance, mental health, and cognition, after controlling for age, sex at birth, race, pubertal status, data collection sites, and family relatives. Results Out of 338 unique connectivity measurements tested, both higher total sleep disturbance (TSD) from Sleep Disturbance Scale and higher total problems (TP) from Child Behavior Checklist associated with higher between-network connectivity between default mode network (DMN) and dorsal attentional network (DAN), and lower within-network connectivity measurements (DMN-DMN and DAN-DAN) (all p<0.05 FDR corrected; all R2 > 0.02). Mediation analysis revealed that all three connectivity measurements mediated the effects of TSD on TP (all bootstrapped p<0.005). In contrast, only DMN-DMN mediated the effect of TP on TSD (bootstrapped p<0.05). Follow-up partial correlation analyses showed that DMN-DAN and DAN-DAN, but not DMN-DMN, were significantly correlated with total cognitive composite score from NIH toolbox (r = -0.0363 and 0.0237, respectively). Conclusions By establishing three-way relationships between network connectivity, sleep disturbance, and mental disorder, this study shed light on a common neural mechanism through which sleep disturbance and mental problems may affect each other. Different from normal development, a less segregated DMN and DAN, perhaps due to sleep disturbance, is associated with negative outcomes on mental well-being and cognition. 11871/11871Secondary AnalysisPrivate
"I Don't Understand": Who Is Missed When We Ask Early Adolescents, "Are You Transgender"?NA11870/11870Secondary AnalysisShared
Birth weight and childhood psychopathology in the ABCD cohort: association is strongest for attention problems and is moderated by sex.Many studies have shown low birth weight is associated with psychopathology later in life, particularly attention-deficit/hyperactivity disorder (ADHD). The association is well-replicated, independent from a variety of potential familial confounds, and follows a dose-response curve (decreasing birth weight linked with increasing odds of disorder). However, the specificity of the association to attention problems is called into question by the extent of comorbidity in ADHD, and recent findings that the association is stronger for autism than ADHD. We test the relative dose-response strength of birth weight on multiple aspects of behavior to explore specificity of the effect to attention problems. We also test recent suggestions that the association between birth weight and attention problems is driven by males. Our sample consisted of 9,076 children aged 9-10 from the United States (Adolescent Brain Cognitive Development study). Outcomes included 9 problem-scales and the total problems scale from the Child Behavior Checklist (CBCL). Attention problems were the most strongly associated with birth weight after controlling for gestational age, potential familial confounds, and multiple testing, supporting the outcome-specificity of this association. Contrary to recent registry-based findings, an association between birth weight and an autism scale was not observed. Sex moderated the effect of birth weight on total problems, attention problems and aggressive behavior such that these inverse associations were strongly driven by males. Our findings have strong implications for sex-specific prediction and etiological models of childhood psychopathology.11870/11870Secondary AnalysisShared
African American Children’s Diminished Returns of Subjective Family Socioeconomic Status on Fun SeekingBackground: Reward sensitivity (fun-seeking) is a risk factor for a wide range of high-risk behaviors. While high socioeconomic status (SES) is known to reduce reward sensitivity and associated high-risk behaviors, less is known about the differential effects of SES on reward sensitivity. It is plausible to expect weaker protective effects of family SES on reward sensitivity in racial minorities, a pattern called Minorities’ Diminished Returns (MDRs). Aim: We compared Caucasian and African American (AA) children for the effects of subjective family SES on children’s fun-seeking. Methods: This was a cross-sectional analysis of 7061 children from the Adolescent Brain Cognitive Development (ABCD) study. The independent variable was subjective family SES. The main outcome was children’s fun-seeking measured by the behavioral approach system (BAS) and behavioral avoidance system (BIS). Age, gender, marital status, and household size were the covariates. Results: In the overall sample, high subjective family SES was associated with lower levels of fun-seeking. We also found a statistically significant interaction between race and subjective family SES on children’s fun-seeking in the overall sample, suggesting that high subjective family SES is associated with a weaker effect on reducing fun-seeking among AA than Caucasian children. In race-stratified models, high subjective family SES was protective against fun-seeking of Caucasian but not AA children. Conclusion: Subjective family SES reduces the fun-seeking for Caucasian but not AA children.11867/11867Secondary AnalysisPrivate
Family Income Mediates the Effect of Parental Education on Adolescents’ Hippocampus Activation During an N-Back Memory TaskAbstract: Introduction: Hippocampus, a medial temporal lobe structure, has significant implications in memory formation and learning. Although hippocampus activity is believed to be affected by socioeconomic status (SES), limited knowledge exists on which SES indicators influence hippocampus function. Purpose: This study explored the separate and combined effects of three SES indicators, namely parental education, family income, and neighborhood income, on adolescents’ hippocampus activation during an N-Back memory task. As some of the effects of parental education may be through income, we also tested if the effect of parental education on hippocampus activation during our N-Back memory task is mediated by family or neighborhood income. Methods: The Adolescent Brain Cognitive Development (ABCD) study is a national multi-center investigation of American adolescents’ brain development. Functional magnetic resonance imaging (fMRI) data of a total sample of 3067 9–10-year-old adolescents were used. The primary outcome was left- hippocampus activation during the N-Back memory task (mean beta weight for N-Back run 1 2 back versus 0 back contrast in left hippocampus). The independent variable was parental education. Family income and neighborhood income were two possible mediators. Age, sex, and marital status were the covariates. To test mediation, we used hierarchical linear regression models first without and then with our mediators. Full mediation was defined according to Kenny. The Sobel test was used to confirm statistical mediation. Results: In the absence of family and neighborhood income in the model, higher parental educational attainment was associated with lower level of left hippocampus activation during the N-Back memory task. This effect was significant while age, sex, and marital status were controlled. The association between parental educational attainment and hippocampus activation during the N-Back memory task was no more significant when we controlled for family and neighborhood income. Instead, family income was associated with hippocampus activation during the N-Back memory task. These findings suggested that family income fully mediates the effect of parental educational attainment on left hippocampus activation during the N-Back memory task. Conclusions: The effect of parental educational attainment on adolescents’ hippocampus activation during an N-Back memory task is fully explained by family income. That means low family income is why adolescents with low-educated parents show highlighted hippocampus activation during an N-Back memory task. Given the central role of the hippocampus in learning and memory and as income is a modifiable factor by tax and economic policies, income-redistribution policies, fair taxation, and higher minimum wage may have implications for promotion of adolescent equality and social justice. There is a need to focus on family-level economic needs across all levels of neighborhood income. 11867/11867Secondary AnalysisPrivate
Obesity and Eating Disorder Disparities among Sexual and Gender Minority YouthObesity and eating disorders (EDs) in youth are prevalent, associated with medical and psychosocial consequences, and may persist into adulthood; therefore identifying subgroups of youth vulnerable to one or both conditions is critical. One group that may be at-risk for obesity and disordered eating is sexual and gender minorities (SGM; those who identify as lesbian, gay, bisexual, and/or transgender or whose sexual orientation or gender identity/expression do not conform to societal conventions). Though SGM identities may begin in childhood and early adolescence, many studies assess older adolescents and adults, and rely upon self-reported weight and eating pathology. Given the adverse sequelae of obesity and EDs, the identification of disparities among SGM youth has implications for clinical practice and public health.11852/11852Secondary AnalysisShared
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Analyzing prenatal cannabis exposure and its impacts on frontolimbic white matter pathway development Abstract: Many pregnant women use cannabis to soothe symptoms of many discomforts of pregnancy, such as morning sickness and anxiety. This is significant due to recent research which has shown that fetal neurodevelopment may be disrupted by cross placental transfer of cannabis constituents, such as delta-9-tetrahydrocannabinol (THC). One of the impacts of this cross placental transfer of THC is the disruption of the endocannabinoid system, which can have adverse effects on the neurodevelopment of the child, these effects could have implications across the child’s lifespan. Previous research has shown that endocannabinoids and cannabinoid receptors are expressed in the fetal brain, including the white matter, as early as five weeks into gestation. We used the data from the ongoing nationwide NIH Adolescent Brain Cognitive Development (ABCD) study to examine the impact of prenatal cannabis use on the integrity of frontolimbic white matter pathways. We focused on frontolimbic pathways since they are known to be susceptible to cannabis use. Variations in endocannabinoid signaling has shown to be important for modulating frontolimbic development. This study reports on diffusion tensor imaging (DTI) data collected from 10,579 youth (M ± SD = 9.92 ± 0.62 years; 48% female; 52% White, 12.5% Black, 18.7% Hispanic, 1.8% Asian, 5.3% Other). Prenatal cannabis use was measured via a parent retrospective report. Fractional anisotropy (FA) was estimated for frontolimbic white matter tracts. In this sample, 3.9% of parents (n = 410) reported using cannabis prior to knowledge of pregnancy, and 1.1% (n = 119) reported using after knowledge. We found that prenatal cannabis exposure before knowledge of pregnancy was associated with lower FA in the left parahippocampal cingulum, left inferior-fronto-occipital fasciculus, and the right and left fornices. After FDR correction and including covariates (i.e., race, gender, ethnicity) only the right fornix remained significant (F [1, 10578] = 15.69, p < 0.001, 𝜷 = -0.038, r2 = 0.001, p < 0.001). Prenatal cannabis exposure after knowledge of pregnancy was associated with lower FA in the right and left fornices, right and left cingulate cingulum, right parahippocampal cingulum, and the left uncinate. After FDR correction and adding covariates, none of these tracts remained significant. These data add to the growing body of evidence linking prenatal cannabis exposure to altered neurodevelopment. These findings indicate that variation in frontolimbic white matter pathways may explain the link between prenatal cannabis exposure and elevated risk of mental health outcomes in offspring and should be used to encourage women to abstain from cannabis use during pregnancy or pre-conception.11812/11812Secondary AnalysisShared
Screen time is associated with mental health, academic outcomes, and peer relationships in the Adolescent Brain Cognitive Development ℠ StudyWe are using screens more than ever. The high rate of electronic media use among children and adolescents begs the question: is screen time harming our youth? The current study draws from a nationwide sample of 11,875 participants in the United States, aged 9 to 10 years, from the Adolescent Brain Cognitive Development Study (ABCD Study®). We investigate relationships between screen time and mental health, behavioral problems, academic performance, sleep habits, and peer relationships by conducting a series of correlation and regression analyses, controlling for SES and race/ethnicity. We find that more screen time is associated with worse mental health, increased behavioral problems, decreased academic performance, and poorer sleep, but heightened quality of peer relationships. However, effect sizes associated with screen time and the various outcomes were small; SES was more strongly associated with each outcome measure. Our analyses do not establish causality and the small effect sizes observed suggest that while adolescents spend a considerable amount of time behind screens, screen time is unlikely to be directly harmful to 9-and-10-year-old children. 11792/11792Primary AnalysisShared
Relationship between obstructive sleep disordered breathing and childhood behavioral problems is mediated by frontal lobe structureParents frequently report behavioral problems among children who snore. Our understanding of the relationship between symptoms of obstructive sleep disordered breathing (oSDB)—e.g. snoring—and childhood behavioral problems attributable to brain structural alterations is limited. Therefore, we examined the relationships among oSDB symptoms, problem behaviors and brain morphometry in a diverse dataset comprising 10,140 preadolescents. We demonstrate that the symptoms of oSDB predicted composite and domain-specific behavioral measures. Cortical morphometric alterations demonstrating the strongest negative associations with oSDB symptoms are most pronounced within the frontal lobe. The relationships between oSDB symptoms and behavioral measures are mediated by significantly smaller volumes of multiple frontal lobe regions. These results provide population-level evidence for regional structural alterations in cortical gray matter accompanying problem behaviors in children with oSDB. 11752/11752Secondary AnalysisPrivate
Structural alterations in the frontal lobe mediate the impact of snoring and associated symptoms on childhood behaviorParents frequently report behavioral problems among children who snore. Our understanding of the relationship between symptoms of obstructive sleep disordered breathing (oSDB)—e.g. snoring—and childhood behavioral problems attributable to brain structural alterations is limited. Therefore, we examined the relationships among oSDB symptoms, problem behaviors and brain morphometry in a diverse dataset comprising 10,140 preadolescents. We demonstrate that the symptoms of oSDB strongly predicted composite and domain-specific behavioral measures. Cortical morphometric alterations demonstrating the strongest negative associations with oSDB symptoms were most pronounced within the frontal lobe. The relationships between oSDB symptoms and behavioral measures were mediated by significantly smaller volumes of multiple frontal lobe regions. These results provide population-level evidence for regional structural alterations in cortical gray matter accompanying problem behaviors in children with oSDB. Timely recognition and treatment of oSDB may ameliorate these changes and the associated neurobehavioral morbidity while the frontal lobe still retains age-dependent plasticity.11752/11752Secondary AnalysisPrivate
Limits to the generalizability of resting-state fMRI studies of youth: An examination of ABCD Study® baseline dataThis study examined characteristics of 9- to 10-year-old participants recommended (REC) and not recommended (N-REC) for resting-state fMRI analyses due to data quality in the baseline ABCD Study®. REC (n=4,356) and N-REC (n=7,437) were compared using Chi-squared analyses and t-tests. Linear mixed models examined relationships between demographic and clinical characteristics and average head motion in REC. Relative to N-REC, REC included more females, Caucasians, and youth with married parents, higher parent education, and greater household incomes (ORs=1.32-1.42). REC youth were also older and had higher neurocognitive skills, lower BMIs, and fewer externalizing and neurodevelopmental problems (ds=0.12-0.30). Within REC, several clinical and demographic characteristics related to motion. REC data may be less representative of the general population and motion may remain a confound within REC. Future rs-fMRI studies of youth should consider these limitations in the design and analysis stages.11741/11741Secondary AnalysisPrivate
Genome-wide association analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 peopleThe use of spoken and written language is a capacity that is unique to humans. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30-80%, depending on the trait. The relevant genetic architecture is complex, heterogeneous, and multifactorial, and yet to be investigated with well-powered studies. Here, we present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures: word reading, nonword reading, spelling, phoneme awareness, and nonword repetition, with total sample sizes ranging from 13,633 to 33,959 participants aged 5-26 years (12,411 to 27,180 for those with European ancestry, defined by principal component analyses). We identified a genome-wide significant association with word reading (rs11208009, p=1.098 x 10-8) independent of known loci associated with intelligence or educational attainment. All five reading-/language-related traits had robust SNP-heritability estimates (0.13–0.26), and genetic correlations between them were modest to high. Using genomic structural equation modelling, we found evidence for a shared genetic factor explaining the majority of variation in word and nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence and educational attainment. A multivariate GWAS was performed to jointly analyse word and nonword reading, spelling, and phoneme awareness, maximizing power for follow-up investigation. Genetic correlation analysis of multivariate GWAS results with neuroimaging traits identified association with cortical surface area of the banks of the left superior temporal sulcus, a brain region with known links to processing of spoken and written language. Analysis of evolutionary annotations on the lineage that led to modern humans showed enriched heritability in regions depleted of Neanderthal variants. Together, these results provide new avenues for deciphering the biological underpinnings of these uniquely human traits.10217/11710Primary AnalysisShared
Prevalence and Correlates of Concussion in Children: Data from the Adolescent Brain Cognitive Development StudyIntroduction: Concussions are one of the most common causes for emergency room use in the United States (US) among youth and adolescents; however, prevalence data on concussion in this population are inconsistent. A growing body of literature has explored associations of a range of variables with pediatric concussion, but they have not been explored simultaneously in a well-powered sample in the United States. The present study aimed to present lifetime concussion prevalence, evaluate demographic, psychological, and cognitive correlates of concussion, and assess for differences across these variables based on age of first concussion in a large sample of US children. Methods: We analyzed the Adolescent Brain Cognitive Development (ABCD) sample, which monitors biopsychosocial development in 11,875 children at 21 sites across the US between ages 9 and 10. Along with presenting rates of concussion, we also evaluated the association of demographics, sleep disturbance, cognitive functioning, and externalizing and internalizing symptoms with concussion history using backwards binary logistic regression. We further conducted univariate comparisons of all variables between those who experienced their first concussion before and after age 5. Significance was based on α = .02, with Benjamini-Hochberg FDR adjustments for multiple comparisons. Results: We found approximately 4% of the sample had experienced a concussion, and significant correlates of experiencing a concussion were male sex, increased family income, and higher somatic symptoms after FDR correction. Symptoms of ADHD were also noted as nominally significant. No differences based on age of first concussion were found. Discussion: Our analyses provided updated prevalence estimates of pediatric concussion in the US that aligns with many hospital records-based studies. The strongest correlates we found largely mirrored those in the literature with the exception of somatic symptoms. Limitations of findings and implications of individual findings are discussed.11655/11655Secondary AnalysisPrivate
35.2 Probing Structural and Functional Subcortical Regions Implicated in Youth DepressionBackground: Prior structural and functional neuroimaging research in adolescent major depressive disorder (MDD) has consistently implicated abnormalities in subcortical regions (Auerbach et at., 2014; Luking et al., 2016). However, research has often relied on sample sizes that limit power to detect effects that are presumed to be small. Additionally, heterogeneity in disease course and treatment history undoubtedly affects the reliable identification of structural and functional abnormalities among unaffected, high-risk youth as well as youth diagnosed with MDD. To reconcile inconsistent structural and functional neuroimaging findings, the presentation will leverage data from the Adolescent Brain and Cognitive Development (ABCD) Study and Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA). ABCD is a multi-site project that was designed to assess normal variability in adolescent brain and cognitive development among 9-10-year-old children. By contrast, BANDA is a human connectome project that aims to characterize neural circuitry underlying depression and anxiety in adolescents ages 14-16 years. Collectively, these projects afford a unique opportunity to probe subcortical abnormalities in at-risk and currently depressed youth. Methods: The ABCD Study acquired structural MRI data from 9-10-year-old children (n = 4,521). Of these children, 29.7% (n = 1,343) had a parental depressive history. Secondary analyses also tested whether subcortical brain differences were present in youth with a lifetime depressive disorder history. For BANDA, adolescents (n = 141) completed an incentive processing task while fMRI data were collected. Primary analyses probed differences in subcortical activation, and secondary analyses will test whether blunted activation within striatal regions related to anhedonia and a history of suicidal thoughts and behaviors. Results: Several findings emerged. Within ABCD, relative to low-risk youth, high-risk participants with a maternal, but not paternal, depression history exhibited smaller volumes of the right putamen, right accumbens, and left pallidum (FDR-corrected p < 0.05, p < 0.002, t < −2.57) as well as smaller left amygdala volumes (this latter finding did not pass FDR correction). As expected, depressive disorders were more common among those with a parental history of depression (15.96% [parental depressive history] vs. 8.72% [no parental depressive history]; χ2(1) = 47.36, p = 5.90 x 10–12), but there were no significant associations (after FDR correction) between subcortical volumes and children’s depressive disorder history. Among all BANDA participants, there was greater activation in the nucleus accumbens for reward versus loss (t(140) = 10.00, p < 0.001). Preliminary analyses showed that the reward-loss contrast activation was blunted in adolescents with depression and anxiety (B = −0.47, t = −2.29, p = 0.02). For adolescents with depression and anxiety, incentive-related activation was altered in a number of other regions in whole brain analyses, including reduced anterior insula and anterior cingulate activation as well as increased activation in the mPFC and posterior cingulate.11534/11534Secondary AnalysisShared
Subjective neurodevelopmental risk is more robustly associated with cortical structure than objective measures of executive function in the ABCD Study sampleNeurodevelopmental disorders (NDDs) possess some shared symptoms (e.g., executive function deficits) and structural brain presentations, so it may be useful to study neural processes in NDDs transdiagnostically. We aimed to assess subjective and objective measures of neurodevelopmental risk (ND risk) in relation to structural magnetic resonance imaging (sMRI) metrics in the baseline sample of the Adolescent Brain Cognitive Development Study (Release 2.0.1). We hypothesized that greater ND risk would cross-sectionally relate to decreased cortical volume, surface area, and thickness.11534/11534Secondary AnalysisPrivate
Gray matter volumetric correlates of behavioral activation and inhibition system traits in children: An exploratory voxel-based morphometry study of the ABCD project dataApproach and avoidance represent two fundamental behavioral traits that develop early in life. Previous studies have examined the neural correlates of approach and avoidance traits in adults and adolescents. Here, using the data set of the Adolescent Brain Cognition Development project, we investigated the structural cerebral bases of behavioral activation system (BAS) and behavioral inhibition system (BIS) in children. We employed voxel-based morphometry to examine how gray matter volumes (GMV) related specifically to BAS and BIS traits in 11,542 children (5491 girls, age 9–10 years) with 648 and 2697 identified as monozygotic twins (MZ) and dizygotic twins/siblings (DZ), respectively. After accounting for the BIS score, higher BAS scores (residuals) were positively correlated with the GMV of the ventral striatum (VS), and the correlation was stronger in MZ than in DZ and unrelated children, with a heritability (h2) of 0.8463. Higher BAS scores were negatively correlated with the GMV of bilateral visual, lateral orbitofrontal, temporal, and inferior frontal cortex, as well as the precuneus. Higher BIS (after accounting for BAS) scores were negatively correlated with the GMVs of the ventral caudate and bilateral putamen/pallidum, hypothalamus, and right anterior insula, and the correlation was stronger in MZ than in DZ and unrelated children, with a heritability of 0.8848. A cluster in the VS showed positive and negative correlation with the BAS and BIS scores, respectively. These findings suggest shared and distinct cerebral volumetric bases of the BAS and BIS traits in children. Whereas both traits have a strong genetic basis, the BAS relative to BIS appears to be more amenable to environmental influences. These findings add to the literature of developmental neuroscience and may help identify genetic risk factors of externalizing and internalizing psychopathology.11512/11512Primary AnalysisShared
The Role of Social and Neural Connectedness in Predicting Neurodevelopmental Functioning in AdolescenceBecause neurodevelopmental disorders (NDDs) are associated with significant impairment and public health costs and few psychological interventions are known to be effective for reducing neurodevelopmental symptomatology, identification of novel treatment targets for individuals with NDDs is needed. The present longitudinal study will address this need by utilizing a large, nationally-representative sample of youth (i.e., the ABCD Study sample; N = 11,500+; age 9-10) to examine the roles of social connectedness (i.e., extracurricular involvement, family dynamics, and relationships with peers and parents) and related neural connectedness (i.e., functional connectivity within the salience network) in predicting future neurodevelopmental functioning (indexed by both parent-reported symptoms and objective executive function tasks). Results from this study could therefore delineate modifiable social factors and underlying neural mechanisms that are protective against neurodevelopmental symptomatology in early adolescence and inform future clinical research. 11273/11273Secondary AnalysisPrivate
Association Between Discrimination Stress and Suicidality in Preadolescent ChildrenObjective: Youth suicide rates in the United States have been increasing in recent years, especially in Black Americans, the reasons for which are unclear. Environmental adversity is key in youth suicidality; hence there is a need to study stressors that have a disproportionate impact on Black youths. We aimed to disentangle the unique contribution of racial/ethnic discrimination from other adversities associated with childhood suicidal ideation and attempts (suicidality). Method: We analyzed data from the Adolescent Brain Cognitive Development (ABCD) Study, which included a large, diverse sample of US children (N 1⁄4 11,235, mean age 10.9 years, 20.2% Black), assessed for multiple environmental adversities including discrimination. Multivariate regression models tested the association of self-reported racial/ethnic discrimination with suicidality, covarying for multiple confounders including other discrimination types (toward nonUS-born individuals, sexual orientationbased, and weight-based). Matched analyses contrasted effects of racial/ ethnic discrimination and racial identity on suicidality. Results: Black youths reported more discrimination and higher suicidality rates than non-Black youths. High racial/ethnic discrimination was positively and significantly associated with suicidality, adjusting for other discrimination types (odds ratio 1⁄4 2.6, 95% CI 1⁄4 2.13.2). Findings remained significant after adjusting for multiple suicidality risk factors. Once experienced, racial/ethnic discrimination was similarly associated with suicidality in White, Black, and Hispanic youths. Matched analyses revealed that racial/ethnic discrimination was associated with suicidality (relative risk 1⁄4 2.7, 95% CI 1⁄4 23.5), whereas Black race was not (relative risk 1⁄4 0.9, 95% CI 1⁄4 0.71.2). Conclusion: Racial/ethnic discrimination is disproportionately experienced by Black children, and is associated with preadolescent suicidality, over and above other adversities. Findings highlight the need to address discrimination as part of suicide prevention strategies. Cross-sectional design hampers causal inferences.11235/11235Secondary AnalysisPrivate
Nutritional Quality ScoreThis project is geared towards investigating the best approach(es) to using the dietary intake data from the adolescent brain cognition development study. The study comes with 14 questions regarding the dietary intake of adolescents. In our study we will use three approaches to analyzing the dietary intake data: 1) Theory driven summary scores of the 14 dietary intake variables. 2) Supervised learning approach to maximizing prediction of body mass index and waist circumference using a iterative random forest model of the 14 dietary intake variables. 3) Unsupervised learning approach to finding groups of people with similar dietary intake profiles. We plan to use these groupings to see if they predict body mass index or waist circumference.11235/11235Secondary AnalysisPrivate
The Emotional Word-Emotional Face Stroop task in the ABCD study: Psychometric validation and associations with measures of cognition and psychopathologyCharacterizing the interactions among attention, cognitive control, and emotion during adolescence may provide important insights into why this critical developmental period coincides with a dramatic increase in risk for psychopathology. However, it has proven challenging to develop a single neurobehavioral task that simultaneously engages and differentially measures these diverse domains. In the current study, we describe properties of performance on the Emotional Word-Emotional Face Stroop (EWEFS) task in the Adolescent Brain Cognitive Development (ABCD) Study, a task that allows researchers to concurrently measure processing speed/attentional vigilance (i.e., performance on congruent trials), inhibitory control (i.e., Stroop interference effect), and emotional information processing (i.e., difference in performance on trials with happy as compared to angry distracting faces). We first demonstrate that the task manipulations worked as designed and that Stroop performance is associated with multiple cognitive constructs derived from different measures at a prior time point. We then show that Stroop metrics tapping these three domains are preferentially associated with aspects of externalizing psychopathology and inattention. These results highlight the potential of the EWEFS task to help elucidate the longitudinal dynamics of attention, inhibitory control, and emotion across adolescent development, dynamics which may be altered by level of psychopathology.11234/11234Secondary AnalysisPrivate
Childhood trauma and health-promoting behaviors in pre-adolescentsObjective: To understand the relationship between childhood trauma and diet, sleep, and screen time. Methods: Baseline and one-year follow-up data from the Adolescent Brain Cognitive Development (ABCD) study were analyzed for children 9-10 (unweighted n = 11,233). For childhood trauma, parents completed the Kiddie Schedule for Affective Disorders and Schizophrenia for DSM-5 (KSADS-COMP) subsection for traumatic events at baseline. We created three levels of childhood adversity: exposure to no childhood adversity, exposure to one category of childhood adversity, and exposure to two or more categories of childhood adversity. Health promoting behaviors were assessed at the 1-year follow-up. Diet quality was measured from parent report as the sum score of 14 yes/no questions about healthy diet. Sleep problems were measured by parent report as the total sleep disturbance scale; higher scores indicate worse sleep. Screen time was assessed by calculating an average daily screen time from a youth survey. Linear regression analyses were used to assess the relationship between childhood trauma and each health promoting behavior, adjusting for family income and sex. Results: Compared to children with no trauma, childhood trauma was associated with a lower diet score - one trauma (-0.24 (95% CI -0.44 to -0.03), p=0.03) and two or more traumas (-0.66 (-0.90 to -0.42), p<0.001). Similarly, childhood trauma was associated with a higher sleep disruption score - one trauma (1.8 (0.27 to 6.4), p<0.001) and two or more traumas (3.8 (0.44 to 8.7), p<0.001). Finally, childhood trauma was associated with more screen time - one trauma (0.41 hours (0.20 to 0.62), p<0.001) and two or more traumas (0.89 hours (0.53 to 1.24), p<0.001). Conclusions: Childhood trauma in pre-adolescents is associated with unhealthy diet, sleep disruption, and more screen time. These findings suggest potential behaviors to target to mitigate the negative impact of childhood trauma on adult health. 11233/11233Secondary AnalysisPrivate
Neuroanatomical correlates of impulsive traits in children aged 9 to 10Impulsivity refers to a set of traits that are generally negatively related to critical domains of adaptive functioning and are core features of numerous psychiatric disorders. The current study examined the gray and white matter correlates of five impulsive traits measured using an abbreviated version of the UPPS-P (Urgency, (lack of) Premeditation, (lack of) Perseverance, Sensation-Seeking, Positive Urgency) impulsivity scale in children aged 9 to 10 (N = 11,052) from the Adolescent Brain and Cognitive Development (ABCD) study. Linear mixed effect models and elastic net regression were used to examine features of regional gray matter and white matter tractography most associated with each UPPS-P scale; intraclass correlations were computed to examine the similarity of the neuroanatomical correlates among the scales. Positive Urgency showed the most robust association with neuroanatomy, with similar but less robust associations found for Negative Urgency. Perseverance showed little association with neuroanatomy. Premeditation and Sensation Seeking showed intermediate associations with neuroanatomy. Critical regions across measures include the dorsolateral prefrontal cortex, lateral temporal cortex, and orbitofrontal cortex; critical tracts included the superior longitudinal fasciculus and inferior fronto-occipital fasciculus. Negative Urgency and Positive Urgency showed the greatest neuroanatomical similarity. Some UPPS-P traits share neuroanatomical correlates, while others have distinct correlates or essentially no relation to neuroanatomy. Neuroanatomy tended to account for relatively little variance in UPPS-P traits (i.e., Model R2 < 1%) and effects were spread throughout the brain, highlighting the importance of well powered samples.11051/11051Secondary AnalysisShared
A Family-Built Brain: Associations between family environment and child brain function and structureThis project examines the relation between family environment (FE) and brain functioning and structure. We hypothesize that an unsupportive FE accelerates brain development, and will examine whether pubertal status mediates the relation between FE and brain functioning. FE will be measured by a latent construct combining questionnaire data on family relationships and demographical information, such as socioeconomic status and parental marital status, using structural equation modeling in MPlus. Pubertal status will be measured by the Pubertal Development Scale and sex hormones. Brain function and structure will be assessed using resting-state fMRI, DTI and T1 weighted scans. 10966/10966Secondary AnalysisShared
Peer victimization is linked to heightened corticolimbic activation during emotion processing in early adolescentsBullying, or peer victimization, is a salient stressor that affects over 5 million adolescents in the US every year, regardless of ethnicity, gender, or socioeconomic status. Prior research links peer victimization to increased risk of anxiety disorders, which are the most common mental health disorders and affect approximately one in three individuals. Anxiety disorders commonly begin during early adolescence and neuroimaging studies suggest that altered functioning of emotion processing corticolimbic neural circuitry (e.g., amygdala, hippocampus, anterior cingulate cortex, insula) may underlie the link between peer victimization and vulnerability to anxiety. Here, we leveraged neuroimaging data from the Adolescent Brain Cognitive Development (ABCD) study to test the hypothesis that victimization shapes the functional recruitment of corticolimbic circuitry during emotion processing during early adolescence. Using the emotional n-back task (N = 4,822, age 10-11 years, 47% female), we found that youth who were more frequent victims of overt, relational, or reputational victimization reported more anxiety symptoms (r’s>.09, p’s<.001). However, youth who were more frequent victims of overt (but not relational or reputational) victimization demonstrated heightened activation of the hippocampus, insula, and rostral ACC (rACC) to emotional faces (r’s>.03, p’s<.04). Further, overt victimization moderated the association between rACC response and anxiety (b=-1, 95% CI [-1.5, -.49], t=3.77, p=.0002). In particular, higher anxiety was associated with lower rACC response at higher levels of victimization. At lower levels of victimization, in contrast, higher anxiety was associated with higher rACC response. These data reveal a candidate mechanism driving elevated risk for anxiety in peer victimized youth.10898/10898Secondary AnalysisShared
Association of Gray Matter Volumes with General and Specific Dimensions of Psychopathology in ChildrenChildhood is an important time for the manifestation of psychopathology. Psychopathology is characterized by considerable comorbidity which is mirrored in the underlying neural correlates of psychopathology. Both common and dissociable variations in brain volume have been found across multiple mental disorders in adult and youth samples. However, the majority of these studies used samples with broad age ranges which may obscure developmental differences. The current study examines associations between regional gray matter volumes (GMV) and psychopathology in a large sample of children with a narrowly defined age range. We used data from 9,608 children 9 to 10 years of age collected as part of the Adolescent Brain and Cognitive Development (ABCD) Study. A bifactor model identified a general psychopathology factor that reflects common variance across disorders and specific factors representing internalizing symptoms, ADHD symptoms, and conduct problems. Brain volume was acquired using 3T MRI. After correction for multiple testing, structural equation modeling revealed nearly global inverse associations between regional GMVs and general psychopathology and conduct problems, with associations also found for ADHD symptoms (pfdrvalues ≤ .048). Age, sex, and race were included as covariates. Sensitivity analyses including total GMV or intracranial volume (ICV) as covariates support this global association, as a large majority of region-specific results become non-significant. Sensitivity analyses including income and parental education as covariates demonstrate largely convergent results. These findings suggest that globally smaller GMVs are a nonspecific risk factor for general psychopathology, and possibly for conduct problems and ADHD as well.10626/10626Secondary AnalysisPrivate
Atypical functional network topology emerges during rest and task performance in children with ADHD symptomsWhen neural networks deviate from typical development, the resulting dysfunction is thought to contribute to varying forms of psychopathology. To overcome research limitations in network-level underpinnings of psychopathology (e.g., psychological comorbidities, diagnostic categories), the present study examined the topology of functional networks in association with four psychopathology dimensions— general psychopathology, internalizing, conduct problems, and attention-deficit/hyperactivity disorder (ADHD)— in a sample of 3,568 children from the Adolescent Brain and Cognitive DevelopmentSM Study (ABCD Study®). Local and global graph theory metrics were calculated at rest and during tasks of reward processing, inhibition, and working memory. Consistently across rest and tasks, greater ADHD symptoms were associated with lower modularity, as well as reduced local efficiency in motor networks at rest. These findings indicate nonoptimal short-range communication and a lack of information hub formation specific to the ADHD dimension. Overall, deficits in local functional network communication may be a neurobiological marker of ADHD symptoms.10626/10626Secondary AnalysisPrivate
General and specific factors of environmental stress and their associations with brain structureObjective: Early life stress involving neglect as well as emotional, physical, and sexual abuse, coupled with environmental factors such as poverty, urban living, and lack of interpersonal support can adversely affect the developing brain. While hierarchical modeling has established the existence of a general factor of psychopathology, no studies have modeled a general factor of environmental stress and related this to brain development. Using a large sample of 11,878 children aged 9 to 10 years from the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®), the current study aimed to identify general and specific factors of environmental stress and test their associations with brain structures. Method: Exploratory structural equation modeling and bifactor modeling identified general and specific factors of environmental stress: family dynamics, interpersonal support, neighborhood deprivation, and urbanicity. The associations between these factors and regional gray matter volume (GMV) and cortical thickness were examined. Results: The general environmental stress factor was associated with globally smaller cortical and subcortical GMV, as well as thinner cortices across widespread regions. Family dynamics was associated with globally smaller cortical and subcortical GMV. Neighborhood deprivation was associated with mostly thinner cortices in frontal regions and smaller regional subcortical GMV. Urbanicity was associated with larger cortical and subcortical GMV, as well as thicker cortices in frontotemporal regions. Conclusions: This study used hierarchical modeling to identify general and specific factors of environmental stress in the ABCD Study. These factors were associated with aberrations in the developing brain, suggesting the need for early interventions at the systemic level. 10626/10626Secondary AnalysisPrivate
Multivariate Associations between Dimensional Psychopathology and Brain Volume in ChildrenPsychopathology can be conceptualized as a hierarchy of dimensional symptom domains, with common and dissociable neural substrates. While many studies of brain-behavior relationships rely on individual univariate analyses, multivariate approaches allow us to examine relationships between psychopathology and neural substrates simultaneously. However, there are multiple multivariate approaches to consider with few studies illustrating their potential differences. We used data from 8,362 9- to 10-year-old children from the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®) to examine the congruence in brain-behavior relationships between two multivariate approaches: partial least squares (PLS) analysis and canonical correlation analysis (CCA). A hierarchical model was used to derive psychopathology dimensions including general psychopathology, attention-deficit/hyperactivity disorder symptoms, conduct problems, and internalizing symptoms. Regional gray matter volume was acquired using 3T MRI. The PLS analysis showed a global pattern of smaller brain volumes associated with psychopathology, while CCA showed a variable pattern of either smaller and larger brain volumes related to psychopathology. Train-test analyses also revealed that PLS results remained similar across both samples, while the pattern of results for CCA changed between train and test samples. Together, these results illustrate the differences in the interpretation and replicability of the results based on the multivariate approach used. 10626/10626Secondary AnalysisPrivate
The Association between Latent Trauma and Brain Structure in ChildrenThe developing brain is marked by high plasticity which can lead to vulnerability to early life stressors, such as trauma. Previous studies indicate that childhood maltreatment is associated with structural aberrations across a number of brain regions. However, prior work is limited by small sample sizes, heterogeneous age groups, select regions chosen a priori, and the confounding of different types of early life stressors which may contribute to high variability across studies. The present study aimed to investigate how trauma specifically is associated with cortical thickness and gray matter volume (GMV) differences by leveraging a large sample of children (N = 9,270) from the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®). A latent measure of trauma exposure was derived using DSM-5 criterion A traumatic events and related to the brain using structural equation modeling. After correcting for multiple comparisons, trauma exposure was associated with reduced cortical thickness in the bilateral superior frontal gyri and right caudal middle frontal gyrus (pfdr-values < .001) as well as increased cortical thickness in the left isthmus cingulate and posterior cingulate (pfdr-values ≤ .027). Furthermore, trauma exposure was associated with decreased GMV in the right amygdala and right putamen (pfdr-values ≤ .048). Results of sensitivity analyses that control for income and parent level of education were largely consistent with the main findings for cortical thickness. The present results suggest that trauma may be an important risk factor for structural aberrations, specifically for cortical thickness differences in frontal and cingulate regions in children.10626/10626Secondary AnalysisPrivate
Shared genetic etiology between cortical brain morphology and tobacco, alcohol, and cannabis useGenome-wide association studies (GWAS) have identified genomic variants associated with brain morphology and substance use behaviors (SUB). However, the genetic overlap between brain structure and SUB has not been characterized. We leveraged GWAS summary data of 71 brain imaging measures and alcohol, tobacco, and cannabis use to investigate their genetic overlap using a linkage disequilibrium score regression. We used genomic structural equation modeling to model a ‘SUB common genetic factor’ and investigated its genetic overlap with brain structure. Furthermore, we estimated SUB polygenic risk scores (PRS) and examined whether they predicted brain imaging traits using the Adolescent Behavior and Cognitive Development (ABCD) study. We identified eight significant negative genetic correlations, including between (a) alcoholic drinks per week and average cortical thickness, and (b) intracranial volume with age of smoking initiation. We observed five positive genetic correlations, including those between (a) insula surface area and lifetime cannabis use, and (b) the common SUB genetic factor and pericalcarine surface area. SUB polygenic risk scores were associated brain structure variation in ABCD. Our findings highlight a shared genetic etiology between variation in cortical brain morphology and SUB, suggesting that genetic variants associated with SUB may be causally related to brain structure differences.10403/10403Primary AnalysisShared
Fine particulate matter exposure during childhood relates to hemispheric-specific differences in brain structure Background Emerging findings have increased concern that exposure to fine particulate matter air pollution (aerodynamic diameter ≤2.5 μm; PM2.5) may be neurotoxic, even at lower levels of exposure. Yet, additional studies are needed to determine if exposure to current PM2.5 levels may be linked to hemispheric and regional patterns of brain development in children across the United States. Objectives We examined the cross-sectional associations between geocoded measures of concurrent annual average outdoor PM2.5 exposure, regional- and hemisphere-specific differences in brain morphometry and cognition in 10,343 9- and 10- year-old children. Methods High-resolution structural T1-weighted brain magnetic resonance imaging (MRI) and NIH Toolbox measures of cognition were collected from children at ages 9-10 years. FreeSurfer was used to quantify cortical surface area, cortical thickness, as well as subcortical and cerebellum volumes in each hemisphere. PM2.5 concentrations were estimated using an ensemble-based model approach and assigned to each child’s primary residential address collected at the study visit. We used mixed-effects models to examine regional- and hemispheric- effects of PM2.5 exposure on brain estimates and cognition after considering nesting of participants by familial relationships and study site, adjustment for socio-demographic factors and multiple comparisons. Results Annual residential PM2.5 exposure (7.63 ± 1.57 µg/m3) was associated with hemispheric specific differences in gray matter across cortical regions of the frontal, parietal, temporal and occipital lobes as well as subcortical and cerebellum brain regions. There were hemispheric-specific associations between PM2.5 exposures and cortical surface area in 9/31 regions; cortical thickness in 22/27 regions; and volumes of the thalamus, pallidum, and nucleus accumbens. We found neither significant associations between PM2.5 and task performance on individual measures of neurocognition nor evidence that sex moderated the observed associations. Discussion Even at relatively low-levels, current PM2.5 exposure across the U.S. may be an important environmental factor influencing patterns of structural brain development in childhood. Prospective follow-up of this cohort will help determine how current levels of PM2.5 exposure may affect brain development and subsequent risk for cognitive and emotional problems across adolescence. 10343/10343Secondary AnalysisShared
The Relationship Between Polygenic Risk for Anorexia Nervosa and Anorexia Symptom Change in Early Adolescence: Change in Obsessive-Compulsive Disorder Symptoms as a MediatorResearch Questions 1: Is the polygenic risk score for anorexia nervosa (AN-PRS) associated with anorexia (AN) symptoms at time one? 2: Is PRS-AN associated with latent change scores for AN symptoms? 3: Is PRS-AN associated with obsessive-compulsive disorder (OCD) symptoms at time one? 4: Is PRS-AN associated with latent change scores for OCD symptoms? 5: Does change in OCD symptoms partially mediate the relationship between PRS-AN and change in AN symptoms? 10217/10217Secondary AnalysisPrivate
Neighborhood deprivation, prefrontal structure, and cognitive function BACKGROUND: Neighborhood deprivation adversely effects neurodevelopment and cognitive function; however, mechanisms remain unexplored. Neighborhood deprivation could be particularly impactful in late childhood/early adolescence, in neural regions with protracted developmental trajectories, e.g., prefrontal cortex (PFC). METHODS: The Adolescent Brain Cognitive Development (ABCD) study recruited 10,205 youth. Geocoded residential history was used to extract individual neighborhood characteristics. A general cognitive ability index and MRI scans were completed. Associations with neurocognition were examined. The relation of PFC surface area and cortical thickness to neighborhood deprivation was tested. PFC subregions and asymmetry, with putative differential environmental susceptibility during key developmental periods, were explored. Analyses tested PFC area as a possible mediating mechanism. RESULTS: Neighborhood deprivation predicted neurocognitive performance (β = - 0.11), even after accounting for parental education and household income (β = -0.07). Higher neighborhood deprivation related to greater overall PFC surface area (η p 2 = 0.003), and differences in leftward asymmetry were observed for area (η p 2 = 0.001), and thickness (η p 2 = 0.003). Subregion analyses highlighted differences among critical areas that are actively developing in late childhood/early adolescence and are essential to modulating high order cognitive function. These included orbitofrontal, superior frontal, rostral middle frontal, and frontal pole regions (Cohen’s d = 0.03-0.09). PFC surface area partially mediated the relation between neighborhood deprivation and neurocognition. DISCUSSION: Neighborhood deprivation related to cognitive function (a foundational skill tied to a range of lifetime outcomes) and PFC morphology, with evidence found for partial mediation of PFC on neurocognitive function. Results inform public health conceptualizations of development and environmental vulnerability.10204/10204Secondary AnalysisShared
Distinct Regionalization Patterns of Cortical Morphology are Associated with Cognitive Performance Across Different DomainsCognitive performance in children is predictive of academic and social outcomes; therefore, understanding neurobiological mechanisms underlying individual differences in cognition during development may be important for improving quality of life. The belief that a single, psychological construct underlies many cognitive processes is pervasive throughout society. However, it is unclear if there is a consistent neural substrate underlying many cognitive processes. Here, we show that a distributed configuration of cortical surface area and apparent thickness, when controlling for global imaging measures, is differentially associated with cognitive performance on different types of tasks in a large sample (N = 10 145) of 9–11-year-old children from the Adolescent Brain and Cognitive DevelopmentSM (ABCD) study. The minimal overlap in these regionalization patterns of association has implications for competing theories about developing intellectual functions. Surprisingly, not controlling for sociodemographic factors increased the similarity between these regionalization patterns. This highlights the importance of understanding the shared variance between sociodemographic factors, cognition and brain structure, particularly with a population-based sample such as ABCD.10092/10092Secondary AnalysisShared
Association of lead-exposure risk and family income with childhood brain outcomesSocioeconomic factors influence brain development and structure, but most studies have overlooked neurotoxic insults that impair development, such as lead exposure. Childhood lead exposure affects cognitive development at the lowest measurable concentrations, but little is known about its impact on brain development during childhood. We examined cross-sectional associations among brain structure, cognition, geocoded measures of the risk of lead exposure and sociodemographic characteristics in 9,712 9- and 10-year-old children. Here we show stronger negative associations of living in high-lead-risk census tracts in children from lower- versus higher-income families. With increasing risk of exposure, children from lower-income families exhibited lower cognitive test scores, smaller cortical volume and smaller cortical surface area. Reducing environmental insults associated with lead-exposure risk might confer greater benefit to children experiencing more environmental adversity, and further understanding of the factors associated with high lead-exposure risk will be critical for improving such outcomes in children.9712/9712Primary AnalysisShared
Cortical thickness, surface area, and subcortical volumes across a spectrum of psychopathology symptoms during childhoodBackground: Gray matter morphometry studies have lent seminal insights into the etiology of mental illness. Existing research has primarily focused on adults and then, typically on a single disorder. Examining brain characteristics in late childhood, when the brain is preparing to undergo significant adolescent reorganization and various forms of serious psychopathology are just first emerging, may allow for a unique and highly important perspective of overlapping and unique pathogenesis. Methods: A total of 8,645 youth were recruited as part of the Adolescent Brain and Cognitive Development study. Magnetic resonance imaging (MRI) scans were collected, and psychotic-like experiences (PLEs), depressive, and anxiety symptoms were assessed three times over a two-year period. Cortical thickness, surface area, and subcortical volume were used to predict baseline symptomatology and symptom progression over time. Results: Some features could possibly signal common vulnerability, predicting progression across forms of psychopathology (e.g., superior frontal and middle temporal regions). However, there was specific predictive value for emerging PLEs (lateral occipital and precentral thickness), anxiety (parietal thickness/area and cingulate), and depression (e.g. parahippocampal and inferior temporal). Conclusion: Findings indicate common and distinct patterns of vulnerability for varying forms of psychopathology are present during late childhood, before the adolescent reorganization, and have direct relevance for informing novel conceptual models along with early prevention and intervention efforts. 9612/9612Primary AnalysisShared
? Study Title: Adolescent Brain Cognitive Development Study® (ABCD) Data Release: COVID Rapid Response Research (RRR) Survey Second data release The Adolescent Brain Cognitive Development℠ Study (ABCD Study®), the largest longitudinal study of brain development and child health in the United States, follows over 10 years 11,878 children recruited from 21 U.S. research sites, recruited at ages 9-10 in 2016-18. In March 2020, when our participants were ages 11- to 13-years-old, the world became substantially affected by the COVID-19 pandemic, leading to an upheaval in the economy and the lives of almost every family. The ABCD Study developed brief surveys sent electronically to all ABCD participants and their participating parent/guardian about the impact of the pandemic on their lives. An overview of the ABCD Study is at https://abcdstudy.org. We sent Survey 1 May 16-22, 2020, Survey 2 June 24-27, 2020, Survey 3 August 4-5, 2020, survey 4 October 8, 2020, survey 5 December 13, 2020, and survey 6 March 12-13, 2021. Data from the survey 4, 5, and 6 constitute this data release. Future releases will contain data from subsequent surveys.9471/9471Primary AnalysisShared
Adolescent Brain Cognitive Development Study® (ABCD) Data Release: COVID Rapid Response Research (RRR) Survey First data release (Surveys #1, 2, and 3)The Adolescent Brain Cognitive Development℠ Study (ABCD Study®), the largest longitudinal study of brain development and child health in the United States, follows over 10 years 11,878 children recruited from 21 U.S. research sites, recruited at ages 9-10 in 2016-18. In March 2020, when our participants were ages 11- to 13-years-old, the world became substantially affected by the COVID-19 pandemic, leading to an upheaval in the economy and the lives of almost every family. The ABCD Study developed brief surveys sent electronically to all ABCD participants and their participating parent/guardian about the impact of the pandemic on their lives. An overview of the ABCD Study is at https://abcdstudy.org. We sent Survey 1 May 16-22, 2020, Survey 2 June 24-27, 2020, and Survey 3 August 4-5, 2020. Data from these first three surveys constitute this data release. Future releases will contain data from subsequent surveys.9268/9268Primary AnalysisShared
Companion Animals and Adolescent Stress and Adaptive Coping During the COVID-19 PandemicThe pandemic associated with the coronavirus disease (COVID-19) has caused significant life disruptions for youth worldwide. In addition to the physical health challenges of COVID-19, the social isolation caused by lockdowns, school closures, and social distancing guidelines have the potential to significantly impact adolescent mental health and well-being. Adolescents are at particular risk, given the importance of social development during this developmental period. Given this risk, there is a need for identifying contextual resources that may help promote stress reduction, positive mental health outcomes, and adaptive coping during the pandemic. Pets can play a role in providing emotional support for youth, and are not subject to the same social distancing restrictions as human social contacts during COVID-19. This analysis explores the role of companion animals in the family as a source of resilience during the pandemic may provide important information about how to support adaptive coping in adolescence.9268/9268Secondary AnalysisPrivate
Profiles of pet ownership during the COVID-19 pandemicThis study aims to investigate the profiles of pet owners during COVID-19. To better understand the role of pets during COVID for diverse families, the goal of this analysis is to 1) assess if there are systematic sociodemographic differences between families with and without pets, and 2) explore if these sociodemographic differences are related to acquiring or losing a pet during the pandemic COVID.9268/9268Secondary AnalysisShared
Resilience to COVID-19: Socioeconomic disadvantage associated with positive caregiver-youth communication and youth preventative actionsSocioeconomic disadvantage is associated with larger COVID-19 disease burdens and pandemic-related economic impacts. We utilized the longitudinal Adolescent Brain Cognitive Development Study to understand how family- and neighborhood-level socioeconomic disadvantage relate to disease burden, family communication, and preventative responses to the pandemic in over 6,000 youth-caregiver dyads. Data were collected at three timepoints (May to August 2020). Here, we show that both family- and neighborhood-level disadvantage were associated with caregivers’ reports of greater family COVID-19 disease burden, less perceived exposure risk, more frequent caregiver-youth conversations about COVID-19 risk/prevention and reassurance, and greater youth preventative behaviors. Families with more socioeconomic disadvantage may be adaptively incorporating more protective strategies to reduce emotional distress and likelihood of COVID-19 infection. The results highlight the importance of caregiver-youth communication and disease-preventative practices for buffering the economic and disease burdens of COVID-19, along with policies and programs that reduce these burdens for families with socioeconomic disadvantage. Full text: https://www.frontiersin.org/articles/10.3389/fpubh.2022.734308/full9267/9267Primary AnalysisShared
Discovery of genomic loci of the human cerebral cortex using genetically informed brain atlasesTo determine the impact of genetic variants on the brain, we used genetically-informed brain atlases in genome-wide association studies of regional cortical surface area and thickness in 39,898 adults and 9136 children. We uncovered 440 genome-wide significant loci in the discovery cohort and 800 from a post-hoc combined meta-analysis. Loci in adulthood were largely captured in childhood, showing signatures of negative selection, and were linked to early neurodevelopment and pathways associated with neuropsychiatric risk. Opposing gradations of decreased surface area and increased thickness were associated with common inversion polymorphisms. Inferior frontal regions, encompassing Broca’s area which is important for speech, were enriched for human-specific genomic elements. Thus a mixed genetic landscape of conserved and human-specific features is concordant with brain hierarchy and morphogenetic gradients.9136/9136Secondary AnalysisPrivate
Breastfeeding Duration is Associated With Domain-Specific Improvements in Cognitive Performance in 9-10-Year-Old ChildrenSignificant immunological, physical and neurological benefits of breastfeeding in infancy are well-established, but to what extent these gains persist into later childhood remain uncertain. This study examines the association between breastfeeding duration and subsequent domain-specific cognitive performance in a diverse sample of 9-10-year-olds enrolled in the Adolescent Brain Cognitive Development (ABCD) Study®. The analyses included 9,116 children that attended baseline with their biological mother and had complete neurocognitive and breastfeeding data. Principal component analysis was conducted on data from an extensive battery of neurocognitive tests using varimax-rotation to extract a three-component model encompassing General Ability, Executive Functioning, and Memory. Propensity score weighting using generalized boosted modeling was applied to balance the distribution of observed covariates for children breastfed for 0, 1-6, 7-12, and more than 12 months. Propensity score-adjusted linear regression models revealed a significant association between breastfeeding duration and performance on neurocognitive tests representing General Ability, but no evidence of a strong association with Executive Function or Memory. Benefits on General Ability ranged from a .109 (1-6 months) to .301 (> 12 months) standardized beta coefficient difference compared to those not breastfed. Results indicate clear cognitive benefits of breastfeeding but that these do not generalize to all measured domains, with implications for public health policy as it pertains to nutrition during infancy.9115/9115Secondary AnalysisShared
Differentiating distinct and converging neural correlates of types of systemic environmental exposuresBackground: Systemic environmental disadvantage relates to a host of health and functional outcomes. Specific structural factors have seldom been linked to neural structure, however, clouding understanding of putative mechanisms. Examining relations during childhood/preadolescence, a dynamic period of neurodevelopment, could aid bridge this gap. Methods: A total of 10,213 youth were recruited from the Adolescent Brain and Cognitive Development study. Self-report and objective measures (Census and Federal bureau of investigation metrics extracted using geocoding) of environmental exposures were used, including stimulation indexing lack of safety and high attentional demands, discrepancy indexing social exclusion/lack of belonging, and deprivation indexing lack of environmental enrichment. Environmental measures were related to cortical thickness, surface area and subcortical volume regions, controlling for other environmental exposures and accounting for other brain regions. Results: Self-report (|β|=0.04-0.09) and objective (|β|=0.02-0.06) environmental domains related to area/thickness in overlapping (e.g. insula, caudal anterior cingulate), and unique regions (e.g. for discrepancy, rostral anterior and isthmus cingulate, implicated in socioemotional functions; for stimulation, precuneus, critical for cue reactivity and integration of environmental cues, and for deprivation, superior frontal, integral to executive functioning). For stimulation and discrepancy exposures, self-report and objective measures showed similarities in correlate regions, while deprivation exposures evidenced distinct correlates for self-report and objective measures. Conclusions: Results represent a necessary step toward broader work aimed at establishing mechanisms and correlates of structural disadvantage, highlighting the relevance of going beyond aggregate models by considering types of environmental factors, and the need to incorporate both subjective and objective measurements in these efforts. 9043/9043Primary AnalysisShared
Microstructural development from 9 to 14 years: Evidence from the ABCD StudyDuring late childhood behavioral changes, such as increased risk-taking and emotional reactivity, have been associated with the maturation of cortico-cortico and cortico-subcortical circuits. Understanding microstructural changes in both white matter and subcortical regions may aid our understanding of how individual differences in these behaviors emerge. Restriction spectrum imaging (RSI) is a framework for modelling diffusion-weighted imaging that decomposes the diffusion signal from a voxel into hindered, restricted, and free compartments. This yields greater specificity than conventional methods of characterizing diffusion. Using RSI, we quantified voxelwise restricted diffusion across the brain and measured age associations in a large sample (n = 8086) from the Adolescent Brain and Cognitive Development (ABCD) study aged 9–14 years. Older participants showed a higher restricted signal fraction across the brain, with the largest associations in subcortical regions, particularly the basal ganglia and ventral diencephalon. Importantly, age associations varied with respect to the cytoarchitecture within white matter fiber tracts and subcortical structures, for example age associations differed across thalamic nuclei. This suggests that age-related changes may map onto specific cell populations or circuits and highlights the utility of voxelwise compared to ROI-wise analyses. Future analyses will aim to understand the relevance of this microstructural developmental for behavioral outcomes.9040/9040Secondary AnalysisPrivate
ABCD Machine LearningThis study will use machine learning models to predict ADHD from patients' fMRI imaging data. We have two objectives: i) we aim at increasing prediction accuracy to assist clinical ADHD diagnoses; ii) we will interpret prediction results for understanding ADHD by study interactions among the region of interest to reveal brain activity patterns in ADHD patients. We design this analysis by three steps: i) treat fMRI image data as graph structure data; ii) use state-of-the-art graph neural network models such as graph scattering transform, graph attention network, and graph ordinary differentiation equation. iii) apply transfer learning of trained model from ABCD on our GESTation and Environment cohort (GESTE) fMRI data. We plan first to compare prediction accuracy with traditional demographics based methods. Then interpret the machine learning models by looking at parameters such as attention weights. We request the following data: i) processed fMRI data for each patient with atlas information (data matrix of region(s) of interest by the intensity at measured time steps); ii) patients ADHD diagnoses; iii) patients demographics information; iv) patients other neuropsychological related diseases information.8969/8969Primary AnalysisPrivate
Individual Differences in Cognitive Performance Are Better Predicted by Global Rather Than Localized BOLD Activity Patterns Across the CortexDespite its central role in revealing the neurobiological mechanisms of behavior, neuroimaging research faces the challenge of producing reliable biomarkers for cognitive processes and clinical outcomes. Statistically significant brain regions, identified by mass univariate statistical models commonly used in neuroimaging studies, explain minimal phenotypic variation, limiting the translational utility of neuroimaging phenotypes. This is potentially due to the observation that behavioral traits are influenced by variations in neuroimaging phenotypes that are globally distributed across the cortex and are therefore not captured by thresholded, statistical parametric maps commonly reported in neuroimaging studies. Here, we developed a novel multivariate prediction method, the Bayesian polyvertex score, that turns a unthresholded statistical parametric map into a summary score that aggregates the many but small effects across the cortex for behavioral prediction. By explicitly assuming a globally distributed effect size pattern and operating on the mass univariate summary statistics, it was able to achieve higher out-of-sample variance explained than mass univariate and popular multivariate methods while still preserving the interpretability of a generative model. Our findings suggest that similar to the polygenicity observed in the field of genetics, the neural basis of complex behaviors may rest in the global patterning of effect size variation of neuroimaging phenotypes, rather than in localized, candidate brain regions and networks.8892/8892Primary AnalysisPrivate
Association of Local Variation in Neighborhood Disadvantage in Metropolitan Areas With Youth Neurocognition and Brain StructureImportance: Neighborhood disadvantage is an important social determinant of health in childhood and adolescence. Less is known about the association of neighborhood disadvantage with youth neurocognition and brain structure, and particularly whether associations are similar across metropolitan areas and are attributed to local differences in disadvantage. Objective: To test whether neighborhood disadvantage is associated with youth neurocognitive performance and with global and regional measures of brain structure after adjusting for family socioeconomic status and perceptions of neighborhood characteristics, and to assess whether these associations (1) are pervasive or limited, (2) vary across metropolitan areas, and (3) are attributed to local variation in disadvantage within metropolitan areas. Design, Setting and Participants: This cross-sectional study analyzed baseline data from the Adolescent Brain and Cognitive Development (ABCD) Study, a cohort study conducted at 21 sites across the US. Participants were children aged 9.00 to 10.99 years at enrollment. They and their parent or caregiver completed a baseline visit between October 1, 2016, and October 31, 2018. Exposure: Neighborhood disadvantage factor based on U.S. census tract characteristics Main Outcome(s) and Measure(s): Neurocognition was measured with the NIH Toolbox Cognition Battery, and T1-weighted magnetic resonance imaging was used to assess whole-brain and regional measures of structure. Linear mixed-effects models examined the association between neighborhood disadvantage and outcomes after adjusting for sociodemographic factors. Results: Of the 11 875 children in the ABCD Study cohort, 8598 children (72.4%) were included in this analysis. The study sample had a mean (SD) age of 118.8 (7.4) months and included 4526 boys (52.6%). Every 1-unit increase in the neighborhood disadvantage factor was associated with lower performance on 6 of 7 subtests, such as Flanker Inhibitory Control and Attention (unstandardized Β = −0.5; 95% CI, −0.7 to −0.2; false discovery rate (FDR)–corrected P = .001) and List Sorting Working Memory (unstandardized Β = −0.7; 95% CI, −1.0 to −0.3; FDR-corrected P < .001), as well as on all composite measures of neurocognition, such as the Total Cognition Composite (unstandardized Β = −0.7; 95% CI, −0.9 to −0.5; FDR-corrected P < .001). Each 1-unit increase in neighborhood disadvantage was associated with lower whole-brain cortical surface area (unstandardized Β = −692.6 mm2; 95% CI, −1154.9 to −230.4 mm2; FDR-corrected P = .007) and subcortical volume (unstandardized Β = −113.9 mm3; 95% CI, −198.5 to −29.4 mm3; FDR-corrected P = .03) as well as with regional surface area differences, primarily in the frontal, parietal, and temporal lobes. Associations largely remained after adjusting for perceptions of neighborhood safety and were both consistent across metropolitan areas and primarily explained by local variation in each area. Conclusions and Relevance: This study found that, in the US, local variation in neighborhood disadvantage was associated with lower neurocognitive performance and smaller cortical surface area and subcortical volume in young people. The findings demonstrate that neighborhood disadvantage is an environmental risk factor for neurodevelopmental and population health and enhancing the neighborhood context is a promising approach to improving the health and development of children and adolescents.8598/8598Secondary AnalysisShared
Direct and Indirect Associations of Widespread Individual Differences in Brain White Matter Microstructure with Executive Functioning and General and Specific Dimensions of Psychopathology in ChildrenBackground: Executive functions (EF) are centrally important because they are broadly associated with risk for psychopathology and substance abuse. Because EF has been linked to white matter microstructure, we tested the prediction that fractional anisotropy (FA) and mean diffusivity (MD) in white matter tracts are associated with EF and both general and specific dimensions of psychopathology in children younger than the age of widespread psychoactive substance use. Method: Parent symptom ratings, EF test scores, and diffusion tensor parameters were obtained from 9,500 9-10 year olds in the Adolescent Brain Cognitive Development (ABCD) Study. Results: A latent factor derived from EF test scores was significantly associated with all general and specific factors of psychopathology defined in a bifactor model. Furthermore, latent EF was associated with MD in 16 of 17 bilateral white matter tracts (range: β = -0.05; SE = 0.02; - β = -0.23; SE = 0.05) and FA in eight tracts. There were no direct associations of psychopathology with FA or MD in any tract, but there were significant indirect associations via EF of FA in multiple association and projection fibers and MD in all tracts except the forceps minor with both specific conduct problems and attention-deficit hyperactivity problems (ADHD) (range: β = 0.01; SE = 0.01; through β = 0.08; SE = 0.02). Conclusions: EF in children is inversely associated with indices of white matter microstructural integrity throughout the brain and the variance in white matter microstructure shared with EF is significantly associated with ADHD and conduct problems. 8587/8587Secondary AnalysisPrivate
Positive economic, psychosocial, and physiological ecologies predict brain structure and cognitive performance in 9- 10-year-old childrenWhile low socioeconomic status (SES) introduces risk for developmental outcomes among children, there are an array of proximal processes that determine the ecologies and thus the lived experiences of children. This study examined interrelations between 22 proximal measures in the economic, psychosocial, physiological, and perinatal ecologies of children, in association with brain structure and cognitive performance in a diverse sample of 8,158 9-10-year-old children from the Adolescent Brain Cognitive Development (ABCD) study. SES was measured by the income-to-needs ratio (INR), a measure used by federal poverty guidelines. Within the ABCD study, in what is one of the largest and most diverse cohort of children studied in the United States, we replicate associations of low SES with lower total cortical surface area and worse cognitive performance. Associations between low SES (<200% INR) and measures of development showed the steepest increases with INR, with apparent increases still visible beyond the level of economic disadvantage in the range of 200% - 400% INR. Notably, we found three latent factors encompassing positive ecologies for children across the areas of economic, psychosocial, physiological and perinatal well-being in association with better cognitive performance and higher total cortical surface area beyond the effects of SES. Specifically, latent factors encompassing youth perceived social support and perinatal well-being were positive predictors of developmental measures for all children, regardless of SES. Further, we found a general latent factor explained relationships between 20 of the proximal measures and encompassed a joint ecology of higher social and economic resources relative to low adversity across psychosocial, physiological, and perinatal domains. The association between the resource-to-adversity latent factor and cognitive performance was moderated by SES, such that for children in higher SES households, cognitive performance progressively increased with these latent factor scores, while for lower SES, cognitive performance increased only among children with the highest latent factor scores. Our findings suggest that both positive ecologies of increased access to resources and lower adversity are mutually critical for promoting better cognitive development in children from low SES households. Our findings inform future studies aiming to examine positive factors that influence healthier development in children.8158/8158Secondary AnalysisPrivate
Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD studyAttention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits, including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R2 = 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R2 = 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task.7999/7999Secondary AnalysisShared
Intra-individual variability in task performance after cognitive training is associated with long-term outcomes in childrenThe potential benefits and mechanistic effects of working memory training in children are the subject of much research and debate. The cumulative evidence indicates that training can alter brain structure and function in the short term and have lasting effects on behaviour. We show that five weeks of school-based, adaptive working memory training led to greater activity in prefrontal and striatal brain regions, higher task accuracy, and reduced intra-individual variability in response times. Using a sequential sampling decision model, we demonstrate that this reduction in intra-individual variability can be explained by changes to the evidence accumulation rates and thresholds. Critically, intra-individual variability was more closely associated with academic skills and mental health 6-12 months after the end of training than task accuracy. Taken together, our results suggest that improvements in attention control are the initial mechanism that leads to the long-run benefits from adaptive working memory training. Improvements in selective and sustained attention after the training might serve as a scaffold for subsequent changes in higher cognitive processes, academic skills, and general well-being. Furthermore, these results highlight that the selection of outcome measures and the timing of the assessments play a crucial role in detecting training efficacy. Intra-individual variability appears to be useful in quantifying the immediate impact of cognitive training interventions and predicting the future emergence of academic and socioemotional skills. Thus, evaluating intra-individual variability, during or directly after training could allow for the early tailoring of training interventions in terms of duration or content to maximise their impact.7844/7844Primary AnalysisPrivate
The association of outdoor ambient fine particulate matter with intracellular white matter microstructural properties among children in a cross-sectional studyOutdoor fine particulate matter (PM2.5) is a ubiquitous environmental neurotoxicant that may affect the developing brain. Little is known about associations between PM2.5 and white matter connectivity. Objectives: To identify associations between annual residential PM2.5 exposure and white matter microstructure health in a national sample of children ages 9-10 years-old; to determine if associations are specific to certain white matter pathways or vary across neuroimaging diffusion markers reflective of intracellular and extracellular microstructural processes. Design: Cross-sectional Setting: The Adolescent Brain and Cognitive Development (ABCD) study®, comprised of 21 study sites across the United States, using baseline data collected from October 2016 to October 2018 Participants: Children ages 9-10 years-old Exposure: Annual average of fine particulate matter (PM2.5 exposure) estimated by ensemble-based models and assigned to the primary residential addresses at baseline Main Outcomes and Measures: Diffusion-weighted imaging (DWI) and tractography were used to delineate white matter tracts. The biophysical modeling technique of restriction spectrum imaging (RSI) was implemented to examine total hindered diffusion and restricted, isotropic and anisotropic intracellular diffusion in each tract. Hierarchical mixed effects models with natural splines were utilized to analyze the associations between PM2.5 exposure and DWI. Results: In a study population of 7,602 children (ages 8.9-11.1 years; 47.8% female), hemispheric effects were seen in associations between annual ambient PM2.5 and white matter microstructure. Hemisphere-stratified models revealed significant associations between PM2.5 exposure and restricted isotropic intracellular diffusion in the left cingulum, left superior longitudinal fasciculus, and bilaterally in the fornix and uncinate fasciculus. In tracts with the strongest positive associations, a PM2.5 increase from 8 µg/m3 to 12 µg/m3 related to increases of 2.164% (95% CI: 0.490, 3.838) in the left cingulum, 1.949% (95% CI: 0.430, 3.468) in the left uncinate, and 1.676% (95% CI: 0.014, 3.338) in the right uncinate. Widespread negative associations were observed between PM2.5 and mean diffusivity. Conclusions and Relevance: In this cross-sectional study, our findings suggested that annual average PM2.5 exposure during childhood relates to increased restricted isotropic diffusion and decreased mean diffusivity of specific white matter tracts, potentially reflecting differences in the composition of white matter microarchitecture. 7602/7601Secondary Anal