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. 

NDA Help Center

Login Dialog

Frequently Asked Questions

Glossary

NDA Help Center

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.

Loading...

Login
Reset Password

NDA provides a single access to de-identified autism research data. For permission to download data, you will need an NDA account with approved access to NDA or a connected repository (AGRE, IAN, or the ATP). For NDA access, you need to be a research investigator sponsored by an NIH recognized institution with federal wide assurance. See Request Access for more information.

Warning Notice

This is a U.S. Government computer system, which may be accessed and used only for authorized Government business by authorized personnel. Unauthorized access or use of this computer system may subject violators to criminal, civil, and/or administrative action. All information on this computer system may be intercepted, recorded, read, copied, and disclosed by and to authorized personnel for official purposes, including criminal investigations. Such information includes sensitive data encrypted to comply with confidentiality and privacy requirements. Access or use of this computer system by any person, whether authorized or unauthorized, constitutes consent to these terms. There is no right of privacy in this system.

Update Password

You have logged in with a temporary password. Please update your password. Passwords must contain 8 or more characters and must contain at least 3 of the following types of characters:

  • Uppercase
  • Lowercase
  • Numbers
  • Special Characters limited to: %,_,!,@,#,$,-,%,&,+,=,),(,*,^,:,;

Subscribe to our mailing list

Mailing List(s)
Email Format

You are now leaving the NIMH Data Archive (NDA) web site to go to:

Click on the address above if the page does not change within 10 seconds.

Disclaimer

NDA is not responsible for the content of this external site and does not monitor other web sites for accuracy.

Accept Terms
Filter Cart
No filters selected
Description
Value Range
Notes
Data Structures with shared data
No filters have been selected
Switch User

1 Numbers reported are subjects by age
New Trial
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
1780Using fMRI to Measure Neural-level Signals Underlying Visual Memory BehaviorfMRI06/11/2021
1779fMRI-EmotionfMRI06/04/2021
1778MB6-Resting2fMRI06/04/2021
1777MB6-Resting1fMRI06/04/2021
1775K24 MRI Task - EBDMfMRI06/03/2021
1774Translating DiamondfMRI05/28/2021
1772RestingfMRI05/26/2021
1771Surround ModulationfMRI05/26/2021
1770Offset ResponsefMRI05/25/2021
1769MSITfMRI05/25/2021
1768Resting State fMRIfMRI05/25/2021
1767Meridian LocalizerfMRI05/20/2021
1766FOV LocalizerfMRI05/20/2021
1765Video Threat TaskfMRI05/20/2021
1764Dynamic Faces/Objects TaskfMRI05/20/2021
1763Social Density Video TaskfMRI05/20/2021
1762Using fMRI to Distinguish Between Models of Memory fMRI05/20/2021
1761LOC Localizer fMRI05/19/2021
1760EVC LocalizerfMRI05/19/2021
1759CNTR Localizer fMRI05/19/2021
1758Emotion Conflict TaskfMRI05/19/2021
1757Value of Control (VOC) TaskfMRI05/19/2021
1756MT localizerfMRI05/17/2021
1749Rest - 8 min - LIBRfMRI05/11/2021
1748Aim 1EEG05/10/2021
1747Overlay Hippocampus TAMUfMRI05/07/2021
1746 Overlay Whole Brain TAMUfMRI05/07/2021
1745T1-weighted (MPRAGE) TAMUfMRI05/07/2021
1744Resting state TAMUfMRI05/07/2021
1743Resting-state - Wayne StatefMRI05/07/2021
1742Resting-state - EmoryfMRI05/07/2021
1741Passive Faces - EmoryfMRI05/07/2021
1740IAPS Task - EmoryfMRI05/07/2021
1739Passive Faces - Wayne StatefMRI05/07/2021
1738IAPS Task - Wayne StatefMRI05/07/2021
1737Emotional Go-noGo (eGNG) Task - Wayne StatefMRI05/07/2021
1736Emotional Go-noGo (eGNG) Task - EmoryfMRI05/07/2021
1735emoreg_emg_cohort1EEG04/27/2021
1734genotyping for parent of originOmics04/22/2021
1733TASIT_AEye Tracking04/16/2021
1732RSVPEye Tracking04/16/2021
1731HierarchyfMRI04/15/2021
1730Resting StatefMRI04/14/2021
1729baseline_emg_cohort1EEG04/14/2021
1728Monetary EEG TaskEEG04/12/2021
1727iPSC-derived neurons from MDD patientsOmics04/07/2021
1726Face-matching Task 2fMRI04/06/2021
1725Emotion Interference TaskfMRI04/06/2021
1724Emotion Processing TaskfMRI04/06/2021
1723Incentive Processing TaskfMRI04/06/2021
Collection - Add Experiment
Add Supporting Documentation
Select File

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.

Request Submission Exemption
Characters Remaining:
Not Eligible

The Data Expected list for this Collection shows some data as missing. Contact the NDA Help Desk with any questions.

Collection Updated

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.

[CMS] Attention

Please confirm that you will not be enrolling any more subjects and that all data has been collected and submitted.

[CMS] Error

Unable to change collection phase where targeted enrollment is less than 90%

Delete Submission Exemption
Are you sure you want to delete this submission exemption?
You have requested to move the sharing dates for the following assessments:
Data Expected Item Original Sharing Date New Sharing Date

Please provide a reason for this change, which will be sent to the Program Officers listed within this collection:

Explanation must be between 20 and 200 characters in length.

Please press Save or Cancel
Add New Email Address - Dialog
New Email Address
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
$134,797,802.00
11,892
Loading Chart...
NIH - Extramural None

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 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_Public.zip Background Please Read - Release Notes: Adolescent Brain Cognitive Development (ABCD) Fix Release 2.0.1 General Public
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_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
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
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

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 $3,345,408.00
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 340 340 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 ABCL Scores Clinical Assessments 6571
ABCD ACS Post Stratification Weights Clinical Assessments 11878
ABCD Adult Behavior Checklist Clinical Assessments 6571
ABCD Brief Problem Monitor-Teacher Form For Ages 6-18 (BPMT) Clinical Assessments 11878
ABCD Cash Choice Task Clinical Assessments 11878
ABCD Child Nutrition Assessment Clinical Assessments 11235
ABCD Children's Report of Parental Behavioral Inventory Clinical Assessments 11878
ABCD Cyber Bully Clinical Assessments 6571
ABCD Delay Discounting Trial Level Behavior Clinical Assessments 8973
ABCD Developmental History Questionnaire Clinical Assessments 11878
ABCD Early Adolescent Temperament Questionnaire Parent Clinical Assessments 6571
ABCD Emotional Stroop Task Trial Level Behavior Clinical Assessments 8966
ABCD Family History Assessment Part 1 Clinical Assessments 11878
ABCD Family History Assessment Part 2 Clinical Assessments 11878
ABCD Fasttrack QC Instrument Imaging 11818
ABCD Follow-Up Scheduling Screener Clinical Assessments 6571
ABCD Game of Dice Summary Scores Clinical Assessments 6571
ABCD Game of Dice Trial Level Behavior Clinical Assessments 6498
ABCD Hormone Saliva Salimetric Scores Clinical Assessments 11878
ABCD Irma Substudy Child Clinical Assessments 11875
ABCD Irma Substudy Parent Clinical Assessments 11875
ABCD Little Man Task Summary Scores Clinical Assessments 11878
ABCD Little Man Task Trial Level Behavior Clinical Assessments 11797
ABCD Longitudinal Parent Demographics Survey Clinical Assessments 11878
ABCD Longitudinal Parent Diagnostic Interview for DSM-5 Background Items Full (KSAD) Clinical Assessments 11359
ABCD Longitudinal Parent Medical History Questionnaire Clinical Assessments 11359
ABCD Longitudinal Parent Ohio State Traumatic Brain Injury Screen-Short Modified (OTBI) Clinical Assessments 11359
ABCD Longitudinal Parent Sports and Activities Involvement Questionnaire (SAIQ) Clinical Assessments 11359
ABCD Longitudinal Summary Scores Medical History Clinical Assessments 11359
ABCD Longitudinal Summary Scores Sports Activity Clinical Assessments 11359
ABCD Longitudinal Summary Scores Traumatic Brain Injury Clinical Assessments 11359
ABCD Longitudinal Tracking Clinical Assessments 11878
ABCD MR Findings Clinical Assessments 11878
ABCD MRI Info Imaging 11809
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 NIH Toolbox Trial Level Behavior Clinical Assessments 11878
ABCD Occupation Survey Parent Clinical Assessments 6571
ABCD Other Resilience Clinical Assessments 11878
ABCD Pain Questionnaire Clinical Assessments 6571
ABCD Parent Acculturation Survey Modified from PhenX (ACC) Clinical Assessments 11878
ABCD Parent Adult Self Report Raw Scores Aseba (ASR) Clinical Assessments 11878
ABCD Parent Adult Self Report Scores Aseba (ASR) Clinical Assessments 11878
ABCD Parent Child Behavior Checklist Raw Scores Aseba (CBCL) Clinical Assessments 11878
ABCD Parent Child Behavior Checklist Scores Aseba (CBCL) Clinical Assessments 11878
ABCD Parent Community Risk and Protective Factors (CRPF) Clinical Assessments 11878
ABCD Parent Demographics Survey Clinical Assessments 11878
ABCD Parent Diagnostic Interview for DSM-5 (KSADS) Traumatic Events Clinical Assessments 11878
ABCD Parent Diagnostic Interview for DSM-5 Background Items Full (KSADS-5) Clinical Assessments 11878
ABCD Parent Diagnostic Interview for DSM-5 Full (KSADS-5) Clinical Assessments 11878
ABCD Parent Family Environment Scale-Family Conflict Subscale Modified from PhenX (FES) Clinical Assessments 11878
ABCD Parent Family History Summary Scores Clinical Assessments 11878
ABCD Parent Fitbit Baseline Clinical Assessments 164
ABCD Parent Fitbit Followup Clinical Assessments 153
ABCD Parent Gender Identity Clinical Assessments 11359
ABCD Parent KSADS Conduct Disorder Clinical Assessments 11878
ABCD Parent Life Events Clinical Assessments 11359
ABCD Parent Medical History Questionnaire (MHX) Clinical Assessments 11878
ABCD Parent Medications Survey Inventory Modified from PhenX (PMP) Clinical Assessments 11878
ABCD Parent Mexican American Cultural Values Scale Modified (MACV) Clinical Assessments 11878
ABCD Parent Mobil Tech Postassessment Clinical Assessments 67
ABCD Parent Mobil Tech Preassessment Clinical Assessments 82
ABCD Parent Multi-Group Ethnic Identity-Revised Survey (MEIM) Clinical Assessments 11878
ABCD Parent Neighborhood Safety/Crime Survey Modified from PhenX (NSC) Clinical Assessments 11878
ABCD Parent Ohio State Traumatic Brain Injury Screen-Short Modified (OTBI) Clinical Assessments 11878
ABCD Parent Parent General Behavior Inventory-Mania (PGBI) Clinical Assessments 11878
ABCD Parent Participant Last Use Survey Day 2 3 4 (PLUS) Clinical Assessments 11878
ABCD Parent PhenX Community Cohesion Clinical Assessments 6571
ABCD Parent Pubertal Development Scale and Menstrual Cycle Survey History (PDMS) Clinical Assessments 11878
ABCD Parent School Attendance and Grades Clinical Assessments 6571
ABCD Parent Screen Time Survey (STQ) Clinical Assessments 11878
ABCD Parent Short Social Responsiveness Scale Clinical Assessments 11235
ABCD Parent Sleep Disturbance Scale for Children (SDS) Clinical Assessments 11878
ABCD Parent Sports and Activities Involvement Questionnaire (SAIQ) Clinical Assessments 11878
ABCD Parent Survey of Substance Use Density, Storage, and Exposure Clinical Assessments 6571
ABCD Parent Vancouver Index of Acculturation-Short Survey (VIA) Clinical Assessments 11878
ABCD Parental Monitoring Survey Clinical Assessments 11878
ABCD Parental Rules on Substance Use Clinical Assessments 11878
ABCD Pearson Scores Clinical Assessments 11878
ABCD Peer Experiences Questionnaire Clinical Assessments 6571
ABCD Post-assessment Parent Survey for Fitbit Protocol Clinical Assessments 6571
ABCD Post-assessment Youth Survey for Fitbit Protocol Clinical Assessments 6571
ABCD Pre-assessment Parent Survey for Fitbit Protocol Clinical Assessments 6571
ABCD Pre-assessment Youth Survey for Fitbit Protocol Clinical Assessments 6571
ABCD Prodromal Psychosis Scale Clinical Assessments 11878
ABCD Pubertal Hormone Saliva Clinical Assessments 11878
ABCD RA Scanning Checklist and Notes Clinical Assessments 11878
ABCD Recommended Imaging Inclusion Imaging 11810
ABCD School Risk and Protective Factors Survey Clinical Assessments 11878
ABCD Screener Clinical Assessments 11878
ABCD Social Influence Summary Scores Clinical Assessments 6571
ABCD Social Influence Task Trial Level Behavior Clinical Assessments 6498
ABCD Specialty Summary Score Clinical Assessments 11878
ABCD Sum Scores Culture & Environment Parent Clinical Assessments 11878
ABCD Sum Scores Culture & Environment Youth Clinical Assessments 11878
ABCD Sum Scores Mobil Tech Youth Clinical Assessments 11878
ABCD Sum Scores Physical Health Parent Clinical Assessments 11878
ABCD Sum Scores Physical Health Youth Clinical Assessments 11878
ABCD Sum Scores Traumatic Brain Injury Clinical Assessments 11878
ABCD Summary Scores Brief Problem Monitor-Teacher Form for Ages 6-18 Clinical Assessments 11878
ABCD Summary Scores Developmental History Clinical Assessments 11878
ABCD Summary Scores Medical History Clinical Assessments 11878
ABCD Summary Scores Sports Activity Clinical Assessments 11878
ABCD Summary Scores Substance Use Clinical Assessments 11878
ABCD Task fMRI MID Average Beta Weights Destrieux Parcellations Part 1 Imaging 10515
ABCD Task fMRI MID Average Beta Weights Destrieux Parcellations Part 2 Imaging 10515
ABCD Task fMRI MID Average Beta Weights Part 1 Imaging 10515
ABCD Task fMRI MID Average Beta Weights Part 2 Imaging 10515
ABCD Task fMRI MID Average SEM Destrieux Parcellations Part 1 Imaging 10515
ABCD Task fMRI MID Average SEM Destrieux Parcellations Part 2 Imaging 10515
ABCD Task fMRI MID Average Standard Error of the Mean Part 1 Imaging 10515
ABCD Task fMRI MID Average Standard Error of the Mean Part 2 Imaging 10515
ABCD Task fMRI MID Behavior Clinical Assessments 11878
ABCD Task fMRI MID Run 1 Beta Weights Destrieux Parcellations Part 1 Imaging 10515
ABCD Task fMRI MID Run 1 Beta Weights Destrieux Parcellations Part 2 Imaging 10515
ABCD Task fMRI MID Run 1 Beta Weights Part 1 Imaging 10515
ABCD Task fMRI MID Run 1 Beta Weights Part 2 Imaging 10515
ABCD Task fMRI MID Run 1 SEM Destrieux Parcellations Part 1 Imaging 10515
ABCD Task fMRI MID Run 1 SEM Destrieux Parcellations Part 2 Imaging 10515
ABCD Task fMRI MID Run 1 Standard Error of the Mean Part 1 Imaging 10515
ABCD Task fMRI MID Run 1 Standard Error of the Mean Part 2 Imaging 10515
ABCD Task fMRI MID Run 2 Beta Weights Destrieux Parcellations Part 1 Imaging 10312
ABCD Task fMRI MID Run 2 Beta Weights Destrieux Parcellations Part 2 Imaging 10312
ABCD Task fMRI MID Run 2 Beta Weights Part 1 Imaging 10312
ABCD Task fMRI MID Run 2 Beta Weights Part 2 Imaging 10312
ABCD Task fMRI MID Run 2 SEM Destrieux Parcellations Part 1 Imaging 10312
ABCD Task fMRI MID Run 2 SEM Destrieux Parcellations Part 2 Imaging 10312
ABCD Task fMRI MID Run 2 Standard Error of the Mean Part 1 Imaging 10312
ABCD Task fMRI MID Run 2 Standard Error of the Mean Part 2 Imaging 10312
ABCD Task fMRI MID Trial Level Behavior Imaging 10911
ABCD Task fMRI REC Behavior Clinical Assessments 11878
ABCD Task fMRI SST Average Beta Weights Imaging 10434
ABCD Task fMRI SST Average Beta Weights Destrieux Parcellations Part 1 Imaging 10434
ABCD Task fMRI SST Average Beta Weights Destrieux Parcellations Part 2 Imaging 10434
ABCD Task fMRI SST Average SEM Destrieux Parcellations Part 1 Imaging 10434
ABCD Task fMRI SST Average SEM Destrieux Parcellations Part 2 Imaging 10434
ABCD Task fMRI SST Average Standard Error of the Mean Imaging 10434
ABCD Task fMRI SST Behavior Clinical Assessments 11878
ABCD Task fMRI SST Run 1 Beta Weights Imaging 10434
ABCD Task fMRI SST Run 1 Beta Weights Destrieux Parcellations Part 1 Imaging 10434
ABCD Task fMRI SST Run 1 Beta Weights Destrieux Parcellations Part 2 Imaging 10434
ABCD Task fMRI SST Run 1 SEM Destrieux Parcellations Part 1 Imaging 10434
ABCD Task fMRI SST Run 1 SEM Destrieux Parcellations Part 2 Imaging 10434
ABCD Task fMRI SST Run 1 Standard Error of the Mean Imaging 10434
ABCD Task fMRI SST Run 2 Beta Weights Imaging 10148
ABCD Task fMRI SST Run 2 Beta Weights Destrieux Parcellations Part 1 Imaging 10148
ABCD Task fMRI SST Run 2 Beta Weights Destrieux Parcellations Part 2 Imaging 10148
ABCD Task fMRI SST Run 2 SEM Destrieux Parcellations Part 1 Imaging 10148
ABCD Task fMRI SST Run 2 SEM Destrieux Parcellations Part 2 Imaging 10148
ABCD Task fMRI SST Run 2 Standard Error of the Mean Imaging 10148
ABCD Task fMRI SST Trial Level Behavior Imaging 10802
ABCD Task fMRI nBack Average Beta Weights Imaging 10372
ABCD Task fMRI nBack Average Beta Weights Destrieux Parcellations Part 1 Imaging 10372
ABCD Task fMRI nBack Average Beta Weights Destrieux Parcellations Part 2 Imaging 10372
ABCD Task fMRI nBack Average SEM Destrieux Parcellations Part 1 Imaging 10372
ABCD Task fMRI nBack Average SEM Destrieux Parcellations Part 2 Imaging 10372
ABCD Task fMRI nBack Average Standard Error of the Mean Imaging 10372
ABCD Task fMRI nBack Behavior Clinical Assessments 11878
ABCD Task fMRI nBack Run 1 Beta Weights Imaging 10372
ABCD Task fMRI nBack Run 1 Beta Weights Destrieux Parcellations Part 1 Imaging 10372
ABCD Task fMRI nBack Run 1 Beta Weights Destrieux Parcellations Part 2 Imaging 10372
ABCD Task fMRI nBack Run 1 SEM Destrieux Parcellations Part 1 Imaging 10372
ABCD Task fMRI nBack Run 1 SEM Destrieux Parcellations Part 2 Imaging 10372
ABCD Task fMRI nBack Run 1 Standard Error of the Mean Imaging 10372
ABCD Task fMRI nBack Run 2 Beta Weights Imaging 10218
ABCD Task fMRI nBack Run 2 Beta Weights Destrieux Parcellations Part 1 Imaging 10218
ABCD Task fMRI nBack Run 2 Beta Weights Destrieux Parcellations Part 2 Imaging 10218
ABCD Task fMRI nBack Run 2 SEM Destrieux Parcellations Part 1 Imaging 10218
ABCD Task fMRI nBack Run 2 SEM Destrieux Parcellations Part 2 Imaging 10218
ABCD Task fMRI nBack Run 2 Standard Error of the Mean Imaging 10218
ABCD Task fMRI nBack Trial Level Behavior Imaging 10671
ABCD Timeline Follow-back Survey Calendar Scores (TLFB) Clinical Assessments 11878
ABCD Twin Zygosity Rating Clinical Assessments 11878
ABCD Youth 10 Item Delinquency Scale Clinical Assessments 11359
ABCD Youth 7-Up Mania Items Clinical Assessments 11235
ABCD Youth Acculturation Survey Modified from PhenX (ACC) Clinical Assessments 11878
ABCD Youth Alcohol Measures Clinical Assessments 11359
ABCD Youth Alcohol Screen Clinical Assessments 11878
ABCD Youth Anthropometrics Modified From PhenX (ANT) Clinical Assessments 11878
ABCD Youth Behavioral Inhibition/Behavioral Approach System Scales Modified from PhenX (BIS/BAS) Clinical Assessments 11878
ABCD Youth Block Food Screen Clinical Assessments 6571
ABCD Youth Blood Analysis Clinical Assessments 6571
ABCD Youth Blood Pressure Clinical Assessments 6571
ABCD Youth Brief Problem Monitor Clinical Assessments 11457
ABCD Youth Community Risk and Protective Factors Clinical Assessments 6571
ABCD Youth Delay Discounting Sum Scores Clinical Assessments 11235
ABCD Youth Diagnostic Interview for DSM-5 5 (KSADS-5) Clinical Assessments 11878
ABCD Youth Diagnostic Interview for DSM-5 Background Items 5 (KSADS-5) Clinical Assessments 11878
ABCD Youth Discrimination Measure Clinical Assessments 11359
ABCD Youth Edinburgh Handedness Inventory Short Form (EHIS) Clinical Assessments 11878
ABCD Youth Emotional Stroop Task Clinical Assessments 11235
ABCD Youth Family Environment Scale-Family Conflict Subscale Modified from PhenX (FES) Clinical Assessments 11878
ABCD Youth Fitbit Baseline Clinical Assessments 162
ABCD Youth Fitbit Daily Physical Activity Summaries Clinical Assessments 5761
ABCD Youth Fitbit Daily Sleep Summaries Clinical Assessments 4518
ABCD Youth Fitbit Followup Clinical Assessments 150
ABCD Youth Fitbit Weekly Physical Activity Summaries Clinical Assessments 5518
ABCD Youth Fitbit Weekly Sleep Summaries Clinical Assessments 4422
ABCD Youth Gender Identity Clinical Assessments 11359
ABCD Youth Genetic Blood (RUCDR) Clinical Assessments 11878
ABCD Youth Genetic Saliva (RUCDR) Clinical Assessments 11878
ABCD Youth Gish2 Clinical Assessments 6571
ABCD Youth Hair Results Clinical Assessments 676
ABCD Youth Hair Sample Clinical Assessments 11878
ABCD Youth Life Events Clinical Assessments 11359
ABCD Youth Marijuana Illicit Drug Measures Clinical Assessments 11359
ABCD Youth Mexican American Cultural Values Scale Clinical Assessments 6571
ABCD Youth Mid Year Phone Interview Substance Use Clinical Assessments 11612
ABCD Youth Mobil Tech Postassessment Clinical Assessments 66
ABCD Youth Mobil Tech Preassessment Clinical Assessments 81
ABCD Youth Monetary Incentive Delay Task Survey Post Scan Questionnaire Clinical Assessments 11878
ABCD Youth Munich Chronotype Questionnaire Clinical Assessments 6571
ABCD Youth NIH TB Summary Scores Clinical Assessments 11878
ABCD Youth NIH Toolbox Positive Affect Items Clinical Assessments 11424
ABCD Youth Neighborhood Safety/Crime Survey Modified from PhenX (NSC) Clinical Assessments 11878
ABCD Youth Nicalert Clinical Assessments 11359
ABCD Youth Nicotine Measures Clinical Assessments 11359
ABCD Youth Participant Last Use Survey Day 1 2 3 4 (PLUS) Clinical Assessments 11878
ABCD Youth Peer Behavior Profile Clinical Assessments 6571
ABCD Youth Peer Network Health Protective Scaler Clinical Assessments 6571
ABCD Youth Post Scan Questionnaire 2 Clinical Assessments 11878
ABCD Youth Post Scan Questionnaire 1 Clinical Assessments 11878
ABCD Youth Pre Scan Questionnaire 1 Clinical Assessments 11878
ABCD Youth Pre Scan Questionnaire 2 Clinical Assessments 11878
ABCD Youth Pubertal Development Scale and Menstrual Cycle Survey History (PDMS) Clinical Assessments 11878
ABCD Youth Rescan Monetary Incentive Delay Task Survey Post Scan Questionnaire Clinical Assessments 11878
ABCD Youth School Attendance and Grades Clinical Assessments 6571
ABCD Youth Screen Time Survey (STQ) Clinical Assessments 11878
ABCD Youth Snellen Vision Screener (SVS) Clinical Assessments 11878
ABCD Youth Substance Use Attitudes Clinical Assessments 11359
ABCD Youth Substance Use Interview Clinical Assessments 11878
ABCD Youth Substance Use Introduction and Patterns Clinical Assessments 11359
ABCD Youth Summary Scores BPM and POA Clinical Assessments 11457
ABCD Youth Teeth Collection Clinical Assessments 11878
ABCD Youth Toxicology Test Clinical Assessments 11878
ABCD Youth Wills Problem Solving Scale Clinical Assessments 11235
ABCD Youth Youth Risk Behavior Survey Exercise Physical Activity (YRB) Clinical Assessments 11878
ABCD dMRI DTI Destrieux Parcellations Part 1 Imaging 11787
ABCD dMRI DTI Destrieux Parcellations Part 2 Imaging 11787
ABCD dMRI DTI Full Destrieux Parcellation Part 1 Imaging 11787
ABCD dMRI DTI Full Destrieux Parcellation Part 2 Imaging 11787
ABCD dMRI DTI Full Part 1 Imaging 11787
ABCD dMRI DTI Full Part 2 Imaging 11787
ABCD dMRI DTI Part 1 Imaging 11787
ABCD dMRI DTI Part 2 Imaging 11787
ABCD dMRI Post Processing QC Imaging 11539
ABCD dMRI RSI Destrieux Parcellation Part 1 Imaging 11787
ABCD dMRI RSI Destrieux Parcellation Part 2 Imaging 11787
ABCD dMRI RSI Destrieux Parcellation Part 3 Imaging 11787
ABCD dMRI RSI Part 1 Imaging 11787
ABCD dMRI RSI Part 2 Imaging 11787
ABCD rsfMRI Destrieux Imaging 11532
ABCD rsfMRI Gordon Network Correlations Imaging 11532
ABCD rsfMRI Network to Subcortical ROI Correlations Imaging 11532
ABCD rsfMRI Temporal Variance Imaging 11532
ABCD sMRI Destrieux Parcellation Part 1 Imaging 11787
ABCD sMRI Destrieux Parcellation Part 2 Imaging 11787
ABCD sMRI Part 1 Imaging 11787
ABCD sMRI Part 2 Imaging 11787
Automated Post-Processing QC Metrics Imaging 11790
FreeSurfer QC Imaging 11799
Genomics Sample Genomics 10217
Image Imaging 11808
MRI QC Raw Part 1 Imaging 11820
MRI QC Raw Part 2 Imaging 11820
MRI QC Raw Part 3 Imaging 11810
Manual fMRI Post-Processing QC Imaging 11693
Mobile Data Imaging 5339
Parent Prosocial Behavior Survey Clinical Assessments 11878
Processed MRI Data Imaging 11783
Residential History Derived Scores Clinical Assessments 11878
Social Development Child Alabama Parenting Questionnaire Clinical Assessments 11235
Social Development Child Difficulties in Emotion Regulation Clinical Assessments 11235
Social Development Child Feedback Clinical Assessments 11235
Social Development Child Firearms Clinical Assessments 11235
Social Development Child Peer Behavior Clinical Assessments 11235
Social Development Child Personality Disposition Clinical Assessments 11235
Social Development Child Reported Delinquency Clinical Assessments 11235
Social Development Child Victimization Clinical Assessments 11235
Social Development Contact Track Clinical Assessments 11878
Social Development Parent Alabama Parenting Questionnaire Clinical Assessments 11235
Social Development Parent Difficulties in Emotion Regulation Clinical Assessments 11235
Social Development Parent Feedback Clinical Assessments 11235
Social Development Parent Firearms Clinical Assessments 11235
Social Development Parent Neighborhood Clinical Assessments 11235
Social Development Parent Personality Disposition Clinical Assessments 11235
Social Development Parent Reported Delinquency Clinical Assessments 11235
Social Development Parent Victimization Clinical Assessments 11235
Social Development Visit Type Clinical Assessments 11235
Sum Scores Mental Health Parent Clinical Assessments 11878
Sum Scores Mental Health Youth Clinical Assessments 11878
UPPS-P for Children Short Form (ABCD-version) Clinical Assessments 11878
Youth Prosocial Behavior Survey Clinical Assessments 11878

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

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
34079688Create StudyEffects of Adolescent Cannabis Use on Motivation and Depression: A Systematic Review.Current addiction reportsPacheco-Colón, Ileana; Ramirez, Ana Regina; Gonzalez, RaulDecember 1, 2019Not Determined
34033672Create StudyPrediction of suicidal ideation and attempt in 9 and 10 year-old children using transdiagnostic risk features.PloS oneHarman, Gareth; Kliamovich, Dakota; Morales, Angelica M; Gilbert, Sydney; Barch, Deanna M; Mooney, Michael A; Feldstein Ewing, Sarah W; Fair, Damien A; Nagel, Bonnie JJanuary 1, 2021Not Determined
34013256Create StudyResilience to COVID-19: Socioeconomic Disadvantage Associated With Higher Positive Parent-youth Communication and Youth Disease-prevention Behavior.Research squareMarshall, Andrew; Hackman, Daniel; Baker, Fiona; Breslin, Florence; Brown, Sandra; Dick, Anthony; Gonzalez, Marybel; Guillaume, Mathieu; Kiss, Orsolya; Lisdahl, Krista; McCabe, Connor; Iii, William Pelham; Sheth, Chandni; Tapert, Susan; Rinsveld, Amandine Van; Wade, Natasha; Sowell, ElizabethApril 23, 2021Not Determined
34008881Create StudyCommentary: Reply to ''Transgender and mental health'' by Philip Graham.Journal of child psychology and psychiatry, and allied disciplinesPotter, AlexandraMay 19, 2021Not Determined
33984711Create StudyEcological stress, amygdala reactivity, and internalizing symptoms in preadolescence: Is parenting a buffer?Cortex; a journal devoted to the study of the nervous system and behaviorDemidenko, Michael I; Ip, Ka I; Kelly, Dominic P; Constante, Kevin; Goetschius, Leigh G; Keating, Daniel PJuly 1, 2021Not Determined
33981668Create StudyBreastfeeding Duration Is Associated With Domain-Specific Improvements in Cognitive Performance in 9-10-Year-Old Children.Frontiers in public healthLopez, Daniel A; Foxe, John J; Mao, Yunjiao; Thompson, Wesley K; Martin, Hayley J; Freedman, Edward GJanuary 1, 2021Not Determined
33965165Create StudyThe Neurocircuit Signature of Retaliation in Adolescents With Alcohol Problems.Biological psychiatry. Cognitive neuroscience and neuroimagingBjork, James MMay 1, 2021Not Determined
33900639Create StudyExtracurricular Activities, Screen Media Activity, and Sleep May Be Modifiable Factors Related to Children''s Cognitive Functioning: Evidence From the ABCD Study®.Child developmentKirlic, Namik; Colaizzi, Janna M; Cosgrove, Kelly T; Cohen, Zsofia P; Yeh, Hung-Wen; Breslin, Florence; Morris, Amanda S; Aupperle, Robin L; Singh, Manpreet K; Paulus, Martin PApril 26, 2021Not Determined
33850154Create StudyAssociations between frontal lobe structure, parent-reported obstructive sleep disordered breathing and childhood behavior in the ABCD dataset.Nature communicationsIsaiah, Amal; Ernst, Thomas; Cloak, Christine C; Clark, Duncan B; Chang, LindaApril 13, 2021Not Determined
33816055Create StudyRisks versus consequences of adolescent and young adult substance use: A focus on executive control.Current addiction reportsLuciana, MonicaDecember 1, 2020Not Determined
33809905Create StudyParental Education and Left Lateral Orbitofrontal Cortical Activity during N-Back Task: An fMRI Study of American Adolescents.Brain sciencesAssari, Shervin; Boyce, Shanika; Saqib, Mohammed; Bazargan, Mohsen; Caldwell, Cleopatra HMarch 22, 2021Not Determined
33806587Create StudyResting-State Functional Connectivity between Putamen and Salience Network and Childhood Body Mass Index.Neurology internationalAssari, Shervin; Boyce, ShanikaMarch 4, 2021Not Determined
33799042Create StudyContributions from resting state functional connectivity and familial risk to early adolescent-onset MDD: Results from the Adolescent Brain Cognitive Development study.Journal of affective disordersCai, Yuqi; Elsayed, Nourhan M; Barch, Deanna MMay 15, 2021Not Determined
33777643Create StudyNeural and behavioral correlates associated with adolescent marijuana use.Current addiction reportsSubramaniam, Punitha; Yurgelun-Todd, DeborahDecember 1, 2020Not Determined
33754935Create StudyThe Relationship between Early Alcohol Use Behaviors and Adolescent Pubertal and Psychosocial Development: A Latent Growth Analysis.Substance use & misuseMay, A C; Aguinaldo, L D; Tan, R; Courtney, K E; Jacobus, JJanuary 1, 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
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
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
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
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 JDecember 16, 2020Not 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
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
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
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
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
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
32841716Create StudyDeep learning identifies morphological determinants of sex differences in the pre-adolescent brain.NeuroImageAdeli, Ehsan; Zhao, Qingyu; Zahr, Natalie M; Goldstone, Aimee; Pfefferbaum, Adolf; Sullivan, Edith V; Pohl, Kilian MDecember 1, 2020Not Determined
32832919Create StudyRace, Socioeconomic Status, and Sex Hormones among Male and Female American Adolescents.Reproductive medicine (Basel, Switzerland)Assari, Shervin; Boyce, Shanika; Bazargan, Mohsen; Caldwell, Cleopatra HSeptember 1, 2020Not Determined
32814618Create StudyPrevalence and correlates of concussion in children: Data from the Adolescent Brain Cognitive Development study.Cortex; a journal devoted to the study of the nervous system and behaviorDufour, Steven C; Adams, Rachel Sayko; Brody, David L; Puente, Antonio N; Gray, Joshua COctober 1, 2020Not Determined
32803367Create StudyThe effects of nicotine and cannabis co-use during adolescence and young adulthood on white matter cerebral blood flow estimates.PsychopharmacologyCourtney, Kelly E; Baca, Rachel; Doran, Neal; Jacobson, Aaron; Liu, Thomas T; Jacobus, JoannaDecember 2020Not Determined
32803159Create StudyReplication of Associations With Psychotic-Like Experiences in Middle Childhood From the Adolescent Brain Cognitive Development (ABCD) Study.Schizophrenia bulletin openKarcher, Nicole R; Loewy, Rachel L; Savill, Mark; Avenevoli, Shelli; Huber, Rebekah S; Simon, Tony J; Leckliter, Ingrid N; Sher, Kenneth J; Barch, Deanna MJanuary 1, 2020Not Determined
32800084Create StudyCognitive Functioning Related to Binge Alcohol and Cannabis Co-Use in Abstinent Adolescents and Young Adults.Journal of studies on alcohol and drugsWade, Natasha E; Bagot, Kara S; Tapert, Susan F; Gruber, Staci A; Filbey, Francesca M; Lisdahl, Krista MJuly 2020Not Determined
32795607Create StudyObsessive-Compulsive Disorder in the Adolescent Brain Cognitive Development Study: Impact of Changes From DSM-IV to DSM-5.Journal of the American Academy of Child and Adolescent PsychiatryPotter, Alexandra S; Owens, Max M; Albaugh, Matthew; Garavan, Hugh; Sher, Kenneth J; Kaufman, Joan; Barch, Deanna MApril 1, 2021Not Determined
32771178Create StudyPragmatic and Explanatory Progress Using Statistical Models of Disturbed Mind, Brain, and Behavior to Improve Mental Health.Biological psychiatry. Cognitive neuroscience and neuroimagingPaulus, Martin PAugust 1, 2020Not Determined
32771177Create StudyUnderstanding the Nature and Treatment of Psychopathology: Can the Data Guide the Way?Biological psychiatry. Cognitive neuroscience and neuroimagingBarch, Deanna MAugust 1, 2020Not Determined
32768868Create StudyAssociations between age and brain microstructure in older community-dwelling men and women: the Rancho Bernardo Study.Neurobiology of agingReas, Emilie T; Hagler Jr, Donald J; Andrews, Murray J; Lee, Roland R; Dale, Anders M; McEvoy, Linda KNovember 1, 2020Not Determined
32758445Create StudyPrecision Neuroimaging Opens a New Chapter of Neuroplasticity Experimentation.NeuronFair, Damien A; Yeo, B T ThomasAugust 5, 2020Not Determined
32737734Create StudyThe Main and Interactive Associations between Demographic Factors and Psychopathology and Treatment Utilization in Youth: A Test of Intersectionality in the ABCD Study.Research on child and adolescent psychopathologyMennies, Rebekah J; Birk, Samantha L; Norris, Lesley A; Olino, Thomas MJanuary 1, 2021Not Determined
32731811Create StudyReward Processing in Children With Disruptive Behavior Disorders and Callous-Unemotional Traits in the ABCD Study.The American journal of psychiatryHawes, Samuel W; Waller, Rebecca; Byrd, Amy L; Bjork, James M; Dick, Anthony S; Sutherland, Matthew T; Riedel, Michael C; Tobia, Michael J; Thomson, Nicholas; Laird, Angela R; Gonzalez, RaulApril 2021Not Determined
32731083Create StudyAssociation of prenatal alcohol exposure with preadolescent alcohol sipping in the ABCD study®.Drug and alcohol dependenceLees, Briana; Mewton, Louise; Stapinski, Lexine A; Teesson, Maree; Squeglia, Lindsay MSeptember 2020Not Determined
32718077Create StudySubjective Family Socioeconomic Status and Adolescents'' Attention: Blacks'' Diminished Returns.Children (Basel, Switzerland)Assari, Shervin; Boyce, Shanika; Bazargan, MohsenJuly 2020Not Determined
32715317Create StudyBOLD responses to inhibition in cannabis-using adolescents and emerging adults after 2 weeks of monitored cannabis abstinence.PsychopharmacologyWallace, Alexander L; Maple, Kristin E; Barr, Alicia T; Lisdahl, Krista MNovember 2020Not Determined
32699512Create StudyAdolescent brain and the natural allure of digital media
.Dialogues in clinical neuroscienceGiedd, Jay NJune 1, 2020Not Determined
32685340Create StudySleep and Alcohol Use in Women.Alcohol research : current reviewsInkelis, Sarah M; Hasler, Brant P; Baker, Fiona CJanuary 2020Not Determined
32682894Create StudyEnvironmental Risk Factors and Psychotic-like Experiences in Children Aged 9-10.Journal of the American Academy of Child and Adolescent PsychiatryKarcher, Nicole R; Schiffman, Jason; Barch, Deanna MApril 1, 2021Not Determined
32672986Create StudyCriterion validity and relationships between alternative hierarchical dimensional models of general and specific psychopathology.Journal of abnormal psychologyMoore, Tyler M; Kaczkurkin, Antonia N; Durham, E Leighton; Jeong, Hee Jung; McDowell, Malerie G; Dupont, Randolph M; Applegate, Brooks; Tackett, Jennifer L; Cardenas-Iniguez, Carlos; Kardan, Omid; Akcelik, Gaby N; Stier, Andrew J; Rosenberg, Monica D; Hedeker, Donald; Berman, Marc G; Lahey, Benjamin BOctober 1, 2020Not Determined
32665545Create StudyUnderstanding the genetic determinants of the brain with MOSTest.Nature communicationsvan der Meer, Dennis; Frei, Oleksandr; Kaufmann, Tobias; Shadrin, Alexey A; Devor, Anna; Smeland, Olav B; Thompson, Wesley K; Fan, Chun Chieh; Holland, Dominic; Westlye, Lars T; Andreassen, Ole A; Dale, Anders MJuly 2020Not Determined
32660094Create StudyAfrican American Children''s Diminished Returns of Subjective Family Socioeconomic Status on Fun Seeking.Children (Basel, Switzerland)Assari, Shervin; Akhlaghipour, Golnoush; Boyce, Shanika; Bazargan, Mohsen; Caldwell, Cleopatra HJuly 2020Not Determined
32659528Create StudyFine particulate matter exposure during childhood relates to hemispheric-specific differences in brain structure.Environment internationalCserbik, Dora; Chen, Jiu-Chiuan; McConnell, Rob; Berhane, Kiros; Sowell, Elizabeth R; Schwartz, Joel; Hackman, Daniel A; Kan, Eric; Fan, Chun C; Herting, Megan MOctober 2020Not Determined
32656052Create StudyAfrican Americans'' Diminished Returns of Parental Education on Adolescents'' Depression and Suicide in the Adolescent Brain Cognitive Development (ABCD) Study.European journal of investigation in health, psychology and educationAssari, Shervin; Boyce, Shanika; Bazargan, Mohsen; Caldwell, Cleopatra HJune 2020Not Determined
32654667Create StudyCallous-unemotional traits and reduced default mode network connectivity within a community sample of children.Development and psychopathologyUmbach, Rebecca H; Tottenham, NimJuly 13, 2020Not Determined
32607126Create StudyThe importance of social factors in the association between physical activity and depression in children.Child and adolescent psychiatry and mental healthConley, May I; Hindley, Isabella; Baskin-Sommers, Arielle; Gee, Dylan G; Casey, B J; Rosenberg, Monica DJanuary 2020Not Determined
32605891Create StudyPrenatal cannabis exposure and sleep outcomes in children 9-10 years of age in the adolescent brain cognitive development SM study.Sleep healthWiniger, Evan A; Hewitt, John KDecember 1, 2020Not Determined
32603213Create StudyNeighborhood Deprivation Shapes Motivational-Neurocircuit Recruitment in Children.Psychological scienceMullins, Teagan S; Campbell, Ethan M; Hogeveen, JeremyJuly 2020Not Determined
32601990Create StudyCaffeine intake and cognitive functions in children.PsychopharmacologyZhang, Han; Lee, Zu Xuan; Qiu, AnqiOctober 2020Not Determined
32593800Create StudyNeighborhood deprivation, prefrontal morphology and neurocognition in late childhood to early adolescence.NeuroImageVargas, Teresa; Damme, Katherine S F; Mittal, Vijay AOctober 2020Not Determined
32591777Create StudyInvestigation of Psychiatric and Neuropsychological Correlates of Default Mode Network and Dorsal Attention Network Anticorrelation in Children.Cerebral cortex (New York, N.Y. : 1991)Owens, Max M; Yuan, DeKang; Hahn, Sage; Albaugh, Matthew; Allgaier, Nicholas; Chaarani, Bader; Potter, Alexandra; Garavan, HughNovember 3, 2020Not Determined
32575523Create StudyReward Responsiveness in the Adolescent Brain Cognitive Development (ABCD) Study: African Americans'' Diminished Returns of Parental Education.Brain sciencesAssari, Shervin; Boyce, Shanika; Akhlaghipour, Golnoush; Bazargan, Mohsen; Caldwell, Cleopatra HJune 2020Not Determined
32553194Create StudyParsing Psychiatric Heterogeneity Through Common and Unique Circuit-Level Deficits.Biological psychiatrySatterthwaite, Theodore D; Feczko, Eric; Kaczkurkin, Antonia N; Fair, Damien AJuly 1, 2020Not Determined
32541809Create StudyThe ABCD study: understanding the development of risk for mental and physical health outcomes.Neuropsychopharmacology : official publication of the American College of NeuropsychopharmacologyKarcher, Nicole R; Barch, Deanna MJanuary 2021Not Determined
32539089Create StudyPhenotype-specific differences in polygenicity and effect size distribution across functional annotation categories revealed by AI-MiXeR.Bioinformatics (Oxford, England)Shadrin, Alexey A; Frei, Oleksandr; Smeland, Olav B; Bettella, Francesco; O'Connell, Kevin S; Gani, Osman; Bahrami, Shahram; Uggen, Tea K E; Djurovic, Srdjan; Holland, Dominic; Andreassen, Ole A; Dale, Anders MSeptember 15, 2020Not Determined
32522466Create StudyAdverse childhood experiences and psychotic-like experiences are associated above and beyond shared correlates: Findings from the adolescent brain cognitive development study.Schizophrenia researchKarcher, Nicole R; Niendam, Tara A; Barch, Deanna MAugust 2020Not Determined
32522303Create StudyIncipient alcohol use in childhood: Early alcohol sipping and its relations with psychopathology and personality.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 JJune 2020Not Determined
32511674Create StudyAssociation of Prenatal Opioid Exposure With Precentral Gyrus Volume in Children.JAMA pediatricsHartwell, Micah L; Croff, Julie M; Morris, Amanda Sheffield; Breslin, Florence J; Dunn, KellySeptember 2020Not Determined
32503310Create StudyFamily Socioeconomic Status and Exposure to Childhood Trauma: Racial Differences.Children (Basel, Switzerland)Assari, ShervinJune 2020Not Determined
32463952Create StudyEarly adolescent gender diversity and mental health in the Adolescent Brain Cognitive Development study.Journal of child psychology and psychiatry, and allied disciplinesPotter, Alexandra; Dube, Sarahjane; Allgaier, Nicholas; Loso, Hannah; Ivanova, Masha; Barrios, Lisa C; Bookheimer, Susan; Chaarani, Bader; Dumas, Julie; Feldstein-Ewing, Sarah; Freedman, Edward G; Garavan, Hugh; Hoffman, Elizabeth; McGlade, Erin; Robin, Leah; Johns, Michelle MFebruary 2021Not Determined
32455841Create StudyParental Education on Youth Inhibitory Control in the Adolescent Brain Cognitive Development (ABCD) Study: Blacks'' Diminished Returns.Brain sciencesAssari, ShervinMay 2020Not Determined
32451322Create StudyBehavioral and Neural Signatures of Working Memory in Childhood.The Journal of neuroscience : the official journal of the Society for NeuroscienceRosenberg, Monica D; Martinez, Steven A; Rapuano, Kristina M; Conley, May I; Cohen, Alexandra O; Cornejo, M Daniela; Hagler Jr, Donald J; Meredith, Wesley J; Anderson, Kevin M; Wager, Tor D; Feczko, Eric; Earl, Eric; Fair, Damien A; Barch, Deanna M; Watts, Richard; Casey, B JJune 2020Not Determined
32443584Create StudyMinorities'' Diminished Returns of Parental Educational Attainment on Adolescents'' Social, Emotional, and Behavioral Problems.Children (Basel, Switzerland)Assari, Shervin; Boyce, Shanika; Caldwell, Cleopatra H; Bazargan, MohsenMay 2020Not Determined
32439147Create StudyParent versus child report of children''s sexual orientation: associations with psychiatric morbidity in the Adolescent Brain Cognitive Development study.Annals of epidemiologyClark, Kirsty A; Mennies, Rebekah J; Olino, Thomas M; Dougherty, Lea R; Pachankis, John EMay 2020Not Determined
32433925Create StudyTwin studies of brain, cognition, and behavior.Neuroscience and biobehavioral reviewsHewitt, John KAugust 1, 2020Not Determined
32414481Create StudyWhat Is the Link Between Attention-Deficit/Hyperactivity Disorder and Sleep Disturbance? A Multimodal Examination of Longitudinal Relationships and Brain Structure Using Large-Scale Population-Based Cohorts.Biological psychiatryShen, Chun; Luo, Qiang; Chamberlain, Samuel R; Morgan, Sarah; Romero-Garcia, Rafael; Du, Jingnan; Zhao, Xingzhong; Touchette, Évelyne; Montplaisir, Jacques; Vitaro, Frank; Boivin, Michel; Tremblay, Richard E; Zhao, Xing-Ming; Robaey, Philippe; Feng, Jianfeng; Sahakian, Barbara JSeptember 2020Not Determined
32399985Create StudyUnique longitudinal relationships between symptoms of psychopathology in youth: A cross-lagged panel network analysis in the ABCD study.Journal of child psychology and psychiatry, and allied disciplinesFunkhouser, Carter J; Chacko, Anjali A; Correa, Kelly A; Kaiser, Ariela J E; Shankman, Stewart AFebruary 2021Not Determined
32354687Create StudyExamining Specificity of Neural Correlates of Childhood Psychotic-like Experiences During an Emotional n-Back Task.Biological psychiatry. Cognitive neuroscience and neuroimagingO'Brien, Kathleen J; Barch, Deanna M; Kandala, Sridhar; Karcher, Nicole RJune 2020Not Determined
32339569Create StudyTwin studies of brain, cognition, and behavior.Neuroscience and biobehavioral reviewsHewitt, John KAugust 1, 2020Not Determined
32333792Create StudyParental Family History of Alcohol Use Disorder and Neural Correlates of Response Inhibition in Children From the Adolescent Brain Cognitive Development (ABCD) Study.Alcoholism, clinical and experimental researchLees, Briana; Aguinaldo, Laika; Squeglia, Lindsay M; Infante, Maria Alejandra; Wade, Natasha E; Hernandez Mejia, Margie; Jacobus, JoannaJune 2020Not Determined
32325210Create StudyRemoval of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity.NeuroImageGratton, Caterina; Dworetsky, Ally; Coalson, Rebecca S; Adeyemo, Babatunde; Laumann, Timothy O; Wig, Gagan S; Kong, Tania S; Gratton, Gabriele; Fabiani, Monica; Barch, Deanna M; Tranel, Daniel; Miranda-Dominguez, Oscar; Fair, Damien A; Dosenbach, Nico U F; Snyder, Abraham Z; Perlmutter, Joel S; Petersen, Steven E; Campbell, Meghan CAugust 2020Not Determined
32322677Create StudyBinge and Cannabis Co-Use Episodes in Relation to White Matter Integrity in Emerging Adults.Cannabis and cannabinoid researchWade, Natasha E; Thomas, Alicia M; Gruber, Staci A; Tapert, Susan F; Filbey, Francesca M; Lisdahl, Krista MMarch 2020Not Determined
32307027Create StudyImpact of 2 Weeks of Monitored Abstinence on Cognition in Adolescent and Young Adult Cannabis Users.Journal of the International Neuropsychological Society : JINSWallace, Alexander L; Wade, Natasha E; Lisdahl, Krista MSeptember 2020Not Determined
32267484Create StudyNeurobiology, Clinical Presentation, and Treatment of Methamphetamine Use Disorder: A Review.JAMA psychiatryPaulus, Martin P; Stewart, Jennifer LSeptember 1, 2020Not Determined
32260480Create StudyDo Adolescents Use Substances to Relieve Uncomfortable Sensations? A Preliminary Examination of Negative Reinforcement among Adolescent Cannabis and Alcohol Users.Brain sciencesMay, April C; Jacobus, Joanna; Stewart, Jennifer L; Simmons, Alan N; Paulus, Martin P; Tapert, Susan FApril 2020Not Determined
32257767Create StudyBehavioral Treatments for Adolescent Cannabis Use Disorder: a Rationale for Cognitive Retraining.Current addiction reportsAguinaldo, Laika D; Squeglia, Lindsay M; Gray, Kevin M; Coronado, Clarisa; Lees, Briana; Tomko, Rachel L; Jacobus, JoannaDecember 2019Not Determined
32217469Create StudyHeterogeneity of executive function revealed by a functional random forest approach across ADHD and ASD.NeuroImage. ClinicalCordova, Michaela; Shada, Kiryl; Demeter, Damion V; Doyle, Olivia; Miranda-Dominguez, Oscar; Perrone, Anders; Schifsky, Emma; Graham, Alice; Fombonne, Eric; Langhorst, Beth; Nigg, Joel; Fair, Damien A; Feczko, EricJanuary 1, 2020Not Determined
32201043Create StudyGenome-wide Association Analysis of Parkinson''s Disease and Schizophrenia Reveals Shared Genetic Architecture and Identifies Novel Risk Loci.Biological psychiatrySmeland, Olav B; Shadrin, Alexey; Bahrami, Shahram; Broce, Iris; Tesli, Martin; Frei, Oleksandr; Wirgenes, Katrine V; O'Connell, Kevin S; Krull, Florian; Bettella, Francesco; Steen, Nils Eiel; Sugrue, Leo; Wang, Yunpeng; Svenningsson, Per; Sharma, Manu; Pihlstrøm, Lasse; Toft, Mathias; O'Donovan, Michael; Djurovic, Srdjan; Desikan, Rahul; Dale, Anders M; Andreassen, Ole AFebruary 2021Not Determined
32179028Create StudyEffect of alcohol use on the adolescent brain and behavior.Pharmacology, biochemistry, and behaviorLees, Briana; Meredith, Lindsay R; Kirkland, Anna E; Bryant, Brittany E; Squeglia, Lindsay MMay 2020Not Determined
32171431Create StudyRisk and protective factors for childhood suicidality: a US population-based study.The lancet. PsychiatryJaniri, Delfina; Doucet, Gaelle E; Pompili, Maurizio; Sani, Gabriele; Luna, Beatriz; Brent, David A; Frangou, SophiaApril 2020Not Determined
32153355Create StudyImage-Derived Phenotyping Informed by Independent Component Analysis-An Atlas-Based Approach.Frontiers in neuroscienceMoradi, Mahdi; Ekhtiari, Hamed; Victor, Teresa A; Paulus, Martin; Kuplicki, RayusJanuary 2020Not Determined
32144045Create StudyDisruptive Behavior Problems, Callous-Unemotional Traits, and Regional Gray Matter Volume in the Adolescent Brain and Cognitive Development Study.Biological psychiatry. Cognitive neuroscience and neuroimagingWaller, Rebecca; Hawes, Samuel W; Byrd, Amy L; Dick, Anthony S; Sutherland, Matthew T; Riedel, Michael C; Tobia, Michael J; Bottenhorn, Katherine L; Laird, Angela R; Gonzalez, RaulMay 2020Not Determined
32119636Create StudySleep and Women''s Health: Sex- and Age-Specific Contributors to Alcohol Use Disorders.Journal of women''s health (2002)Baker, Fiona C; Carskadon, Mary A; Hasler, Brant PMarch 2020Not Determined
32107167Create StudyComputational Evidence for Underweighting of Current Error and Overestimation of Future Error in Anxious Individuals.Biological psychiatry. Cognitive neuroscience and neuroimagingHowlett, Jonathon R; Thompson, Wesley K; Paulus, Martin PApril 2020Not Determined
32105123Create StudyAn item response theory analysis of the Prodromal Questionnaire-Brief Child Version: Developing a screening form that informs understanding of self-reported psychotic-like experiences in childhood.Journal of abnormal psychologyKarcher, Nicole R; Perino, Michael T; Barch, Deanna MApril 2020Not Determined
32102994Create StudyParental and social factors in relation to child psychopathology, behavior, and cognitive function.Translational psychiatryZhang, Han; Lee, Zu Xuan; White, Tonya; Qiu, AnqiFebruary 2020Not Determined
32098300Create StudyAssessing the Role of Cannabis Use on Cortical Surface Structure in Adolescents and Young Adults: Exploring Gender and Aerobic Fitness as Potential Moderators.Brain sciencesSullivan, Ryan M; Wallace, Alexander L; Wade, Natasha E; Swartz, Ann M; Lisdahl, Krista MFebruary 2020Not Determined
32079563Create StudyA Neurobiological Model of Alcohol Marketing Effects on Underage Drinking.Journal of studies on alcohol and drugs. SupplementCourtney, Andrea L; Casey, B J; Rapuano, Kristina MMarch 2020Not Determined
32078973Create StudyCommon and distinct brain activity associated with risky and ambiguous decision-making.Drug and alcohol dependencePoudel, Ranjita; Riedel, Michael C; Salo, Taylor; Flannery, Jessica S; Hill-Bowen, Lauren D; Eickhoff, Simon B; Laird, Angela R; Sutherland, Matthew TApril 2020Not Determined
32046896Create StudySleep Disturbance Predicts Depression Symptoms in Early Adolescence: Initial Findings From the Adolescent Brain Cognitive Development Study.The Journal of adolescent health : official publication of the Society for Adolescent MedicineGoldstone, Aimée; Javitz, Harold S; Claudatos, Stephanie A; Buysse, Daniel J; Hasler, Brant P; de Zambotti, Massimiliano; Clark, Duncan B; Franzen, Peter L; Prouty, Devin E; Colrain, Ian M; Baker, Fiona CMay 2020Not Determined
32039857Create StudySerial Reaction Time Task Performance in Older Adults with Neuropsychologically Defined Mild Cognitive Impairment.Journal of Alzheimer''s disease : JADHong, Yue; Alvarado, Rachel L; Jog, Amod; Greve, Douglas N; Salat, David HJanuary 1, 2020Not Determined
32031652Create StudyPrevalence and Family-Related Factors Associated With Suicidal Ideation, Suicide Attempts, and Self-injury in Children Aged 9 to 10 Years.JAMA network openDeVille, Danielle C; Whalen, Diana; Breslin, Florence J; Morris, Amanda S; Khalsa, Sahib S; Paulus, Martin P; Barch, Deanna MFebruary 2020Not Determined
32015467Create StudySleep duration, brain structure, and psychiatric and cognitive problems in children.Molecular psychiatryCheng, Wei; Rolls, Edmund; Gong, Weikang; Du, Jingnan; Zhang, Jie; Zhang, Xiao-Yong; Li, Fei; Feng, JianfengFebruary 2020Not Determined
32005346Create StudySensors Capabilities, Performance, and Use of Consumer Sleep Technology.Sleep medicine clinicsde Zambotti, Massimiliano; Cellini, Nicola; Menghini, Luca; Sarlo, Michela; Baker, Fiona CMarch 2020Not Determined
31983035Create StudyWhite Matter Tract Integrity, Involvement in Sports, and Depressive Symptoms in Children.Child psychiatry and human developmentGorham, Lisa S; Barch, Deanna MJune 2020Not Determined
31932788Create StudyAssociation of lead-exposure risk and family income with childhood brain outcomes.Nature medicineMarshall, Andrew T; Betts, Samantha; Kan, Eric C; McConnell, Rob; Lanphear, Bruce P; Sowell, Elizabeth RJanuary 2020Not Determined
31931163Create StudyEditorial: Family History of Depression and Child Striatal Volumes in the ABCD Study: Promise and Perils of Neuroimaging Research With Large Samples.Journal of the American Academy of Child and Adolescent PsychiatryBeauchaine, Theodore POctober 1, 2020Not Determined
31883424Create StudyNeural mechanisms underlying suicide behavior in youth with bipolar disorder.Bipolar disordersHuber, Rebekah S; Yurgelun-Todd, Deborah AMarch 1, 2020Not Determined
31872334Create StudyMeta-analytic clustering dissociates brain activity and behavior profiles across reward processing paradigms.Cognitive, affective & behavioral neuroscienceFlannery JS, Riedel MC, Bottenhorn KL, Poudel R, Salo T, Hill-Bowen LD, Laird AR, Sutherland MTApril 2020Not Determined
31841018Create StudyFactor structure, measurement and structural invariance, and external validity of an abbreviated youth version of the UPPS-P Impulsive Behavior Scale.Psychological assessmentWatts, Ashley L; Smith, Gregory T; Barch, Deanna M; Sher, Kenneth JApril 2020Not Determined
31822320Create StudyNeuropsychological Trajectories Associated with Adolescent Alcohol and Cannabis Use: A Prospective 14-Year Study.Journal of the International Neuropsychological Society : JINSInfante, M Alejandra; Nguyen-Louie, Tam T; Worley, Matthew; Courtney, Kelly E; Coronado, Clarisa; Jacobus, JoannaMay 2020Not Determined
31818798Create StudyPrevalence and correlates of maladaptive guilt in middle childhood.Journal of affective disordersDonohue, Meghan Rose; Tillman, Rebecca; Perino, Michael T; Whalen, Diana J; Luby, Joan; Barch, Deanna MFebruary 2020Not Determined
31816020Create StudyAssociations Among Body Mass Index, Cortical Thickness, and Executive Function in Children.JAMA pediatricsLaurent, Jennifer S; Watts, Richard; Adise, Shana; Allgaier, Nicholas; Chaarani, Bader; Garavan, Hugh; Potter, Alexandra; Mackey, ScottFebruary 2020Not Determined
31796137Create StudyMinnesota Center for Twin and Family Research.Twin research and human genetics : the official journal of the International Society for Twin StudiesWilson, Sylia; Haroian, Kevin; Iacono, William G; Krueger, Robert F; Lee, James J; Luciana, Monica; Malone, Stephen M; McGue, Matt; Roisman, Glenn I; Vrieze, ScottDecember 2019Not Determined
31778819Create StudyCorrection of respiratory artifacts in MRI head motion estimates.NeuroImageFair, Damien A; Miranda-Dominguez, Oscar; Snyder, Abraham Z; Perrone, Anders; Earl, Eric A; Van, Andrew N; Koller, Jonathan M; Feczko, Eric; Tisdall, M Dylan; van der Kouwe, Andre; Klein, Rachel L; Mirro, Amy E; Hampton, Jacqueline M; Adeyemo, Babatunde; Laumann, Timothy O; Gratton, Caterina; Greene, Deanna J; Schlaggar, Bradley L; Hagler Jr, Donald J; Watts, Richard; Garavan, Hugh; Barch, Deanna M; Nigg, Joel T; Petersen, Steven E; Dale, Anders M; Feldstein-Ewing, Sarah W; Nagel, Bonnie J; Dosenbach, Nico U FMarch 2020Not Determined
31727084Create StudyScreen time and problem behaviors in children: exploring the mediating role of sleep duration.The international journal of behavioral nutrition and physical activityGuerrero MD, Barnes JD, Chaput JP, Tremblay MSNovember 2019Not Determined
31700677Create StudySex differences in brain correlates of STEM anxiety.NPJ science of learningGonzalez, Ariel A; Bottenhorn, Katherine L; Bartley, Jessica E; Hayes, Timothy; Riedel, Michael C; Salo, Taylor; Bravo, Elsa I; Odean, Rosalie; Nazareth, Alina; Laird, Robert W; Sutherland, Matthew T; Brewe, Eric; Pruden, Shannon M; Laird, Angela RJanuary 2019Not Determined
31699293Create StudyConvergent Evidence for Predispositional Effects of Brain Gray Matter Volume on Alcohol Consumption.Biological psychiatryBaranger, David A A; Demers, Catherine H; Elsayed, Nourhan M; Knodt, Annchen R; Radtke, Spenser R; Desmarais, Aline; Few, Lauren R; Agrawal, Arpana; Heath, Andrew C; Barch, Deanna M; Squeglia, Lindsay M; Williamson, Douglas E; Hariri, Ahmad R; Bogdan, RyanApril 2020Not Determined
31653478Create StudyDriven by Pain, Not Gain: Computational Approaches to Aversion-Related Decision Making in Psychiatry.Biological psychiatryPaulus, Martin PFebruary 2020Not Determined
31648682Create StudyErratum.Biological psychiatryNovember 15, 2019Not Determined
31646343Create StudyChildhood Obesity, Cortical Structure, and Executive Function in Healthy Children.Cerebral cortex (New York, N.Y. : 1991)Ronan, Lisa; Alexander-Bloch, Aaron; Fletcher, Paul CApril 2020Not Determined
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
31624235Create StudyDelineating and validating higher-order dimensions of psychopathology in the Adolescent Brain Cognitive Development (ABCD) study.Translational psychiatryMichelini, Giorgia; Barch, Deanna M; Tian, Yuan; Watson, David; Klein, Daniel N; Kotov, RomanOctober 2019Not Determined
31614255Create StudyIdentifying reproducible individual differences in childhood functional brain networks: An ABCD study.Developmental cognitive neuroscienceMarek, Scott; Tervo-Clemmens, Brenden; Nielsen, Ashley N; Wheelock, Muriah D; Miller, Ryland L; Laumann, Timothy O; Earl, Eric; Foran, William W; Cordova, Michaela; Doyle, Olivia; Perrone, Anders; Miranda-Dominguez, Oscar; Feczko, Eric; Sturgeon, Darrick; Graham, Alice; Hermosillo, Robert; Snider, Kathy; Galassi, Anthony; Nagel, Bonnie J; Ewing, Sarah W Feldstein; Eggebrecht, Adam T; Garavan, Hugh; Dale, Anders M; Greene, Deanna J; Barch, Deanna M; Fair, Damien A; Luna, Beatriz; Dosenbach, Nico U FDecember 2019Not Determined
31561859Create StudyBrain Changes Induced by Electroconvulsive Therapy Are Broadly Distributed.Biological psychiatryOusdal, Olga Therese; Argyelan, Miklos; Narr, Katherine L; Abbott, Christopher; Wade, Benjamin; Vandenbulcke, Mathieu; Urretavizcaya, Mikel; Tendolkar, Indira; Takamiya, Akihiro; Stek, Max L; Soriano-Mas, Carles; Redlich, Ronny; Paulson, Olaf B; Oudega, Mardien L; Opel, Nils; Nordanskog, Pia; Kishimoto, Taishiro; Kampe, Robin; Jorgensen, Anders; Hanson, Lars G; Hamilton, J Paul; Espinoza, Randall; Emsell, Louise; van Eijndhoven, Philip; Dols, Annemieke; Dannlowski, Udo; Cardoner, Narcis; Bouckaert, Filip; Anand, Amit; Bartsch, Hauke; Kessler, Ute; Oedegaard, Ketil J; Dale, Anders M; Oltedal, Leif; GEMRICMarch 1, 2020Not Determined
31522280Create StudyAdolescent Substance Use Disorder Treatment: an Update on Evidence-Based Strategies.Current psychiatry reportsFadus MC, Squeglia LM, Valadez EA, Tomko RL, Bryant BE, Gray KMSeptember 2019Not Determined
31520123Create StudyDiscovery of shared genomic loci using the conditional false discovery rate approach.Human geneticsSmeland OB, Frei O, Shadrin A, O'Connell K, Fan CC, Bahrami S, Holland D, Djurovic S, Thompson WK, Dale AM, Andreassen OASeptember 2019Not Determined
31512192Create StudyNeurobiological and Cognitive Profile of Young Binge Drinkers: a Systematic Review and Meta-Analysis.Neuropsychology reviewLees, Briana; Mewton, Louise; Stapinski, Lexine A; Squeglia, Lindsay M; Rae, Caroline D; Teesson, MareeSeptember 2019Not Determined
31464996Create StudyThe emerging pattern of shared polygenic architecture of psychiatric disorders, conceptual and methodological challenges.Psychiatric geneticsSmeland OB, Frei O, Fan CC, Shadrin A, Dale AM, Andreassen OAOctober 2019Not Determined
31427753Create StudyPrediction of neurocognition in youth from resting state fMRI.Molecular psychiatrySripada, Chandra; Rutherford, Saige; Angstadt, Mike; Thompson, Wesley K; Luciana, Monica; Weigard, Alexander; Hyde, Luke H; Heitzeg, MaryDecember 2020Not Determined
31415884Create StudyImage processing and analysis methods for the Adolescent Brain Cognitive Development Study.NeuroImageHagler Jr, Donald J; Hatton, SeanN; Cornejo, M Daniela; Makowski, Carolina; Fair, Damien A; Dick, Anthony Steven; Sutherland, Matthew T; Casey, B J; Barch, Deanna M; Harms, Michael P; Watts, Richard; Bjork, James M; Garavan, Hugh P; Hilmer, Laura; Pung, Christopher J; Sicat, Chelsea S; Kuperman, Joshua; Bartsch, Hauke; Xue, Feng; Heitzeg, Mary M; Laird, Angela R; Trinh, Thanh T; Gonzalez, Raul; Tapert, Susan F; Riedel, Michael C; Squeglia, Lindsay M; Hyde, Luke W; Rosenberg, Monica D; Earl, Eric A; Howlett, Katia D; Baker, Fiona C; Soules, Mary; Diaz, Jazmin; de Leon, Octavio Ruiz; Thompson, Wesley K; Neale, Michael C; Herting, Megan; Sowell, Elizabeth R; Alvarez, Ruben P; Hawes, Samuel W; Sanchez, Mariana; Bodurka, Jerzy; Breslin, Florence J; Morris, Amanda Sheffield; Paulus, Martin P; Simmons, W Kyle; Polimeni, Jonathan R; van der Kouwe, Andre; Nencka, Andrew S; Gray, Kevin M; Pierpaoli, Carlo; Matochik, John A; Noronha, Antonio; Aklin, Will M; Conway, Kevin; Glantz, Meyer; Hoffman, Elizabeth; Little, Roger; Lopez, Marsha; Pariyadath, Vani; Weiss, Susan Rb; Wolff-Hughes, Dana L; DelCarmen-Wiggins, Rebecca; Feldstein Ewing, Sarah W; Miranda-Dominguez, Oscar; Nagel, Bonnie J; Perrone, Anders J; Sturgeon, Darrick T; Goldstone, Aimee; Pfefferbaum, Adolf; Pohl, Kilian M; Prouty, Devin; Uban, Kristina; Bookheimer, Susan Y; Dapretto, Mirella; Galvan, Adriana; Bagot, Kara; Giedd, Jay; Infante, M Alejandra; Jacobus, Joanna; Patrick, Kevin; Shilling, Paul D; Desikan, Rahul; Li, Yi; Sugrue, Leo; Banich, Marie T; Friedman, Naomi; Hewitt, John K; Hopfer, Christian; Sakai, Joseph; Tanabe, Jody; Cottler, Linda B; Nixon, Sara Jo; Chang, Linda; Cloak, Christine; Ernst, Thomas; Reeves, Gloria; Kennedy, David N; Heeringa, Steve; Peltier, Scott; Schulenberg, John; Sripada, Chandra; Zucker, Robert A; Iacono, William G; Luciana, Monica; Calabro, Finnegan J; Clark, Duncan B; Lewis, David A; Luna, Beatriz; Schirda, Claudiu; Brima, Tufikameni; Foxe, John J; Freedman, Edward G; Mruzek, Daniel W; Mason, Michael J; Huber, Rebekah; McGlade, Erin; Prescot, Andrew; Renshaw, Perry F; Yurgelun-Todd, Deborah A; Allgaier, Nicholas A; Dumas, Julie A; Ivanova, Masha; Potter, Alexandra; Florsheim, Paul; Larson, Christine; Lisdahl, Krista; Charness, Michael E; Fuemmeler, Bernard; Hettema, John M; Maes, Hermine H; Steinberg, Joel; Anokhin, Andrey P; Glaser, Paul; Heath, Andrew C; Madden, Pamela A; Baskin-Sommers, Arielle; Constable, R Todd; Grant, Steven J; Dowling, Gayathri J; Brown, Sandra A; Jernigan, Terry L; Dale, Anders MNovember 2019Not Determined
31413180Create Study24-Hour Movement Behaviors and Impulsivity.PediatricsGuerrero MD, Barnes JD, Walsh JJ, Chaput JP, Tremblay MS, Goldfield GSSeptember 2019Not Determined
31385460Create StudyCannabis and the developing brain: What does the evidence say?Birth defects researchJacobus, Joanna; Courtney, Kelly E; Hodgdon, Elizabeth A; Baca, RachelOctober 2019Not Determined
31376925Create StudyMachine Learning and Brain Imaging: Opportunities and Challenges.Trends in neurosciencesPaulus MP, Kuplicki R, Yeh HWOctober 2019Not Determined
31350420Create StudyGenetic variation across RNA metabolism and cell death gene networks is implicated in the semantic variant of primary progressive aphasia.Scientific reportsBonham, Luke W; Steele, Natasha Z R; Karch, Celeste M; Broce, Iris; Geier, Ethan G; Wen, Natalie L; Momeni, Parastoo; Hardy, John; Miller, Zachary A; Gorno-Tempini, Maria Luisa; Hess, Christopher P; Lewis, Patrick; Miller, Bruce L; Seeley, William W; Manzoni, Claudia; Desikan, Rahul S; Baranzini, Sergio E; Ferrari, Raffaele; Yokoyama, Jennifer S; International FTD-Genomics Consortium (IFGC)July 2019Not Determined
31305867Create StudyEnsuring the Best Use of Data: The Adolescent Brain Cognitive Development Study.JAMA pediatricsCompton, Wilson M; Dowling, Gayathri J; Garavan, HughSeptember 2019Not Determined
31288867Create StudyDemographic, psychological, behavioral, and cognitive correlates of BMI in youth: Findings from the Adolescent Brain Cognitive Development (ABCD) study.Psychological medicineGray, Joshua C; Schvey, Natasha A; Tanofsky-Kraff, MarianJuly 2020Not Determined
31258099Create StudyPubertal development mediates the association between family environment and brain structure and function in childhood.Development and psychopathologyThijssen, Sandra; Collins, Paul F; Luciana, MonicaMay 2020Not Determined
31200279Create StudyThe rise of e-cigarettes, pod mod devices, and JUUL among youth: Factors influencing use, health implications, and downstream effects.Drug and alcohol dependenceFadus MC, Smith TT, Squeglia LMAugust 2019Not Determined
31156374Create StudyAutomated, Efficient, and Accelerated Knowledge Modeling of the Cognitive Neuroimaging Literature Using the ATHENA Toolkit.Frontiers in neuroscienceRiedel, Michael C; Salo, Taylor; Hays, Jason; Turner, Matthew D; Sutherland, Matthew T; Turner, Jessica A; Laird, Angela RJanuary 2019Not Determined
31134293Create StudyComputational approaches and machine learning for individual-level treatment predictions.PsychopharmacologyPaulus, Martin P; Thompson, Wesley KMay 2021Not Determined
31110341Create StudyNo evidence for a bilingual executive function advantage in the nationally representative ABCD study.Nature human behaviourDick, Anthony Steven; Garcia, Nelcida L; Pruden, Shannon M; Thompson, Wesley K; Hawes, Samuel W; Sutherland, Matthew T; Riedel, Michael C; Laird, Angela R; Gonzalez, RaulJuly 2019Not Determined
31106219Create StudyToward a Neurobiological Basis for Understanding Learning in University Modeling Instruction Physics Courses.Frontiers in ICT (Lausanne, Switzerland)Brewe, Eric; Bartley, Jessica E; Riedel, Michael C; Sawtelle, Vashti; Salo, Taylor; Boeving, Emily R; Bravo, Elsa I; Odean, Rosalie; Nazareth, Alina; Bottenhorn, Katherine L; Laird, Robert W; Sutherland, Matthew T; Pruden, Shannon M; Laird, Angela RMay 2018Not Determined
31079000Create StudyAnterior cingulate volume reductions in abstinent adolescent and young adult cannabis users: Association with affective processing deficits.Psychiatry research. NeuroimagingMaple KE, Thomas AM, Kangiser MM, Lisdahl KMJune 2019Not Determined
31062126Create StudyDifferential Relationships of Child Anxiety and Depression to Child Report and Parent Report of Electronic Media Use.Child psychiatry and human developmentFors, Payton Q; Barch, Deanna MDecember 2019Not Determined
31043184Create StudyDecision-Making as a Latent Construct and its Measurement Invariance in a Large Sample of Adolescent Cannabis Users.Journal of the International Neuropsychological Society : JINSPacheco-Colón I, Hawes SW, Duperrouzel JC, Lopez-Quintero C, Gonzalez RAugust 2019Not Determined
31034667Create StudyCerebral circulation time derived from fMRI signals in large blood vessels.Journal of magnetic resonance imaging : JMRIYao, Jinxia Fiona; Wang, James H; Yang, Ho-Ching Shawn; Liang, Zhenhu; Cohen-Gadol, Aaron A; Rayz, Vitaliy L; Tong, YunjieNovember 2019Not Determined
31009035Create StudyNicotine Effects on White Matter Microstructure in Young Adults.Archives of clinical neuropsychology : the official journal of the National Academy of NeuropsychologistsKangiser MM, Thomas AM, Kaiver CM, Lisdahl KMJanuary 2019Not Determined
30980042Create StudyChronic sleep fragmentation enhances habenula cholinergic neural activity.Molecular psychiatryGe, Feifei; Mu, Ping; Guo, Rong; Cai, Li; Liu, Zheng; Dong, Yan; Huang, Yanhua HMarch 1, 2021Not Determined
30950740Create StudyGrowth Effects on Velopharyngeal Anatomy From Childhood to Adulthood.Journal of speech, language, and hearing research : JSLHRPerry, Jamie L; Kollara, Lakshmi; Sutton, Bradley P; Kuehn, David P; Fang, XiangmingMarch 25, 2019Not Determined
30949565Create StudyStress exposures, neurodevelopment and health measures in the ABCD study.Neurobiology of stressHoffman, Elizabeth A; Clark, Duncan B; Orendain, Natalia; Hudziak, James; Squeglia, Lindsay M; Dowling, Gayathri JFebruary 2019Not Determined
30926513Create StudyMeta-analytic Evidence for Neural Dysactivity Underlying Sexual Dysfunction.The journal of sexual medicinePoeppl TB, Langguth B, Laird AR, Eickhoff SBMay 2019Not Determined
30916716Create StudyAssociation of Prenatal Cannabis Exposure With Psychosis Proneness Among Children in the Adolescent Brain Cognitive Development (ABCD) Study.JAMA psychiatryFine JD, Moreau AL, Karcher NR, Agrawal A, Rogers CE, Barch DM, Bogdan RJuly 2019Not Determined
30905689Create StudyInvolvement in Sports, Hippocampal Volume, and Depressive Symptoms in Children.Biological psychiatry. Cognitive neuroscience and neuroimagingGorham LS, Jernigan T, Hudziak J, Barch DMMay 2019Not Determined
30875890Create StudyDo Stand-Biased Desks in the Classroom Change School-Time Activity and Sedentary Behavior?International journal of environmental research and public healthSwartz AM, Tokarek NR, Lisdahl K, Maeda H, Strath SJ, Cho CCMarch 2019Not Determined
30865236Create StudyAssociation Between Childhood Anhedonia and Alterations in Large-scale Resting-State Networks and Task-Evoked Activation.JAMA psychiatryPornpattananangkul, Narun; Leibenluft, Ellen; Pine, Daniel S; Stringaris, ArgyrisJune 2019Not Determined
30850130Create StudyResting-State Functional Connectivity and Psychotic-like Experiences in Childhood: Results From the Adolescent Brain Cognitive Development Study.Biological psychiatryKarcher NR, O'Brien KJ, Kandala S, Barch DMJuly 2019Not Determined
30846008Create StudyAssessing callous-unemotional traits: development of a brief, reliable measure in a large and diverse sample of preadolescent youth.Psychological medicineHawes, Samuel W; Waller, Rebecca; Thompson, Wesley K; Hyde, Luke W; Byrd, Amy L; Burt, S Alexandra; Klump, Kelly L; Gonzalez, RaulFebruary 2020Not Determined
30780067Create StudyTesting helping behavior and its relationship to antisocial personality and psychopathic traits.Psychiatry researchSakai, Joseph T; Raymond, Kristen M; McWilliams, Shannon K; Mikulich-Gilbertson, Susan KApril 2019Not Determined
30760808Create StudyBasic Units of Inter-Individual Variation in Resting State Connectomes.Scientific reportsSripada, Chandra; Angstadt, Mike; Rutherford, Saige; Kessler, Daniel; Kim, Yura; Yee, Mike; Levina, ElizavetaFebruary 2019Not Determined
30610197Create StudyGenome-wide analysis reveals extensive genetic overlap between schizophrenia, bipolar disorder, and intelligence.Molecular psychiatrySmeland, Olav B; Bahrami, Shahram; Frei, Oleksandr; Shadrin, Alexey; O'Connell, Kevin; Savage, Jeanne; Watanabe, Kyoko; Krull, Florian; Bettella, Francesco; Steen, Nils Eiel; Ueland, Torill; Posthuma, Danielle; Djurovic, Srdjan; Dale, Anders M; Andreassen, Ole AApril 2020Not Determined
30595399Create StudyThe structure of cognition in 9 and 10 year-old children and associations with problem behaviors: Findings from the ABCD study''s baseline neurocognitive battery.Developmental cognitive neuroscienceThompson, Wesley K; Barch, Deanna M; Bjork, James M; Gonzalez, Raul; Nagel, Bonnie J; Nixon, Sara Jo; Luciana, MonicaApril 2019Not Determined
30580899Create StudyFiber pathways supporting early literacy development in 5-8-year-old children.Brain and cognitionBroce IJ, Bernal B, Altman N, Bradley C, Baez N, Cabrera L, Hernandez G, De Feria A, Dick ASAugust 2019Not Determined
30578952Create StudySexual minority children: Mood disorders and suicidality disparities.Journal of affective disordersBlashill, Aaron J; Calzo, Jerel PMarch 2019Not Determined
30573013Create StudyAdolescent Brain Surface Area Pre- and Post-Cannabis and Alcohol Initiation.Journal of studies on alcohol and drugsInfante, M Alejandra; Courtney, Kelly E; Castro, Norma; Squeglia, Lindsay M; Jacobus, JoannaNovember 2018Not Determined
30557152Create StudyNIH''s Adolescent Brain Cognitive Development (ABCD) Study.Alcohol research : current reviewsAlcohol Research: Current Reviews Editorial StaffJanuary 1, 2018Not Determined
30481666Create StudyThe frontal aslant tract (FAT) and its role in speech, language and executive function.Cortex; a journal devoted to the study of the nervous system and behaviorDick AS, Garic D, Graziano P, Tremblay PFebruary 2019Not Determined
30476983Create StudyPrevalence of Eating Disorders Among US Children Aged 9 to 10 Years: Data From the Adolescent Brain Cognitive Development (ABCD) Study.JAMA pediatricsRozzell K, Moon DY, Klimek P, Brown T, Blashill AJJanuary 2019Not Determined
30474579Create StudyAerobic Fitness Level Moderates the Association Between Cannabis Use and Executive Functioning and Psychomotor Speed Following Abstinence in Adolescents and Young Adults.Journal of the International Neuropsychological Society : JINSWade, Natasha E; Wallace, Alexander L; Swartz, Ann M; Lisdahl, Krista MFebruary 2019Not Determined
30465762Create StudyThe Big Reveal: Precision Mapping Shines a Gigantic Floodlight on the Cerebellum.NeuronFair DANovember 2018Not Determined
30382511Create StudyEditors' Commentary for Special Issue: The 2017 CALDAR Summer Institute and International Conference Promoting Global Health-Precision Research in Substance Abuse, HIV, and Care.Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune PharmacologyChang L, Li MD, Hser YIDecember 2018Not Determined
30380617Create StudyParental Educational Attainment and Mental Well-Being of College Students; Diminished Returns of Blacks.Brain sciencesAssari, ShervinOctober 2018Not Determined
30347017Create StudyGenetic Predisposition vs Individual-Specific Processes in the Association Between Psychotic-like Experiences and Cannabis Use.JAMA psychiatryKarcher NR, Barch DM, Demers CH, Baranger DAA, Heath AC, Lynskey MT, Agrawal AJanuary 2019Not Determined
30343458Create StudyCognitive Deficits in Psychotic Disorders: A Lifespan Perspective.Neuropsychology reviewSheffield JM, Karcher NR, Barch DMDecember 2018Not Determined
30339913Create StudyScreen media activity and brain structure in youth: Evidence for diverse structural correlation networks from the ABCD study.NeuroImagePaulus, Martin P; Squeglia, Lindsay M; Bagot, Kara; Jacobus, Joanna; Kuplicki, Rayus; Breslin, Florence J; Bodurka, Jerzy; Morris, Amanda Sheffield; Thompson, Wesley K; Bartsch, Hauke; Tapert, Susan FJanuary 2019Not Determined
30295694Create StudyEffects of Cannabis Use and Subclinical ADHD Symptomology on Attention Based Tasks in Adolescents and Young Adults.Archives of clinical neuropsychology : the official journal of the National Academy of NeuropsychologistsWallace AL, Wade NE, Hatcher KF, Lisdahl KMOctober 2018Not Determined
30268792Create StudyAssociations between 24 hour movement behaviours and global cognition in US children: a cross-sectional observational study.The Lancet. Child & adolescent healthWalsh JJ, Barnes JD, Cameron JD, Goldfield GS, Chaput JP, Gunnell KE, Ledoux AA, Zemek RL, Tremblay MSNovember 2018Not Determined
30268791Create StudyConvergent influences of lifestyle behaviour on neurocognitive development in children.The Lancet. Child & adolescent healthBustamante, Eduardo EstebanNovember 2018Not Determined
30208469Create StudyChild Sexual Orientation and Gender Identity in the Adolescent Brain Cognitive Development Cohort Study.JAMA pediatricsCalzo JP, Blashill AJNovember 2018Not Determined
30195242Create StudyThe importance of considering polysubstance use: lessons from cocaine research.Drug and alcohol dependenceLiu Y, Williamson V, Setlow B, Cottler LB, Knackstedt LANovember 2018Not Determined
30159951Create StudyLaterality of the frontal aslant tract (FAT) explains externalizing behaviors through its association with executive function.Developmental scienceGaric, Dea; Broce, Iris; Graziano, Paulo; Mattfeld, Aaron; Dick, Anthony StevenMarch 2019Not Determined
30025312Create StudyOrbitofrontal connectivity is associated with depression and anxiety in marijuana-using adolescents.Journal of affective disordersSubramaniam, Punitha; Rogowska, Jadwiga; DiMuzio, Jennifer; Lopez-Larson, Melissa; McGlade, Erin; Yurgelun-Todd, DeborahOctober 2018Not Determined
30006199Create StudyVolume of the Human Hippocampus and Clinical Response Following Electroconvulsive Therapy.Biological psychiatryOltedal L, Narr KL, Abbott C, Anand A, Argyelan M, Bartsch H, Dannlowski U, Dols A, Van Eijndhoven P, Emsell L, Erchinger VJ, Espinoza R, Hahn T, Hanson LG, Hellemann G, Jorgensen MB, Kessler U, Oudega ML, Paulson OB, Redlich R, Sienaert P, Stek ML, Tendolkar I, Vandenbulcke M, Oedegaard KJ, et al.October 2018Not Determined
29977984Create StudySex Differences in the Developmental Neuroscience of Adolescent Substance Use Risk.Current opinion in behavioral sciencesHeitzeg, Mary M; Hardee, Jillian E; Beltz, Adriene MOctober 2018Not Determined
29946511Create StudyAbnormal cortical gyrification in criminal psychopathy.NeuroImage. ClinicalMiskovich, Tara A; Anderson, Nathaniel E; Harenski, Carla L; Harenski, Keith A; Baskin-Sommers, Arielle R; Larson, Christine L; Newman, Joseph P; Hanson, Jessica L; Stout, Daniel M; Koenigs, Michael; Shollenbarger, Skyler G; Lisdahl, Krista M; Decety, Jean; Kosson, David S; Kiehl, Kent AJanuary 2018Not Determined
29944961Create StudyMeta-analytic evidence for a core problem solving network across multiple representational domains.Neuroscience and biobehavioral reviewsBartley JE, Boeving ER, Riedel MC, Bottenhorn KL, Salo T, Eickhoff SB, Brewe E, Sutherland MT, Laird ARSeptember 2018Not Determined
29910020Create StudyThe racially diverse affective expression (RADIATE) face stimulus set.Psychiatry researchConley MI, Dellarco DV, Rubien-Thomas E, Cohen AO, Cervera A, Tottenham N, Casey BJDecember 2018Not Determined
29884281Create StudyInteroception and Mental Health: A Roadmap.Biological psychiatry. Cognitive neuroscience and neuroimagingKhalsa, Sahib S; Adolphs, Ralph; Cameron, Oliver G; Critchley, Hugo D; Davenport, Paul W; Feinstein, Justin S; Feusner, Jamie D; Garfinkel, Sarah N; Lane, Richard D; Mehling, Wolf E; Meuret, Alicia E; Nemeroff, Charles B; Oppenheimer, Stephen; Petzschner, Frederike H; Pollatos, Olga; Rhudy, Jamie L; Schramm, Lawrence P; Simmons, W Kyle; Stein, Murray B; Stephan, Klaas E; Van den Bergh, Omer; Van Diest, Ilse; von Leupoldt, Andreas; Paulus, Martin P; Interoception Summit 2016 participantsJune 2018Not Determined
29884279Create StudyTaking Aim at Interoception's Role in Mental Health.Biological psychiatry. Cognitive neuroscience and neuroimagingKhalsa SS, Feinstein JS, Simmons WK, Paulus MPJune 2018Not Determined
29879391Create StudyNeuroimaging Impaired Response Inhibition and Salience Attribution in Human Drug Addiction: A Systematic Review.NeuronZilverstand A, Huang AS, Alia-Klein N, Goldstein RZJune 2018Not Determined
29874361Create StudyAssessment of the Prodromal Questionnaire-Brief Child Version for Measurement of Self-reported Psychoticlike Experiences in Childhood.JAMA psychiatryKarcher, Nicole R; Barch, Deanna M; Avenevoli, Shelli; Savill, Mark; Huber, Rebekah S; Simon, Tony J; Leckliter, Ingrid N; Sher, Kenneth J; Loewy, Rachel LAugust 2018Not Determined
29773510Create StudyImplications of the ABCD study for developmental neuroscience.Developmental cognitive neuroscienceFeldstein Ewing, Sarah W; Bjork, James M; Luciana, MonicaAugust 2018Not Determined
29706313Create StudyA description of the ABCD organizational structure and communication framework.Developmental cognitive neuroscienceAuchter, Allison M; Hernandez Mejia, Margie; Heyser, Charles J; Shilling, Paul D; Jernigan, Terry L; Brown, Sandra A; Tapert, Susan F; Dowling, Gayathri JAugust 2018Not Determined
29703560Create StudyRecruiting the ABCD sample: Design considerations and procedures.Developmental cognitive neuroscienceGaravan H, Bartsch H, Conway K, Decastro A, Goldstein RZ, Heeringa S, Jernigan T, Potter A, Thompson W, Zahs DAugust 2018Not Determined
29680211Create StudyOutreach and innovation: Communication strategies for the ABCD Study.Developmental cognitive neuroscienceHoffman, Elizabeth A; Howlett, Katia D; Breslin, Florence; Dowling, Gayathri JAugust 2018Not Determined
29679914Create StudyA multi-site proof-of-concept investigation of computerized approach-avoidance training in adolescent cannabis users.Drug and alcohol dependenceJacobus J, Taylor CT, Gray KM, Meredith LR, Porter AM, Li I, Castro N, Squeglia LMJune 2018Not Determined
29655614Create StudyA brief validated screen to identify boys and girls at risk for early marijuana use.Developmental cognitive neuroscienceLoeber, Rolf; Clark, Duncan B; Ahonen, Lia; FitzGerald, Douglas; Trucco, Elisa M; Zucker, Robert AAugust 2018Not Determined
29636283Create StudyCurrent, future and potential use of mobile and wearable technologies and social media data in the ABCD study to increase understanding of contributors to child health.Developmental cognitive neuroscienceBagot, K S; Matthews, S A; Mason, M; Squeglia, Lindsay M; Fowler, J; Gray, K; Herting, M; May, A; Colrain, I; Godino, J; Tapert, S; Brown, S; Patrick, KAugust 2018Not Determined
29627333Create StudyAssessment of culture and environment in the Adolescent Brain and Cognitive Development Study: Rationale, description of measures, and early data.Developmental cognitive neuroscienceZucker RA, Gonzalez R, Feldstein Ewing SW, Paulus MP, Arroyo J, Fuligni A, Morris AS, Sanchez M, Wills TAugust 2018Not Determined
29606560Create StudyBiospecimens and the ABCD study: Rationale, methods of collection, measurement and early data.Developmental cognitive neuroscienceUban KA, Horton MK, Jacobus J, Heyser C, Thompson WK, Tapert SF, Madden PAF, Sowell ER, August 2018Not Determined
29567376Create StudyThe Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites.Developmental cognitive neuroscienceCasey BJ, Cannonier T, Conley MI, Cohen AO, Barch DM, Heitzeg MM, Soules ME, Teslovich T, Dellarco DV, Garavan H, Orr CA, Wager TD, Banich MT, Speer NK, Sutherland MT, Riedel MC, Dick AS, Bjork JM, Thomas KM, Chaarani B, Mejia MH, Hagler DJ, Daniela Cornejo M, Sicat CS, Harms MP, et al.March 2018Not Determined
29559216Create StudyAdolescent brain cognitive development (ABCD) study: Overview of substance use assessment methods.Developmental cognitive neuroscienceLisdahl, Krista M; Sher, Kenneth J; Conway, Kevin P; Gonzalez, Raul; Feldstein Ewing, Sarah W; Nixon, Sara Jo; Tapert, Susan; Bartsch, Hauke; Goldstein, Rita Z; Heitzeg, MaryAugust 2018Not Determined
29556250Create StudyDetermining Genetic Causal Variants Through Multivariate Regression Using Mixture Model Penalty.Frontiers in geneticsSundar, V S; Fan, Chun-Chieh; Holland, Dominic; Dale, Anders MJanuary 2018Not Determined
29527590Create StudyChronic Stress in Adolescents and Its Neurobiological and Psychopathological Consequences: An RDoC Perspective.Chronic stress (Thousand Oaks, Calif.)Sheth, Chandni; McGlade, Erin; Yurgelun-Todd, DeborahJanuary 2017Not Determined
29525452Create StudyAdolescent neurocognitive development and impacts of substance use: Overview of the adolescent brain cognitive development (ABCD) baseline neurocognition battery.Developmental cognitive neuroscienceLuciana, M; Bjork, J M; Nagel, B J; Barch, D M; Gonzalez, R; Nixon, S J; Banich, M TAugust 2018Not Determined
29496476Create StudyIntroduction.Developmental cognitive neuroscienceJernigan TL, Brown SA, August 2018Not Determined
29484767Create StudyDissociable meta-analytic brain networks contribute to coordinated emotional processing.Human brain mappingRiedel MC, Yanes JA, Ray KL, Eickhoff SB, Fox PT, Sutherland MT, Laird ARJune 2018Not Determined
29467408Create StudyPrediction complements explanation in understanding the developing brain.Nature communicationsRosenberg MD, Casey BJ, Holmes AJFebruary 2018Not Determined
29460352Create StudyThe Adolescent Brain Cognitive Development Study.Journal of research on adolescence : the official journal of the Society for Research on AdolescenceJernigan TL, Brown SA, Dowling GJMarch 2018Not Determined
29460349Create StudyAdolescent Brain Development: Implications for Understanding Risk and Resilience Processes Through Neuroimaging Research.Journal of research on adolescence : the official journal of the Society for Research on AdolescenceMorris, Amanda Sheffield; Squeglia, Lindsay M; Jacobus, Joanna; Silk, Jennifer SMarch 2018Not Determined
29437252Create StudyHigh temporal resolution motion estimation using a self-navigated simultaneous multi-slice echo planar imaging acquisition.Journal of magnetic resonance imaging : JMRITeruel JR, Kuperman JM, Dale AM, White NSFebruary 2018Not Determined
29337280Create StudyBehavioral interventions for reducing head motion during MRI scans in children.NeuroImageGreene, Deanna J; Koller, Jonathan M; Hampton, Jacqueline M; Wesevich, Victoria; Van, Andrew N; Nguyen, Annie L; Hoyt, Catherine R; McIntyre, Lindsey; Earl, Eric A; Klein, Rachel L; Shimony, Joshua S; Petersen, Steven E; Schlaggar, Bradley L; Fair, Damien A; Dosenbach, Nico U FMay 2018Not Determined
29315334Create StudyImmune-related genetic enrichment in frontotemporal dementia: An analysis of genome-wide association studies.PLoS medicineBroce, Iris; Karch, Celeste M; Wen, Natalie; Fan, Chun C; Wang, Yunpeng; Tan, Chin Hong; Kouri, Naomi; Ross, Owen A; Höglinger, Günter U; Muller, Ulrich; Hardy, John; International FTD-Genomics Consortium; Momeni, Parastoo; Hess, Christopher P; Dillon, William P; Miller, Zachary A; Bonham, Luke W; Rabinovici, Gil D; Rosen, Howard J; Schellenberg, Gerard D; Franke, Andre; Karlsen, Tom H; Veldink, Jan H; Ferrari, Raffaele; Yokoyama, Jennifer S; Miller, Bruce L; Andreassen, Ole A; Dale, Anders M; Desikan, Rahul S; Sugrue, Leo PJanuary 1, 2018Not Determined
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 JD, Agrawal A, Werner KB, Mccutcheon VV, Nelson EC, Madden PAF, Bucholz KK, Heath AC, Sartor CEOctober 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
PubMed IDStudyTitleJournalAuthorsDate
No records found.

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.

Expected dates should be selected based on the standard Data Sharing Regimen and are restricted to within date ranges based on the project start and end dates.

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
11,783
Approved
Evaluated Data info icon
11,50001/15/2018
11,848
Approved
Imaging (Structural, fMRI, DTI, PET, microscopy) info icon
11,50004/24/2017
11,808
Approved
Wearable Data info icon
15004/24/2017
5,339
Approved
Task Based info icon
4,52401/15/2018
0
Approved
ABCD Med History Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Questionnaire Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Task Based Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Substance Use Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Social Adjustment Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Phys Characteristics Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Phys Exam Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Diagnostic Measures info icon
11,50001/15/2018
11,878
Approved
ABCD PTSD Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Sleep Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Activity Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Socioeconomic Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Personality Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Behavior Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Parenting Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Trauma Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Demographics Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Cognitive Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Summary Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Treatment Measures info icon
11,50001/15/2018
11,878
Approved
ABCD Psychosis Measures info icon
11,50001/15/2018
11,878
Approved
Structure not yet defined

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

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
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
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
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
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
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
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 the p factor in 9,845 preadolescents from the Adolescent Behavior Cognitive Development Study longitudinally over two years. We identified higher-order and correlated factors models of psychopathology at baseline and one- and two-year follow-ups. Consistent with previous research, we found a cross-sectional inverse relationship between EF and p. Using residualized-change models, we found that baseline EF prospectively predicted p scores two years later, controlling for baseline and one-year follow-up p scores as well as sex, age, race/ethnicity, and parental education. We also found evidence that baseline p scores prospectively predicted change in EF two years later. Tests of specificity revealed that relations with EF were generalizable across externalizing, internalizing, neurodevelopmental, somatization, and detachment symptoms. These novel results suggest that executive dysfunction is both a non-specific risk factor for and consequence of general psychopathology. EF may be a promising transdiagnostic intervention target to prevent the onset and maintenance of psychopathology. 11878/11878Secondary AnalysisPrivate
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
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
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
Sleep_ApneaSleep Disorder 11878/11878Primary 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
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 AnalysisPrivate
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 AnalysisPrivate
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
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
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
titletitle11833/11833Primary AnalysisPrivate
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
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.11741/11741Primary AnalysisPrivate
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
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
Validating the ABCD Emotional Stroop task and its relationship to behavior and brainIn the current study, we investigate the psychometric properties of the Emotional Stroop task within the ABCD study, including assessing the construct validity of the Stroop interference effect, determine the degree to which gender and valence of distracting faces may have differential effects on performance, identify the neural correlates of individual differences in Stroop performance, and determine the degree to which Stroop performance and related behavioral and neural measures are driven by genetic and/or environmental factors. Analyses will be first run at the baseline time point but will be followed up with longitudinal analyses to evaluate how performance on the Stroop task, as well as the behavioral and neural correlates of performance, change across adolescents development. 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
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
CCA studyAbstract forthcoming10626/10626Secondary AnalysisPrivate
Resting state modularity and psychopathologyAbstract forthcoming10626/10626Secondary AnalysisPrivate
Stress EnvironmentAbstract forthcoming 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
The Impact of Parental Substance Use History on Reward Processing in the Adolescent BrainWe examined how parental substance use history relates to nucleus accumbens (NAcc) and putamen activation among pre-adolescents in the Adolescent Brain Cognitive Development (ABCD) Study. We included participants with usable fMRI Baseline data from the Monetary Incentive Delay task and parent substance use history from Data Release 2.0 (N =10,622). Parent-history-positive (PH+) participants had at least one parent with two+ problems with alcohol (n = 741) and/or drugs (n = 638). Participants who were PH+ for alcohol problems had increased activation in the right NAcc during large reward anticipation, relative to participants who were PH-. Participants who were PH+ for drug problems showed enhanced left putamen activation during large reward anticipation, as compared to participants who were PH-. These findings suggest that pre-adolescents who are PH+ for substance-related problems process rewards differently relative to their PH- peers.10622/10622Primary AnalysisPrivate
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
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 childhoodObjective: 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 9,612 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 signaled common vulnerability, predicting progression across forms of psychopathology (e.g., temporal regions including parahippocampal, fusiform, and middle temporal). However, there was unique predictive value for predicting emerging PLEs (pars opercularis thickness and hippocampal volume), anxiety (lateral occipital thickness), and depression (thickness in limbic isthmus cingulate region). 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 AnalysisPrivate
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
Pet ownership 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 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
Local variation in neighborhood disadvantage within metropolitan areas is associated with adolescent neurocognition and brain structure across a national sample Importance: Neighborhood disadvantage is an important social determinant of health in childhood and adolescence. Less is known about its associations with neurocognition and brain structure, and particularly whether associations are similar across metropolitan areas and driven by local differences in neighborhood disadvantage. Objective: To determine whether neighborhood disadvantage is independently associated with youth neurocognitive performance and brain structure in a large, national sample and if associations (a) are pervasive or limited, (b) vary across metropolitan areas, and (c) are driven by neighborhood differences within metropolitan regions. Design: Cross-sectional Setting: The Adolescent Brain and Cognitive Development (ABCD) study, a 21-site U.S. study, using baseline data collected from October 2016 - 2018. Participants: Youth 9-10 years old (n = 8, 598) Exposure: Neighborhood disadvantage, based on U.S. census tract characteristics Main Outcome(s) and Measure(s): Neurocognition was measured with the NIH toolbox, and T1-weighted magnetic resonance imaging (MRI) was used to assess whole brain and regional measures of structure. Linear mixed-effects models examined the association between neighborhood disadvantage and outcomes, adjusting for socio-demographic factors and perceptions of neighborhood safety. Results: Neighborhood disadvantage was associated with worse performance on 6/7 specific subtests (e.g. cognitive control, B = -0.5, 95% CI -0.7,-0.2; working memory, B = -0.7, 95% CI -1.0, -0.3) and all composite measures of neurocognition (e.g. total composite, B= -0.7 95% CI -0.9, -0.5). Higher neighborhood disadvantage was associated with lower whole-brain cortical surface area (B = -692.6, 95% CI -1,154.9, -230.4) and subcortical volume (B = -113.9, 95% CI -198.5, -29.4), and regional differences in surface area primarily in the frontal, parietal, and temporal lobes. Associations were largely independent of perceptions of neighborhood safety. Overall, associations of neighborhood disadvantage with neurocognition and brain structure were consistent across metropolitan areas and primarily explained by local variation within each area. Conclusions and Relevance: Local variation in neighborhood disadvantage is independently associated with lower neurocognitive performance and smaller cortical surface area and subcortical volume across the U.S. These associations demonstrate the widespread importance of neighborhood disadvantage as an environmental risk factor and that improving local neighborhood contexts may be a promising approach to prevention.8598/8598Secondary AnalysisPrivate
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
Testing the Replicability of Internalizing Symptom Network Structure in Subclinically Anxious or Depressed YouthBackground: Network analysis is increasingly used to examine relationships among individual symptoms in psychopathology. However, substantial concerns have been raised about the replicability of these analyses (Forbes et al., 2019). Prior research has focused on symptom networks in adults, with mixed findings on the replicability of edge presence and centrality statistics across moderately sized samples (Borsboom et al., 2017; Fried et al., 2018). We tested the replicability of the network structure of internalizing symptoms in a large sample of community youth with subclinical anxiety or depressive symptoms. Methods: Among 11866 youth assessed at baseline, we selected 7142 youth (60%) with at least one self- or parent-endorsed symptom on screener questions for depressive or anxiety disorders (e.g., generalized anxiety, separation anxiety) from the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS) interview. Our sample was 50% male, 77% non-Hispanic, 60% White, 18% Black, 7% other race and 13% multi-racial, with a mean T-score of 50 (SD = 10.87) on the internalizing scale of the Child Behavior Checklist (CBCL). The sample was randomly split into halves via propensity score matching to ensure no significant differences in race, ethnicity, gender, or internalizing symptom severity. Networks were estimated independently for each split-half, using binarized data from the 32 questions on the CBCL internalizing scale. Symptom networks were estimated using an Ising model and L-1 regularized logistic regression with model selection by the Extended Bayesian Information Criterion (van Borkulo et al., 2014). Analyses were conducted using R package IsingFit (van Borkulo & Epskamp, 2016). Edge weight accuracy was examined using bootstrapped 95% confidence intervals (CI’s). Stability of strength centrality was measured by the correlation stability (CS) coefficient using R package bootnet (Epskamp et al., 2018). A Network Comparison Test (NCT) was conducted to compare the split-half networks on global strength and network structure invariance using R package NetworkComparisonTest (van Borkulo et al., 2016). Results: The first and second networks had 166 and 182 non-zero edges, respectively, with 77% of the non-zero edges in the first network present in the second. Around half of the replicating edges across the networks had 95% CI’s that did not cross zero. Both networks had CS coefficients = 0.75 for strength centrality, demonstrating stable estimation. Networks did not differ in global strength (S = 3.17, p = 0.35) or structure (M = 0.67, p = 0.52). Conclusions: The high degree of overlapping edges in each network, stable strength centrality, and lack of between-network differences in global strength and structure support the replicability of the internalizing symptom network examined. This suggests that network analysis is an appropriate method to investigate relationships between internalizing symptoms in a large community youth sample. Further information about potentially causal relationships between symptoms in youth may inform treatment for internalizing disorders. Future directions include investigating which network characteristics are associated with development of anxiety or depressive disorders in youth.7141/7141Secondary AnalysisPrivate
Neurocognition ABCD 2.0.1The development of objective brain-based measures of individual differences in psychological traits is a longstanding goal of clinical neuroscience. Here we show that reliable objective markers of children’s neurocognitive abilities can be built from measures of brain connectivity. The sample consists of 5,937 9- and 10-year-olds in the Adolescent Brain Cognitive Development multi-site study with high-quality functional connectomes that capture brain-wide connectivity. Using multivariate methods, we built predictive neuromarkers for a general factor of neurocognitive ability as well as for a number of specific cognitive abilities (e.g., spatial reasoning, working memory). Neuromarkers for the general neurocognitive factor successfully predicted scores for held-out participants at 19 out of 19 held-out sites, explaining over 14% of the variance in their scores. Neuromarkers for specific neurocognitive abilities also exhibited statistically reliable generalization to new participants. This study provides the strongest evidence to date that objective quantification of psychological traits is possible with functional neuroimaging.6449/6449Secondary AnalysisPrivate
Differentiating kinds of systemic chronic stressors with relation to psychotic-like experiences in late childhood and early adolescence: the stimulation, discrepancy, and deprivation model of psychosisConceptualizations that distinguish systems-level stress exposures are lacking; the stimulation (lack of safety and high attentional demands), discrepancy (social exclusion and lack of belonging), and deprivation (SDD; lack of environmental enrichment) theory of psychosis and stressors occurring at the systems level has not been directly tested. Exploratory factor analysis was conducted on 3,207 youths, and associations with psychotic-like experiences (PLEs) were explored. Although model fit was suboptimal, five factors were defined, and four were consistent with the SDD theory and related to PLEs. Objective and subjective or self-report exposures for deprivation showed significantly stronger PLE associations compared with discrepancy and objective stimulation factors. Objective and subjective or self-report measures converged overall, although self-report stimulation exhibited a significantly stronger association with PLEs compared with objective stimulation. Considering distinct systems-level exposures could help clarify putative mechanisms and psychosis vulnerability. The preliminary approach potentially informs health policy efforts aimed at psychopathology prevention and intervention.6427/6427Secondary AnalysisShared
Neighborhood deprivation shapes motivational neurocircuit recruitment in childrenImplementing motivated behaviors based on prior reward is central to adaptive human functioning, but aberrant reward-motivated behavior is a core feature of neuropsychiatric illness. Children from disadvantaged neighborhoods have decreased access to rewards, which may shape motivational neurocircuits and risk for psychopathology. Here, we leverage the unprecedented neuroimaging data from the Adolescent Brain Cognitive Development (ABCD) study to test the hypothesis that neighborhood socioeconomic disadvantage shapes the functional recruitment of motivational neurocircuits in children. Specifically, via ABCD’s Monetary Incentive Delay task (N=6,396 9-10 year old children), we find that children from zip codes with a high Area Deprivation Index (ADI) demonstrate blunted recruitment of striatum (dorsal and ventral nuclei) and pallidum during reward anticipation. In fact, blunted dorsal striatal recruitment during reward anticipation mediated the association between ADI and increased attention problems. These data reveal a candidate mechanism driving elevated risk for psychopathology in children from socioeconomically disadvantaged neighborhoods. 6396/6396Secondary 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. 5880/5880Secondary AnalysisPrivate
Nucleus Accumbens Cytoarchitecture Predicts Weight Gain in ChildrenThe prevalence of obesity in children and adolescents worldwide has quadrupled since 1975 and is a key predictor of obesity later in life. Previous work has consistently observed relationships between macroscale measures of reward-related brain regions (e.g., the nucleus accumbens [NAcc]) and unhealthy eating behaviors and outcomes; however, the mechanisms underlying these associations remain unclear. Recent work has highlighted a potential role of neuroinflammation in the NAcc in animal models of diet-induced obesity. Here we leverage a novel diffusion MRI technique, restriction spectrum imaging, to probe the microstructure (cellular density) of subcortical brain regions. More specifically, we test the hypothesis that the cell density of reward-related regions is associated with obesity-related metrics and early weight gain. In a large cohort of nine- and ten-year-olds enrolled in the Adolescent Brain Cognitive Development (ABCD) study, we demonstrate that cellular density in the NAcc is related to individual differences in waist circumference at baseline and is predictive of increases in waist circumference after one year. These findings suggest a neurobiological mechanism for pediatric obesity consistent with rodent work showing that high saturated fat diets increase gliosis and neuroinflammation in reward-related brain regions, which in turn lead to further unhealthy eating and obesity. 5334/5334Primary AnalysisShared
The association between child alcohol sipping and alcohol expectancies in the ABCD studyBackground Underage drinking is a serious societal concern, yet relatively little is known about child sipping of alcohol and its relation to beliefs about alcohol. The current study aimed to (1) examine the contexts in which the first sip of alcohol occurs (e.g., type of alcohol, who provided sip, sip offered or taken without permission); (2) examine the association between sipping and alcohol expectancies; and (3) explore how different contexts of sipping are related to alcohol expectancies. We expected to find that children who had sipped alcohol would have increased positive expectancies and reduced negative expectancies compared to children who had never sipped alcohol. Methods Data were derived from the 2.0 release of the Adolescent Brain Cognitive Development (ABCD) study, a longitudinal study of children in the United States. We utilized data from 4,842 children ages 9 to 11; 52% were male, 60% were White, 19% were Hispanic/Latinx, and 9% were Black/African American. Results We found that 22% of the sample had sipped alcohol. Children reported sipping beer most frequently, and the drink most often belonged to the child’s father. We found that children who had sipped had higher positive alcohol expectancies than children who had not while accounting for variables related to alcohol expectancies. Child sipping was not significantly associated with negative expectancies and the context of the first sip of alcohol was not significantly associated with positive and negative expectancies. Conclusions Providing sips of alcohol to children is associated with them having more favorable expectations about drinking. 4831/4831Secondary AnalysisShared
Conduct disorder symptomatology is associated with an altered functional connectome in a large national youth sampleConduct disorder (CD), characterized by youth antisocial behavior, is associated with a variety of neurocognitive impairments. However, questions remain regarding the neural underpinnings of these impairments. To investigate novel neural mechanisms that may support these neurocognitive abnormalities, the present study applied a graph analysis to resting-state functional magnetic resonance imaging (fMRI) data collected from a national sample of 4,781 youth, ages 9–10, who participated in the baseline session of the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®). Analyses were then conducted to examine the relationships among levels of CD symptomatology, metrics of global topology, node-level metrics for subcortical structures, and performance on neurocognitive assessments. Youth higher on CD displayed higher global clustering (β = .039, 95% CIcorrected [.0027 .0771]), but lower Degreesubcortical (β = −.052, 95% CIcorrected [−.0916 −.0152]). Youth higher on CD had worse performance on a general neurocognitive assessment (β = −.104, 95% CI [−.1328 −.0763]) and an emotion recognition memory assessment (β = −.061, 95% CI [−.0919 −.0290]). Finally, global clustering mediated the relationship between CD and general neurocognitive functioning (indirect β = −.002, 95% CI [−.0044 −.0002]), and Degreesubcortical mediated the relationship between CD and emotion recognition memory performance (indirect β = −.002, 95% CI [−.0046 −.0005]). CD appears associated with neuro-topological abnormalities and these abnormalities may represent neural mechanisms supporting CD-related neurocognitive disruptions.4781/4781Primary AnalysisShared
Adolescent Brain Cognitive Development Study (ABCD) - Annual Release 1.0The ABCD Curated Annual Release 1.0 includes high quality baseline data from the first ~4,500 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 physical & mental health, neurocognition, substance use, biospecimens 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 1.0 Summary document.4521/4521Primary AnalysisShared
Adolescent Brain Cognitive Development Study (ABCD) - Annual Release 1.1The ABCD Curated Annual Release 1.1 includes high quality baseline data from the first ~4,500 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, physical & mental health, neurocognition, substance use, biospecimens 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 1.1 Summary document.4521/4521Primary AnalysisShared
Demographic, Psychological, Behavioral, and Cognitive Correlates of BMI in Youth: Findings from the Adolescent Brain Cognitive Development (ABCD) StudyBackground: Previous research has implicated demographic, psychological, behavioral, and cognitive variables in the onset and maintenance of pediatric overweight/obesity. No adequately-powered study has simultaneously modeled these variables to assess their relative associations with body mass index (BMI; kg/m2) in a nationally representative sample of youth. Methods: Multiple machine learning regression approaches were employed to estimate the relative importance of 43 demographic, psychological, behavioral, and cognitive variables previously associated with BMI in youth to elucidate the associations of both fixed (e.g., demographics) and potentially modifiable (e.g., psychological/behavioral) variables with BMI in a diverse representative sample of youth. The primary analyses consisted of 9-10 year olds divided into a training (n = 2724) and test (n = 1123) sets. Secondary analyses were conducted by sex, ethnicity, and race. Results: The full sample model captured 12% of the variance in both the training and test sets, suggesting good generalizability. Stimulant medications and demographic factors were most strongly associated with BMI. Lower attention problems and matrix reasoning (i.e., nonverbal abstract problem solving and inductive reasoning) and higher social problems and screen time were robust positive correlates in the primary analyses and in analyses separated by sex. Conclusions: Beyond demographics and stimulant use, this study highlights abstract reasoning as an important cognitive variable and reaffirms social problems and screen time as significant correlates of BMI and as modifiable therapeutic targets. Prospective data are needed to understand the predictive power of these variables for BMI gain.4521/4521Secondary AnalysisShared
Association Between Childhood Anhedonia and Alterations in Large-scale Resting-State Networks and Task-Evoked ActivationIMPORTANCE: Anhedonia can present in children and predict detrimental clinical outcomes. OBJECTIVE: To map anhedonia in children onto changes in intrinsic large-scale connectivity and task-evoked activation and to probe the specificity of these changes in anhedonia against other clinical phenotypes (low mood, anxiety, and attention-deficit/hyperactivity disorder [ADHD]). DESIGN, SETTING, AND PARTICIPANTS: Functional magnetic resonance imaging (fMRI) data were from the first annual release of the Adolescent Brain Cognitive Development study, collected between September 2016 and September 2017 and analyzed between April and September 2018. Cross-sectional data of children aged 9 to 10 years from unreferred, community samples during rest (n = 2878) and during reward anticipation (n = 2874) and working memory (n = 2745) were analyzed. MAIN OUTCOMES AND MEASURES: Alterations in fMRI data during rest, reward anticipation, and working memory were examined, using both frequentist and Bayesian approaches. Functional MRI connectivity within large-scale networks, between networks, and between networks and subcortical regions were examined during rest. Functional MRI activation were examined during reward anticipation and working memory using the monetary incentive delayed and N-back tasks, respectively. RESULTS: Among 2878 children with adequate-quality resting-state fMRI data (mean [SD] age, 10.03 [0.62] years; 1400 girls [48.6%]), children with anhedonia (261 [9.1%]), compared with those without anhedonia (2617 [90.9%]), showed hypoconnectivity among various large-scale networks and subcortical regions, including between the arousal-related cingulo-opercular network and reward-related ventral striatum area (mean [SD] with anhedonia, 0.08 [0.10] vs without anhedonia, 0.10 [0.10]; t2,876 = 3.33; P < .001; q[false discovery rate] = 0.03; ln[Bayes factor10] = 2.85). Such hypoconnectivity did not manifest among children with low mood (277 of 2878 [9.62%]), anxiety (109 of 2878 [3.79%]), or ADHD (459 of 2878 [15.95%]), suggesting specificity. Similarly, among 2874 children (mean [SD] age, 10.03 [0.62] years; 1414 girls [49.2%]) with high-quality task-evoked fMRI data, children with anhedonia (248 of 2874 [8.63%]) demonstrated hypoactivation during reward anticipation in various areas, including the dorsal striatum and areas of the cingulo-opercular network. This hypoactivity was not found among children with low mood (268 of 2874 [9.32%]), anxiety (90 of 2874 [3.13%]), or ADHD (473 of 2874 [16.46%]). Moreover, we also found context- and phenotype-specific double dissociations; while children with anhedonia showed altered activation during reward anticipation (but not working memory), those with ADHD showed altered activation during working memory (but not reward anticipation). CONCLUSIONS AND RELEVANCE: Using the Adolescent Brain Cognitive Development study data set, phenotype-specific alterations were found in intrinsic large-scale connectivity and task-evoked activation in children with anhedonia. The hypoconnectivity at rest and hypoactivation during reward anticipation complementarily map anhedonia onto aberrations in neural-cognitive processes: lack of intrinsic reward-arousal integration during rest and diminishment of extrinsic reward-arousal activity during reward anticipation. These findings help delineate the pathophysiological underpinnings of anhedonia in children.4520/4520Secondary AnalysisShared
Differential Relationships of Child Anxiety and Depression to Child Report and Parent Report of Electronic Media UseChild depression and anxiety have been associated with electronic media use, but the comorbidity between the two has rarely been accounted for in analyses. We examined both child and parent reports of electronic media use in relation to parent-reported child depression and anxiety. Using survey and interview data collected for 9- to 11-year-olds from the 21-site Adolescent Brain Cognitive Development Study, we conducted generalized linear mixed models. Our results demonstrated that electronic media use was more strongly associated with depression than anxiety, and that accounting for depression significantly reduced the relationship between electronic media use and anxiety. Different categories of electronic media showed differential relationships to anxiety and depression, with video gaming and video chatting related to anxiety, but video watching related to depression. These findings provide important data to ground theories of the mechanisms that contribute to these associations.4520/4520Primary AnalysisShared
A Cross-Ethnoracial Comparison of Objective and Subjective Neighborhood Predictors of Early Adolescents’ Prosocial BehaviorAlthough the Family Stress Model (FSM) has been widely tested, expanded conceptualizations of stressors, intervening mechanisms, and developmental outcomes from this perspective is becoming increasingly common in order to better explain adolescent adjustment. Additionally, though extant research analyzes the utility of the FSM in African American and European American samples, little is known about the representativeness of the FSM in Latino/a samples, and cross-ethnoracial comparisons are scarce. The present study addresses these gaps by conducting cross-ethnic comparisons in a modified FSM between African American, European American, and U.S. Latino/a ethnoracial adolescents. Findings revealed that perceived neighborhood safety was indirectly associated with youth prosocial behavior through parent mental health symptoms and family conflict for African Americans, U.S. Latino/as, and European Americans. Objective neighborhood risk predicted parent mental health symptoms but was not indirectly associated with youths’ prosocial behavior. Results generally suggest that the FSM may adequately represent family processes across ethnoracial groups. The usefulness and practical implications of the FSM are discussed. 4517/4517Secondary AnalysisShared
ABCD Neurocognitive Prediction Challenge 2019: Test SetThe test data set for the ABCD Neurocognitive Prediction Challenge 2019 contains skull stripped and segmented T1-weighted MRIs, and volumetric brain measures of 3648 participants of the ABCD study. https://sibis.sri.com/abcd-np-challenge provides a detailed description about the processing. When using the data in publications, the Data Supplement of "Pfefferbaum et al., Altered Brain Developmental Trajectories in Adolescents After Initiating Drinking. Am J Psychiatry, 175(4), pp. 370-380, 2018" for should be cited as description of the processing pipeline. The data in this Study were derived from the Adolescent Brain Cognitive Development 1.1 Release (http://dx.doi.org/10.15154/1460410, accessed on or before November 15, 2018) and the Fast Track DICOM share in the Adolescent Brain Cognitive Development Study Collection 2573 (https://ndar.nih.gov/edit_collection.html?id=2573, accessed on or before November 15, 2018). The individual-level imaging phenotype data in this Collection was computed by a custom processing pipeline developed by the organizers of the ABCD Prediction Challenge. The imaging phenotype data may therefore differ from the values shared by the ABCD Study investigators in Release 1.1 or future releases4516/4516Secondary AnalysisShared
Fluid Intelligence Classification Based On Cortical WM/GM Contrast, Cortical Thickness and VolumetryFluid intelligence refers to the ability of solving and reasoning problems. The recent Neurocognitive Prediction Challenge (ABCD-NP-Challenge 2019) demonstrated that predicting residual fluid intelligence from structural MR images is indeed challenging; the correlation between predicted and actual intelligence scores was extremely weak. The correlation was low for all entries including the winner (r = 0.03). In order to better understand this apparent non-relationship we (i) considered a simplified version of the prediction problem by grouping the top and bottom 10% of children on fluid intelligence scores and attempting to classify these two groups; (ii) tested different classification methods on this problem; and (iii) investigated the role that scanner heterogeneity might be playing in producing these poor predictions by using either data from all scanners or a single scanner.4153/4153Secondary AnalysisPrivate
Testing whether implicit emotion regulation mediates the association between discrimination and symptoms of psychopathology in late childhood: An RDoC perspectiveINTRODUCTION: Discrimination has been associated with adverse mental health outcomes, though it is unclear how early in life this association becomes apparent. Implicit emotion regulation, developing during childhood, is a foundational skill tied to a range of outcomes. Implicit emotion regulation has yet to be tested as an associated process for mental illness symptoms that can often emerge during this sensitive developmental period. METHOD: Youth aged 9-11 were recruited for the ABCD study. Associations between psychotic-like experiences, depressive symptoms, and total discrimination (due to race, ethnicity, nationality, weight, or sexual minority status) were tested, as well as associations with implicit emotion regulation measures (emotional updating working memory and inhibitory control). Analyses examined whether associations with symptoms were mediated by implicit emotion regulation. RESULTS: Discrimination related to decreased implicit emotion regulation performance, and increased endorsement of depressive symptoms and psychotic-like experiences. Emotional updating working memory performance partially mediated the association between discrimination and psychotic-like experiences, while emotional inhibitory control did not. DISCUSSION: Discrimination and implicit emotion regulation could serve as putative transdiagnostic markers of vulnerability. Results support the utility of using multiple units of analysis to improve understanding of complex emerging neurocognitive functions and developmentally sensitive periods. 4059/4059Secondary AnalysisShared
Assessment of the Prodromal Questionnaire-Brief Child Version for Measurement of Self-Reported Psychoticlike Experiences in ChildhoodIMPORTANCE: Childhood psychoticlike experiences (PLEs) are associated with greater odds of a diagnosis of a psychotic disorder during adulthood. However, no known, well-validated self-report tools have been designed to measure childhood PLEs. OBJECTIVE: To examine the construct validity and psychometric properties of a measure of PLEs, the Prodromal Questionnaire-Brief Child Version (PQ-BC). DESIGN, SETTING, AND PARTICIPANTS: This validation study used data from the first wave of the Adolescent Brain and Cognitive Development (ABCD) Study, a prospective longitudinal study aimed at assessing risk factors associated with adverse physical and mental health outcomes from ages 9 to 10 years into late adolescence and early adulthood. The population-based sample of 3984 children within the ABCD data set was recruited from 20 research sites across the United States. Data for this study were collected from June 1, 2016, through August 31, 2017. MAIN OUTCOMES AND MEASURES: The PQ-BC Total and Distress scores were analyzed for measurement invariance across race/ethnicity and sex, their associations with measures of PLEs, and their associations with known correlates of PLEs, including internalizing and externalizing symptoms, neuropsychological test performance, and developmental milestones. RESULTS: The study analyses included 3984 participants (1885 girls [47.3%] and 2099 boys [52.7%]; mean [SE] age, 10.0 [0.01] years). The results demonstrated measurement invariance across race/ethnicity and sex. A family history of psychotic disorder was associated with higher mean (SE) PQ-BC Total (3.883 [0.352]; β = 0.061; 95% CI, 0.027-0.094) and Distress (10.210 [1.043]; β = 0.051; 95% CI, 0.018-0.084) scores, whereas a family history of depression or mania was not. Higher PQ-BC scores were associated with higher rates of child-rated internalizing symptoms (Total score: β range, 0.218 [95% CI, 0.189-0.246] to 0.273 [95% CI, 0.245-0.301]; Distress score: β range, 0.248 [95% CI, 0.220-0.277] to 0.310 [95% CI, 0.281-0.338]), neuropsychological test performance deficits such as working memory (Total score: β = -0.042 [95% CI, -0.077 to -0.008]; Distress score: β = -0.051 [95% CI, -0.086 to -0.017]), and motor and speech developmental milestone delays (Total score: β = 0.057 [95% CI, 0.026-0.086] for motor; β = 0.042 [95% CI, 0.010-0.073] for speech; Distress score: β = 0.048 [95% CI, 0.017-0.079] for motor; β = 0.049 [95% CI, 0.018-0.081] for speech). CONCLUSIONS AND RELEVANCE: These results provide support for the construct validity and demonstrate adequate psychometric properties of a self-report instrument designed to measure childhood PLEs, providing evidence that the PQ-BC may be a useful measure of early risk for psychotic disorders. Furthermore, these data suggest that PLEs at school age are associated with many of the same familial, cognitive, and emotional factors associated with psychotic symptoms in older populations, consistent with the dimensionality of psychosis across the lifespan. 3982/3982Secondary AnalysisShared
Childhood obesity, cortical structure and executive function in healthy childrenThe development of executive function is linked to maturation of prefrontal cortex in childhood. Childhood obesity has been associated with changes in brain structure, particularly in prefrontal cortex, as well as deficits in executive functions. We aimed to determine whether differences in cortical structure mediate the relationship between executive function and childhood obesity. We analysed MR-derived measures of cortical thickness for 2,700 children between the ages of 9-11 years, recruited as part of the NIH ABCD study. We related our findings to measures of executive function and body mass index (BMI). In our analysis, increased BMI was associated with significantly reduced mean cortical thickness, as well as specific bilateral reduced cortical thickness in prefrontal cortical regions. This relationship remained after accounting for age, sex, race, parental education, household income, birth-weight and in-scanner motion. Increased BMI was also associated with lower executive function. Reduced cortical thickness was found to mediate the relationship between BMI and executive function such that reduced thickness in the rostral medial and superior frontal cortex, the inferior frontal gyrus and the lateral orbitofrontal cortex accounted for partial reductions in executive function. These results suggest that childhood obesity is associated with compromised executive function. This relationship may be partly explained by BMI-associated reduced cortical thickness in the prefrontal cortex. 3921/3921Secondary AnalysisShared
ABCD Neurocognitive Prediction Challenge 2019: Training SetTraining data set for the ABCD Neurocognitive Prediction Challenge 2019 containing skull stripped and segmented T1-weighted MRIs, volumetric brain measures, and residual fluid intelligence scores of 3739 participants of the ABCD study. https://sibis.sri.com/abcd-np-challenge provides a detailed description about the processing. When using the data in publications, the Data Supplement of "Pfefferbaum et al., Altered Brain Developmental Trajectories in Adolescents After Initiating Drinking. Am J Psychiatry, 175(4), pp. 370-380, 2018" for should be cited as description of the processing pipeline. The data in this Study were derived from the Adolescent Brain Cognitive Development 1.1 Release (http://dx.doi.org/10.15154/1460410, accessed on or before November 15, 2018) and the Fast Track DICOM share in the Adolescent Brain Cognitive Development Study Collection 2573 (https://ndar.nih.gov/edit_collection.html?id=2573, accessed on or before November 15, 2018). The individual-level imaging phenotype data in this Collection was computed by a custom processing pipeline developed by the organizers of the ABCD Prediction Challenge. The imaging phenotype data may therefore differ from the values shared by the ABCD Study investigators in Release 1.1 or future releases3728/3739Secondary AnalysisShared
Resting State Functional Connectivity and Psychotic-Like Experiences in Childhood: Results from the Adolescent Brain Cognitive Development StudyBackground: Psychotic-like experiences (PLEs) during childhood are associated with greater risk of developing a psychotic disorder, highlighting the importance of identifying neural correlates of childhood PLEs. Three major cortical networks- the cingulo-opercular network (CON), default mode network (DMN), and fronto-parietal network (FPN)- are consistently implicated in psychosis as well as PLEs in adults. However, it is unclear whether variation in functional connectivity is associated with PLEs in school-aged children. Methods: Using hierarchical linear models, we examined the relationships between childhood PLEs and resting-state functional connectivity of the CON, DMN, and FPN, as well as the other networks using an a priori network parcellation, using data from 3,434 9-10-year-olds in the Adolescent Brain Cognitive Development (ABCD) study. We examined within-network, between-network, and subcortical connectivity. Results: Decreased CON and DMN connectivity, as well as cingulo-parietal (CPAR) network connectivity, were associated with greater PLEs, even after accounting for family history of psychotic disorders, internalizing symptoms, and cognitive performance. Decreased DMN network connectivity was more strongly associated with increased delusional ideation, whereas decreased CON connectivity was more strongly associated with increased perceptual distortions. Increased CON-cerebellar and decreased CPAR-cerebellar connectivity were also associated with increased PLEs, and CPAR-cerebellar connectivity was more strongly associated with increased perceptual distortions. Conclusion: Consistent with hypotheses about the dimensionality of psychosis, our results provide evidence that neural correlates of PLEs, such as reduced functional connectivity of higher-order cognitive networks, are present even in school-aged children. Therefore, the results provide further validation for continuity of PLEs across the lifespan. 3434/3434Secondary AnalysisShared
Genetic variation in endocannabinoid signaling is associated with differential network-level functional connectivity in youthThe endocannabinoid system is an important regulator of emotional responses such as fear, and a number of studies have implicated endocannabinoid signaling in anxiety. The fatty acid amide hydrolase (FAAH) C385A polymorphism, which is associated with reduced endocannabinoid signaling in the brain, has been identified across species as a potential protective factor from anxiety. In particular, adults with the variant FAAH 385A allele have greater fronto-amygdala connectivity and lower anxiety symptoms. Whether broader network-level differences in connectivity exist, and when during development this neural phenotype emerges, remains unknown and represents an important next step in understanding how the FAAH C385A polymorphism impacts neurodevelopment and risk for anxiety disorders. Here, we leveraged data from 3,109 participants in the nationwide Adolescent Brain Cognitive Development Study℠ (10.04 ± 0.62 years old; 44.23% female, 55.77% male) and a cross-validated, data-driven approach to examine associations between genetic variation and large-scale resting-state brain networks. Our findings revealed a distributed brain network, comprising functional connections that were both significantly greater (95% CI for p values = [5.339e-08, 2.931e-26]) and lesser (95% CI for p values = [4.694e-03, 1.120e-17]) in A-allele carriers relative to non-carriers. Further, there was a significant interaction between genotype and the summarized connectivity of functional connections that were greater in A-allele carriers, such that non-carriers with connectivity more similar to A-allele carriers (i.e., greater connectivity) had lower anxiety symptoms (t=-2.011, p=0.044). These findings provide novel evidence of network-level changes in neural connectivity associated with genetic variation in endocannabinoid signaling and suggest that genotype-associated neural differences may emerge at a younger age than genotype-associated differences in anxiety.3109/3109Secondary AnalysisPrivate
What Is the Link Between Attention-Deficit/Hyperactivity Disorder and Sleep Disturbance? A Multimodal Examination of Longitudinal Relationships and Brain Structure Using Large-Scale Population-Based CohortsBackground: Attention-deficit/hyperactivity disorder (ADHD) comorbid with sleep disturbances can produce profound disruption in daily life and negatively impact quality of life of both the child and the family. However, the temporal relationship between ADHD and sleep impairment is unclear, as are underlying common brain mechanisms. Methods: This study used data from the Quebec Longitudinal Study of Child Development (n = 1601, 52% female) and the Adolescent Brain Cognitive Development Study (n = 3515, 48% female). Longitudinal relationships between symptoms were examined using cross-lagged panel models. Gray matter volume neural correlates were identified using linear regression. The transcriptomic signature of the identified brain-ADHD-sleep relationship was characterized by gene enrichment analysis. Confounding factors, such as stimulant drugs for ADHD and socioeconomic status, were controlled for. Results: ADHD symptoms contributed to sleep disturbances at one or more subsequent time points in both cohorts. Lower gray matter volumes in the middle frontal gyrus and inferior frontal gyrus, amygdala, striatum, and insula were associated with both ADHD symptoms and sleep disturbances. ADHD symptoms significantly mediated the link between these structural brain abnormalities and sleep dysregulation, and genes were differentially expressed in the implicated brain regions, including those involved in neurotransmission and circadian entrainment. Conclusions: This study indicates that ADHD symptoms and sleep disturbances have common neural correlates, including structural changes of the ventral attention system and frontostriatal circuitry. Leveraging data from large datasets, these results offer new mechanistic insights into this clinically important relationship between ADHD and sleep impairment, with potential implications for neurobiological models and future therapeutic directions.3075/3075Secondary AnalysisShared
Investigation of Psychiatric and Neuropsychological Correlates of Default Mode Network and Dorsal Attention Network Anticorrelation in Children.The default mode network (DMN) and dorsal attention network (DAN) demonstrate an intrinsic "anticorrelation" in healthy adults, which is thought to represent the functional segregation between internally and externally directed thought. Reduced segregation of these networks has been proposed as a mechanism for cognitive deficits that occurs in many psychiatric disorders, but this association has rarely been tested in pre-adolescent children. The current analysis used data from the Adolescent Brain Cognitive Development study to examine the relationship between the strength of DMN/DAN anticorrelation and psychiatric symptoms in the largest sample to date of 9- to 10-year-old children (N = 6543). The relationship of DMN/DAN anticorrelation to a battery of neuropsychological tests was also assessed. DMN/DAN anticorrelation was robustly linked to attention problems, as well as age, sex, and socioeconomic factors. Other psychiatric correlates identified in prior reports were not robustly linked to DMN/DAN anticorrelation after controlling for demographic covariates. Among neuropsychological measures, the clearest correlates of DMN/DAN anticorrelation were the Card Sort task of executive function and cognitive flexibility and the NIH Toolbox Total Cognitive Score, although these did not survive correction for socioeconomic factors. These findings indicate a complicated relationship between DMN/DAN anticorrelation and demographics, neuropsychological function, and psychiatric problems.3004/3004Secondary AnalysisPrivate
Neurocognition ABCD 1.1Difficulties with higher-order cognitive functions in youth are a potentially important vulnerability factor for the emergence of problematic behaviors and a range of psychopathologies. This study examined 2,0139-10 year olds in the first data release from theAdolescent Brain Cognitive Development21-site consortium study inorder to identify resting state functional connectivity patterns that predict individual-differences in three domainsof higher-order cognitive functions:General Ability, Speed/Flexibility, and Learning/Memory.For General Ability scores in particular, we observed consistent cross-site generalizability, with statistically significant predictions in 14outof 15held-outsites.These resultssurvived several tests forrobustness includingreplication in split half analysis and in a low head motion subsample.Weadditionallyfound that connectivity patterns involving task control networks and defaultmode network were prominently implicated in predicting differencesinGeneral Abilityacrossparticipants. These findings demonstrate that restingstate connectivity can be leveraged to produce generalizable markers of neurocognitive functioning. Additionally, they highlight the importance of task control-default mode network interconnectionsas a major locus of individual differences in cognitive functioning in early adolescence.2206/2206Secondary AnalysisPrivate
Cortical Thickness in Bilingual and Monolingual Children: Relationships to Language Use and Language SkillThere is a growing body of evidence based on adult neuroimaging that suggests that the brain adapts to bilingual experiences to support language proficiency. The Adolescent Brain Cognitive Development (ABCD) Study is a useful source of data for evaluating this claim during childhood, as it involves data from a large sample of American children. Using the baseline ABCD Study data collected at ages nine and ten, the goal of this study was to identify differences in cortical thickness between bilinguals and monolinguals and to evaluate how variability in English vocabulary and English use within bilinguals might explain these group differences. We identified bilingual participants as children who spoke a non-English language and were exposed to the non-English language at home. We then identified a matched sample of English monolingual participants based on age, sex, pubertal status, parent education, household income, non-verbal IQ, and handedness. Bilinguals had thinner cortex than monolinguals in widespread cortical regions. Within bilinguals, more English use was associated with greater frontal and parietal cortical thickness; greater English vocabulary was associated with greater frontal and temporal cortical thickness. These findings replicate and extend previous research with bilingual children and highlight unexplained cortical thickness differences between bilinguals and monolinguals.1356/1356Secondary AnalysisPrivate
Decomposing complex links between the childhood environment and brain structure in school-aged youthChildhood experiences play a profound role in conferring risk and resilience for brain and behavioral development. However, how different facets of the environment shape neurodevelopment remains largely unknown. Here we sought to decompose heterogeneous relationships between environmental factors and brain structure in 989 school-aged children from the Adolescent Brain Cognitive Development Study. We applied a cross-modal integration and clustering approach called ‘Similarity Network Fusion’, which combined two brain morphometrics (i.e., cortical thickness and myelin-surrogate markers), and key environmental factors (i.e., trauma exposure, neighborhood safety, school environment, and family environment) to identify homogeneous subtypes. Depending on the subtyping resolution, results identified two or five subgroups, each characterized by distinct brain structure-environment profiles. Notably, more supportive caregiving and school environments were associated with greater myelination, whereas less supportive caregiving, higher family conflict and psychopathology, and higher perceived neighborhood safety were observed with greater cortical thickness. These subtypes were highly reproducible and predicted externalizing symptoms and overall mental health problems. Our findings support the theory that distinct environmental exposures are differentially associated with alterations in structural neurodevelopment. Delineating more precise associations between risk factors, protective factors, and brain development may inform approaches to enhance risk identification and optimize interventions targeting specific experiences.989/989Secondary AnalysisShared
Distinguishing Remitted Bipolar Disorder from Remitted Unipolar Depression in Pre-Adolescent Children: A Neural Reward Processing PerspectiveBipolar disorder (BD) is often misdiagnosed as unipolar depression (UD), highlighting the need to identify clinically useful markers to differentiate them. To provide insights into this endeavor, the current study will employ functional magnetic resonance imaging and conduct region-of-interest (ROI; ventral striatum and orbitofrontal cortex), whole-brain, and connectivity analyses to examine the similarities and differences between children with BD, children with UD, and healthy controls (HCs) in brain activation patterns and functional coupling between brain regions within the context of reward processing, as evoked by the Monetary Incentive Delay task. The current study represents the first examination of neural reward processing in preadolescent children with remitted BD or UD. We aim to (a) test whether preadolescent children with remitted BD or UD display abnormal patterns of neural activation and connectivity in response to reward, relative to HCs and (b) compare remitted UD and BD directly with each other to evaluate whether they can be distinguished by neural activation and connectivity during reward processing826/826Secondary AnalysisShared
Reward processing in preadolescents with bipolar disorder: An fMRI studyIntroduction: Reward processing dysfunction has long been implicated in adults with bipolar disorder. Nevertheless, little research has been conducted to examine whether such dysregulation also occurs in preadolescents with bipolar disorder. Methods: The current study will employ functional magnetic resonance imaging and conduct region-of-interest (ventral striatum and orbitofrontal cortex), whole-brain, and connectivity analyses to examine the similarities and differences in reward-related brain activation patterns, evoked by the Monetary Incentive Delay task, between 169 preadolescents with remitted bipolar disorder and 245 preadolescent healthy controls without personal and family history of Axis I disorders. Results: We hypothesize that activity in the prefrontal cortex (PFC) and the striatum would be elevated in preadolescents with remitted bipolar disorder during reward processing, relative to healthy controls. We also predict aberrant connectivity between the PFC and the striatum in response to reward in preadolescents with remitted bipolar disorder, relative to healthy controls. Conclusions: Early-onset bipolar disorder is often associated with remarkably long treatment delays and a persistently pernicious course of illness, underscoring the significance of studying mood disorders during this developmental period. Owing to the paucity of research and data on preadolescent bipolar disorder, accurate diagnosis in this population is challenging. Identifying objective markers of preadolescent bipolar disorder has the potential to enhance our ability to diagnose pediatric bipolar disorder accurately. Besides, early accurate diagnosis may improve our ability to intervene with appropriate treatments that may lead to a more benign course of bipolar disorder in adolescence and adulthood. 604/604Secondary AnalysisShared
Automatic Emotion Regulation and Asian American Adolescent Mental Health: The Moderating Role of Cumulative RiskBackground and Purpose. Contrary to widespread perceptions, Asian American (AA) adolescents experience substantial mental health problems. An emerging body of literature suggests that automatic emotion regulation (AER), an implicit cognitive capacity regulating interference from emotional stimuli, may be an important but underexplored factor in shaping AA adolescent mental health. Importantly, the ecological perspective argues that the association of AER with adolescent mental health may vary based on contextual factors in the adolescent’s environment. Further, the primary-secondary model of coping suggests that the role of AER in adolescent mental health may be especially relevant in context with high level of uncontrollable stressors. Such conceptual speculations have not been empirically tested in relation to AER and AA youth, despite their potential for guiding the most effective approaches to targeting prevention. In order to better understand the embedded nature of individuals’ AER in the environment, this study aimed to examine 1) whether AER is associated with internalizing and externalizing behavior in AA youth and 2) whether this association is moderated by uncontrollable stressors, measured by cumulative risk exposure. Methods. Data came from a sub-sample of parent-identified AA adolescents aged 9 – 10 in the Adolescent Brain and Cognitive Development (ABCD) study who had complete data on all study variables (N = 471; 51.4% female) from 21 sites nationwide. The total correct score from the Emotional N-Back task was used to measure AER. Internalizing (α = .84; M = 4.21, SD = 4.86) and externalizing (α = .90; M = 3.12, SD = 4.66) behaviors were assessed with the Child Behavior Checklist. Cumulative risk exposure was created by dichotomizing 15 risk factors across the family, neighborhood, and community levels and summing these categorical indicators (M = 1.98, SD = 1.84). Multiple regression was the main modeling strategy performed using SPSS version 25. Covariates included gender, age, bi-/multiracial status, and ethnic group (East vs. South/Southeast Asian). Results. The main effects model showed that higher levels of AER were significantly associated with lower levels of internalizing (b = -.06, p < .001) and externalizing (b = -.04, p = .012) behavior. Cumulative risk moderated the relationship for internalizing (b = -.41, p = .034), but not for externalizing behavior (b = -.32, p = .089). To probe the interaction term further, simple slopes were calculated – higher levels of AER were predictive of internalizing behavior in the high cumulative risk (1SD+) group (b = -1.18, p = .003), but were not in the low cumulative risk (1SD-) group (b = .32, p = .475). Conclusions and Implications. The results suggest that lower levels of AER are associated with increased mental health symptomatology among Asian youth, particularly in environments characterized by elevated levels of risk and stressors. Our study findings provide individual- and ecological-level implications for developing social work policy and practice strategies that focus on promoting youth’s AER as well as reducing cumulative risk in order to support AA adolescent mental health.554/554Secondary AnalysisPrivate
Altered hippocampal microstructure and function in children who experienced Hurricane Irma.Hurricane Irma was the most powerful Atlantic hurricane in recorded history, displacing 6 million and killing over 120 people in the state of Florida alone. Unpredictable disasters like Irma are associated with poor cognitive and health outcomes that can disproportionately impact children. This study examined the effects of Hurricane Irma on the hippocampus and memory processes previously related to unpredictable stress. We used an innovative application of an advanced diffusion-weighted imaging technique, restriction spectrum imaging (RSI), to characterize hippocampal microstructure (i.e., cell density) in 9- to 10-year-old children who were exposed to Hurricane Irma relative to a non-exposed control group (i.e., assessed the year before Hurricane Irma). We tested the hypotheses that the experience of Hurricane Irma would be associated with decreases in: (a) hippocampal cellularity (e.g., neurogenesis), based on known associations between unpredictable stress and hippocampal alterations; and (b) hippocampal-related memory function as indexed by delayed recall. We show an association between decreased hippocampal cellularity and delayed recall memory in children who experienced Hurricane Irma relative to those who did not. These findings suggest an important role of RSI for assessing subtle microstructural changes related to functionally significant changes in the developing brain in response to environmental events.423/423Primary AnalysisShared
ABCD Neurocognitive Prediction Challenge 2019: Validation setValidation data set for the ABCD Neurocognitive Prediction Challenge 2019 containing skull stripped and segmented T1-weighted MRIs, volumetric brain measures, and residual fluid intelligence scores of 415 participants of the ABCD study. https://sibis.sri.com/abcd-np-challenge provides a detailed description about the processing. When using the data in publications, the Data Supplement of "Pfefferbaum et al., Altered Brain Developmental Trajectories in Adolescents After Initiating Drinking. Am J Psychiatry, 175(4), pp. 370-380, 2018" for should be cited as description of the processing pipeline. The data in this Study were derived from the Adolescent Brain Cognitive Development 1.1 Release (http://dx.doi.org/10.15154/1460410, accessed on or before November 15, 2018) and the Fast Track DICOM share in the Adolescent Brain Cognitive Development Study Collection 2573 (https://ndar.nih.gov/edit_collection.html?id=2573, accessed on or before November 15, 2018). The individual-level imaging phenotype data in this Collection was computed by a custom processing pipeline developed by the organizers of the ABCD Prediction Challenge. The imaging phenotype data may therefore differ from the values shared by the ABCD Study investigators in Release 1.1 or future releases414/415Secondary AnalysisShared
Hypothalamic gliosis predicts weight gain in children at risk for obesityAccumulating evidence from animal models of diet-induced obesity demonstrate that a cellular inflammatory reaction, named reactive gliosis, occurs in response to high-fat diet feeding in a key brain region for energy homeostasis, the arcuate nucleus of the hypothalamus. Using MRI, it is possible to detect evidence of gliosis in the mediobasal hypothalamus (MBH), which encompasses the arcuate nucleus. MRI evidence of MBH gliosis has been found in humans with obesity but longitudinal data examining weight gain are lacking. We investigated, in a large pediatric population, if MBH gliosis is associated with baseline or change over 1year in body adiposity. Study 1 included 169 9-11-year-old children enrolled in the ABCD Study with baseline T2-weighted MRI images and anthropometrics from baseline and 1-year follow-up study visits. Signal ratios compared T2 signal intensity in MBH and 2 reference regions (amygdala [AMY] and putamen) as a measure of MBH gliosis. Study 2 included 238 children from the ABCD Study with overweight or obesity to confirm initial findings in an independent sample. In Study 1, MBH/AMY T2 signal ratio was positively associated with BMI z-score (β=4.27 P<0.001). A significant interaction for the association of MBH/AMY signal ratio with change in BMI z-score suggested relationships differed by baseline weight status. Study 2 found that higher MBH/AMY signal ratios associated with increase in BMI z-score for children with overweight (β=0.58 P=0.01), but not those with obesity (β=0.02 P=0.91). Greater evidence of hypothalamic gliosis by MRI predicts adiposity gain in young children at risk of obesity. 407/407Secondary AnalysisPrivate
Sexual dimorphism and laterality in neurostructural development from late childhood to early adulthood: A cross-sectional voxel based morphometry studyIntro: Adolescence is a sensitive period for social, emotional, risk, and reward behavior and is an onset period for serious psychiatric disorders. Changes in behavior in adolescence may be mediated by the rapid changes in brain structure observed during this time period. While adolescent structural development has been extensively analyzed, less is known about the developmental effects of sex or lateralized differences. Understanding how the brain typically develops during these critical periods may give insight into when structural deviations occur that result in psychopathology. Methods: Structural Magnetic Resonance Imaging (MRI) scans were obtained from samples of children (age 9-11, n=344), adolescents (age 13-14, n=271), and adults (age 22-25, n=56) using the same scanner and acquisition sequences. Gray and white matter densities and volumes were assessed using voxel-based morphometry, as were ventricular volumes, total tissue volumes, and average tissue densities. Asymmetry indices were created by comparing the left and right hemispheres of each individual’s brain maps. Age, sex, an age and sex interaction, age2, and an age2 and sex interaction were examined in a simultaneous multiple regression for each brain metric. Results: Gray matter density and volume declined with age, while white matter increased. Males had greater total volumes while females had greater white matter densities. After correcting for total tissue volume, local sex differences were largely greater in females. Laterality analyses suggested that medial brain structures developed earlier in the right hemisphere. Conclusions: Our findings suggest structural changes occur throughout adolescence and likely continue past early adulthood in frontal structures, primarily in white matter. Changes in density appear to precede volumetric changes. Males had larger global, not local, brain volumes. Total gray matter volume and average white matter densities changed faster in females. Lateralized differences in developmental timing offer a new line of investigation in adolescent approach and avoidance behavior.344/344Primary AnalysisPrivate
Resilience to Adversity in Reward Networks in Children Living in Unsafe Neighborhoods Living in an unsafe neighborhood, where crime and/or community violence frequently occurs, is a source of early life adversity and associated neurodevelopmental and behavioral abnormalities. Some children exhibit substantial resilience to such adversities but the neural dynamics of resilience are not well understood. The purpose of this study was to examine neural activation patterns in children living in either high or low crime neighborhoods.280/280Secondary AnalysisPrivate
A growth curve of the human eye from 0-20 yearsThis study involves the semi automatic segmentation of the eyes of pediatric subjects for volume measurements19/173Secondary AnalysisPrivate
Effective Velopharyngeal Ratio: A More Clinically Relevant Measure of Velopharyngeal Function Purpose: Velopharyngeal (VP) ratios are commonly used to study normal VP anatomy and normal VP function. An effective VP (EVP) ratio may be a more appropriate indicator of normal parameters for speech. The aims of this study are to examine if the VP ratio is preserved across the age span or if it varies with changes in the VP portal and to analyze if the EVP ratio is more stable across the age span. Methods: Magnetic resonance imaging (MRI) was used to analyze VP variables of 270 participants. For statistical analysis, the participants were divided into the following groups based on age: infants, children, adolescents and adults. ANOVAs and a Games Howell Post Hoc Test were used to compare variables between groups. Results: There was a statistically significant difference (p < .05) in all measurements between the age groups. Pairwise comparisons reported statistically significant adjacent group differences (p < .05) for velar length, VP ratio, effective velar length, adenoid depth, and pharyngeal depth. No statistically significant differences between adjacent age groups was reported for the EVP ratio. Conclusions: Results from this study report the EVP ratio was not statistically significant between adjacent age groups, while the VP ratio was statistically significant between adjacent age groups. This study suggests that the EVP ratio is more correlated to VP function than the VP ratio and provides a more stable and consistent ratio of VP function across the age span. 19/42Secondary AnalysisShared
Growth Effects on Velopharyngeal Anatomy From Childhood to AdulthoodPurpose: The observed sexual dimorphism of velopharyngeal structures among adult populations has not been observed in the young child (4- to 9-year-old) population. The purpose of this study was to examine the age at which sexual dimorphism of velopharyngeal structures become apparent and to examine how growth trends vary between boys and girls. Method: Static 3-dimensional magnetic resonance imaging velopharyngeal data were collected among 202 participants ranging from 4 to 21 years of age. Participants were divided into 3 groups based on age, including Group 1: 4–10 years of age, Group 2: 11–17 years of age, and Group 3: 18–21 years of age. Nine velopharyngeal measures were obtained and compared between groups. Results: Significant sex effects were evident for levator length (p = .011), origin to origin (p = .018), and velopharyngeal ratio (p = .036) for those in Group 2 (11–17 years of age). Sex effects became increasingly apparent with age, with 7 of 9 variables becoming significantly different between male and female participants in Group 3. Boys, in general, displayed a delayed growth peak in velopharyngeal growth compared to girls. Conclusion: Results from this study demonstrate the growth of velopharyngeal anatomy with sexual dimorphism becoming apparent predominantly after 18 years of age. However, velopharyngeal variables displayed variable growth trends with some variables presenting sexual dimorphism at an earlier age compared to other velopharyngeal variables.19/42Secondary AnalysisShared
* Data not on individual level
Edit