NDA Help Center

Collection - General Tab

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

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

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

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

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

Blinded Clinical Trial Status:

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

Funding Source

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

Supporting Documentation

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

Grant Information 

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

Clinical Trials

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

Frequently Asked Questions

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

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

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

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

Glossary

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

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

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

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

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

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

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

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

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

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

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

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

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

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

NDA Help Center

Collection - Shared Data Tab

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

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

 

Frequently Asked Questions

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

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

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

Glossary

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

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

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

NDA Help Center

fMRi

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

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

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

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

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

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

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

Frequently Asked Questions

Glossary

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

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

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

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

NDA Help Center

Collection - Submissions Tab

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

Here, you can:

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

Frequently Asked Questions

Glossary

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

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

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

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

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

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

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

NDA Help Center

Collection - Publications Tab

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

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

 

Frequently Asked Questions

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

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

Glossary

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

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

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

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

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

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

NDA Help Center

EEG

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

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

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

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

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

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

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

Frequently Asked Questions

Glossary

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

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

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

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

NDA Help Center

Collection - Data Expected

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

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

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

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

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

 

Frequently Asked Questions

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

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

Glossary

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

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

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

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

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

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

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

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

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

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

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

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

NDA Help Center

Collection - Permissions Tab

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

The available permission groups include:

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

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

Frequently Asked Questions

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

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

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

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

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

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

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

Glossary

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

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

NDA Help Center

Eye Tracking

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

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

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

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

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

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

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

Frequently Asked Questions

Glossary

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

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

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

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

NDA Help Center

Collection - Experiments Tab

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

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

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

Frequently Asked Questions

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

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

     

Glossary

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

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

NDA Help Center

Omics

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

Experiment Parameters

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

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

Platform

Continue to select the Platform (box 3).

Extraction

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

Processing

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

Additional Information

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

 

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

Frequently Asked Questions

Glossary

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

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

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

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

NDA Help Center

Filter Cart

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

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

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

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

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

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

Additional Tips:

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

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

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

Frequently Asked Questions

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

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

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

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

Glossary

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

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

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

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Collection - Associated Studies

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

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

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

Frequently Asked Questions

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

Glossary

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

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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.

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1 Numbers reported are subjects by age
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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
1869RRAY fMRI ScanfMRI11/27/2021
1867Resting StatefMRI11/22/2021
1866MNA fMRIfMRI11/16/2021
1865Motion AftereffectsEye Tracking11/05/2021
1864Tilt Aftereffects (TAE)Eye Tracking11/05/2021
1863Negative Afterimages (AI)Eye Tracking11/05/2021
1862Face-Matching TaskfMRI11/03/2021
1861Resting StatefMRI11/03/2021
1860CARIT (Go/NoGo Task)fMRI11/03/2021
1859PCR-free sequencingOmics10/29/2021
1858GNG Anger, Gender, Happy Tasks- EEGEEG10/15/2021
1857PVDM, imaging sessionEye Tracking10/14/2021
1856PVDM, imaging sessionfMRI10/13/2021
1855PVDM, behavioral sessionEye Tracking10/13/2021
1854Cerebellar Dysfunction in Autism: resting state fMRIfMRI10/13/2021
1852snRNAseq_controls_DLPFC/sgACCOmics09/30/2021
1851Reappraisal Emotion Regulation Task - V2fMRI09/22/2021
1850Reappraisal Emotion Regulation Task - V1fMRI09/22/2021
1849Stop-Signal Arrows - Randomization BfMRI09/22/2021
1848Stop-Signal Arrows - Randomization AfMRI09/22/2021
1847NPU Threat Countdown Short - V2fMRI09/22/2021
1846NPU Threat Countdown Short - V1fMRI09/22/2021
1836Alcohol Cue ReactivityEEG09/02/2021
1835Doors Reward ParadigmEEG08/30/2021
1834Flanker ArrowsEEG08/30/2021
1833Transcriptomic data of Clozapine-treated Ngn2-induced Human Excitatory NeuronsOmics08/20/2021
1830Illumina Global Screening ArrayOmics08/02/2021
1829Single-cell multiome sequencing: ATAC-seqOmics07/26/2021
1828Single-cell multiome sequencing - RNA-seqOmics07/26/2021
1827scATACseqOmics07/26/2021
1826scRNAseqOmics07/26/2021
1825Fetal Resting-state fMRI Brain MasksfMRI07/23/2021
1824Apex of Cognitive ControlfMRI07/22/2021
1823Face adaptationEye Tracking07/21/2021
1822Presaccadic AttentionEye Tracking07/21/2021
1821templefMRI07/19/2021
1820parvizi_eeg_145EEG07/16/2021
1819parvizi_eeg_166EEG07/16/2021
1818parvizi_eeg_164EEG07/16/2021
1817parvizi_eeg_165EEG07/16/2021
1816parvizi_eeg_162EEG07/16/2021
1815parvizi_eeg_161EEG07/16/2021
1814eeg_parvizi_160EEG07/16/2021
1813parvizi_eeg_159EEG07/16/2021
1812Singleton distractor rejectionEEG07/16/2021
1810InterlayerfMRI07/15/2021
1809Alpha, BOLD, experience, and expectancy during associative learningEEG07/14/2021
1808Alpha, BOLD, experience, and expectancy during associative learningfMRI07/14/2021
1807Correlating concurrent EEG/BOLD in occipital cortex while presenting Gabor patch steadily increasing in contrastEEG07/14/2021
1806Correlating concurrent EEG/BOLD in occipital cortex while presenting Gabor patch steadily increasing in contrastfMRI07/14/2021
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Collection Summary Collection Charts
Collection Title Collection Investigators Collection Description
Biomarkers of Developmental Trajectories and Treatment in ASD
Susan Bookheimer 
This is a renewal for the UCLA Autism Center of Excellence. The primary focus of the UCLA ACE renewal is to understand the relationship between aberrant brain development and core deficits in autism by identifying mechanisms relating genes to brain structure/function and brain to behavior, and to develop effective interventions based on basic experimental and clinical research findings that will change outcomes in autism. In five interdependent projects and cores, our center builds on our expertise in autism genetics, multimodal brain imaging, early detection and analysis of core autism features, and experience in implementing randomized control trials of novel interventions that target these core symptoms. In this renewal application, projects focus on defining longitudinal trajectories of brain and behavioral development in infants with multiple risks for autism (Proj I); infants and toddlers with early signs of autism (Proj II), nonverbal school aged children with autism (Proj III), and higher functioning children/ adolescents (Proj IV),using a shared set of imaging, neurophysiological and neurobehavioral biomarkers, as well as genetic risk and expression analysis (Proj V) in longitudinal studies. This center is focused on understanding both early and later trajectories of emerging and developing functional connectivity and behavioral change in relation to variation in autism phenotypes, defining how genetic risks mediate both imaging and behavioral phenotypes, and altering trajectories through two separate treatments focused on core deficits in ASD, one targeted developing joint attention and social orientation in infants, and one focused on improving language nonverbal children with augmentative pharmacological intervention. Four cores support the scientific goals: an Administrative Core, facilitating scientific progress and providing data management/statistics support; a Diagnositc and Phenotyping Core; a Neuroimaging/Neurophysiology core, and a Research Education and Outreach core. The UCLA ACE benefits from our years of working together as a team. We present a highly integrated center with multiple collaborations across levels of analysis to further a strongly translational research strategy aimed at changing outcomes in children with autism spectrum disorders.
NIMH Data Archive
NIMH Data Archive
Autism Centers of Excellence (ACE)
Funding Completed
Close Out
Shared
No
$12,075,743.00
629
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NIH - Extramural None


P50HD055784-06 Biomarkers of Developmental Trajectories and Treatment in ASD 09/04/2012 07/31/2022 748 Not Reported UNIVERSITY OF CALIFORNIA LOS ANGELES $12,075,743.00

IDNameCreated DateStatusType
130Jeste Lab UCLA ACEii EEG02/24/2014ApprovedEEG
131Jeste Lab UCLA ACEii: Charlie Brown and Sesame Street - Project 102/27/2014ApprovedEye Tracking
132Jeste Lab UCLA ACEii: Animacy - Project 102/27/2014ApprovedEye Tracking
133Jeste Lab UCLA ACEii: Mom Stranger - Project 202/27/2014ApprovedEye Tracking
134Jeste Lab UCLA ACEii: Face Emotion - Project 302/27/2014ApprovedEye Tracking
238P1_resting8min01/15/2015ApprovedfMRI
239P1-nativelang01/15/2015ApprovedfMRI
240P4_rewards01/15/2015ApprovedfMRI
241P4_resting6min01/15/2015ApprovedfMRI
242P4_faces01/15/2015ApprovedfMRI
243P1_language01/15/2015ApprovedfMRI
320Geschwind 2015-9017 Omni2.5-806/10/2015ApprovedOmics

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.

ACE Family Medical History Clinical Assessments 208
ACE Subject Medical History Clinical Assessments 214
ACE Subject Physical Exam Clinical Assessments 74
Aberrant Behavior Checklist (ABC) - Community Clinical Assessments 40
Abnormal Involuntary Movement Scale Clinical Assessments 41
Autism Diagnostic Interview, Revised (ADI-R) Clinical Assessments 89
Autism Diagnostic Observation Schedule (ADOS)- Module 3 Clinical Assessments 22
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 1 Clinical Assessments 76
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 2 Clinical Assessments 74
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 3 Clinical Assessments 10
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Toddler Module Clinical Assessments 162
Autism Observation Scale for Infants Clinical Assessments 86
BRIEF-Parent Clinical Assessments 77
Child Behavior Checklist (CBCL) 6-18 Clinical Assessments 76
Child Symptom Inventory Parent/Teacher Checklist Clinical Assessments 77
Children's Yale-Brown Obsessive Compulsive Scale Clinical Assessments 21
Clinical Global Impression (CGI) Clinical Assessments 41
Clinical Lab Tests Clinical Assessments 30
Concomitant Medications Clinical Assessments 20
Demographics form UCLA Clinical Assessments 33
EEG Subject Files Imaging 195
Early Social Communication Scale (ESCS) Clinical Assessments 145
Eye Tracking Subject-Experiment Imaging 200
Genomics Genetic Test Genomics 104
Genomics Sample Genomics 169
Genomics Subject Genomics 169
Image Imaging 166
Infant Medical History Questionnaire Clinical Assessments 87
Interpersonal Competence Scale Clinical Assessments 78
Interpersonal Reactivity Index (IRI) Clinical Assessments 74
Leiter International Performance Scale-Revised (Leiter-R), Visualization and Reasoning Battery Clinical Assessments 41
M-CHAT Clinical Assessments 59
MacArthur-Bates CDI - Words and Gestures Form Clinical Assessments 88
MacArthur-Bates CDI - Words and Sentences Form Clinical Assessments 74
Mullen Scales of Early Learning Clinical Assessments 177
Parent Concerns Questionaire Clinical Assessments 94
Peabody Picture Vocabulary Test, Fourth Edition-Form A Clinical Assessments 72
Preschool Language Scales Fifth edition (PLS-5) Clinical Assessments 41
Repetitive Behavior Scale - Revised (RBS-R) Clinical Assessments 120
Research Subject Clinical Assessments 608
SRS-2. Adult, Preschool and School Age Clinical Assessments 340
Sensory Profile Short Clinical Assessments 76
Side Effects Clinical Assessments 41
Simpson-Angus Extrapyramidal Side Effects Scale Clinical Assessments 41
Social Communication Questionnaire (SCQ) - Current Form Clinical Assessments 117
Social Communication Questionnaire (SCQ) - Lifetime Clinical Assessments 45
Social Responsiveness Scale (SRS) Clinical Assessments 78
Vineland-II - Parent and Caregiver Rating Form (2005) Clinical Assessments 86
Vineland-II - Survey Form (2005) Clinical Assessments 73
Vital Signs Clinical Assessments 41
WASI-2 Clinical Assessments 27
Wechsler Abbreviated Scale of Intelligence (WASI) Clinical Assessments 31
Wechsler Intelligence Scale for Children - IV [part 1] Clinical Assessments 16
Wechsler Intelligence Scale for Children - IV [part 2] Clinical Assessments 16

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
34098753Create StudyWhat are the odds? Predicting the likelihood of a negative episode in a sample of toddlers with autism spectrum disorder.Autism : the international journal of research and practiceDimachkie Nunnally, Amanda; Sterrett, Kyle; Gulsrud, Amanda; Kasari, ConnieNovember 1, 2021Not Determined
34050248Create StudyTranscriptome analysis of MBD5-associated neurodevelopmental disorder (MAND) neural progenitor cells reveals dysregulation of autism-associated genes.Scientific reportsMullegama, Sureni V; Klein, Steven D; Williams, Stephen R; Innis, Jeffrey W; Probst, Frank J; Haldeman-Englert, Chad; Martinez-Agosto, Julian A; Yang, Ying; Tian, Yuchen; Elsea, Sarah H; Ezashi, ToshihikoMay 28, 2021Not Determined
33866373Create StudyAltered Thalamocortical Connectivity in 6-Week-Old Infants at High Familial Risk for Autism Spectrum Disorder.Cerebral cortex (New York, N.Y. : 1991)Nair, Aarti; Jalal, Rhideeta; Liu, Janelle; Tsang, Tawny; McDonald, Nicole M; Jackson, Lisa; Ponting, Carolyn; Jeste, Shafali S; Bookheimer, Susan Y; Dapretto, MirellaJuly 29, 2021Not Determined
33860866Create StudyBeyond Baby Siblings-Expanding the Definition of "High-Risk Infants" in Autism Research.Current psychiatry reportsMcDonald, Nicole M; Jeste, Shafali SApril 16, 2021Not Determined
33587311Create StudyAssociations between physiological and neural measures of sensory reactivity in youth with autism.Journal of child psychology and psychiatry, and allied disciplinesJung, Jiwon; Zbozinek, Tomislav D; Cummings, Kaitlin K; Wilhelm, Frank H; Dapretto, Mirella; Craske, Michelle G; Bookheimer, Susan Y; Green, Shulamite AOctober 1, 2021Not Determined
33436538Create StudySensory over-responsivity is related to GABAergic inhibition in thalamocortical circuits.Translational psychiatryWood, Emily T; Cummings, Kaitlin K; Jung, Jiwon; Patterson, Genevieve; Okada, Nana; Guo, Jia; O'Neill, Joseph; Dapretto, Mirella; Bookheimer, Susan Y; Green, Shulamite AJanuary 12, 2021Not Determined
33389145Create Study5q35 duplication presents with psychiatric and undergrowth phenotypes mediated by NSD1 overexpression and mTOR signaling downregulation.Human geneticsQuintero-Rivera, Fabiola; Eno, Celeste C; Sutanto, Christine; Jones, Kelly L; Nowaczyk, Małgorzata J M; Wong, Derek; Earl, Dawn; Mirzaa, Ghayda; Beck, Anita; Martinez-Agosto, Julian AApril 1, 2021Not Determined
33368921Create StudyLack of neural evidence for implicit language learning in 9-month-old infants at high risk for autism.Developmental scienceLiu, Janelle; Tsang, Tawny; Ponting, Carolyn; Jackson, Lisa; Jeste, Shafali S; Bookheimer, Susan Y; Dapretto, MirellaJuly 1, 2021Not Determined
33043498Create StudyFunctional connectivity during language processing in 3-month-old infants at familial risk for autism spectrum disorder.The European journal of neuroscienceTran, Xuan A; McDonald, Nicole; Dickinson, Abigail; Scheffler, Aaron; Frohlich, Joel; Marin, Andrew; Kure Liu, Christopher; Nosco, Erin; Şentürk, Damla; Dapretto, Mirella; Spurling Jeste, ShafaliMarch 1, 2021Not Determined
32860348Create StudySex Differences in Salience Network Connectivity and its Relationship to Sensory Over-Responsivity in Youth with Autism Spectrum Disorder.Autism research : official journal of the International Society for Autism ResearchCummings, Kaitlin K; Lawrence, Katherine E; Hernandez, Leanna M; Wood, Emily T; Bookheimer, Susan Y; Dapretto, Mirella; Green, Shulamite ASeptember 2020Not Determined
32798139Create StudyMultivariate Neural Connectivity Patterns in Early Infancy Predict Later Autism Symptoms.Biological psychiatry. Cognitive neuroscience and neuroimagingDickinson, Abigail; Daniel, Manjari; Marin, Andrew; Gaonkar, Bilwaj; Dapretto, Mirella; McDonald, Nicole M; Jeste, ShafaliJanuary 1, 2021Not Determined
32658762Create StudyEmerging atypicalities in functional connectivity of language-related networks in young infants at high familial risk for ASD.Developmental cognitive neuroscienceLiu, Janelle; Okada, Nana J; Cummings, Kaitlin K; Jung, Jiwon; Patterson, Genevieve; Bookheimer, Susan Y; Jeste, Shafali S; Dapretto, MirellaOctober 1, 2020Not Determined
32634676Create StudyFunctional genomics links genetic origins to pathophysiology in neurodegenerative and neuropsychiatric disease.Current opinion in genetics & developmentWamsley, Brie; Geschwind, Daniel HDecember 1, 2020Not Determined
32215919Create StudyElectrophysiological signatures of visual statistical learning in 3-month-old infants at familial and low risk for autism spectrum disorder.Developmental psychobiologyMarin, Andrew; Hutman, Ted; Ponting, Carolyn; McDonald, Nicole M; Carver, Leslie; Baker, Elizabeth; Daniel, Manjari; Dickinson, Abigail; Dapretto, Mirella; Johnson, Scott P; Jeste, Shafali SSeptember 1, 2020Not Determined
31696785Create StudyPositive social feedback alters emotional ratings and reward valuation of neutral faces.Quarterly journal of experimental psychology (2006)Young, Katherine S; Hasratian, Anni M; Parsons, Christine E; Zinbarg, Richard E; Nusslock, Robin; Bookheimer, Susan Y; Craske, Michelle GJuly 2020Not Determined
31654560Create StudyBehavioral characterization of dup15q syndrome: Toward meaningful endpoints for clinical trials.American journal of medical genetics. Part ADiStefano, Charlotte; Wilson, Rujuta B; Hyde, Carly; Cook, Edwin H; Thibert, Ronald L; Reiter, Lawrence T; Vogel-Farley, Vanessa; Hipp, Joerg; Jeste, ShafaliJanuary 2020Not Determined
31639285Create StudyMutations in the sonic hedgehog pathway cause macrocephaly-associated conditions due to crosstalk to the PI3K/AKT/mTOR pathway.American journal of medical genetics. Part AKlein, Steven D; Nguyen, Dzung C; Bhakta, Viraj; Wong, Derek; Chang, Vivian Y; Davidson, Tom B; Martinez-Agosto, Julian ADecember 2019Not Determined
31589284Create StudyDevelopmental Trajectories of Infants With Multiplex Family Risk for Autism: A Baby Siblings Research Consortium Study.JAMA neurologyMcDonald, Nicole M; Senturk, Damla; Scheffler, Aaron; Brian, Jessica A; Carver, Leslie J; Charman, Tony; Chawarska, Katarzyna; Curtin, Suzanne; Hertz-Piccioto, Irva; Jones, Emily J H; Klin, Ami; Landa, Rebecca; Messinger, Daniel S; Ozonoff, Sally; Stone, Wendy L; Tager-Flusberg, Helen; Webb, Sara Jane; Young, Gregory; Zwaigenbaum, Lonnie; Jeste, Shafali SJanuary 2020Not Determined
31585457Create StudyDefining and distinguishing infant behavioral states using acoustic cry analysis: is colic painful?Pediatric researchParga, Joanna J; Lewin, Sharon; Lewis, Juanita; Montoya-Williams, Diana; Alwan, Abeer; Shaul, Brianna; Han, Carol; Bookheimer, Susan Y; Eyer, Sherry; Dapretto, Mirella; Zeltzer, Lonnie; Dunlap, Lauren; Nookala, Usha; Sun, Daniel; Dang, Bianca H; Anderson, Ariana EFebruary 2020Not Determined
31500805Create StudySynaptic and Gene Regulatory Mechanisms in Schizophrenia, Autism, and 22q11.2 Copy Number Variant-Mediated Risk for Neuropsychiatric Disorders.Biological psychiatryForsyth, Jennifer K; Nachun, Daniel; Gandal, Michael J; Geschwind, Daniel H; Anderson, Ariana E; Coppola, Giovanni; Bearden, Carrie EJanuary 2020Not Determined
31462477Create StudyMulticentre, randomised waitlist control trial investigating a parent-assisted social skills group programme for adolescents with brain injuries: protocol for the friends project.BMJ openGilmore, Rose; Sakzewski, Leanne; Ziviani, Jenny; Mcintyre, Sarah; Smithers Sheedy, Hayley; Hilton, Nicola; Williams, Tracey; Quinn, Kirsten; Sarandrea, Anne Marie; Laugeson, Elizabeth; Chatfield, MarkAugust 2019Not Determined
31419043Create StudyEarly patterns of functional brain development associated with autism spectrum disorder in tuberous sclerosis complex.Autism research : official journal of the International Society for Autism ResearchDickinson, Abigail; Varcin, Kandice J; Sahin, Mustafa; Nelson 3rd, Charles A; Jeste, Shafali SDecember 2019Not Determined
31312421Create StudyMechanisms underlying the EEG biomarker in Dup15q syndrome.Molecular autismFrohlich J, Reiter LT, Saravanapandian V, Distefano C, Huberty S, Hyde C, Chamberlain S, Bearden CE, Golshani P, Irimia A, Olsen RW, Hipp JF, Jeste SSJanuary 2019Not Determined
31232238Create StudyHotspot Mutations in DICER1 Causing GLOW Syndrome-Associated Macrocephaly via Modulation of Specific microRNA Populations Result in the Activation of PI3K/ATK/mTOR Signaling.MicroRNA (Shariqah, United Arab Emirates)Klein, Steven D; Martinez-Agosto, Julian AJanuary 1, 2020Not Determined
31230465Create StudyDistinct Patterns of Neural Habituation and Generalization in Children and Adolescents With Autism With Low and High Sensory Overresponsivity.The American journal of psychiatryGreen, Shulamite A; Hernandez, Leanna; Lawrence, Katherine E; Liu, Janelle; Tsang, Tawny; Yeargin, Jillian; Cummings, Kaitlin; Laugeson, Elizabeth; Dapretto, Mirella; Bookheimer, Susan YDecember 2019Not Determined
31223334Create StudyEEG Data Collection in Children with ASD: The Role of State in Data Quality and Spectral Power.Research in autism spectrum disordersDiStefano, Charlotte; Dickinson, Abigail; Baker, Elizabeth; Jeste, Shafali SpurlingJanuary 2019Not Determined
31163191Create StudyMethodological considerations in the use of Noldus EthoVision XT video tracking of children with autism in multi-site studies.Biological psychologySabatos-DeVito, Maura; Murias, Michael; Dawson, Geraldine; Howell, Toni; Yuan, Andrew; Marsan, Samuel; Bernier, Raphael A; Brandt, Cynthia A; Chawarska, Katarzyna; Dzuira, James D; Faja, Susan; Jeste, Shafali S; Naples, Adam; Nelson, Charles A; Shic, Frederick; Sugar, Catherine A; Webb, Sara J; McPartland, James C; Autism Biomarkers Consortium for Clinical TrialsSeptember 2019Not Determined
31150625Create StudyHuman Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice.CellSharon, Gil; Cruz, Nikki Jamie; Kang, Dae-Wook; Gandal, Michael J; Wang, Bo; Kim, Young-Mo; Zink, Erika M; Casey, Cameron P; Taylor, Bryn C; Lane, Christianne J; Bramer, Lisa M; Isern, Nancy G; Hoyt, David W; Noecker, Cecilia; Sweredoski, Michael J; Moradian, Annie; Borenstein, Elhanan; Jansson, Janet K; Knight, Rob; Metz, Thomas O; Lois, Carlos; Geschwind, Daniel H; Krajmalnik-Brown, Rosa; Mazmanian, Sarkis KMay 2019Not Determined
31141683Create StudyReduced Prefrontal Synaptic Connectivity and Disturbed Oscillatory Population Dynamics in the CNTNAP2 Model of Autism.Cell reportsLazaro, Maria T; Taxidis, Jiannis; Shuman, Tristan; Bachmutsky, Iris; Ikrar, Taruna; Santos, Rommel; Marcello, G Mark; Mylavarapu, Apoorva; Chandra, Swasty; Foreman, Allison; Goli, Rachna; Tran, Duy; Sharma, Nikhil; Azhdam, Michelle; Dong, Hongmei; Choe, Katrina Y; Peñagarikano, Olga; Masmanidis, Sotiris C; Rácz, Bence; Xu, Xiangmin; Geschwind, Daniel H; Golshani, PeymanMay 2019Not Determined
30974225Create StudyERP evidence of semantic processing in children with ASD.Developmental cognitive neuroscienceDistefano C, Senturk D, Jeste SSApril 2019Not Determined
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23452686Create StudyBeyond autism: a baby siblings research consortium study of high-risk children at three years of age.Journal of the American Academy of Child and Adolescent PsychiatryMessinger, Daniel; Young, Gregory S; Ozonoff, Sally; Dobkins, Karen; Carter, Alice; Zwaigenbaum, Lonnie; Landa, Rebecca J; Charman, Tony; Stone, Wendy L; Constantino, John N; Hutman, Ted; Carver, Leslie J; Bryson, Susan; Iverson, Jana M; Strauss, Mark S; Rogers, Sally J; Sigman, MarianMarch 2013Not Determined
23352155Create StudyRare inherited variation in autism: beginning to see the forest and a few trees.NeuronStein JL, Parikshak NN, Geschwind DHJanuary 23, 2013Not Determined
23298182Create StudyDecreased reelin expression and organophosphate pesticide exposure alters mouse behaviour and brain morphology.ASN neuroMullen, Brian R; Khialeeva, Elvira; Hoffman, Daniel B; Ghiani, Cristina A; Carpenter, Ellen M2013Not Determined
22965298Create StudyPreschool based JASPER intervention in minimally verbal children with autism: pilot RCT.Journal of autism and developmental disordersGoods KS, Ishijima E, Chang YC, Kasari CMay 2013Not Determined
22962003Create StudyDeficits in mental state attributions in individuals with 22q11.2 deletion syndrome (velo-cardio-facial syndrome).Autism research : official journal of the International Society for Autism ResearchHo JS, Radoeva PD, Jalbrzikowski M, Chow C, Hopkins J, Tran WC, Mehta A, Enrique N, Gilbert C, Antshel KM, Fremont W, Kates WR, Bearden CEDecember 2012Not Determined
22958829Create StudyAutism-associated promoter variant in MET impacts functional and structural brain networks.NeuronRudie, Jeffrey D; Hernandez, Leanna M; Brown, Jesse A; Beck-Pancer, Devora; Colich, Natalie L; Gorrindo, Philip; Thompson, Paul M; Geschwind, Daniel H; Bookheimer, Susan Y; Levitt, Pat; Dapretto, MirellaSeptember 6, 2012Not Determined
22843504Create StudyIndividual common variants exert weak effects on the risk for autism spectrum disorders.Human molecular geneticsAnney, Richard; Klei, Lambertus; Pinto, Dalila; Almeida, Joana; Bacchelli, Elena; Baird, Gillian; Bolshakova, Nadia; Bölte, Sven; Bolton, Patrick F; Bourgeron, Thomas; Brennan, Sean; Brian, Jessica; Casey, Jillian; Conroy, Judith; Correia, Catarina; Corsello, Christina; Crawford, Emily L; de Jonge, Maretha; Delorme, Richard; Duketis, Eftichia; Duque, Frederico; Estes, Annette; Farrar, Penny; Fernandez, Bridget A; Folstein, Susan E; Fombonne, Eric; Gilbert, John; Gillberg, Christopher; Glessner, Joseph T; Green, Andrew; Green, Jonathan; Guter, Stephen J; Heron, Elizabeth A; Holt, Richard; Howe, Jennifer L; Hughes, Gillian; Hus, Vanessa; Igliozzi, Roberta; Jacob, Suma; Kenny, Graham P; Kim, Cecilia; Kolevzon, Alexander; Kustanovich, Vlad; Lajonchere, Clara M; Lamb, Janine A; Law-Smith, Miriam; Leboyer, Marion; Le Couteur, Ann; Leventhal, Bennett L; Liu, Xiao-Qing; Lombard, Frances; Lord, Catherine; Lotspeich, Linda; Lund, Sabata C; Magalhaes, Tiago R; Mantoulan, Carine; McDougle, Christopher J; Melhem, Nadine M; Merikangas, Alison; Minshew, Nancy J; Mirza, Ghazala K; Munson, Jeff; Noakes, Carolyn; Nygren, Gudrun; Papanikolaou, Katerina; Pagnamenta, Alistair T; Parrini, Barbara; Paton, Tara; Pickles, Andrew; Posey, David J; Poustka, Fritz; Ragoussis, Jiannis; Regan, Regina; Roberts, Wendy; Roeder, Kathryn; Roge, Bernadette; Rutter, Michael L; Schlitt, Sabine; Shah, Naisha; Sheffield, Val C; Soorya, Latha; Sousa, Inês; Stoppioni, Vera; Sykes, Nuala; Tancredi, Raffaella; Thompson, Ann P; Thomson, Susanne; Tryfon, Ana; Tsiantis, John; Van Engeland, Herman; Vincent, John B; Volkmar, Fred; Vorstman, J A S; Wallace, Simon; Wing, Kirsty; Wittemeyer, Kerstin; Wood, Shawn; Zurawiecki, Danielle; Zwaigenbaum, Lonnie; Bailey, Anthony J; Battaglia, Agatino; Cantor, Rita M; Coon, Hilary; Cuccaro, Michael L; Dawson, Geraldine; Ennis, Sean; Freitag, Christine M; Geschwind, Daniel H; Haines, Jonathan L; Klauck, Sabine M; McMahon, William M; Maestrini, Elena; Miller, Judith; Monaco, Anthony P; Nelson, Stanley F; Nurnberger Jr, John I; Oliveira, Guiomar; Parr, Jeremy R; Pericak-Vance, Margaret A; Piven, Joseph; Schellenberg, Gerard D; Scherer, Stephen W; Vicente, Astrid M; Wassink, Thomas H; Wijsman, Ellen M; Betancur, Catalina; Buxbaum, Joseph D; Cook, Edwin H; Gallagher, Louise; Gill, Michael; Hallmayer, Joachim; Paterson, Andrew D; Sutcliffe, James S; Szatmari, Peter; Vieland, Veronica J; Hakonarson, Hakon; Devlin, BernieNovember 1, 2012Not Determined
22760337Create StudyNeural and behavioral responses during self-evaluative processes differ in youth with and without autism.Journal of autism and developmental disordersPfeifer, Jennifer H; Merchant, Junaid S; Colich, Natalie L; Hernandez, Leanna M; Rudie, Jeff D; Dapretto, MirellaFebruary 2013Not Determined

Relevant Publications
PubMed IDStudyTitleJournalAuthorsDate
28700096Create StudyPeak alpha frequency is a neural marker of cognitive function across the autism spectrum.The European journal of neuroscienceDickinson, Abigail; DiStefano, Charlotte; Senturk, Damla; Jeste, Shafali SpurlingMarch 1, 2018

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
Mullen Scales of Early Learning info icon
37407/31/2013
177
Approved
Genomics/omics info icon
17711/27/2017
169
Approved
ABC Community info icon
12507/31/2013
40
Approved
Leiter International Performance Scale-Revised (Leiter-R) info icon
37401/15/2014
41
Approved
ADOS info icon
19707/31/2013
243
Approved
Simpson-Angus Rating Scale (SAS) info icon
12507/31/2013
41
Approved
ADI-R info icon
19707/31/2013
89
Approved
Childrens Yale-Brown OC Scale (CY-BOCS) info icon
37407/31/2013
21
Approved
Medical History info icon
12507/31/2013
230
Approved
Eye Tracking info icon
23001/15/2014
200
Approved
Social Responsiveness Scale (SRS) info icon
37407/31/2013
416
Approved
Wechsler Abbreviated Scale of Intelligence (WASI) info icon
37407/31/2013
58
Approved
Genetic Test info icon
49207/31/2013
104
Approved
Interpersonal Reactivity Index info icon
12507/31/2013
74
Approved
Social Communication Questionnaire (SCQ) info icon
7207/31/2013
162
Approved
Demographics info icon
3307/31/2013
33
Approved
Child Behavior Checklist (CBCL) info icon
12507/31/2013
76
Approved
M-CHAT info icon
37401/31/2015
59
Approved
Abnormal Involuntary Movement Scale (AIMS) info icon
7201/15/2014
41
Approved
Clinical Global Impression (CGI) info icon
10501/15/2014
41
Approved
Autism Observation Scale for Infants (AOSI) info icon
7201/15/2014
86
Approved
Vital Signs Assessment info icon
37407/31/2013
41
Approved
Early Social Communication Scales (ESCS) info icon
24911/27/2017
145
Approved
Child Symptom Inventory Parent Checklist info icon
37407/31/2013
77
Approved
Interpersonal Competence Scale (ICS) info icon
23007/31/2013
78
Approved
Parent Concerns Questionaire info icon
17707/31/2013
94
Approved
Wechsler Intelligence Scale for Children info icon
25007/31/2013
16
Approved
MacArthur Bates Communicative Development Inventory info icon
7201/15/2014
90
Approved
Peabody Picture Vocabulary Test, Fourth Edition info icon
10507/31/2013
72
Approved
Repetitive Behavior Scale - Revised (RBS-R) info icon
7207/31/2013
120
Approved
Preschool Language Scale (PLS) info icon
37407/31/2013
41
Approved
Physical Exam info icon
37407/31/2013
74
Approved
Sensory Profile info icon
37407/31/2013
76
Approved
Behavior Rating Inventory of Executive Function (BRIEF) info icon
25007/31/2013
77
Approved
Research Subject and Pedigree info icon
14407/15/2014
620
Approved
Clinical Lab Tests info icon
7201/15/2014
30
Approved
Side Effects info icon
10501/15/2014
41
Approved
Vineland (Parent and Caregiver) info icon
19707/31/2013
158
Approved
Concomitant Medication info icon
10507/15/2015
20
Approved
Imaging (Structural, fMRI, DTI, PET, microscopy) info icon
49207/31/2013
166
Approved
EEG info icon
23002/28/2014
195
Approved
Structure not yet defined

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Associated Studies

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

Study NameAbstractCollection/Study SubjectsData UsageState
Examining the validity of the use of ratio IQs in psychological assessments IQ tests are amongst the most used psychological assessments, both in research and clinical settings. For participants who cannot complete IQ tests normed for their age, ratio IQ scores (RIQ) are routinely computed and used as a proxy of IQ, especially in large research databases to avoid missing data points. However, because it has never been scientifically validated, this practice is questionable. In the era of big data, it is important to examine the validity of this widely used practice. In this paper, we use the case of autism to examine the differences between standard full-scale IQ (FSIQ) and RIQ. Data was extracted from four databases in which ages, FSIQ scores and subtests raw scores were available for autistic participants between 2 and 17 years old. The IQ tests included were the MSEL (N=12033), DAS-II early years (N=1270), DAS-II school age (N=2848), WISC-IV (N=471) and WISC-V (N=129). RIQs were computed for each participant as well as the discrepancy (DSC) between RIQ and FSIQ. We performed two linear regressions to respectively assess the effect of FSIQ and of age on the DSC for each IQ test, followed by additional analyses comparing age subgroups as well as FSIQ subgroups on DSC. Participants at the extremes of the FSIQ distribution tended to have a greater DSC than participants with average FSIQ. Furthermore, age significantly predicted the DSC, with RIQ superior to FSIQ for younger participants while the opposite was found for older participants. These results question the validity of this widely used alternative scoring method, especially for individuals at the extremes of the normal distribution, with whom RIQs are most often employed.193/17423Secondary AnalysisPrivate
Controls for SCCRIPTo establish a well characterized cohort for pediatric patients living with sickle cell disease81/11185Secondary AnalysisPrivate
Working Title: Differentiating Core Autism SymptomatologyAutism spectrum disorder (ASD) is characterized by persistent deficits in social communication and social interaction, social-emotional reciprocity, and repetitive behavior or restricted interest (American Psychiatric Association [APA], 2013). This study extends the existing literature by clarifying the extent to which mental health disorder symptoms differentially converge with autism symptoms related to social communication and restricted and repetitive behavior, as well as the extent to which mental health symptoms are empirically differentiated from the core autism symptom domains. Although there is a well-documented correlation between the severity of core ASD symptoms and the presence of mental health disorder symptoms, such as anxiety and irritability, the nature of this linkage remains poorly understood. In this project, the National Database for Autism Research (NDAR) and Research Domain Criteria Database (RDoCdb) were used to observe continuous symptom measures such as the Social Responsiveness Scale (SRS) and the Child Behavior Checklist (CBCL) to examine correlation matrices as well as factor structure models to examine these patterns of association. The SRS “social communication” and “repetitive restricted” subscales were correlated with the CBCL externalizing, internalizing, attention, conduct, aggression, psychosomatic, and withdrawn subscales. We hypothesized that “repetitive and restricted” behaviors would be more correlated with the CBCL scales than would the “social communication” scale. These results were also interpreted according to age and IQ. In conclusion, this study may elucidate ongoing questions about the centrality of mental health symptoms like anxiety to aspects of ASD taxonomy. 387/11144Secondary AnalysisPrivate
Characterizing Auditory Hyperreactivity in AutismObjective: To answer the following research questions: 1) What is the prevalence of auditory hyper-reactivity in ASD? 2) Does auditory hyper-reactivity severity change with age? and 3) What are the most common auditory stimuli reported to be bothersome? Research Design: Primarily descriptive secondary data analysis. Methods: Type of data: Questionnaire items regarding auditory hyper-reactivity will be filtered from: Autism Diagnostic Interview-Revised, Sensory Profile (all forms), Sensory Over-Responsivity Scale, and Sensory Experiences Questionnaire in addition to demographics (i.e., age, race, ethnicity, diagnoses). Analysis Plan: Descriptive statistics, tables and figures will be used to summarize the prevalence and severity of auditory hyper-reactivity by age. Linear regression modeling will be used to evaluate changes in auditory hyper-reactivity by age. If data is available for control subjects, statistical analyses will be conducted for means comparison (ASD vs. non-ASD). 89/7001Secondary AnalysisPrivate
The effect of compensatory mechanisms during and after pregnancy on a child's developmentEarly childhood involves rapid processes of human growth leading to different trajectories in physical, cognitive, social, and emotional development (Graignic-Philippe et al., 2014). These processes are influenced by a wide variety of factors such as maternal health, environmental stressors, and early childhood experiences. Current literature has shown how exposure to both acute and chronic stress during pregnancy have a pathogenetic effect throughout childhood (Kim & Leventhal, 2015; Rice, et al, 2010), leading to neurotypical or atypical development. Studies have shown how these stressors are linked neurodevelopmental disorders such Autism Spectrum Disorders (Zerbo et al., 2015; Atladóttir et al., 2012) or Attention Deficit Hyperactivity Disorder (Rosenqvist et al., 2019). In recent years, there has been a shift from traditional diagnostic research models to synthesis of different scientific fields to map lifecourse development in order for rapid translation into healthcare practices (Halfon et al., 2014). Whilst there are studies showing links between stress and atypical developmental outcomes, there is still very limited literature on compensatory mechanisms found pre- and post-pregnancy, which illustrate development of protective factors (such as presence of self-regulation, high verbal intelligence, sociability, adept social communication) against atypical developmental outcomes. This study aims to identify and measure the presence of these protective factors that appear to guard against or mitigate the emergence of neurodevelopmental disorders. Therefore, nationwide and longitudinal data are needed in order to accurately create risk models in order to map developmental trajectories. 78/5717Secondary AnalysisPrivate
Investigating autism etiology and heterogeneity by decision tree algorithmAutism spectrum disorder (ASD) is a neurodevelopmental disorder that causes deficits in cognition, communication and social skills. ASD, however, is a highly heterogeneous disorder. This heterogeneity has made identifying the etiology of ASD a particularly difficult challenge, as patients exhibit a wide spectrum of symptoms without any unifying genetic or environmental factors to account for the disorder. For better understanding of ASD, it is paramount to identify potential genetic and environmental risk factors that are comorbid with it. Identifying such factors is of great importance to determine potential causes for the disorder, and understand its heterogeneity. Existing large-scale datasets offer an opportunity for computer scientists to undertake this task by utilizing machine learning to reliably and efficiently obtain insight about potential ASD risk factors, which would in turn assist in guiding research in the field. In this study, decision tree algorithms were utilized to analyze related factors in datasets obtained from the National Database for Autism Research (NDAR) consisting of nearly 3000 individuals. We were able to identify 15 medical conditions that were highly associated with ASD diagnoses in patients; furthermore, we extended our analysis to the family medical history of patients and we report six potentially hereditary medical conditions associated with ASD. Associations reported had a 90% accuracy. Meanwhile, gender comparisons highlighted conditions that were unique to each gender and others that overlapped. Those findings were validated by the academic literature, thus opening the way for new directions for the use of decision tree algorithms to further understand the etiology of autism. 38/3382Secondary AnalysisShared
Autism Sensory Research Consortium Cross-lab Integrative Data Analysis Since 2013, when sensory features were officially added to the diagnostic criteria for autism, research into the sensory manifestations of the condition has increased dramatically. However, the majority of this research has primarily been conducted using small laboratory-based samples of children on the autism spectrum, substantially limiting the hypotheses that can be tested in any one dataset and the generalizability of results to the wider autistic population. The Autism Sensory Research Consortium (ASRC), funded by the Nancy Lurie Marks Family Foundation, represents the first major international collaboration of over a dozen research groups that study sensory functioning in autism. As a major thrust of this collaboration, the ASRC has begun a data sharing initiative, in which all participating labs can contribute existing data from their past and present research studies to a centralized database. These “Big Data” can then be systematically examined using powerful large-sample statistical techniques such as structural equation modeling and item response theory, which will allow researchers to test more complex hypotheses regarding the nature of sensory differences in autism and their relationships with sociodemographic and non-sensory clinical features. Once data from all sites has been pooled, it will be analyzed using a method called integrative data analysis, which is specially designed to derive insights from large and heterogeneous samples. One major advantage of this methodology is the ability to construct and test measurement models of sensory symptoms, determining the most appropriate set of questions for assessing each construct and making sure that the scales do not produce biased comparisons when they are examined across diagnostic groups or subsets of the autistic population. Furthermore, measurement models can be constructed to bridge multiple questionnaires, allowing for the calculation of robust composite scores that can be compared between studies that only administered items from one of the contributing questionnaires. These models can further facilitate pooling of data across studies, allowing us to amass even larger datasets to answer questions about sensory function in the autistic population. Furthermore, moving forward, the composite sensory measures from the integrative data analysis can be employed in other studies, providing investigators in sensory autism research with a suite of reliable and valid behavioral measures that can be used as outcomes in trials of interventions targeting these symptoms. In the long term, this project has the potential to help us better understand the nature of sensory function in persons on the spectrum, as well as how sensory alterations relate to broader features of the condition—specifically, for whom and/or at what point in development sensory features are most predictive of core autism behaviors or other meaningful clinical outcomes such as language acquisition and adaptive behavior. Incorporation of neuroscientific data collected within the ASRC can also possibly shed some light on the neural basis of sensory disruptions in the autistic population. All of this will help to lay a foundation for future work testing the efficacy of candidate interventions aimed at improving sensory function and more distal skills in autistic individuals.1/2110Secondary AnalysisPrivate
Development of a Short Form of the SRS: An Application of IRTBackground: Research and practice in autism spectrum disorder (ASD) rely on quantitative measures, such as the Social Responsiveness Scale (SRS), for characterization and diagnosis. Like many ASD diagnostic measures, SRS scores are influenced by factors unrelated to ASD core features. This study further interrogates the psychometric properties of the SRS using item response theory (IRT), and demonstrates a strategy to enhance measure specificity by applying IRT results. Methods: SRS analyses were conducted on a large sample (N=21,426) of youth from four ASD databases. Items were subjected to item factor analyses and evaluation of item bias by gender, age, and expressive language level. Results: Item selection based on dimensionality and DIF analyses produced a reduced item SRS subscale that was unidimensional in structure, highly reliable (α=.96), and free of gender, age, expressive language, and non-verbal IQ influence. The subscale also showed strong relationships with established measures of autism symptom severity (ADOS, ADI-R, Vineland). Degree of association between all measures varied as a function of expressive language. Conclusions: Results identified specific SRS items that are more vulnerable to non-ASD-related traits. The resultant 16-item SRS subscale may possess superior psychometric properties compared to the original scale and emerge as a more precise measure of ASD core symptom severity, facilitating research and practice. Future research using IRT is needed to further refine existing measures of autism symptomatology. 67/1478Secondary AnalysisPrivate
Gender as a Moderator of the Association between Social Responsiveness and Cognitive Ability for Children with Autism27/977Secondary AnalysisPrivate
Brain-based sex differences in autism spectrum disorder across the lifespan: A systematic review of structural MRI, fMRI, and DTI findingsFemales with autism spectrum disorder (ASD) have been long overlooked in neuroscience research, but emerging evidence suggests they show distinct phenotypic trajectories and age-related brain differences. Sex-related biological factors (e.g., hormones, genes) may play a role in ASD etiology and have been shown to influence neurodevelopmental trajectories. Thus, a lifespan approach is warranted to understand brain-based sex differences in ASD. This systematic review on MRI-based sex differences in ASD was conducted to elucidate variations across the lifespan and inform biomarker discovery of ASD in females. We identified articles through two database searches. Fifty studies met criteria and underwent integrative review. We found that regions expressing replicable sex-by-diagnosis differences across studies overlapped with regions showing sex differences in neurotypical (NT) cohorts, in particular regions showing NT male>female volumes. Furthermore, studies investigating age-related brain differences across a broad age-span suggest distinct neurodevelopmental patterns in females with ASD. Qualitative comparison across youth and adult studies also supported this hypothesis. However, many studies collapsed across age, which may mask differences. Furthermore, accumulating evidence supports the female protective effect in ASD, although only one study examined brain circuits implicated in “protection.” When synthesized with the broader literature, brain-based sex differences in ASD may come from various sources, including genetic and endocrine processes involved in brain “masculinization” and “feminization” across early development, puberty, and other lifespan windows of hormonal transition. Furthermore, sex-related biology may interact with peripheral processes, in particular the stress axis and brain arousal system, to produce distinct neurodevelopmental patterns in males and females with ASD. Future research on neuroimaging-based sex differences in ASD would benefit from a lifespan approach in well-controlled and multivariate studies. Possible relationships between behavior, sex hormones, and brain development in ASD remain largely unexamined.162/759Secondary AnalysisShared
Combining Gaze and Demographic Feature Descriptors for Autism ClassificationPeople with autism suffer from social challenges and communication difficulties, which may prevent them from leading a fruitful and enjoyable life. It is imperative to diagnose and start treatments for autism as early as possible and, in order to do so, accurate methods of identifying the disorder are vital. We propose a novel method for classifying autism through the use of eye gaze and demographic feature descriptors that include a subject’s age and gender. We construct feature descriptors that incorporate the subject’s age and gender, as well as features based on eye gaze data. Using eye gaze information from the National Database for Autism Research, we tested our constructed feature descriptors on three different classifiers; random regression forests, C4.5 decision tree, and PART. Our proposed method for classifying autism resulted in a top classification rate of 96.2%. 162/756Secondary AnalysisShared
Personalized Autism Symptom Assessment with the Youth Top Problems Scale: Observational and Parent-Report Formats for Clinical Trials ApplicationsTo date, few measures of comorbid psychiatric symptoms in the context of autism spectrum disorder (ASD) have been established as both psychometrically robust and sensitive to the effects of treatment. Therefore, I propose to conduct an item response theory (IRT) analysis for this study using the Child and Adolescent Symptom Inventory (CASI) data from the National Database for Autism Research. Item parameters will be obtained through an IRT calibration of CASI items using flexMIRT.3 (Cai, 2016). In order to conduct IRT, the CASI calibration sample will include both these NDAR participants and a sample of 68 children with diagnoses of ASD and IQ>70 (ages 6-13 years) who participated in our recent NIMH-funded clinical trial of cognitive behavioral therapy, which will create a sample large enough for the IRT analysis. I plan to publish this data as part of a broader psychometric study of children with autism.2/746Secondary AnalysisPrivate
Gender differences in restricted and repetitive behaviors and interests in autismBackground: The female autism phenotype has been defined by differences in core autism spectrum disorder (ASD) symptomology related to reciprocal social communication and restricted and repetitive behaviors and interests (RRBI). Previous research on RRBI in ASD has found that affected boys have increased stereotyped and restricted behaviors compared to girls with ASD (Hiller, Young, & Weber, 2014; Mandy et al., 2012). Other domains of RRBI (i.e., self-injurious, compulsive, and insistence on sameness behaviors), which contribute to DSM-5 diagnosis, are less studied and have not been examined across gender. To date, no studies have examined gender differences using a comprehensive RRBI measure, which spans stereotyped, self-injurious, compulsive, insistence on sameness, and restricted behavior domains. Objectives: To investigate whether symptoms of RRBI (i.e., stereotyped, self-injurious, ritualistic, compulsive, insistence on sameness, and restricted behavior), as measured by item-level data on the Repetitive Behavior Scale-Revised (RBS-R), can classify males versus females with ASD. Methods: Participants included 615 youth with ASD (507 males; 82.4%), between 3 and 18 years of age (M=10.26, SD=4.20), who agreed to share data with the National Database for Autism Research (NDAR). A stepwise discriminant function analysis (DFA) was used to predict the degree RBS-R data could correctly classify gender in a large sample of individuals with ASD. Standardized canonical function coefficients (SCFC) from the DFA represent the contribution of each variable to the discrimination between groups, with greater SCFC indicating greater discrimination. Results: DFA results suggest that RBS-R items significantly differentiate girls versus boys with ASD, Wilks’ λ=0.89, χ2=70.79, p<0.001. Of note, gender was classified based on a set of 8 items (see table 1). Interestingly, the items that differentiated boys from girls did not solely consist of higher stereotyped and restricted behavior in boys (as indicated by negative SCFC scores). Half of the items that differentiated gender were higher in females with ASD (as indicated by positive SCFC scores) and from the self-injurious, compulsive, and insistence on sameness domains. This set of RBS-R items had greater success in correctly classifying boys with ASD (67.90%) than in correctly classifying affected girls (61.00%). Conclusions: This study extends findings of gender differences in RRBI for ASD, demonstrating that girls with ASD may demonstrate higher self-injurious, compulsive, and insistence on sameness behavior than affected boys. It is important for future research to disentangle whether these elevated rates of RRBI in girls with ASD are central to the female autism phenotype or an epiphenomenon of the high rates of co-occurring disorders (e.g., anxiety) noted in affected girls. 40/612Secondary AnalysisPrivate
Derivation of Quality Measures for Time-Series Images by Neuroimaging PipelinesUsing the National Database for Autism Research cloud platform, MRI data were analyzed using neuroimaging pipelines that included packages available as part of the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) Computational Environment to derive standardized measures of MR image quality. Time series QA was performed according to Friedman, et al. (http://www.ncbi.nlm.nih.gov/pubmed/16952468) providing values for Signal to Noise Ratio that can be compared to other subjects.41/356Secondary AnalysisShared
Neural Correlates of Restricted Repetitive Behavior in Autism Spectrum DisorderThe objective of this study is to investigate relationships between restricted, repetitive behavior and neural circuitry alterations in autism spectrum disorder (ASD). The neural circuitry mediating restricted, repetitive behaviors is largely unknown, and consequently effective treatments are lacking. In order to perform these investigations we will use the National Database for Autism Research (NDAR) to access questionnaires and assessments related to repetitive behavior as well as MRI, fMRI, and DTI scans from subjects with autism spectrum disorder (ASD) and typically developing controls. We will perform between-group morphological comparisons, as well as assessments of brain connectivity (e.g. diffusion tractography). For subjects with ASD, we will also correlate neuroimaging data to repetitive behavior scores. This study will help to better understand the link between restricted, repetitive behavior and specific brain alterations 4/192Secondary 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 measurements2/173Secondary AnalysisPrivate
Critical test items to differentiate individuals with SPCD from those with ASD and typical controlsSocial (pragmatic) communication disorder (SPCD) is a new category in the DSM-5. This study used IRT modelling to analyze archive data of item responses to the Social Communication Question-Lifetime (SCQ) from the National Database of Autism Research (NDAR), to select critical test items that could efficiently differentiate SPCD from ASD and TD. Methods: The SCQ records were downloaded from the NDAR. The item difficulty values and participants ability in the social communication and repetitive behavior and restricted interests were estimated through Winsteps. The items with difficulty values mostly matching the participants ability at the cut-off zones among three groups were selected. Result: The eight test items were identified for screening SPCD with 75% sensitivity. The specificity for differentiating SPCD from TD and ASD is 86.27% and 68.9% respectively. Conclusion: This study provides a short list of critical items that could be used to screen SPCD from TD and ASD. 1/151Secondary AnalysisPrivate
Inflexible neurobiological signatures precede atypical development in infants at high risk for autismVariability in neurobiological signatures is ubiquitous in early life but the link to adverse developmental milestones in humans is unknown. We examined how levels of signal and noise in movement signatures during the 1st year of life constrain early development in 71 healthy typically developing infants, either at High or Low familial Risk (HR or LR, respectively) for developing Autism Spectrum Disorders (ASD). Delays in early learning developmental trajectories in HR infants (validated in an analysis of 1,445 infants from representative infant-sibling studies) were predicted by worse stochastic patterns in their spontaneous head movements as early as 1–2 months after birth, relative to HR infants who showed more rapid developmental progress, as well as relative to all LR infants. While LR 1–2 mo-old infants’ movements were significantly different during a language listening task compared to during sleep, HR infants’ movements were more similar during both conditions, a striking lack of diversity that reveals context-inflexible experience of ambient information. Contrary to expectation, it is not the level of variability per se that is particularly detrimental in early life. Rather, inflexible sensorimotor systems and/or atypical transition between behavioral states may interfere with the establishment of capacity to extract structure and important cues from sensory input at birth, preceding and contributing to an atypical brain developmental trajectory in toddlerhood.70/70Secondary AnalysisShared
Genetic vulnerability of exposures to antenatal maternal treatments in 1-2 mo-old infantsThe growth and maturation of the nervous system is vulnerable during pregnancy. The impact of antenatal exposures to maternal treatments in the context of genetic vulnerability of the fetus, on sensorimotor functioning in early infancy, remains unexplored. Statistical features of head movements obtained from resting-state sleep fMRI scans are examined in 1-2 month-old infants, both at high risk (HR) for Autism Spectrum Disorder (ASD) due to a biological sibling with ASD and at low risk (LR) (N=56). In utero exposures include maternal prescription medications (psychotropic Rx: N=3HR;N=5LR vs. non-psychotropic Rx: N=11HR;N=9LR vs. none: N=11HR;N=16LR), psychiatric diagnoses (two or more Dx2: N=5HR;N=1LR;one Dx1: N=4HR; N=5LR;no Dx: N=12HR; N=20LR), infections requiring antibiotics (infection: N=5HR; N=8LR; no infection: N=20HR; N=22LR), or high fever (fever:N=2HR;N=2LR; no fever:N=23HR;N=27LR). Movements with significantly higher variability are detected in infants exposed to psychotropics (e.g.opioid analgesics) and those whose mothers had fever, and this effect is significantly worse for infants at HR for ASD. Movements are significantly less variable in HR infants with non-psychotropic exposures (e.g.antibiotics). Heightened number of psychiatric or mental health conditions is associated with noisier movements in both risk groups. Genetic vulnerability due to in utero exposure to maternal treatments is an important future approach to be advanced in the field of early mind and brain development.56/56Secondary AnalysisShared
Failure to attune to language predicts autism in high risk infantsYoung humans are typically sensitive to evolutionarily important aspects of information in the surrounding environment in a way that makes us thrive. Seeking to probe the putative disruptions of this process in infancy, I examined the statistical character of head movements in 52 9–10 mo-old infants, half at high familial risk (HR) for Autism Spectrum Disorders (ASD), who underwent an fMRI scan while listening to words spoken with alternating stress patterns on syllables. Relative to low risk (LR) infants, HR infants, in particular those showing the least rapid receptive language progress, had significantly lower noise-to-signal levels and increased symmetry. A comparison of patterns during a native language and a sleep scan revealed the most atypical ordering of signatures on the 3 tasks in a subset of HR infants, suggesting that the biological mechanism of language development is least acquisitive in those HR infants who go on to develop ASD in toddlerhood.52/52Secondary AnalysisShared
Multi-modal, computer assisted image interpretation for diagnosis of ASDThe ultimate goal of this project is to expand our computer-assisted diagnosis (CAD) system for autism to incorporate information from multiple imaging modalities. Using these data, as well as gene expression and clinical/behavioral reports, available from NDAR, we will refine and validate the system’s ability to characterize subtypes of ASD based upon the gross anatomy of cerebral cortex, white matter microstructure, and resting-state functional connectivity. The CAD system first segments structural MRI and constructs mathematical shape models of the pial and white matter surfaces of the cerebral cortex. BOLD and diffusion-weighted MRI are co-registered with the structural data to map the connectivity between the various Brodmann areas. Machine learning is used to develop a classifier to predict specific behavioral outcomes and genetic risk factors given a set of quantitative descriptors of cortical shape and connectivity.1/2Secondary AnalysisPrivate
* Data not on individual level
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