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1 Numbers reported are subjects by age
New Trial
New Project

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

Please select an experiment type below

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

The table search feature is case insensitive and targets the experiment id, experiment name and experiment type columns. The experiment id is searched only when the search term entered is a number, and filtered using a startsWith comparison. When the search term is not numeric the experiment name is used to filter the results.
SelectExperiment IdExperiment NameExperiment Type
Created On
475MB1-10 (CHOP)Omics06/07/2016
490Illumina Infinium PsychArray BeadChip AssayOmics07/07/2016
501PharmacoBOLD Resting StatefMRI07/27/2016
13Comparison of FI expression in Autistic and Neurotypical Homo SapiensOmics12/28/2010
18AGRE/Broad Affymetrix 5.0 Genotype ExperimentOmics01/06/2011
22Stitching PCR SequencingOmics02/14/2011
29Microarray family 03 (father, mother, sibling)Omics03/24/2011
37Standard paired-end sequencing of BCRsOmics04/19/2011
38Illumina Mate-Pair BCR sequencingOmics04/19/2011
39Custom Jumping LibrariesOmics04/19/2011
40Custom CapBPOmics04/19/2011
43Autism brain sample genotyping, IlluminaOmics05/16/2011
47ARRA Autism Sequencing Collaboration at Baylor. SOLiD 4 SystemOmics08/01/2011
53AGRE Omni1-quadOmics10/11/2011
59AGP genotypingOmics04/03/2012
60Ultradeep 454 sequencing of synaptic genes from postmortem cerebella of individuals with ASD and neurotypical controlsOmics06/23/2012
63Microemulsion PCR and Targeted Resequencing for Variant Detection in ASDOmics07/20/2012
76Whole Genome Sequencing in Autism FamiliesOmics01/03/2013
90Genotyped IAN SamplesOmics07/09/2013
91NJLAGS Axiom Genotyping ArrayOmics07/16/2013
93AGP genotyping (CNV)Omics09/06/2013
106Longitudinal Sleep Study. H20 200. Channel set 2EEG11/07/2013
107Longitudinal Sleep Study. H20 200. Channel set 3EEG11/07/2013
108Longitudinal Sleep Study. AURA 200EEG11/07/2013
105Longitudinal Sleep Study. H20 200. Channel set 1EEG11/07/2013
109Longitudinal Sleep Study. AURA 400EEG11/07/2013
116Gene Expression Analysis WG-6Omics01/07/2014
131Jeste Lab UCLA ACEii: Charlie Brown and Sesame Street - Project 1Eye Tracking02/27/2014
132Jeste Lab UCLA ACEii: Animacy - Project 1Eye Tracking02/27/2014
133Jeste Lab UCLA ACEii: Mom Stranger - Project 2Eye Tracking02/27/2014
134Jeste Lab UCLA ACEii: Face Emotion - Project 3Eye Tracking02/27/2014
151Candidate Gene Identification in familial AutismOmics06/09/2014
152NJLAGS Whole Genome SequencingOmics07/01/2014
154Math Autism Study - Vinod MenonfMRI07/15/2014
160syllable contrastEEG07/29/2014
167School-age naturalistic stimuliEye Tracking09/19/2014
44AGRE/Broad Affymetrix 5.0 Genotype ExperimentOmics06/27/2011
45Exome Sequencing of 20 Sporadic Cases of Autism Spectrum DisorderOmics07/15/2011
78MET GenotypesOmics03/18/2013
Collection - Add Experiment
Add Supporting Documentation
Select File

To add an existing Data Structure, enter its title in the search bar. If you need to request changes, select the indicator "No, it requires changes to meet research needs" after selecting the Structure, and upload the file with the request changes specific to the selected Data Structure. Your file should follow the Request Changes Procedure. If the Data Structure does not exist, select "Request New Data Structure" and upload the appropriate zip file.

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Collection Updated

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

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Collection Summary Collection Charts
Collection Title Collection Investigators Collection Description
The Autism Biomarkers Consortium for Clinical Trials
James McPartland 
The goal of this consortium is to establish tools that can be used as biomarkers and/or sensitive and reliable objective assays of social impairment in autism spectrum disorder (ASD) clinical trials. Specifically, we aim to accelerate the development of effective treatments for social impairment in ASD by validating (a) outcome measures that will be sensitive and reliable assessments of response to treatment and EEG and (b) eye-tracking (ET) biomarkers that can be used to reduce heterogeneity of samples via stratification, indicate early efficacy, and/or demonstrate target engagement. The consortium will conduct a naturalistic, longitudinal study of preschool (3-5 years) and school aged (6-11 years) children with ASD and typical development (TD) with IQ ranging from 50-115. Children will be assessed across three time points (T1: Baseline, T2: 6 weeks, T3: 24 weeks) using clinician, caregiver and lab-based (LB) measures of social impairment, along with a battery of conceptually related EEG and ET tasks and independent ratings of clinical status. This battery measures key facets of social-communication in ASD using well-validated paradigms appropriate for this developmental and cognitive range. Five Collaborating Implementation Sites ("Sites"), all highly experienced in multi-site collaborative clinical research using the methodologies proposed here in both typical and atypical development, will contribute equally to recruitment, screening, diagnosis, testing, and longitudinal assessment. The Data Coordinating Core (DCC) will provide a secure informatics infrastructure to streamline communication and data flow throughout the consortium to ensure organized, secure data management, quality control, and reliable upload to the National Database for Autism Research and NIH/NIMH Data Repositories. The Data Acquisition and Analysis Core (DAAC) will oversee consistent application of scientific standards and methodological rigor for standardized data collection, processing, and analytics. The Administrative Core will oversee the operations of the Sites, the DCC, and the DAAC to coordinate with federal and private partners in this cooperative agreement to: 1) Compare whether LB measures versus clinician and caregiver assessments of social impairment are more sensitive indicators of clinical status; 2) Evaluate whether this set of ET and EEG measures, individually or in combination, has potential utility as stratification biomarkers and/or sensitive and reliable measures of change in clinical trials, assessing viability in terms of: construct validity; test-retest reliability, consistency, and stability; discriminant validity ; convergent validity; and sensitivity to change; 3) Collect blood (DNA) samples from subjects and parents of ASD subjects for future genomic analyses and share raw, processed, and analyzed data to create a community resource accessible for use by all qualified investigators.
NIMH Data Archive
NIMH Repository & Genomics Resource (NRGR)
Funding Completed
Close Out
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NIH - Extramural None

QA-notification.txt Other Quality Assurance Notification Qualified Researchers
Protocol M6.0 2018.06.07 & Memo.pdf Methods ABC-CT Feasibility and Main Study Protocol Qualified Researchers
ABC-CT CLINICAL MOP_M1.9_version 14July2017.pdf Methods ABC-CT Feasibility and Main Study Clinical Manual of Procedure Qualified Researchers
ABC-CTDataManagementMOPv1.202012017.pdf Methods ABC-CT Feasibility and Main Study Data Management Manual of Procedure Qualified Researchers
ABC-CT_EEG_MOP_M2.0.pdf Methods ABC-CT Feasibility and Main Study EEG Manual of Procedure Qualified Researchers
ABC-CTETMOP4.0.5.pdf Methods ABC-CT Feasibility and Main Study Eye Tracking Manual of Procedure Qualified Researchers
CGI MOP_ M1_version 06SEP2016.pdf Methods ABC-CT Feasibility and Main Study CGI-SI Manual of Procedure Qualified Researchers
VT MOP v1.4; 9.8.2017.pdf Methods ABC-CT Feasibility and Main Study VT Manual of Procedure Qualified Researchers
Behavior Management_M1; 12SEP2016.pdf Methods ABC-CT Feasibility and Main Study Behavior Management MOP Qualified Researchers

U19MH108206-01 The Autism Biomarkers Consortium for Clinical Trials 07/01/2015 06/30/2020 1300 1366 YALE UNIVERSITY $29,161,446.00


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 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/nda/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

  • How does the NIMH Data Archive (NDA) determine which Permission Group data are submitted into?
    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.
  • How do I know when a NDA Collection has been created?
    When a Collection is created by NDA staff, an email notification will automatically be sent to the PI(s) of the grant(s) associated with the Collection to notify them.
  • Is a single grant number ever associated with more than one Collection?
    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.
  • Why is there sometimes more than one grant included in a 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).


  • Administrator Privilege
    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.
  • Collection Owner
    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.
  • Collection Phase
    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.
  • Collection Title
    An editable field with the title of the Collection, which is often the title of the grant associated with the Collection.
  • Grant
    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.
  • Supporting Documentation
    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.
  • NIH Research Initiative
    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.
  • Permission Group
    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.
  • Planned Enrollment
    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.
  • Actual Enrollment
    Number of human subjects enrolled in an NIH-funded clinical research study. The data is provided in annual progress reports.
  • NDA Collection
    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.
  • Data Use Limitations
    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.
  • Total Subjects Shared
    The total number of unique subjects for whom data have been shared and are available for users with permission to access data.
IDNameCreated DateStatusType
470ABC-CT ET05/25/2016ApprovedEye Tracking
472ABC-CT Resting06/03/2016ApprovedEEG
479ABC-CT Social/Nonsocial06/20/2016ApprovedEEG
480ABC-CT Biomotion06/20/2016ApprovedEEG
481ABC-CT Emotion06/20/2016ApprovedEEG
482ABC-CT EU AIMS Faces06/20/2016ApprovedEEG
483ABC-CT VEP06/20/2016ApprovedEEG
509ABC-CT Resting v208/18/2016ApprovedEEG
513ABC-CT ET: Main Study09/09/2016ApprovedEye Tracking
544ABC-CT Faces v212/13/2016ApprovedEEG
545ABC-CT VEP v212/13/2016ApprovedEEG
546ABC-CT Biomotion v212/13/2016ApprovedEEG
1229ABC-CT Faces v303/25/2019ApprovedEEG
1230ABC-CT VEP v303/25/2019ApprovedEEG
1231ABC-CT Biomotion v303/25/2019ApprovedEEG

NDA Help Center

Collection - Experiments

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

  • Can an Experiment be associated with more than one Collection?

    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.


  • Experiment Status
    An Experiment must be Approved before data using the associated Experiment_ID may be uploaded.
  • Experiment ID
    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.
A Developmental NEuroPSYchological Assessment (NEPSY-II) Clinical Assessments 434
ABC-CT Eye Tracking Derived Results Imaging 400
ACE Family Medical History Clinical Assessments 305
ACE Subject Medical History Clinical Assessments 305
Aberrant Behavior Checklist (ABC) - Community Clinical Assessments 438
Adverse Events Clinical Assessments 4
Autism Diagnostic Interview, Revised (ADI-R) Clinical Assessments 298
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 1 Clinical Assessments 11
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 2 Clinical Assessments 46
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 3 Clinical Assessments 386
Autism Impact Measure Clinical Assessments 437
BASC 3 Clinical Assessments 49
Child/Adolescent Symptom Inventory Clinical Assessments 430
Clinical Global Impression (CGI) Clinical Assessments 298
DAS-II: Differential Ability Scales 2nd Ed. School Age Clinical Assessments 361
DAS-II:Differential Ability Scales 2nd Ed. Early Years Clinical Assessments 139
Demographics Clinical Assessments 438
EEG Resting Eyes Calm Viewing Imaging 399
EEG Subject Files Imaging 436
Early Childhood Inventory Clinical Assessments 9
Event Related Potential - Visual Evoked Potential Imaging 399
Event Related Potential to Faces - Calm Viewing Imaging 399
Event Related Potential- Biomotion Imaging 399
Eye Tracking Subject-Experiment Imaging 440
Intervention History Clinical Assessments 436
Kaufman Assessment Battery for Children, Second Edition Clinical Assessments 9
LENA Data Model Form Clinical Assessments 47
Noldus Data Model Form Clinical Assessments 351
PDD Behavior Inventory (Parent) Clinical Assessments 438
Pediatric Quality of Life Inventory Clinical Assessments 50
Research Subject Clinical Assessments 438
Social Opportunities Questionnaire Clinical Assessments 50
Social Responsiveness Scale (SRS) Clinical Assessments 438
Social Skills Improvement System Parent Scale Clinical Assessments 50
Study Completion Questionnaire Clinical Assessments 472
Video Tracking Derived Results Imaging 315
Vineland 3 Clinical Assessments 398
Vineland-II - Survey Form (2005) Clinical Assessments 50

NDA Help Center

Collection - Shared Data

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

  • How will I know if another researcher uses data that I shared through the NIMH Data Archive (NDA)?
    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.
  • Can I get a supplement to share data from a completed research project?
    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.
  • Can I get a supplement to share data from a research project that is still ongoing?
    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.


  • Data Structure
    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://nda.nih.gov/general-query.html?q=query=data-structure
  • Data Type
    A grouping of data by similar characteristics such as Clinical Assessments, Omics, or Neurosignal data.
  • Shared
    The term 'Shared' generally means available to others; however, there are some slightly different meanings based on what is Shared. A Shared NDA Study is viewable and searchable publicly regardless of the user's role or whether the user has an NDA account. A Shared NDA Study does not necessarily mean that data 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.

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


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
38430386Create StudyAutistic Individuals Do Not Alter Visual Processing Strategy During Encoding Versus Recognition of Faces: A Hidden Markov Modeling Approach.Journal of autism and developmental disordersGriffin, Jason W; Webb, Sara Jane; Keehn, Brandon; Dawson, Geraldine; McPartland, James CMarch 2, 2024Not Determined
37749934Create StudyThe Selective Social Attention task in children with autism spectrum disorder: Results from the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) feasibility study.Autism research : official journal of the International Society for Autism ResearchShic, Frederick; Barney, Erin C; Naples, Adam J; Dommer, Kelsey J; Chang, Shou An; Li, Beibin; McAllister, Takumi; Atyabi, Adham; Wang, Quan; Bernier, Raphael; Dawson, Geraldine; Dziura, James; Faja, Susan; Jeste, Shafali Spurling; Murias, Michael; Johnson, Scott P; Sabatos-DeVito, Maura; Helleman, Gerhard; Senturk, Damla; Sugar, Catherine A; Webb, Sara Jane; McPartland, James C; Chawarska, Katarzyna; Autism Biomarkers Consortium for Clinical TrialsNovember 1, 2023Not Determined
37638733Create StudyDevelopment of peak alpha frequency reflects a distinct trajectory of neural maturation in autistic children.Autism research : official journal of the International Society for Autism ResearchFinn, Caroline E; Han, Gloria T; Naples, Adam J; Wolf, Julie M; McPartland, James CNovember 1, 2023Not Determined
37405787Create StudyInvestigating the Face Inversion Effect in Autism Across Behavioral and Neural Measures of Face Processing: A Systematic Review and Bayesian Meta-Analysis.JAMA psychiatryGriffin, Jason W; Azu, Margaret A; Cramer-Benjamin, Sophie; Franke, Cassandra J; Herman, Nicole; Iqbal, Reeda; Keifer, Cara M; Rosenthal, Lindsey H; McPartland, James COctober 1, 2023Not Determined
37077750Create StudyA functional model for studying common trends across trial time in eye tracking experiments.Statistics in biosciencesDong, Mingfei; Telesca, Donatello; Sugar, Catherine; Shic, Frederick; Naples, Adam; Johnson, Scott P; Li, Beibin; Atyabi, Adham; Xie, Minhang; Webb, Sara J; Jeste, Shafali; Faja, Susan; Levin, April R; Dawson, Geraldine; McPartland, James C; Şentürk, Damla; Autism Biomarkers Consortium for Clinical TrialsApril 1, 2023Not Determined
36943905Create StudyNeural mechanisms of language development in infancy.Infancy : the official journal of the International Society on Infant StudiesHuberty, Scott; O'Reilly, Christian; Carter Leno, Virginia; Steiman, Mandy; Webb, Sara; Elsabbagh, Mayada; BASIS TeamJanuary 1, 2023Not Determined
36929131Create StudyEvaluation of clinical assessments of social abilities for use in autism clinical trials by the autism biomarkers consortium for clinical trials.Autism research : official journal of the International Society for Autism ResearchFaja, Susan; Sabatos-DeVito, Maura; Sridhar, Aksheya; Kuhn, Jocelyn L; Nikolaeva, Julia I; Sugar, Catherine A; Webb, Sara Jane; Bernier, Raphael A; Sikich, Linmarie; Hellemann, Gerhard; Senturk, Damla; Naples, Adam J; Shic, Frederick; Levin, April R; Seow, Helen A; Dziura, James D; Jeste, Shafali S; Chawarska, Katarzyna; Nelson 3rd, Charles A; Dawson, Geraldine; McPartland, James C; Autism Biomarkers Consortium for Clinical TrialsMay 1, 2023Not Determined
36568688Create StudyElectrophysiological Studies of Reception of Facial Communication in Autism Spectrum Disorder and Schizophrenia.Review journal of autism and developmental disordersLevy, Emily J; Foss-Feig, Jennifer; Isenstein, Emily L; Srihari, Vinod; Anticevic, Alan; Naples, Adam J; McPartland, James CDecember 1, 2022Not Determined
36350848Create StudyNeural correlates of eye contact and social function in autism spectrum disorder.PloS oneHirsch, Joy; Zhang, Xian; Noah, J Adam; Dravida, Swethasri; Naples, Adam; Tiede, Mark; Wolf, Julie M; McPartland, James CJanuary 1, 2022Not Determined
36309762Create StudyPredictability modulates neural response to eye contact in ASD.Molecular autismNaples, Adam J; Foss-Feig, Jennifer H; Wolf, Julie M; Srihari, Vinod H; McPartland, James COctober 29, 2022Not Determined
36086805Create StudyConcomitant medication use in children with autism spectrum disorder: Data from the Autism Biomarkers Consortium for Clinical Trials.Autism : the international journal of research and practiceShurtz, Logan; Schwartz, Chloe; DiStefano, Charlotte; McPartland, James C; Levin, April R; Dawson, Geraldine; Kleinhans, Natalia M; Faja, Susan; Webb, Sara J; Shic, Frederick; Naples, Adam J; Seow, Helen; Bernier, Raphael A; Chawarska, Katarzyna; Sugar, Catherine A; Dziura, James; Senturk, Damla; Santhosh, Megha; Jeste, Shafali SMay 1, 2023Not Determined
36000217Create StudyThe Autism Biomarkers Consortium for Clinical Trials: Initial Evaluation of a Battery of Candidate EEG Biomarkers.The American journal of psychiatryWebb, Sara Jane; Naples, Adam J; Levin, April R; Hellemann, Gerhard; Borland, Heather; Benton, Jessica; Carlos, Carter; McAllister, Takumi; Santhosh, Megha; Seow, Helen; Atyabi, Adham; Bernier, Raphael; Chawarska, Katarzyna; Dawson, Geraldine; Dziura, James; Faja, Susan; Jeste, Shafali; Murias, Michael; Nelson, Charles A; Sabatos-DeVito, Maura; Senturk, Damla; Shic, Frederick; Sugar, Catherine A; McPartland, James CJanuary 1, 2023Not Determined
35821544Create StudyBrief Report: A Specialized Fitness Program for Individuals with Autism Spectrum Disorder Benefits Physical, Behavioral, and Emotional Outcomes.Journal of autism and developmental disordersJackson, Scott L J; Abel, Emily A; Reimer, Shara; McPartland, James CJuly 11, 2022Not Determined
35752729Create StudyDistinct Symptom Network Structure and Shared Central Social Communication Symptomatology in Autism and Schizophrenia: A Bayesian Network Analysis.Journal of autism and developmental disordersHan, Gloria T; Trevisan, Dominic A; Foss-Feig, Jennifer; Srihari, Vinod; McPartland, James CSeptember 1, 2023Not Determined
35690495Create StudyFunctional Connectome-Based Predictive Modeling in Autism.Biological psychiatryHorien, Corey; Floris, Dorothea L; Greene, Abigail S; Noble, Stephanie; Rolison, Max; Tejavibulya, Link; O'Connor, David; McPartland, James C; Scheinost, Dustin; Chawarska, Katarzyna; Lake, Evelyn M R; Constable, R ToddOctober 15, 2022Not Determined
35657448Create StudyAttention Allocation During Exploration of Visual Arrays in ASD: Results from the ABC-CT Feasibility Study.Journal of autism and developmental disordersTsang, Tawny; Naples, Adam J; Barney, Erin C; Xie, Minhang; Bernier, Raphael; Dawson, Geraldine; Dziura, James; Faja, Susan; Jeste, Shafali Spurling; McPartland, James C; Nelson, Charles A; Murias, Michael; Seow, Helen; Sugar, Catherine; Webb, Sara J; Shic, Frederick; Johnson, Scott PAugust 1, 2023Not Determined
35635067Create StudyAssociations between sleep problems and domains relevant to daytime functioning and clinical symptomatology in autism: A meta-analysis.Autism research : official journal of the International Society for Autism ResearchHan, Gloria T; Trevisan, Dominic A; Abel, Emily A; Cummings, Elise M; Carlos, Carter; Bagdasarov, Armen; Kala, Shashwat; Parker, Termara; Canapari, Craig; McPartland, James CJuly 1, 2022Not Determined
35616816Create StudyBrief Report: Exploratory Evaluation of Clinical Features Associated with Suicidal Ideation in Youth with Autism Spectrum Disorder.Journal of autism and developmental disordersEllison, Kimberly S; Jarzabek, Elzbieta; Jackson, Scott L J; Naples, Adam; McPartland, James CFebruary 1, 2024Not Determined
35615454Create StudyIdentifying Age Based Maturation in the ERP Response to Faces in Children With Autism: Implications for Developing Biomarkers for Use in Clinical Trials.Frontiers in psychiatryWebb, Sara Jane; Emerman, Iris; Sugar, Catherine; Senturk, Damla; Naples, Adam J; Faja, Susan; Benton, Jessica; Borland, Heather; Carlos, Carter; Levin, April R; McAllister, Takumi; Santhosh, Megha; Bernier, Raphael A; Chawarska, Katarzyna; Dawson, Geraldine; Dziura, James; Jeste, Shafali; Kleinhans, Natalia; Murias, Michael; Sabatos-DeVito, Maura; Shic, Frederick; McPartland, James C; Autism Biomarkers Consortium for Clinical TrialsJanuary 1, 2022Not Determined
35611602Create StudyMultilevel hybrid principal components analysis for region-referenced functional electroencephalography data.Statistics in medicineCampos, Emilie; Wolfe Scheffler, Aaron; Telesca, Donatello; Sugar, Catherine; DiStefano, Charlotte; Jeste, Shafali; Levin, April R; Naples, Adam; Webb, Sara J; Shic, Frederick; Dawson, Geraldine; Faja, Susan; McPartland, James C; Şentürk, Damla; Autism Biomarkers Consortium for Clinical TrialsAugust 30, 2022Not Determined
35444715Create StudyPatterns of Intervention Utilization Among School-Aged Children with Autism Spectrum Disorder: Findings from a Multi-Site Research Consortium.Research in autism spectrum disordersSridhar, Aksheya; Kuhn, Jocelyn; Faja, Susan; Sabatos-DeVito, Maura; Nikolaeva, Julia I; Dawson, Geraldine; Nelson, Charles A; Webb, Sara J; Bernier, Raphael; Jeste, Shafali; Chawarska, Katarzyna; Sugar, Catherine A; Shic, Frederick; Naples, Adam; Dziura, James; McPartland, James C; ABC-CT ConsortiumJune 1, 2022Not Determined
35313957Create StudyThe autism biomarkers consortium for clinical trials: evaluation of a battery of candidate eye-tracking biomarkers for use in autism clinical trials.Molecular autismShic, Frederick; Naples, Adam J; Barney, Erin C; Chang, Shou An; Li, Beibin; McAllister, Takumi; Kim, Minah; Dommer, Kelsey J; Hasselmo, Simone; Atyabi, Adham; Wang, Quan; Helleman, Gerhard; Levin, April R; Seow, Helen; Bernier, Raphael; Charwaska, Katarzyna; Dawson, Geraldine; Dziura, James; Faja, Susan; Jeste, Shafali Spurling; Johnson, Scott P; Murias, Michael; Nelson, Charles A; Sabatos-DeVito, Maura; Senturk, Damla; Sugar, Catherine A; Webb, Sara J; McPartland, James CMarch 21, 2022Not Determined
34180705Create StudyFace perception predicts affective theory of mind in autism spectrum disorder but not schizophrenia or typical development.Journal of abnormal psychologyAltschuler, Melody R; Trevisan, Dominic A; Wolf, Julie M; Naples, Adam J; Foss-Feig, Jennifer H; Srihari, Vinod H; McPartland, James CMay 1, 2021Not Determined
34043128Create StudyLooking Back at the Next 40 Years of ASD Neuroscience Research.Journal of autism and developmental disordersMcPartland, James C; Lerner, Matthew D; Bhat, Anjana; Clarkson, Tessa; Jack, Allison; Koohsari, Sheida; Matuskey, David; McQuaid, Goldie A; Su, Wan-Chun; Trevisan, Dominic ADecember 1, 2021Not Determined
33955195Create StudyAssociation between spectral electroencephalography power and autism risk and diagnosis in early development.Autism research : official journal of the International Society for Autism ResearchHuberty, Scott; Carter Leno, Virginia; van Noordt, Stefon J R; Bedford, Rachael; Pickles, Andrew; Desjardins, James A; Webb, Sara Jane; BASIS Team; Elsabbagh, MayadaJuly 1, 2021Not Determined
33934921Create StudyRefining biomarker evaluation in ASD.European neuropsychopharmacology : the journal of the European College of NeuropsychopharmacologyMcPartland, James CJuly 1, 2021Not Determined
33882266Create StudyModeling temporal dynamics of face processing in youth and adults.Social neuroscienceHudac, Caitlin M; Naples, Adam; DesChamps, Trent D; Coffman, Marika C; Kresse, Anna; Ward, Tracey; Mukerji, Cora; Aaronson, Benjamin; Faja, Susan; McPartland, James C; Bernier, RaphaelAugust 1, 2021Not Determined
33749161Create StudyThe N170 event-related potential reflects delayed neural response to faces when visual attention is directed to the eyes in youths with ASD.Autism research : official journal of the International Society for Autism ResearchParker, Termara C; Crowley, Michael J; Naples, Adam J; Rolison, Max J; Wu, Jia; Trapani, Julie A; McPartland, James CJuly 1, 2021Not Determined
33714056Create Study12-Month peak alpha frequency is a correlate but not a longitudinal predictor of non-verbal cognitive abilities in infants at low and high risk for autism spectrum disorder.Developmental cognitive neuroscienceCarter Leno, Virginia; Pickles, Andrew; van Noordt, Stefon; Huberty, Scott; Desjardins, James; Webb, Sara Jane; Elsabbagh, Mayada; BASIS TeamApril 1, 2021Not Determined
33073404Create StudyContrast Is in the Eye of the Beholder: Infelicitous Beat Gesture Increases Cognitive Load During Online Spoken Discourse Comprehension.Cognitive scienceMorett, Laura M; Roche, Jennifer M; Fraundorf, Scott H; McPartland, James COctober 1, 2020Not Determined
32818527Create StudyN400 amplitude, latency, and variability reflect temporal integration of beat gesture and pitch accent during language processing.Brain researchMorett, Laura M; Landi, Nicole; Irwin, Julia; McPartland, James CNovember 15, 2020Not Determined
32595540Create StudyAutism Spectrum Disorder and Schizophrenia Are Better Differentiated by Positive Symptoms Than Negative Symptoms.Frontiers in psychiatryTrevisan, Dominic A; Foss-Feig, Jennifer H; Naples, Adam J; Srihari, Vinod; Anticevic, Alan; McPartland, James CJanuary 1, 2020Not Determined
32425762Create StudyDay-to-Day Test-Retest Reliability of EEG Profiles in Children With Autism Spectrum Disorder and Typical Development.Frontiers in integrative neuroscienceLevin, April R; Naples, Adam J; Scheffler, Aaron Wolfe; Webb, Sara J; Shic, Frederick; Sugar, Catherine A; Murias, Michael; Bernier, Raphael A; Chawarska, Katarzyna; Dawson, Geraldine; Faja, Susan; Jeste, Shafali; Nelson, Charles A; McPartland, James C; Şentürk, DamlaJanuary 1, 2020Not Determined
32380941Create StudyEEG-IP: an international infant EEG data integration platform for the study of risk and resilience in autism and related conditions.Molecular medicine (Cambridge, Mass.)van Noordt, Stefon; Desjardins, James A; Huberty, Scott; Abou-Abbas, Lina; Webb, Sara Jane; Levin, April R; Segalowitz, Sidney J; Evans, Alan C; Elsabbagh, MayadaMay 2020Not Determined
32362842Create StudyThe Presence of Another Person Influences Oscillatory Cortical Dynamics During Dual Brain EEG Recording.Frontiers in psychiatryRolison, Max J; Naples, Adam J; Rutherford, Helena J V; McPartland, James CJanuary 1, 2020Not Determined
32346363Create StudyThe Autism Biomarkers Consortium for Clinical Trials (ABC-CT): Scientific Context, Study Design, and Progress Toward Biomarker Qualification.Frontiers in integrative neuroscienceMcPartland, James C; Bernier, Raphael A; Jeste, Shafali S; Dawson, Geraldine; Nelson, Charles A; Chawarska, Katarzyna; Earl, Rachel; Faja, Susan; Johnson, Scott P; Sikich, Linmarie; Brandt, Cynthia A; Dziura, James D; Rozenblit, Leon; Hellemann, Gerhard; Levin, April R; Murias, Michael; Naples, Adam J; Platt, Michael L; Sabatos-DeVito, Maura; Shic, Frederick; Senturk, Damla; Sugar, Catherine A; Webb, Sara J; Autism Biomarkers Consortium for Clinical TrialsJanuary 1, 2020Not Determined
32116606Create StudyReal-Time Eye-to-Eye Contact Is Associated With Cross-Brain Neural Coupling in Angular Gyrus.Frontiers in human neuroscienceNoah, J Adam; Zhang, Xian; Dravida, Swethasri; Ono, Yumie; Naples, Adam; McPartland, James C; Hirsch, JoyJanuary 1, 2020Not Determined
32116579Create StudyBiomarker Acquisition and Quality Control for Multi-Site Studies: The Autism Biomarkers Consortium for Clinical Trials.Frontiers in integrative neuroscienceWebb, Sara Jane; Shic, Frederick; Murias, Michael; Sugar, Catherine A; Naples, Adam J; Barney, Erin; Borland, Heather; Hellemann, Gerhard; Johnson, Scott; Kim, Minah; Levin, April R; Sabatos-DeVito, Maura; Santhosh, Megha; Senturk, Damla; Dziura, James; Bernier, Raphael A; Chawarska, Katarzyna; Dawson, Geraldine; Faja, Susan; Jeste, Shafali; McPartland, James; Autism Biomarkers Consortium for Clinical TrialsJanuary 1, 2019Not Determined
32034650Create StudyLight-Adapted Electroretinogram Differences in Autism Spectrum Disorder.Journal of autism and developmental disordersConstable, Paul A; Ritvo, Edward R; Ritvo, Ariella R; Lee, Irene O; McNair, Morgan L; Stahl, Dylan; Sowden, Jane; Quinn, Stephen; Skuse, David H; Thompson, Dorothy A; McPartland, James CAugust 1, 2020Not 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
30556607Create StudyAutism's existential crisis: a reflection on Livingston et al. (2018).Journal of child psychology and psychiatry, and allied disciplinesMcpartland JCJanuary 2019Not Determined
30391290Create StudyReply to: Can the N170 Be Used as an Electrophysiological Biomarker Indexing Face Processing Difficulties in Autism Spectrum Disorder?Biological psychiatry. Cognitive neuroscience and neuroimagingKang, Erin; McPartland, James C; Keifer, Cara M; Foss-Feig, Jennifer H; Levy, Emily J; Lerner, Matthew DMarch 2019Not Determined
30092916Create StudyAtypicality of the N170 Event-Related Potential in Autism Spectrum Disorder: A Meta-analysis.Biological psychiatry. Cognitive neuroscience and neuroimagingKang, Erin; Keifer, Cara M; Levy, Emily J; Foss-Feig, Jennifer H; McPartland, James C; Lerner, Matthew DAugust 2018Not Relevant
29436853Create StudyElectrophysiological response during auditory gap detection: Biomarker for sensory and communication alterations in autism spectrum disorder?Developmental neuropsychologyFoss-Feig, Jennifer H; Stavropoulos, Katherine K M; McPartland, James C; Wallace, Mark T; Stone, Wendy L; Key, Alexandra PJanuary 1, 2018Not Determined
28695438Create StudyDeveloping Clinically Practicable Biomarkers for Autism Spectrum Disorder.Journal of autism and developmental disordersMcPartland, James CSeptember 2017Not Relevant
28434615Create StudySearching for Cross-Diagnostic Convergence: Neural Mechanisms Governing Excitation and Inhibition Balance in Schizophrenia and Autism Spectrum Disorders.Biological psychiatryFoss-Feig, Jennifer H; Adkinson, Brendan D; Ji, Jie Lisa; Yang, Genevieve; Srihari, Vinod H; McPartland, James C; Krystal, John H; Murray, John D; Anticevic, AlanMay 15, 2017Not Determined
28396215Create StudyEvent-related potentials index neural response to eye contact.Biological psychologyNaples, Adam J; Wu, Jia; Mayes, Linda C; McPartland, James CJuly 1, 2017Not Determined
28214131Create StudySocial Decision-Making and the Brain: A Comparative Perspective.Trends in cognitive sciencesTremblay, Sébastien; Sharika, K M; Platt, Michael LApril 2017Not Determined
28009726Create StudyThe emergence of autism spectrum disorder: insights gained from studies of brain and behaviour in high-risk infants.Current opinion in psychiatryVarcin, Kandice J; Jeste, Shafali SMarch 2017Not Relevant
27750521Create StudyAutistic traits modulate conscious and nonconscious face perception.Social neuroscienceStavropoulos, Katherine K M; Viktorinova, Michaela; Naples, Adam; Foss-Feig, Jennifer; McPartland, James CFebruary 1, 2018Not Determined
27015716Create StudyEye Tracking as a Behavioral Biomarker for Psychiatric Conditions: The Road Ahead.Journal of the American Academy of Child and Adolescent PsychiatryShic, FrederickApril 2016Not Relevant
26886246Create StudyFace perception and learning in autism spectrum disorders.Quarterly journal of experimental psychology (2006)Webb, Sara Jane; Neuhaus, Emily; Faja, SusanMay 2017Not Determined
26844621Create StudyConsiderations in biomarker development for neurodevelopmental disorders.Current opinion in neurologyMcpartland JCApril 2016Not Relevant
26471250Create StudyCommon and distinct modulation of electrophysiological indices of feedback processing by autistic and psychopathic traits.Social neuroscienceCarter Leno, Virginia; Naples, Adam; Cox, Anthony; Rutherford, Helena; McPartland, James CJanuary 1, 2016Not Determined

NDA Help Center

Collection - Publications

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

  • How can I determine if a publication is relevant?
    Publications are considered relevant to a collection when the data shared is directly related to the project or collection.
  • Where does the NDA get the publications?
    PubMed, an online library containing journals, articles, and medical research. Sponsored by NiH and National Library of Medicine (NLM).


  • Create Study
    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.
  • Not Determined Publication
    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.
  • Not Relevant Publication
    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
    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.
  • PubMed ID
    The PUBMed ID is the unique ID number for the publication as recorded in the PubMed database.
  • Relevant Publication
    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.
Data Expected List: Mandatory Data Structures

These data structures are mandatory for your NDA Collection. Please update the Targeted Enrollment number to accurately represent the number of subjects you expect to submit for the entire study.

For NIMH HIV-related research that involves human research participants: Select the dictionary or dictionaries most appropriate for your research. If your research does not require all three data dictionaries, just ignore the ones you do not need. There is no need to delete extra data dictionaries from your NDA Collection. You can adjust the Targeted Enrollment column in the Data Expected tab to “0” for those unnecessary data dictionaries. At least one of the three data dictionaries must have a non-zero value.

Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
Research Subject and Pedigree info icon
To create your project's Data Expected list, use the "+New Data Expected" to add or request existing structures and to request new Data Structures that are not in the NDA Data Dictionary.

If the Structure you need already exists, locate it and specify your dates and enrollment when adding it to your Data Expected list. If you require changes to the Structure you need, select the indicator stating "No, it requires changes to meet research needs," and upload a file containing your requested changes.

If the structure you need is not yet defined in the Data Dictionary, you can select "Upload Definition" and attach the necessary materials to request its creation.

When selecting the expected dates for your data, make sure to follow the standard Data Sharing Regimen and choose dates within the date ranges that correspond to your project start and end dates.

Please visit the Completing Your Data Expected Tutorial for more information.
Data Expected List: Data Structures per Research Aims

These data structures are specific to your research aims and should list all data structures in which data will be collected and submitted for this NDA Collection. Please update the Targeted Enrollment number to accurately represent the number of subjects you expect to submit for the entire study.

Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
ABC Community info icon
ADOS info icon
ADI-R info icon
PDD Behavior Inventory (PDDBI) info icon
Medical History info icon
Eye Tracking info icon
Social Responsiveness Scale (SRS) info icon
Child and Adolescent Symptom Inventory (CASI) info icon
Demographics info icon
Clinical Global Impression (CGI) info icon
Behavior Assessment System for Children (BASC) info icon
Social Skills Improvement System (SSIS) info icon
Quality of Life Assessment info icon
DAS-II: Differential Ability Scales info icon
Intervention History info icon
NEPSY info icon
Early Childhood Inventory info icon
Adverse Event (AE) and Serious Adverse Event (SAE) info icon
Noldus Tools info icon
Vineland (Parent and Caregiver) info icon
Autism Impact Measure (AIM) info icon
EEG info icon
Social Opportunities Questionnaire info icon
Kaufman Assessment Battery for Children, Second Edition info icon
LENA Tools info icon
ABC-CT Derived Results - Eye Tracking info icon
ABC-CT Derived Results - ERP Visual Evoked Potential info icon
ABC-CT Derived Results - ERP Biomotion info icon
ABC-CT Derived Results - EEG info icon
Study Completion info icon
ABC-CT Derived Results - Video Tracking info icon
ABC-CT Derived Results - ERP Faces info icon
Structure not yet defined
No Status history for this Data Expected has been recorded yet

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.

Researchers who are starting their project need to update their Data Expected list to include all the Data Structures they are collecting under their grant and set their initial submission and sharing schedule according to the NDA Data Sharing Regimen.

To add existing Data Structures from the Data Dictionary, to request new Data Structure that are not in the Dictionary, or to request changes to existing Data Structures, click "+New Data Expected".

For step-by-step instructions on how to add existing Data Structures, request changes to an existing Structure, or request a new Data Structure, please visit the Completing Your Data Expected Tutorial.

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

  • What is an NDA Data Structure?
    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.
  • What is the NDA Data Dictionary?
    The NDA Data Dictionary is comprised of electronic definitions known as Data Structures.


  • Analyzed Data
    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.
  • Data Item
    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.
  • Data Structure
    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://nda.nih.gov/general-query.html?q=query=data-structure
  • Data Structure Category
    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).
  • Data Structure Group
    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.
  • Evaluated Data
    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 Data
    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 Share Date
    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 Date
    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.
  • Research Subject and Pedigree
    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.
  • Submission Cycle
    The NDA has two Submission Cycles per year - January 15 and July 15.
  • Submission Exemption
    An interface to notify NDA that data may not be submitted during the upcoming/current submission cycle.

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

Associated Studies

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

Study NameAbstractCollection/Study SubjectsData UsageState
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.438/17423Secondary AnalysisShared
Prognostic early snapshot stratification of autism based on adaptive functioningA major goal of precision medicine is to predict prognosis based on individualized information at the earliest possible points in development. Using early snapshots of adaptive functioning and unsupervised data- driven discovery methods, we uncover highly stable early autism subtypes that yield information relevant to later prognosis. Data from the National Institute of Mental Health Data Archive (NDA) (n = 1,098) was used to uncover three early subtypes (<72 months) that generalize with 96% accuracy. Outcome data from NDA (n = 2,561; mean age, 13 years) also reproducibly clusters into three subtypes with 99% generalization accuracy. Early snapshot subtypes predict developmental trajectories in non-verbal cognitive, language and motor domains and are predictive of membership in different adaptive functioning outcome subtypes. Robust and prognosis- relevant subtyping of autism based on early snapshots of adaptive functioning may aid future research work via prediction of these subtypes with our reproducible stratification model.265/3517Secondary AnalysisShared
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. 66/3382Secondary AnalysisShared
Imbalanced social-communicative and restricted repetitive behavior subtypes in autism spectrum disorder exhibit different neural circuitrySocial-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97–99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.235/1708Secondary AnalysisShared
Investigating possible biomarkers of autism in resting EEGThere are no clinically useful biomarkers of autism spectrum disorder (ASD). Electroencephalogram (EEG) can measure ongoing brain dynamics using cheap and widely available technology and is minimally invasive. As such, any measurement drived from EEG that is capable of serving as a biomarker for ASD would be hugely beneficial. Previous research has been conflicting and a large list of EEG measures have been suggested. 297/771Secondary 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%. 51/756Secondary AnalysisShared
Development of EEG dynamics throughout the lifespanCombining data from across several datasets available on the NIMH data repository, multiple metrics of EEG dynamics were examined in a large cross sectional sample of healthy participants from across the lifespan. The goal was to examine changes in brain dynamics that occur across development. 108/551Secondary AnalysisShared
Face-processing performance is an independent predictor of social affect as measured by the Autism Diagnostic Observation Schedule across large-scale datasetsFace-processing deficits, while not required for the diagnosis of Autism Spectrum Disorder (ASD), have been associated with impaired social skills—a core feature of ASD; however, the strength and prevalence of this relationship remains unclear. Across 445 participants from the NIMH Data Archive, we examined the relationship between Benton Face Recognition Test (BFRT) performance and Autism Diagnostic Observation Schedule-Social Affect (ADOS-SA) scores. Lower BFRT scores (worse face-processing performance) were associated with higher ADOS-SA scores (higher ASD severity)–a relationship that held after controlling for other factors associated with face processing, i.e., age, sex, and IQ. These findings underscore the utility of face discrimination, not just recognition of facial emotion, as a key covariate for the severity of symptoms that characterize ASD.2/445Secondary AnalysisShared
comparing EEG metrics during eyes closed versus eyes open rest in autismUnderstanding the complex relationship between brain dynamics and mental disorders has proved difficult. Sample sizes have often been small, and brain dynamics have often been evaluated in only one state. Here, data obtained from the NIMH data archive were used to create a sample of 395 individuals with both eyes open and eyes closed resting state EEG data. All data were submitted to a standard pipeline to extract power spectra, peak alpha frequency, the slope of the 1/f curve, multi scale sample entropy, phase amplitude coupling, and intersite phase clustering. These data along with the survey data collected at the time of data collection form a valuable resource for interogating the relationship between brain state changes and autism diagnosis.3/336Secondary AnalysisShared
Word Learning and Word FeaturesVocabulary composition and word-learning biases are closely interrelated in typical development. Learning new words involves attending to certain properties to facilitate word learning. Such word-learning biases are influenced by perceptually and conceptually salient word features, including high imageability, concreteness, and iconicity. This study examined the association of vocabulary knowledge and word features in young children with ASD (n = 280) and typically developing (TD) toddlers (n = 1,054). Secondary analyses were conducted using data from the National Database for Autism Research and the Wordbank database. Expressive vocabulary was measured using the MacArthur-Bates Communicative Development Inventory. Although the trajectories for concreteness, iconicity, and imageability are similar between children with ASD and TD toddlers, divergences were observed. Differences in imageability are seen early but resolve to a common trajectory; differences in iconicity are small but consistent; and differences in concreteness only emerge after both groups reach a simultaneous peak, before converging again. This study reports unique information about the nonlinear growth patterns associated with each word feature for and distinctions in these growth patterns between the groups.1/280Primary AnalysisShared
Examining the Shape Bias in Young Autistic Children: A Vocabulary Composition AnalysisShape is a salient object property and one of the first that children use to categorize objects under one label. Colunga and Sims (2017) suggest that noun vocabulary composition and word learning biases are closely interrelated in typical development. The current study examined the association between noun vocabulary knowledge and perceptual word features, specifically shape and material features. Participants included 249 autistic children and 1,245 non-autistic toddlers who were matched on expressive noun vocabulary size and gender. Nouns were categorized using the Samuelson and Smith (1999) noun feature database. A simple group comparison revealed no group differences in shape bias; both groups evidenced developing noun vocabularies that favored shape+solid and nonsolid+material nouns. However, the trajectory of evidence of shape bias as a function of vocabulary size differed between the groups, with autistic children demonstrating a reduced shape-bias initially. Future work should examine how children’s learning biases shift over development and whether the shape bias promotes lexical development to the same degree across groups.1/249Secondary AnalysisShared
Semantic modeling 2023Although it is well documented that children with ASD are slower to develop their lexicons, we still have a limited understanding of the structure of early lexical knowledge in children with ASD. The current study uses network analysis and differential item functioning anlaysis to examine the structure of semantic knowledge, which may provide insight into the learning processes that influence early word learning.1/208Secondary AnalysisShared
Semantic Network ModelingAlthough it is well documented that children with ASD are slower to develop their lexicons, we still have a limited understanding of the structure of early lexical knowledge in children with ASD. The current study uses network analysis to examine the structure of semantic knowledge, which may provide insight into the learning processes that influence early word learning.1/200Secondary AnalysisShared
Semantic Network Modeling in Young Autistic ChildrenBackground: Most young autistic children have delayed vocabulary growth relative to their non-autistic peers. Additionally, previous studies have revealed that autistic children are less likely to encode associated features of novel objects, suggesting inefficient encoding or different processes for acquiring semantic information about words. Recent network analyses of vocabulary growth revealed important relationships between early vocabulary acquisition and the structure of the sematic environment. Methods: We studied the expressive vocabularies of 970 non-autistic toddlers (Mage = 20.82 months) and 194 autistic children (Mage = 54.58 months) in two studies. The groups were vocabulary-matched (words produced: MAutistic = 213.60, MNon-autistic = 213.72). In study 1, we estimated their trajectories of semantic development using network analyses. Network structure was based on child-oriented adult-generated word associations. We compared child semantic networks according to indegree, average shortest path length, and clustering coefficient (features that holistically contribute to well-connected network structure). Then, in study 2, we attempted to relate vocabulary-level effects to word-level learning biases. Results: Study 1 revealed that autistic and non-autistic children are sensitive to the structure of their semantic environment. Both groups demonstrated nonlinear vocabulary trajectories that differed from random acquisition networks. Despite similarities, group differences were observed for each network metric. Differences were most pronounced for clustering coefficient (how closely connected groups of words are), with earlier peaks for autistic children. Study 2 demonstrated that many words differ in their expected vocabulary size of acquisition. Conclusions: Group differences at the vocabulary- and word-levels indicate that, although autistic children are learning from their semantic environment, they may be processing their semantic environment differently. These deviations indicate that autistic children have distinctive learning biases that may align with core autism features. 1/194Secondary AnalysisShared
Cortico-Basal Ganglia Brain Structure and Links to Restricted, Repetitive Behavior in Autism Spectrum DisorderRestricted repetitive behavior (RRB) is one of two criteria domains required for the diagnosis of autism spectrum disorder (ASD). Neuroimaging is widely used to study brain alterations associated with ASD and the domain of social and communication deficits, but there has been less work regarding alterations associated with RRB. In this study we utilized neuroimaging data available from the National Database for Autism Research to assess volume in the basal ganglia and cerebellum, as well as microstructure in basal ganglia and cerebellar white matter tracts in ASD. We also investigated whether these measures differed between males and females with ASD, and how these factors correlated with clinical measures of RRB from the same individuals. We found that individuals with ASD had significant differences in free-water corrected fractional anisotropy (FAT) and free-water in cortico-basal ganglia white matter tracts, but that these measures did not differ between males versus females with ASD. Moreover, both FAT and free-water in these tracts were significantly correlated with measures of RRB. Despite no differences in volumetric measures in basal ganglia and cerebellum, these findings suggest the links between RRB and brain structure are within specific cortico-basal ganglia white matter tracts.2/192Secondary AnalysisShared
* Data not on individual level

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Collection - Associated Studies

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