NIMH Data Archive - Data

Genomics

Neuroimaging

Phenotype¹

New Trial
Clinical Trial

¹ Numbers reported are subjects by age

New Project
Grant/Project Number

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

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.

Select	Experiment Id	Experiment Name	Experiment Type	Created On

24	HI-NGS_R1	Omics	02/16/2011
475	MB1-10 (CHOP)	Omics	06/07/2016
490	Discovery and CRISPR validation of genetic factors associated with antipsychotic-induced weight gain and cardiometabolic risk	Omics	07/07/2016
501	PharmacoBOLD Resting State	fMRI	07/27/2016
506	PVPREF	Omics	08/05/2016
509	ABC-CT Resting v2	EEG	08/18/2016
13	Comparison of FI expression in Autistic and Neurotypical Homo Sapiens	Omics	12/28/2010
18	AGRE/Broad Affymetrix 5.0 Genotype Experiment	Omics	01/06/2011
22	Stitching PCR Sequencing	Omics	02/14/2011
26	ASD_Methylation	Omics	03/01/2011
29	Microarray family 03 (father, mother, sibling)	Omics	03/24/2011
37	Standard paired-end sequencing of BCRs	Omics	04/19/2011
38	Illumina Mate-Pair BCR sequencing	Omics	04/19/2011
39	Custom Jumping Libraries	Omics	04/19/2011
40	Custom CapBP	Omics	04/19/2011
41	Immunofluorescence	Omics	05/11/2011
43	Autism brain sample genotyping, Illumina	Omics	05/16/2011
47	ARRA Autism Sequencing Collaboration at Baylor. SOLiD 4 System	Omics	08/01/2011
53	AGRE Omni1-quad	Omics	10/11/2011
59	AGP genotyping	Omics	04/03/2012
60	Ultradeep 454 sequencing of synaptic genes from postmortem cerebella of individuals with ASD and neurotypical controls	Omics	06/23/2012
63	Microemulsion PCR and Targeted Resequencing for Variant Detection in ASD	Omics	07/20/2012
76	Whole Genome Sequencing in Autism Families	Omics	01/03/2013
519	Resting	fMRI	11/08/2016
90	Genotyped IAN Samples	Omics	07/09/2013
91	NJLAGS Axiom Genotyping Array	Omics	07/16/2013
93	AGP genotyping (CNV)	Omics	09/06/2013
106	Longitudinal Sleep Study. H20 200. Channel set 2	EEG	11/07/2013
107	Longitudinal Sleep Study. H20 200. Channel set 3	EEG	11/07/2013
108	Longitudinal Sleep Study. AURA 200	EEG	11/07/2013
105	Longitudinal Sleep Study. H20 200. Channel set 1	EEG	11/07/2013
109	Longitudinal Sleep Study. AURA 400	EEG	11/07/2013
116	Gene Expression Analysis WG-6	Omics	01/07/2014
131	Jeste Lab UCLA ACEii: Charlie Brown and Sesame Street - Project 1	Eye Tracking	02/27/2014
132	Jeste Lab UCLA ACEii: Animacy - Project 1	Eye Tracking	02/27/2014
133	Jeste Lab UCLA ACEii: Mom Stranger - Project 2	Eye Tracking	02/27/2014
134	Jeste Lab UCLA ACEii: Face Emotion - Project 3	Eye Tracking	02/27/2014
145	AGRE/FMR1_Illumina.JHU	Omics	04/14/2014
146	AGRE/MECP2_Sanger.JHU	Omics	04/14/2014
147	AGRE/MECP2_Junior.JHU	Omics	04/14/2014
151	Candidate Gene Identification in familial Autism	Omics	06/09/2014
152	NJLAGS Whole Genome Sequencing	Omics	07/01/2014
154	Math Autism Study - Vinod Menon	fMRI	07/15/2014
155	Resting	fMRI	07/25/2014
156	Speech	fMRI	07/25/2014
159	Emotion	fMRI	07/25/2014
160	syllable contrast	EEG	07/29/2014
167	School-age naturalistic stimuli	Eye Tracking	09/19/2014
44	AGRE/Broad Affymetrix 5.0 Genotype Experiment	Omics	06/27/2011
45	Exome Sequencing of 20 Sporadic Cases of Autism Spectrum Disorder	Omics	07/15/2011

Collection - Add Experiment

Add Supporting Documentation

Funding Source:
URL:

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.

Use/Modify Existing Data Structure

Request New Data Structure

Targeted Enrollment:

Initial Submission Date:

Initial Share Date:

Data Structure Search:

Data Structures:

Submit

Request Submission Exemption

Not Eligible

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

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

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.

[CMS] Error

[CMS]

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

You have requested to move the sharing dates for the following assessments:

Data Expected Item	Original Sharing Date	New Sharing Date

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

Explanation must be between 20 and 200 characters in length.

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Kansas Intellectual and Developmental Disabilities Research Center #2510

General
Experiments (0)
Shared Data
Publications (313)
Data Expected (7)
Associated Studies (14)

Collection Title	Collection Investigators	Collection Description
Collection Title:	Kansas Intellectual and Developmental Disabilities Research Center
Collection Investigators:	John Colombo
Collection Description:	The Kansas Intellectual and Developmental Disabilities Center KIDDRC supports rigorous and high-impact basic and applied research within themes that are relevant to the etiology, identification, prevention, and treatment of intellectual and developmental disabilities IDD. The Center is organized around projects that fall into four basic themes 1 Language, Communication Disorders, and Cognition, 2 Risk, Intervention, and Prevention, 3 The Neurobiology of IDD, and 4 Cellular and Molecular Biology of Early Development. To achieve its mission, the KIDDRC seeks to develop new interdisciplinary research initiatives relevant to the Centers mission by bringing together scientists across the various sites of the Kansas Center as well as promoting collaboration with researchers at other institutions. It supports existing and new projects with cost-effective, scientifically generative, state-of-the-art core services, resources, and facilities that directly enhance the quality, quantity, and impact of science produced by center investigators and their collaborators, and to provide highly efficient, cost-effective systems for planning, developing, managing, coordinating, and disseminating research activities associated with the center. The KIDDRC proposes to operate five Cores in support of its projects. An Administrative Core coordinates and integrates services and functions across the three physical locations of the KIDDRC in Lawrence and Kansas City and provides scientific leadership and governance mechanisms to ensure that scientific cores are current and efficiently run. A Clinical Translational Core provides KIDDRC investigators with several tools for enhancing translational research, addressed broadly by facilitating contact with individuals with IDD for research. A Preclinical Models Core facilitates translational applications by assisting in the development of cellular and organismal models of IDD. This is done by providing infrastructure and resources needed to create and characterize laboratory models of IDD and by extending KIDDRCs prior capabilities for analyzing behavior, anatomy, physiology, and gene expression. This latter goal includes cutting-edge genome editing technologies to aid in generating cellular models using patient derived cells. A Clinical Outcomes Biobehavioral Technology Core provides high-quality, cost-effective support to KIDDRC research programs requiring quantitative measurement of human neurobehavioral and behavioral outcomes, as well as biological correlates. The CBC includes tools for the generating, collecting, automating, and validating such measures. The fifth core is a Research Design and Analysis Core RDAC, which supports the analysis of data from both preclinical and clinical research through state-of-the-art statistical and bioinformatics methods. Finally, a Research Component housed within the KIDDRC seeks to evaluate the efficacy of multimodal intervention for language in a group of children with autism and minimal verbal skills by comparing results from an experimental intervention to a treatment-as-usual condition, and compare two intensities of the multimodal intervention.
Data Repository:	NIMH Data Archive
Permission Group:
Collection Creation Date:	09/29/2016
Collection Phase:	Funding Completed
Collection Sub-Phase:	Close Out
Blinded Clinical Trial:	No
Total Funded Amount:	$5,096,186.00
Subjects Shared:	45
Collection DOI:	10.15154/v844-0848

{"values":[]}

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Funding Sources:

Funding Source Name	Funding Source URL
NIH - Extramural	None

Supporting Documentation:

Grant Information:

Project Number	Title	Start Date	Original End Date	End Date	Planned Enrollment	Actual Enrollment	Organization	Funds Obligated
U54HD090216-01	Kansas Intellectual and Developmental Disabilities Research Center	09/22/2016	05/31/2021	05/31/2021	560	45	UNIVERSITY OF KANSAS LAWRENCE	$5,096,186.00

Clinical Trials:

helpcenter.collection.general-tab

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).

Glossary

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.

Contact NDA Help Desk

ID	Name	Created Date	Status	Type
No records found.

helpcenter.collection.experiments-tab

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.

Glossary

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.

Contact NDA Help Desk

Shared Data:

Title	Type	Number of Subjects
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 1	Clinical Assessments	22
Communication Complexity Scale	Clinical Assessments	34
MacArthur-Bates CDI - Words and Gestures Form	Clinical Assessments	25
Mullen Scales of Early Learning	Clinical Assessments	34
Peabody Picture Vocabulary Test, Fourth Edition-Form A	Clinical Assessments	45
Research Subject	Clinical Assessments	45
Vineland 3	Clinical Assessments	26

helpcenter.collection.shared-data-tab

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.

Glossary

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.

Contact NDA Help Desk

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 ID	Study	Title	Journal	Authors	Date	Status
42563165	Create Study	Microbially derived glutathione from Eubacterium rectale alleviates oxidative stress and promotes intestinal epithelial recovery.	Microbiome	Richie, Tanner G; Wiechman, Hallie; Vogt, Brooke; Ingold, Carson; Heeren, Leah; Kamke, Abigail; Pogranichniy, Sophia; Monk, Kourtney; Summers, Trey; Ran, Qinghong; Sarkar, Soumyadev; Plattner, Brandon L; Sidebottom, Ashley M; Chang, Eugene B; Lee, Sonny T M	August 4, 2026	Not Determined
42316918	Create Study	Contrasting selection on GxE and main effect loci for soybean grain yield.	Genetics	Happ, Mary M; Graef, George L; Howard, Réka; Hyten, David L	September 2, 2026	Not Determined
42147152	Create Study	Gait variability development in autistic individuals across childhood and adulthood.	Research square	Shafer, Robin L; Wang, Jingying; Qu, Hang; Simpson, Joelle P; Terza, Matthew; Shirley, Desirae J; McKinney, Walker S; Pulver, Stormi; Orlando, Ann-Marie; Romero, Regilda A; Karmakar, Bikram; Mosconi, Matthew W; Wang, Zheng	May 7, 2026	Not Determined
42100472	Create Study	APOE4 Drives Sex- and Diet-Dependent Effects on AD-Like Pathology, Cognition, and Mitochondrial Function.	FASEB bioAdvances	Johnson, Chelsea N; Lysaker, Colton R; Cao, Xin; Csikos, Vivien; Boakye, Frederick; Kueck, Paul J; Franczak, Edziu; Geiger, Paige C; Morris, Jill K; Thyfault, John P; Wilkins, Heather M	May 1, 2026	Not Determined
42098091	Create Study	Cell death modalities modulate inflammatory and regenerative programs in zebrafish sensory organs.	Nature communications	Münch, Daniela; Chen, Shiyuan; Ellis, Elizabeth; Denans, Nicolas; Lush, Mark E; Petentler, Kaitlyn; Javier, Jose E; Bae, KyeongMin; Piotrowski, Tatjana	May 7, 2026	Not Determined
42094045	Create Study	MCT1 governs a metabolic checkpoint at pachytene during spermatogenesis.	Research square	Zhang, Xiaoyu; Liu, Yan; Wang, Ning	April 30, 2026	Not Determined
42079271	Create Study	MCT1 governs a metabolic checkpoint at pachytene during spermatogenesis.	bioRxiv : the preprint server for biology	Zhang, Xiaoyu; Liu, Yan; Wang, Ning	April 22, 2026	Not Determined
42024440	Create Study	Phosphaturia Exacerbates Tubular Injury and Cyst Formation in Polycystic Kidney Disease.	Kidney360	Jansson, Kyle P; Kuluva, Jordan; Swanson, Taylor; Zhang, Shiqin; Fields, Timothy A; Swenson-Fields, Katherine I; Wallace, Darren P; Rowe, Peter S; Stubbs, Jason R	July 1, 2026	Not Determined
41902480	Create Study	Proton FLASH Exposure Preserves Gut Commensal Microbiomes and Spares Intestinal Stem Cells.	Advanced science (Weinheim, Baden-Wurttemberg, Germany)	Chugh, Rishi Man; Bhanja, Payel; Schueddig, Emily; Setianegara, Jufri; Lin, Yuting; Guida, Kenny; Rehman, Shujah; Krepel, Stacey; Koestler, Devin; Chen, Ronald C; Cook, Katherine L; Saha, Subhrajit	June 1, 2026	Not Determined
41741966	Create Study	Feasibility and Preliminary Impacts of a Stress Reduction Intervention for Caregivers of Adolescents and Young Adults With Intellectual and Developmental Disabilities.	Journal of applied research in intellectual disabilities : JARID	Bodde, Amy E; Helsel, Brian C; Willis, Erik; Montgomery, Robert N; Ptomey, Lauren T; Forseth, Bethany	March 1, 2026	Not Determined
41657552	Create Study	Loss of SPECC1L in cranial neural crest cells results in increased hedgehog signaling and frontonasal dysplasia.	Frontiers in physiology	Tran, An J; Hufft-Martinez, Brittany M; Thalman, Dana N; Maili, Lorena; McKinney, Sean A; Goering, Jeremy P; Trainor, Paul A; Saadi, Irfan	January 1, 2026	Not Determined
41446174	Create Study	Targeting Ogt in ADPKD mitigates metabolic reprogramming and renal cystogenesis, extending survival.	bioRxiv : the preprint server for biology	Kavanaugh, Matthew A; Ahmad, Saleem; Isai, Dona Greta; Riddell, Heather A L; Assis, Amanda P; Ranganathan, Chadhve; Chaturvedi, Aakriti; Lam, Vincent; Muthineni, Nikhitha; Abid, Rayyan; Jurgensmeyer, Jenna E; Blades, Casey; Pritchard, Michele T; Sharma, Madhulika; Wallace, Darren P; Parnell, Stephen C; Slawson, Chad; Tran, Pamela V	December 16, 2025	Not Determined
41371340	Create Study	Regulatory role for tumor suppressor REST on estrogen receptor (ESR1) expression and leiomyoma pathophysiology.	The Journal of biological chemistry	Bird, Skylar G; Gunewardena, Sumedha; Cloud, Ashley; Ganeshkumar, Sornakala; Chennathukuzhi, Vargheese M	January 1, 2026	Not Determined
41332626	Create Study	Loss of SPECC1L in cranial neural crest cells results in increased hedgehog signaling and frontonasal dysplasia.	bioRxiv : the preprint server for biology	Tran, An J; Hufft-Martinez, Brittany M; Thalman, Dana N; Maili, Lorena; McKinney, Sean; Goering, Jeremy P; Trainor, Paul A; Saadi, Irfan	November 23, 2025	Not Determined
41292426	Create Study	MtDNA-depleted neuronal cell transcriptomes reveal Alzheimer''s disease-related changes.	Alzheimer''s & dementia : the journal of the Alzheimer''s Association	Menta, Blaise W; Schueddig, Emily; Ranjan, Amol; Li, Yanming; Andrews, Shea J; Wilkins, Heather M; Pei, Dong; Swerdlow, Russell H	November 1, 2025	Not Determined
41278885	Create Study	Genetic interaction of Specc1l and Thm1 reveals cytoskeletal-ciliary crosstalk.	bioRxiv : the preprint server for biology	Hufft-Martinez, Brittany M; Thalman, Dana N; Tran, An J; Goering, Jeremy P; Stetsiv, Marta; Moedritzer, Michael; Wilson, Sarah C; Wang, Henry H; Tran, Pamela V; Saadi, Irfan	November 5, 2025	Not Determined
41256423	Create Study	Ribosome-induced mRNA pseudoknot interactions visualized by DMS MaP-Seq.	bioRxiv : the preprint server for biology	Kellenberger, Preston A; Song, Zhenwei; Heng, Xiao; Cornish, Peter V	October 1, 2025	Not Determined
41187062	Create Study	Stra8 links neuronal activity to inhibitory circuit protection in the adult mouse brain.	Cell reports	Huang, Ming; Yue, Shuwen; Zhang, Xiaoyu; Wu, Lan; Vivian, Jay L; Wang, Zi-Jun; Wang, Ning	November 25, 2025	Not Determined
41168432	Create Study	Precipitation legacy effects on soil microbiota facilitate adaptive drought responses in plants.	Nature microbiology	Ginnan, Nichole A; Custódio, Valéria; Gopaulchan, David; Ford, Natalie; Salas-González, Isai; Jones, Dylan H; Wells, Darren M; Moreno, Ângela; Castrillo, Gabriel; Wagner, Maggie R	November 1, 2025	Not Determined
41025688	Create Study	Extracellular Vesicle miRNAs as Biomarkers of Asthma Severity.	Allergy	Prasad, Chandrashekhar; Griffard, Rachel; Pei, Dong; Haworth, Steven; Dhillon, Navneet K; Castro, Mario; Sundar, Isaac Kirubakaran	January 1, 2026	Not Determined
40996243	Create Study	HCC-derived SNU cell lines as model systems to study HBV life cycle.	Journal of virology	Zaiets, Igor; Chazova, Oleksandra; Gunewardena, Sumedha; Gudima, Severin O	October 23, 2025	Not Determined
40909687	Create Study	Regulatory Role for Tumor Suppressor REST on Estrogen Receptor (ESR1) Expression and Leiomyoma Pathophysiology.	bioRxiv : the preprint server for biology	Bird, Skylar G; Gunewardena, Sumedha; Cloud, Ashley; Ganeshkumar, Sornakala; Chennathukuzhi, Vargheese M	August 31, 2025	Not Determined
40887620	Create Study	Subcortical brain volume variations in autistic individuals across the lifespan.	Molecular autism	Christensen, Danielle; Shin, Young Seon; Wang, Jingying; Cuomo, Carolina R; Dentry, Tyler; Gemmell, Hanna M; Pulver, Stormi L; Orlando, Ann-Marie; McKinney, Walker S; Stevens, Cassie J; Unruh, Kathryn E; Karmakar, Bikram; Coombes, Stephen A; Mosconi, Matthew W; Wang, Zheng	September 1, 2025	Not Determined
40570091	Create Study	Therapeutic potential of NRF2 activating drug RTA-408 in suppressing T cell effector responses and inflammatory bowel disease.	Journal of immunology (Baltimore, Md. : 1950)	Dasgupta, Debolina; Tripathi, Aprajita; Griffard-Smith, Rachel; Yellapu, Nandakumar; Dhorajiya, Poojaben; Pyaram, Kalyani	August 1, 2025	Not Determined
40524523	Create Study	CRABS CLAW-independent floral nectary development in Penstemon barbatus.	American journal of botany	Katzer, Amanda M; Wessinger, Carolyn A; Anaya, Brooklyn M; Hileman, Lena C	June 1, 2025	Not Determined

helpcenter.collection.publications-tab

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).

Glossary

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.

Contact NDA Help Desk

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 Expected	Targeted Enrollment	Initial Submission	Subjects Submitted	Initial Share	Subjects Shared	Status
Research Subject and Pedigree	1	07/15/2017	45	11/15/2017	45	Approved

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 Expected	Targeted Enrollment	Initial Submission	Subjects Submitted	Initial Share	Subjects Shared	Status
Mullen Scales of Early Learning	16	07/15/2017	34	11/15/2017	34	Approved
ADOS	14	07/15/2017	22	11/15/2017	22	Approved
MacArthur Bates Communicative Development Inventory	4	07/15/2017	25	11/15/2017	25	Approved
Peabody Picture Vocabulary Test, Fourth Edition	16	07/15/2017	45	11/15/2017	45	Approved
Vineland (Parent and Caregiver)	12	07/15/2017	26	11/15/2017	26	Approved
Communication Complexity Scale	19	03/01/2019	34	05/15/2019	34	Approved

Structure not yet defined

No Status history for this Data Expected has been recorded yet

helpcenter.collection.data-expected-tab

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.

Glossary

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.

Contact NDA Help Desk

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 NameFilter by Study Name	DOIFilter by DOI	AbstractFilter by Abstract	Collection/Study SubjectsFilter by Collection/Study Subjects	Data UsageFilter by Data Usage	StateFilter by State
Examining the validity of the use of ratio IQs in psychological assessments	10.15154/1522624	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.	32/17423	Secondary Analysis	Shared
Examining Diagnostic Trends and Gender Differences in the ADOS-II	10.15154/jxd2-vw05	Approximately 3–4 boys for every girl meet the clinical criteria for autism in studies of community diagnostic patterns and studies of autism using samples of convenience. However, girls with autism have been hypothesized to be underdiagnosed, possibly because they may present with differing symptom profiles as compared to boys. This secondary data analysis used the National Database of Autism Research (NDAR) to examine how gender and symptom profiles are associated with one another in a gold standard assessment of autism symptoms, the Autism Diagnostic Observation Schedule II (ADOS-II; Lord, C., Luyster, R., Guthrie, W., & Pickles A. (2012a). Patterns of developmental trajectories in toddlers with autism spectrum disorder. Journal of Consulting and Clinical Psychology, 80(3):477–489. https://doi.org/10.1037/a0027214. Epub 2012 Apr 16. PMID: 22506796, PMCID: PMC3365612). ADOS-II scores from 6183 children ages 6–14 years from 78 different studies in the NDAR indicated that gender was a significant predictor of total algorithm, restrictive and repetitive behavioral, and social communicative difficulties composite severity scores. These findings suggest that gender differences in ADOS scores are common in many samples and may reflect on current diagnostic practices.	12/5615	Secondary Analysis	Shared
Gender Differences: Confirmatory Factor Analysis of the ADOS-II	10.15154/4sxe-qh09	Purpose Recent research has suggested that autism may present differently in girls compared to boys, encouraging the exploration of a sex-differential diagnostic criteria. Gender differences in diagnostic assessments have been shown on the ADOS-II, such that, on average, females score significantly lower than males on all scales and are less likely to show atypicality on most items related to social communicative difficulties. Yet, gender differences in the latent structure of instruments like the ADOS-II have not been examined systematically. Methods As such, this secondary data analysis examined 4,100 youth diagnosed with autism (Mage = 9.9, 813 female & 3287 male) examined item response trends by gender on the ADOS-II Module 3. Results Multi-Group Confirmatory Factor Analysis results show that the factor loadings of four ADOS-II items differ across the genders. One SCD item and one RRB item are strongly related to the latent factor in the female group, while two RRB items have larger factor loadings in the male group. Conclusion The assumption of an identical latent factor structure for the ADOS-II Module 3 for males and females might not be justifiable. Possible diagnostic implications are discussed.	12/5615	Secondary Analysis	Shared
Prognostic early snapshot stratification of autism based on adaptive functioning	10.15154/0z1c-1d37	A 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.	19/3517	Secondary Analysis	Shared
Autistic and Non-autistic Vocabulary Growth Modeling	10.15154/3cwp-6085	Background: Autistic children are typically late to develop their expressive vocabulary, but little is known about their early word learning process. This study compared three network growth models on their ability to account for the trajectories of expressive vocabulary acquisition in autistic and non-autistic children. Methods: We studied expressive vocabularies using item-level data from a child vocabulary checklist (n = 721 records from young autistic children; n = 2,166 records from non-autistic toddlers). We estimated vocabulary growth trajectories for autistic and non-autistic children and assessed the goodness of fit of three models of vocabulary growth, with varying sensitivity to the structure of the environment and the learner’s existing vocabulary knowledge. To do so, we first computed word-level acquisition norms that indicate the vocabulary size at which individual words tend to be learned by each group. Then we evaluated how well network growth models, based on natural language co-occurrence structure and word associations, accounted for variance in the autistic and non-autistic acquisition norms. Results: Our word-level vocabulary size of acquisition norms closely aligned with age of acquisition data, indicating their utility when age of acquisition norms cannot be derived for neurodivergent populations. Furthermore, we extended key observations and demonstrated that the growth models explained similar amounts of variance in each group. Both groups are biased to learn words that have many connections to words that have been previously learned; however, even after accounting for this learning influence, autistic and non-autistic vocabulary growth trajectories receive an added boost in learning when words are connected to many other words in the learning environment, indicating a similar learning profile. Conclusions: Both groups preferentially acquire new words by leveraging the semantic structure in the learning environment, indicating an overlap in theoretical accounts of vocabulary growth.	18/370	Secondary Analysis	Shared
Word Learning and Word Features	10.15154/1526346	Vocabulary 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.	13/280	Primary Analysis	Shared
Examining the Shape Bias in Young Autistic Children: A Vocabulary Composition Analysis	10.15154/wjfb-vy71	Shape 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.	12/249	Secondary Analysis	Shared
Modeling Vocabulary Growth in Autistic and Non-Autistic Children	10.15154/q64a-9k34	We assessed the goodness of fit of three models of vocabulary growth, with varying sensitivity to the structure of the environment and the learner’s internal state, to estimated vocabulary growth trajectories in autistic and non-autistic children. We first computed word-level acquisition norms that indicate the vocabulary size at which individual words tend to be learned by each group. We then evaluated how well network growth models based on natural language co-occurrence structure and word associations account for variance in the autistic and non-autistic acquisition norms. In addition to replicating key observations from prior work and observing that the growth models explained similar amounts of variance in each group, we found that autistic vocabulary growth also exhibits growth consistent with “the lure of the associates” model. Thus, both groups leverage semantic structure in the learning environment for vocabulary development, but autistic vocabulary growth is also strongly influenced by existing vocabulary knowledge.	13/247	Secondary Analysis	Shared
Semantic modeling 2023	10.15154/1528994	Although 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.	9/208	Secondary Analysis	Shared
Semantic Network Modeling	10.15154/1522607	Although 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.	9/200	Secondary Analysis	Shared
Semantic Network Modeling in Young Autistic Children	10.15154/z865-cy61	Background: 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.	9/194	Secondary Analysis	Shared
Structure of Autistic Children's Semantic Networks	10.15154/79hg-7d18	In the current study, we estimated the patterns of semantic development using a network analysis approach. We studied the expressive vocabularies of 815 non-autistic and 163 autistic children who were well-matched on expressive vocabulary. Network structure (i.e., the number of connections between words and patterns of connections) was based on child-oriented word associations. We analyzed networks according to measures that index clusters of word knowledge, connections among words, path lengths between words, and a holistic measure of network structure. Autistic and non-autistic children are sensitive to the structure of their semantic environment. Both groups demonstrated vocabulary trajectories that differed from random learning networks. However, group differences were observed, with an early peak in the autistic group’s clustering of word knowledge, followed by a sharp decline. Moreover, relative to non-autistic children and across each network measure, we found that autistic children had reduced small-world structure (with reduced clustering of words and longer paths to connect different words). Group differences indicate that, although autistic children are learning from their semantic environment, they may be processing their semantic environment differently. These differences indicate that autistic children have distinctive learning biases.	4/163	Secondary Analysis	Shared
Investigating Vocabulary Profiles in Preverbal and Minimally Verbal Children with Autism Spectrum Disorder	10.15154/1503887	The majority of children with autism spectrum disorder (ASD) are delayed in producing their first words and approximately 30% continue to be minimally verbal across childhood. The current study examined the syntactic and semantic features of the early words that 64 preverbal and minimally verbal children with ASD produced and compared them to 682 typically developing (TD) toddlers who produced 1-10 words. Word-level responses that were reported on the MacArthur-Bates Communicative Development Inventory were examined. Children with ASD produced a greater proportion of predicates, relative to the TD group. Also, there were group differences in the following semantic categories: action words, people, sound effects, and animals. Of these, children with ASD produced more action words. We further examined the action words by assigning them social scores, with action words that typically involve people having higher social scores. TD toddlers produced action words that were slightly more social than children with ASD. These findings suggest that future studies should examine early verb learning and processing in children with ASD.	6/64	Secondary Analysis	Shared
Vocabulary Comprehension in MV Children with ASD	10.15154/1522453	The majority of children with autism spectrum disorder (ASD) experience early language delays; approximately 30% continue to be minimally verbal throughout childhood. The current study examined the syntactic and semantic features of the early words that 31 minimally verbal (MV) children with ASD were reported to understand. This receptive vocabulary profile was compared to 124 TD toddlers who were matched on expressive vocabulary and 124 TD toddlers who were matched on receptive vocabulary. Word-level responses that were reported on the MacArthur-Bates Communicative Development Inventory were examined. Children with ASD understood a greater proportion of verbs, relative to both the TD groups. Numerous additional differences existed between the MV-ASD group and the TD expressive vocabulary-matched group. In contrast, with a few exceptions, MV children with ASD displayed a similar receptive vocabulary profile to TD toddlers who were matched on receptive vocabulary abilities. These similarities existed despite large differences in expressive vocabulary knowledge, chronological age, and mental age. These findings suggest that future studies should examine early verb learning and processing in MV children with ASD.	8/31	Secondary Analysis	Shared

* Data not on individual level

helpcenter.collection.associated-studies-tab

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

How do I associate a study to my collection?

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

Glossary

Associated Studies Tab

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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