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	Illumina Infinium PsychArray BeadChip Assay	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.

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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.

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[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

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Multimodal Developmental Neurogenetics of Females with ASD #2021

General
Experiments (10)
Shared Data
Publications (98)
Data Expected (21)
Associated Studies (17)

Collection Title	Collection Investigators	Collection Description
Collection Title:	Multimodal Developmental Neurogenetics of Females with ASD
Collection Investigators:	Kevin Pelphrey
Collection Description:	The term autism-spectrum disorders (ASD) exemplifies the tremendous heterogeneity in this developmental disorder at both the phenotypic and underlying genetic levels. It has repeatedly been observed that ASD disproportionately affects males relative to females. Although many hypotheses attempt to explain this bias, no clear answers have emerged because of inconsistent and incomplete phenotyping and small sample sizes. We propose to leverage the interdisciplinary strengths and recruiting power of our network to study sex specific differences by deep phenotyping and genotyping of ASD participants. We will recruit a sex-balanced cohort of ASD (N=125) and matched typically developing (TD) comparison participants (N=125), as well as a set of unaffected siblings. We will quantitatively phenotype multiple behavioral domains and measure several key ASD-related neural systems at the level of brain structure (sMRI), connectivity (DTI and fMRI), function (task based and resting state fMRI), and temporal dynamics (EEG). Additionally, we will measure copy number variation (CNV) and single nucleotide variation (SNV) for these participants and their parents, allowing us to test sex- and circuit-specific genotype-phenotype hypotheses for five candidate ASD genes and ultimately extend our methods to a search for novel sex-specific and high-risk genes. Our Specific Aims are to: 1) Identify sex differences in brain structure, function,connectivity, and temporal dynamics in ASD. 2) Characterize associations between DNA sequence and copy number variants and brain structure and function in ASD and TD versus ASD and TD. 3) Relate brain differences in structure, function, and temporal dynamics to heterogeneity in ASD behavior and genetics. We hypothesize that advanced network methods can aid in understanding the tremendous heterogeneity in ASD by connecting different levels of phenotype with genetic variation. We will therefore combine multiple levels of biology and endophenotypes SNVs, CNVs, behavioral metrics, and resting state imaging and electrophysiology measures into one framework across affected and unaffected siblings and controls using an integrated network analysis, iWGCNA.
Data Repository:	NIMH Data Archive
Permission Group:
Collection Creation Date:	11/23/2012
NIH Research Initiative:	NIMH Repository & Genomics Resource (NRGR)
Collection Phase:	Funding Completed
Collection Sub-Phase:	Close Out
Blinded Clinical Trial:	No
Total Funded Amount:	$16,203,823.00
Subjects Shared:	1,042

{"values":[]}

{"values":[["DTI",13],["MRI",13],["fMRI",13]]}

{"values":[["Autism Spectrum Affected",67],["Autism Spectrum Severely Affected",115],["Autism Spectrum Mildly Affected",4],["Parental Control",183],["Sibling Control",41],["Not Defined",134],["Typical Control",51]]}

Loading Chart...

Funding Sources:

Funding Source Name	Funding Source URL
NIH - Extramural	None

Supporting Documentation:

Grant Information:

Project Number	Project Title	Start Date	End Date	Planned Enrollment	Actual Enrollment	Organization	Funds Obligated
R01MH100028-01	Multimodal Developmental Neurogenetics of Females with ASD	09/04/2012	07/31/2022	625	769	GEORGE WASHINGTON UNIVERSITY	$16,203,823.00

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
195	GENDAAR EEG Biomotion	12/05/2014	Approved	EEG
196	GENDAAR EEG Resting	12/05/2014	Approved	EEG
364	Biopoint fMRI	08/04/2015	Approved	fMRI
366	Faces fMRI	08/06/2015	Approved	fMRI
367	Language fMRI	08/06/2015	Approved	fMRI
368	Resting State fMRI	08/06/2015	Approved	fMRI
369	Social Reward fMRI	08/06/2015	Approved	fMRI
484	GENDAAR Word Segmentation ERP Test Phase	06/20/2016	Approved	EEG
485	GENDAAR Word Segmentation EEG Resting, Exposure, and Test Phase	06/20/2016	Approved	EEG
516	ACE_genomics	11/04/2016	Approved	Omics

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
ACE Family Medical History	Clinical Assessments	210
ACE Subject Medical History	Clinical Assessments	218
Autism Diagnostic Interview, Revised (ADI-R)	Clinical Assessments	223
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 3	Clinical Assessments	205
Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) - Module 4	Clinical Assessments	40
BRIEF-Parent	Clinical Assessments	438
Broad Autism Phenotype Questionnaire (BAPQ)	Clinical Assessments	390
CELF-4 Clinical Eval of Lang Fundamentals, 4th ed	Clinical Assessments	480
Child Behavior Checklist (CBCL) 6-18	Clinical Assessments	438
Child/Adolescent Symptom Inventory	Clinical Assessments	400
DAS-II: Differential Ability Scales 2nd Ed. School Age	Clinical Assessments	508
Demographics	Clinical Assessments	415
EEG Subject Files	Imaging	421
Genomics Genetic Test	Genomics	151
Genomics Sample	Genomics	282
Genomics Subject	Genomics	282
Image	Imaging	409
Pubertal Development Scale	Clinical Assessments	443
Repetitive Behavior Scales - Early Childhood Supplement	Clinical Assessments	441
Research Subject	Clinical Assessments	758
SRS-2. Adult, Preschool and School Age	Clinical Assessments	452
Sensory Profile Adult	Clinical Assessments	277
Sensory Profile Caregiver	Clinical Assessments	151
Social Communication Questionnaire (SCQ) - Lifetime	Clinical Assessments	486
Social Responsiveness Scale (SRS) - Adult/Self Version	Clinical Assessments	356
Vineland-II - Survey Form (2005)	Clinical Assessments	479

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
37860899	Create Study	Pubertal maturation and timing effects on resting state electroencephalography in autistic and comparison youth.	Developmental psychobiology	Rea, Hannah M; Clawson, Ann; Hudac, Caitlin M; Santhosh, Megha; Bernier, Raphael A; Earl, Rachel K; Pelphrey, Kevin A; Webb, Sara Jane; Neuhaus, Emily; GENDAAR Consortium	November 1, 2023	Not Determined
37840458	Create Study	Shared and distinct biological mechanisms for anxiety and sensory over-responsivity in youth with autism versus anxiety disorders.	Journal of neuroscience research	Cummings, Kaitlin K; Jung, Jiwon; Zbozinek, Tomislav D; Wilhelm, Frank H; Dapretto, Mirella; Craske, Michelle G; Bookheimer, Susan Y; Green, Shulamite A	January 1, 2024	Not Determined
37817282	Create Study	Age-related changes in neural responses to sensory stimulation in autism: a cross-sectional study.	Molecular autism	Cakar, Melis E; Cummings, Kaitlin K; Bookheimer, Susan Y; Dapretto, Mirella; Green, Shulamite A	October 11, 2023	Not Determined
37776030	Create Study	Frontal EEG alpha asymmetry in youth with autism: Sex differences and social-emotional correlates.	Autism research : official journal of the International Society for Autism Research	Neuhaus, Emily; Santhosh, Megha; Kresse, Anna; Aylward, Elizabeth; Bernier, Raphael; Bookheimer, Susan; Jeste, Shafali; Jack, Allison; McPartland, James C; Naples, Adam; Van Horn, John D; Pelphrey, Kevin; Webb, Sara Jane; ACE GENDAAR Network	December 1, 2023	Not Determined
37734257	Create Study	Epigenetic modification of the oxytocin receptor gene is associated with child-parent neural synchrony during competition.	Developmental cognitive neuroscience	Marzoratti, Analia; Liu, Megan E; Krol, Kathleen M; Sjobeck, Gus R; Lipscomb, Daniel J; Hofkens, Tara L; Boker, Steven M; Pelphrey, Kevin A; Connelly, Jessica J; Evans, Tanya M	October 1, 2023	Not Determined
37546913	Create Study	Conduction Velocity, G-ratio, and Extracellular Water as Microstructural Characteristics of Autism Spectrum Disorder.	bioRxiv : the preprint server for biology	Newman, Benjamin T; Jacokes, Zachary; Venkadesh, Siva; Webb, Sara J; Kleinhans, Natalia M; McPartland, James C; Druzgal, T Jason; Pelphrey, Kevin A; Van Horn, John Darrell; GENDAAR Research Consortium	February 14, 2024	Not Determined
37005061	Create Study	Associations between thalamocortical functional connectivity and sensory over-responsivity in infants at high likelihood for ASD.	Cerebral cortex (New York, N.Y. : 1991)	Wagner, Lauren; Banchik, Megan; Okada, Nana J; McDonald, Nicole; Jeste, Shafali S; Bookheimer, Susan Y; Green, Shulamite A; Dapretto, Mirella	June 8, 2023	Not Determined
36716136	Create Study	The Gender Self-Report: A multidimensional gender characterization tool for gender-diverse and cisgender youth and adults.	The American psychologist	Strang, John F; Wallace, Gregory L; Michaelson, Jacob J; Fischbach, Abigail L; Thomas, Taylor R; Jack, Allison; Shen, Jerry; Chen, Diane; Freeman, Andrew; Knauss, Megan; Corbett, Blythe A; Kenworthy, Lauren; Tishelman, Amy C; Willing, Laura; McQuaid, Goldie A; Nelson, Eric E; Toomey, Russell B; McGuire, Jenifer K; Fish, Jessica N; Leibowitz, Scott F; Nahata, Leena; Anthony, Laura G; Slesaransky-Poe, Graciela; D'Angelo, Lawrence; Clawson, Ann; Song, Amber D; Grannis, Connor; Sadikova, Eleonora; Pelphrey, Kevin A; Gendaar Consortium; Mancilla, Michael; McClellan, Lucy S; Csumitta, Kelsey D; Winchenbach, Molly R; Jilla, Amrita; Alemi, Farrokh; Yang, Ji Seung	October 1, 2023	Not Determined
35916246	Create Study	Leveraging technology to make parent training more accessible: Randomized trial of in-person versus online executive function training for parents of autistic children.	Autism : the international journal of research and practice	Kenworthy, Lauren; Childress, Deb; Armour, Anna Chelsea; Verbalis, Alyssa; Zhang, Anqing; Troxel, Mary; Handsman, Rebecca; Kocher, Kelly; Myrick, Yetta; Werner, Monica; Alexander, Katie C; Cannon, Lynn; Anthony, Laura G	April 1, 2023	Not Determined
35868485	Create Study	Cingulate-Prefrontal Connectivity During Dynamic Cognitive Control Mediates Association Between p Factor and Adaptive Functioning in a Transdiagnostic Pediatric Sample.	Biological psychiatry. Cognitive neuroscience and neuroimaging	Kaminski, Adam; You, Xiaozhen; Flaharty, Kathryn; Jeppsen, Charlotte; Li, Sufang; Merchant, Junaid S; Berl, Madison M; Kenworthy, Lauren; Vaidya, Chandan J	February 1, 2023	Not Determined
35451672	Create Study	Sex Differences on the ADOS-2.	Journal of autism and developmental disorders	Rea, Hannah M; Øien, Roald A; Shic, Frederick; Webb, Sara Jane; Ratto, Allison B	July 1, 2023	Not Determined
34690348	Create Study	Large-scale functional brain networks of maladaptive childhood aggression identified by connectome-based predictive modeling.	Molecular psychiatry	Ibrahim, Karim; Noble, Stephanie; He, George; Lacadie, Cheryl; Crowley, Michael J; McCarthy, Gregory; Scheinost, Dustin; Sukhodolsky, Denis G	February 1, 2022	Not Determined
34556059	Create Study	Effects of sensory distraction and salience priming on emotion identification in autism: an fMRI study.	Journal of neurodevelopmental disorders	Patterson, Genevieve; Cummings, Kaitlin K; Jung, Jiwon; Okada, Nana J; Tottenham, Nim; Bookheimer, Susan Y; Dapretto, Mirella; Green, Shulamite A	September 23, 2021	Not Determined
34517813	Create Study	Resting state EEG in youth with ASD: age, sex, and relation to phenotype.	Journal of neurodevelopmental disorders	Neuhaus, Emily; Lowry, Sarah J; Santhosh, Megha; Kresse, Anna; Edwards, Laura A; Keller, Jack; Libsack, Erin J; Kang, Veronica Y; Naples, Adam; Jack, Allison; Jeste, Shafali; McPartland, James C; Aylward, Elizabeth; Bernier, Raphael; Bookheimer, Susan; Dapretto, Mirella; Van Horn, John D; Pelphrey, Kevin; Webb, Sara Jane; The ACE GENDAAR Network	September 13, 2021	Not Determined
34422224	Create Study	ESTIMATING REPRODUCIBLE FUNCTIONAL NETWORKS ASSOCIATED WITH TASK DYNAMICS USING UNSUPERVISED LSTMS.	Proceedings. IEEE International Symposium on Biomedical Imaging	Dvornek, Nicha C; Ventola, Pamela; Duncan, James S	April 1, 2020	Not Determined
34308439	Create Study	Efficient Shapley Explanation For Features Importance Estimation Under Uncertainty.	Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention	Li, Xiaoxiao; Zhou, Yuan; Dvornek, Nicha C; Gu, Yufeng; Ventola, Pamela; Duncan, James S	January 1, 2020	Not Determined
34308438	Create Study	Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity.	Machine learning in medical imaging. MLMI (Workshop)	Dvornek, Nicha C; Li, Xiaoxiao; Zhuang, Juntang; Ventola, Pamela; Duncan, James S	January 1, 2020	Not Determined
34238038	Create Study	Adding the missing voice: How self-report of autistic youth self-report on an executive functioning rating scale compares to parent report and that of youth with attention deficit hyperactivity disorder or neurotypical development.	Autism : the international journal of research and practice	Kenworthy, Lauren; Verbalis, Alyssa; Bascom, Julia; daVanport, Sharon; Strang, John F; Pugliese, Cara; Freeman, Andrew; Jeppsen, Charlotte; Armour, Anna C; Jost, Geneva; Hardy, Kristina; Wallace, Gregory L	February 1, 2022	Not Determined
34050743	Create Study	Impact of autism genetic risk on brain connectivity: a mechanism for the female protective effect.	Brain : a journal of neurology	Lawrence, Katherine E; Hernandez, Leanna M; Fuster, Emily; Padgaonkar, Namita T; Patterson, Genevieve; Jung, Jiwon; Okada, Nana J; Lowe, Jennifer K; Hoekstra, Jackson N; Jack, Allison; Aylward, Elizabeth; Gaab, Nadine; Van Horn, John D; Bernier, Raphael A; McPartland, James C; Webb, Sara J; Pelphrey, Kevin A; Green, Shulamite A; Bookheimer, Susan Y; Geschwind, Daniel H; Dapretto, Mirella; GENDAAR Consortium	March 29, 2022	Not Determined
34043128	Create Study	Looking Back at the Next 40 Years of ASD Neuroscience Research.	Journal of autism and developmental disorders	McPartland, James C; Lerner, Matthew D; Bhat, Anjana; Clarkson, Tessa; Jack, Allison; Koohsari, Sheida; Matuskey, David; McQuaid, Goldie A; Su, Wan-Chun; Trevisan, Dominic A	December 1, 2021	Not Determined
33860292	Create Study	A neurogenetic analysis of female autism.	Brain : a journal of neurology	Jack, Allison; Sullivan, Catherine A W; Aylward, Elizabeth; Bookheimer, Susan Y; Dapretto, Mirella; Gaab, Nadine; Van Horn, John D; Eilbott, Jeffrey; Jacokes, Zachary; Torgerson, Carinna M; Bernier, Raphael A; Geschwind, Daniel H; McPartland, James C; Nelson, Charles A; Webb, Sara J; Pelphrey, Kevin A; Gupta, Abha R; GENDAAR Consortium	July 28, 2021	Not Determined
33715473	Create Study	The gap between IQ and adaptive functioning in autism spectrum disorder: Disentangling diagnostic and sex differences.	Autism : the international journal of research and practice	McQuaid, Goldie A; Pelphrey, Kevin A; Bookheimer, Susan Y; Dapretto, Mirella; Webb, Sara J; Bernier, Raphael A; McPartland, James C; Van Horn, John D; Wallace, Gregory L	August 1, 2021	Not Determined
33682042	Create Study	Language and Aggressive Behaviors in Male and Female Youth with Autism Spectrum Disorder.	Journal of autism and developmental disorders	Neuhaus, Emily; Kang, Veronica Youn; Kresse, Anna; Corrigan, Sarah; Aylward, Elizabeth; Bernier, Raphael; Bookheimer, Susan; Dapretto, Mirella; Jack, Allison; Jeste, Shafali; McPartland, James C; Van Horn, John D; Pelphrey, Kevin; Webb, Sara Jane; ACE GENDAAR Consortium	January 1, 2022	Not Determined
33677261	Create Study	Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge.	Medical image analysis	Schirmer, Markus D; Venkataraman, Archana; Rekik, Islem; Kim, Minjeong; Mostofsky, Stewart H; Nebel, Mary Beth; Rosch, Keri; Seymour, Karen; Crocetti, Deana; Irzan, Hassna; Hütel, Michael; Ourselin, Sebastien; Marlow, Neil; Melbourne, Andrew; Levchenko, Egor; Zhou, Shuo; Kunda, Mwiza; Lu, Haiping; Dvornek, Nicha C; Zhuang, Juntang; Pinto, Gideon; Samal, Sandip; Zhang, Jennings; Bernal-Rusiel, Jorge L; Pienaar, Rudolph; Chung, Ai Wern	May 1, 2021	Not Determined
33587311	Create Study	Associations between physiological and neural measures of sensory reactivity in youth with autism.	Journal of child psychology and psychiatry, and allied disciplines	Jung, Jiwon; Zbozinek, Tomislav D; Cummings, Kaitlin K; Wilhelm, Frank H; Dapretto, Mirella; Craske, Michelle G; Bookheimer, Susan Y; Green, Shulamite A	October 1, 2021	Not Determined
33442839	Create Study	Parent Emotion Socialization in Children with Autism Spectrum Disorder and Co-Occurring Anxiety.	Research on child and adolescent psychopathology	Jordan, Rebecca; Kalvin, Carla B; Ibrahim, Karim; Sukhodolsky, Denis G	January 1, 2021	Not Determined
33436538	Create Study	Sensory over-responsivity is related to GABAergic inhibition in thalamocortical circuits.	Translational psychiatry	Wood, Emily T; Cummings, Kaitlin K; Jung, Jiwon; Patterson, Genevieve; Okada, Nana; Guo, Jia; O'Neill, Joseph; Dapretto, Mirella; Bookheimer, Susan Y; Green, Shulamite A	January 12, 2021	Not Determined
33385281	Create Study	Conducting CBT for Anxiety in Children with Autism Spectrum Disorder During COVID-19 Pandemic.	Journal of autism and developmental disorders	Kalvin, Carla B; Jordan, Rebecca P; Rowley, Sonia N; Weis, Anna; Wood, Karen S; Wood, Jeffrey J; Ibrahim, Karim; Sukhodolsky, Denis G	November 1, 2021	Not Determined
33274604	Create Study	Do Biological Sex and Early Developmental Milestones Predict the Age of First Concerns and Eventual Diagnosis in Autism Spectrum Disorder?	Autism research : official journal of the International Society for Autism Research	Harrop, Clare; Libsack, Erin; Bernier, Raphael; Dapretto, Mirella; Jack, Allison; McPartland, James C; Van Horn, John D; Webb, Sara J; Pelphrey, Kevin; GENDAAR Consortium	January 1, 2021	Not Determined
33082616	Create Study	Graph Embedding Using Infomax for ASD Classification and Brain Functional Difference Detection.	Proceedings of SPIE--the International Society for Optical Engineering	Li, Xiaoxiao; Dvornek, Nicha C; Zhuang, Juntang; Ventola, Pamela; Duncan, James	February 1, 2020	Not Determined
33043324	Create Study	Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis.	Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention	Li, Xiaoxiao; Zhou, Yuan; Dvornek, Nicha C; Zhang, Muhan; Zhuang, Juntang; Ventola, Pamela; Duncan, James S	October 1, 2020	Not Determined
32929890	Create Study	Social Motivation Across Multiple Measures: Caregiver-Report of Children with Autism Spectrum Disorder.	Autism research : official journal of the International Society for Autism Research	Neuhaus, Emily; Bernier, Raphael A; Webb, Sara J	February 1, 2021	Not Determined
32863862	Create Study	Parent-Child Concordance on the Pubertal Development Scale in Typically Developing and Autistic Youth.	Research in autism spectrum disorders	Clawson, Ann; Strang, John F; Wallace, Gregory L; Gomez-Lobo, Veronica; Jack, Allison; Webb, Sara J; Pelphrey, Kevin A	September 2020	Not Determined
32860348	Create Study	Sex Differences in Salience Network Connectivity and its Relationship to Sensory Over-Responsivity in Youth with Autism Spectrum Disorder.	Autism research : official journal of the International Society for Autism Research	Cummings, Kaitlin K; Lawrence, Katherine E; Hernandez, Leanna M; Wood, Emily T; Bookheimer, Susan Y; Dapretto, Mirella; Green, Shulamite A	September 2020	Not Determined
32734421	Create Study	Assessing Irritability in Children with Autism Spectrum Disorder Using the Affective Reactivity Index.	Journal of autism and developmental disorders	Kalvin, Carla B; Gladstone, Theresa R; Jordan, Rebecca; Rowley, Sonia; Marsh, Carolyn L; Ibrahim, Karim; Sukhodolsky, Denis G	May 1, 2021	Not Determined
32716854	Create Study	Sex Differences in Internalizing Symptoms and Amygdala Functional Connectivity in Neurotypical Youth.	Developmental cognitive neuroscience	Padgaonkar, N T; Lawrence, K E; Hernandez, L M; Green, S A; Galván, A; Dapretto, M	August 1, 2020	Not Determined
32679533	Create Study	Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results.	Medical image analysis	Li, Xiaoxiao; Gu, Yufeng; Dvornek, Nicha; Staib, Lawrence H; Ventola, Pamela; Duncan, James S	October 1, 2020	Not Determined
32553786	Create Study	Editorial: Taking the Next Step Towards Validating Social Processes From the Research Domain Criteria.	Journal of the American Academy of Child and Adolescent Psychiatry	Wallace, Gregory L; Yerys, Benjamin E	November 1, 2020	Not Determined
32488083	Create Study	Neural responsivity to social rewards in autistic female youth.	Translational psychiatry	Lawrence, Katherine E; Hernandez, Leanna M; Eilbott, Jeffrey; Jack, Allison; Aylward, Elizabeth; Gaab, Nadine; Van Horn, John D; Bernier, Raphael A; Geschwind, Daniel H; McPartland, James C; Nelson, Charles A; Webb, Sara J; Pelphrey, Kevin A; Bookheimer, Susan Y; Dapretto, Mirella; GENDAAR Consortium	June 2020	Not Determined
32350530	Create Study	Sex Differences in Functional Connectivity of the Salience, Default Mode, and Central Executive Networks in Youth with ASD.	Cerebral cortex (New York, N.Y. : 1991)	Lawrence, Katherine E; Hernandez, Leanna M; Bowman, Hilary C; Padgaonkar, Namita T; Fuster, Emily; Jack, Allison; Aylward, Elizabeth; Gaab, Nadine; Van Horn, John D; Bernier, Raphael A; Geschwind, Daniel H; McPartland, James C; Nelson, Charles A; Webb, Sara J; Pelphrey, Kevin A; Green, Shulamite A; Bookheimer, Susan Y; Dapretto, Mirella; GENDAAR Consortium	July 2020	Not Determined
32274471	Create Study	Invertible Network for Classification and Biomarker Selection for ASD.	Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention	Zhuang, Juntang; Dvornek, Nicha C; Li, Xiaoxiao; Ventola, Pamela; Duncan, James S	October 2019	Not Determined
32274470	Create Study	Jointly Discriminative and Generative Recurrent Neural Networks for Learning from fMRI.	Machine learning in medical imaging. MLMI (Workshop)	Dvornek, Nicha C; Li, Xiaoxiao; Zhuang, Juntang; Duncan, James S	October 2019	Not Determined
32178755	Create Study	Preliminary Psychometrics for the Executive Function Challenge Task: A Novel, "Hot" Flexibility, and Planning Task for Youth.	Journal of the International Neuropsychological Society : JINS	Kenworthy, Lauren; Freeman, Andrew; Ratto, Allison; Dudley, Katerina; Powell, Kelly K; Pugliese, Cara E; Strang, John F; Verbalis, Alyssa; Anthony, Laura G	August 1, 2020	Not Determined
32144044	Create Study	Fixel-Based Diffusion Magnetic Resonance Imaging Reveals Novel Associations Between White Matter Microstructure and Childhood Aggressive Behavior.	Biological psychiatry. Cognitive neuroscience and neuroimaging	Grazioplene, Rachael; Tseng, Wan-Ling; Cimino, Kimberly; Kalvin, Carla; Ibrahim, Karim; Pelphrey, Kevin A; Sukhodolsky, Denis G	May 2020	Not Determined
32127526	Create Study	Imaging-genetics of sex differences in ASD: distinct effects of OXTR variants on brain connectivity.	Translational psychiatry	Hernandez, Leanna M; Lawrence, Katherine E; Padgaonkar, N Tanya; Inada, Marisa; Hoekstra, Jackson N; Lowe, Jennifer K; Eilbott, Jeffrey; Jack, Allison; Aylward, Elizabeth; Gaab, Nadine; Van Horn, John D; Bernier, Raphael A; McPartland, James C; Webb, Sara J; Pelphrey, Kevin A; Green, Shulamite A; Geschwind, Daniel H; Bookheimer, Susan Y; Dapretto, Mirella; GENDAAR Consortium	March 2020	Not Determined
31955916	Create Study	Reconciling Dimensional and Categorical Models of Autism Heterogeneity: A Brain Connectomics and Behavioral Study.	Biological psychiatry	Tang, Siyi; Sun, Nanbo; Floris, Dorothea L; Zhang, Xiuming; Di Martino, Adriana; Yeo, B T Thomas	June 15, 2020	Not Determined
31643143	Create Study	Discrepancies between parent and child ratings of anxiety in children with autism spectrum disorder.	Autism research : official journal of the International Society for Autism Research	Kalvin, Carla B; Marsh, Carolyn L; Ibrahim, Karim; Gladstone, Theresa R; Woodward, Diana; Grantz, Heidi; Ventola, Pamela; Sukhodolsky, Denis G	January 1, 2020	Not Determined
31509248	Create Study	Data-driven identification of subtypes of executive function across typical development, attention deficit hyperactivity disorder, and autism spectrum disorders.	Journal of child psychology and psychiatry, and allied disciplines	Vaidya, Chandan J; You, Xiaozhen; Mostofsky, Stewart; Pereira, Francisco; Berl, Madison M; Kenworthy, Lauren	January 1, 2020	Not Determined
31390873	Create Study	Anxiety in 3- to 7-year-old children with autism spectrum disorder seeking treatment for disruptive behavior.	Autism : the international journal of research and practice	Sukhodolsky, Denis G; Lecavalier, Luc; Johnson, Cynthia; Smith, Tristram; Swiezy, Naomi; Bearss, Karen; Kalvin, Carla B; Scahill, Lawrence	February 1, 2020	Not Determined
31347307	Create Study	Altered Neural Connectivity in Females, But Not Males with Autism: Preliminary Evidence for the Female Protective Effect from a Quality-Controlled Diffusion Tensor Imaging Study.	Autism research : official journal of the International Society for Autism Research	Lei, Jiedi; Lecarie, Emma; Jurayj, Jane; Boland, Sarah; Sukhodolsky, Denis G; Ventola, Pamela; Pelphrey, Kevin A; Jou, Roger J	October 2019	Not Determined
31230465	Create Study	Distinct Patterns of Neural Habituation and Generalization in Children and Adolescents With Autism With Low and High Sensory Overresponsivity.	The American journal of psychiatry	Green, Shulamite A; Hernandez, Leanna; Lawrence, Katherine E; Liu, Janelle; Tsang, Tawny; Yeargin, Jillian; Cummings, Kaitlin; Laugeson, Elizabeth; Dapretto, Mirella; Bookheimer, Susan Y	December 2019	Not Determined
31144231	Create Study	Anger Rumination is Associated with Restricted and Repetitive Behaviors in Children with Autism Spectrum Disorder.	Journal of autism and developmental disorders	Ibrahim, Karim; Kalvin, Carla; Marsh, Carolyn L; Anzano, Anthony; Gorynova, Lyudmila; Cimino, Kimberly; Sukhodolsky, Denis G	September 1, 2019	Not Determined
30979647	Create Study	Reduced Amygdala-Prefrontal Functional Connectivity in Children With Autism Spectrum Disorder and Co-occurring Disruptive Behavior.	Biological psychiatry. Cognitive neuroscience and neuroimaging	Ibrahim, Karim; Eilbott, Jeffrey A; Ventola, Pamela; He, George; Pelphrey, Kevin A; McCarthy, Gregory; Sukhodolsky, Denis G	December 1, 2019	Not Determined
30957732	Create Study	Linking social motivation with social skill: The role of emotion dysregulation in autism spectrum disorder.	Development and psychopathology	Neuhaus, Emily; Webb, Sara J; Bernier, Raphael A	August 1, 2019	Not Determined
30901538	Create Study	Defining the Genetic, Genomic, Cellular, and Diagnostic Architectures of Psychiatric Disorders.	Cell	Sullivan, Patrick F; Geschwind, Daniel H	March 2019	Not Determined
30873514	Create Study	Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets.	Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention	Dvornek NC, Yang D, Ventola P, Duncan JS	September 2018	Not Determined
30534065	Create Study	Support Vector Machines, Multidimensional Scaling and Magnetic Resonance Imaging Reveal Structural Brain Abnormalities Associated With the Interaction Between Autism Spectrum Disorder and Sex.	Frontiers in computational neuroscience	Irimia, Andrei; Lei, Xiaoyu; Torgerson, Carinna M; Jacokes, Zachary J; Abe, Sumiko; Van Horn, John D	January 1, 2018	Not Determined
29962977	Create Study	Corrigendum: Resting-State Functional Connectivity in Autism Spectrum Disorders: A Review.	Frontiers in psychiatry	Hull, Jocelyn V; Dokovna, Lisa B; Jacokes, Zachary J; Torgerson, Carinna M; Irimia, Andrei; Van Horn, John Darrell; GENDAAR Research Consortium	January 2018	Not Determined
29550506	Create Study	Early enhanced processing and delayed habituation to deviance sounds in autism spectrum disorder.	Brain and cognition	Hudac, Caitlin M; DesChamps, Trent D; Arnett, Anne B; Cairney, Brianna E; Ma, Ruqian; Webb, Sara Jane; Bernier, Raphael A	June 2018	Not Determined
29517857	Create Study	Neural mechanisms of behavioral change in young adults with high-functioning autism receiving virtual reality social cognition training: A pilot study.	Autism research : official journal of the International Society for Autism Research	Yang, Y J Daniel; Allen, Tandra; Abdullahi, Sebiha M; Pelphrey, Kevin A; Volkmar, Fred R; Chapman, Sandra B	May 2018	Not Determined
29333196	Create Study	Brief report: Reduced anxiety following Pivotal Response Treatment in young children with Autism Spectrum Disorder.	Research in autism spectrum disorders	Lei, Jiedi; Sukhodolsky, Denis G; Abdullahi, Sebiha M; Braconnier, Megan L; Ventola, Pamela	November 2017	Not Determined
29255008	Create Study	A Computational Account of Optimizing Social Predictions Reveals That Adolescents Are Conservative Learners in Social Contexts.	The Journal of neuroscience : the official journal of the Society for Neuroscience	Rosenblau, Gabriela; Korn, Christoph W; Pelphrey, Kevin A	January 2018	Not Determined
29251835	Create Study	Child and family characteristics moderate agreement between caregiver and clinician report of autism symptoms.	Autism research : official journal of the International Society for Autism Research	Neuhaus, Emily; Beauchaine, Theodore P; Bernier, Raphael A; Webb, Sara J	March 2018	Not Determined
29104967	Create Study	Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks.	Machine learning in medical imaging. MLMI (Workshop)	Dvornek, Nicha C; Ventola, Pamela; Pelphrey, Kevin A; Duncan, James S	September 2017	Not Determined
28693737	Create Study	Charting a Course for Autism Biomarkers.	Biological psychiatry	Pelphrey, Kevin	August 2017	Not Determined
28634706	Create Study	Parenting a Child with ASD: Comparison of Parenting Style Between ASD, Anxiety, and Typical Development.	Journal of autism and developmental disorders	Ventola, Pamela; Lei, Jiedi; Paisley, Courtney; Lebowitz, Eli; Silverman, Wendy	September 1, 2017	Relevant
28464352	Create Study	Maternal experience raising girls with autism spectrum disorder: a qualitative study.	Child: care, health and development	Navot, N; Jorgenson, A G; Webb, S J	July 2017	Not Relevant
28397802	Create Study	The connectomes of males and females with autism spectrum disorder have significantly different white matter connectivity densities.	Scientific reports	Irimia, Andrei; Torgerson, Carinna M; Jacokes, Zachary J; Van Horn, John D	April 2017	Relevant
28150911	Create Study	Cerebellar contributions to biological motion perception in autism and typical development.	Human brain mapping	Jack, Allison; Keifer, Cara M; Pelphrey, Kevin A	April 2017	Not Determined
28101064	Create Study	Resting-State Functional Connectivity in Autism Spectrum Disorders: A Review.	Frontiers in psychiatry	Hull, Jocelyn V; Dokovna, Lisa B; Jacokes, Zachary J; Torgerson, Carinna M; Irimia, Andrei; Van Horn, John Darrell	January 2016	Not Relevant
27845779	Create Study	Brain responses to biological motion predict treatment outcome in young children with autism.	Translational psychiatry	Yang D, Pelphrey KA, Sukhodolsky DG, Crowley MJ, Dayan E, Dvornek NC, Venkataraman A, Duncan J, Staib L, Ventola P	November 2016	Not Determined
27843152	Create Study	Additive effects of oxytocin receptor gene polymorphisms on reward circuitry in youth with autism.	Molecular psychiatry	Hernandez, L M; Krasileva, K; Green, S A; Sherman, L E; Ponting, C; McCarron, R; Lowe, J K; Geschwind, D H; Bookheimer, S Y; Dapretto, M	August 2017	Not Determined
27532879	Create Study	Pivotal response treatment prompts a functional rewiring of the brain among individuals with autism spectrum disorder.	Neuroreport	Venkataraman, Archana; Yang, Daniel Y-J; Dvornek, Nicha; Staib, Lawrence H; Duncan, James S; Pelphrey, Kevin A; Ventola, Pamela	September 2016	Not Determined
27230762	Create Study	Brief Report: Reduced Restricted and Repetitive Behaviors after Pivotal Response Treatment.	Journal of autism and developmental disorders	Ventola, Pamela E; Yang, Daniel; Abdullahi, Sebiha M; Paisley, Courtney A; Braconnier, Megan L; Sukhodolsky, Denis G	August 2016	Not Determined
27096285	Create Study	Evaluation of Quantified Social Perception Circuit Activity as a Neurobiological Marker of Autism Spectrum Disorder.	JAMA psychiatry	Björnsdotter, Malin; Wang, Nancy; Pelphrey, Kevin; Kaiser, Martha D	June 2016	Not Determined
26955022	Create Study	Bayesian Community Detection in the Space of Group-Level Functional Differences.	IEEE transactions on medical imaging	Venkataraman A, Yang DY, Pelphrey KA, Duncan JS	August 2016	Not Determined
26886246	Create Study	Face perception and learning in autism spectrum disorders.	Quarterly journal of experimental psychology (2006)	Webb, Sara Jane; Neuhaus, Emily; Faja, Susan	May 2017	Not Relevant
26781567	Create Study	Developmental neurogenetics and multimodal neuroimaging of sex differences in autism.	Brain imaging and behavior	Chen C, Van Horn JD,	January 19, 2016	Not Relevant
26743637	Create Study	Wanting it Too Much: An Inverse Relation Between Social Motivation and Facial Emotion Recognition in Autism Spectrum Disorder.	Child psychiatry and human development	Garman, Heather D; Spaulding, Christine J; Webb, Sara Jane; Mikami, Amori Yee; Morris, James P; Lerner, Matthew D	December 1, 2016	Not Determined
26311606	Create Study	Connected brains and minds--The UMCD repository for brain connectivity matrices.	NeuroImage	Brown JA, Van Horn JD	January 1, 2016	Not Relevant
26106561	Create Study	An unbiased Bayesian approach to functional connectomics implicates social-communication networks in autism.	NeuroImage. Clinical	Venkataraman A, Duncan JS, Yang DY, Pelphrey KA	2015	Not Determined
25891009	Create Study	Gene hunting in autism spectrum disorder: on the path to precision medicine.	The Lancet. Neurology	Geschwind, Daniel H; State, Matthew W	November 2015	Not Determined
25831060	Create Study	The promise of multi-omics and clinical data integration to identify and target personalized healthcare approaches in autism spectrum disorders.	Omics : a journal of integrative biology	Higdon, Roger; Earl, Rachel K; Stanberry, Larissa; Hudac, Caitlin M; Montague, Elizabeth; Stewart, Elizabeth; Janko, Imre; Choiniere, John; Broomall, William; Kolker, Natali; Bernier, Raphael A; Kolker, Eugene	April 2015	Not Determined
25752243	Create Study	The autism-associated chromatin modifier CHD8 regulates other autism risk genes during human neurodevelopment.	Nature communications	Cotney, Justin; Muhle, Rebecca A; Sanders, Stephan J; Liu, Li; Willsey, A Jeremy; Niu, Wei; Liu, Wenzhong; Klei, Lambertus; Lei, Jing; Yin, Jun; Reilly, Steven K; Tebbenkamp, Andrew T; Bichsel, Candace; Pletikos, Mihovil; Sestan, Nenad; Roeder, Kathryn; State, Matthew W; Devlin, Bernie; Noonan, James P	2015	Not Determined
25724689	Create Study	Neuroimaging of the developing brain.	Brain imaging and behavior	Van Horn JD, Pelphrey KA	March 2015	Not Relevant
25666423	Create Study	Interacting with the National Database for Autism Research (NDAR) via the LONI Pipeline workflow environment.	Brain imaging and behavior	Torgerson, Carinna M; Quinn, Catherine; Dinov, Ivo; Liu, Zhizhong; Petrosyan, Petros; Pelphrey, Kevin; Haselgrove, Christian; Kennedy, David N; Toga, Arthur W; Van Horn, John Darrell	March 2015	Not Determined
25660957	Create Study	An integrative neural model of social perception, action observation, and theory of mind.	Neuroscience and biobehavioral reviews	Yang, Daniel Y-J; Rosenblau, Gabriela; Keifer, Cara; Pelphrey, Kevin A	April 2015	Not Relevant
25198094	Create Study	Neural systems for cognitive reappraisal in children and adolescents with autism spectrum disorder.	Developmental cognitive neuroscience	Pitskel NB, Bolling DZ, Kaiser MD, Pelphrey KA, Crowley MJ	October 2014	Not Determined
24981794	Create Study	Neural Correlates of Animacy Attribution Include Neocerebellum in Healthy Adults.	Cerebral cortex (New York, N.Y. : 1991)	Jack, Allison; Pelphrey, Kevin A	November 2015	Not Determined
24683058	Create Study	ASD: Psychopharmacologic Treatments and Neurophysiologic Underpinnings.	Current topics in behavioral neurosciences	Kodish, Ian; Rockhill, Carol M; Webb, Sara J	2014	Not Determined
24481546	Create Study	Building a social neuroscience of autism spectrum disorder.	Current topics in behavioral neurosciences	Pelphrey KA, Yang DY, McPartland JC	2014	Not Determined
24441420	Create Study	Update on diagnostic classification in autism.	Current opinion in psychiatry	King, Bryan H; Navot, Noa; Bernier, Raphael; Webb, Sara Jane	March 2014	Not Determined
24297883	Create Study	Oxytocin enhances brain function in children with autism.	Proceedings of the National Academy of Sciences of the United States of America	Gordon I, Vander Wyk BC, Bennett RH, Cordeaux C, Lucas MV, Eilbott JA, Zagoory-Sharon O, Leckman JF, Feldman R, Pelphrey KA	December 24, 2013	Not Determined
24293083	Create Study	Sex differences in social perception in children with ASD.	Journal of autism and developmental disorders	Coffman, M C; Anderson, L C; Naples, A J; McPartland, J C	February 2015	Not Determined
24203652	Create Study	Graphical neuroimaging informatics: application to Alzheimer's disease.	Brain imaging and behavior	Van Horn JD, Bowman I, Joshi SH, Greer V	June 2014	Not Determined
23876243	Create Study	Sex differences in the development of brain mechanisms for processing biological motion.	NeuroImage	Anderson LC, Bolling DZ, Schelinski S, Coffman MC, Pelphrey KA, Kaiser MD	December 2013	Not Determined
23774715	Create Study	The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.	Molecular psychiatry	Di Martino, A; Yan, C-G; Li, Q; Denio, E; Castellanos, F X; Alaerts, K; Anderson, J S; Assaf, M; Bookheimer, S Y; Dapretto, M; Deen, B; Delmonte, S; Dinstein, I; Ertl-Wagner, B; Fair, D A; Gallagher, L; Kennedy, D P; Keown, C L; Keysers, C; Lainhart, J E; Lord, C; Luna, B; Menon, V; Minshew, N J; Monk, C S; Mueller, S; Müller, R-A; Nebel, M B; Nigg, J T; O'Hearn, K; Pelphrey, K A; Peltier, S J; Rudie, J D; Sunaert, S; Thioux, M; Tyszka, J M; Uddin, L Q; Verhoeven, J S; Wenderoth, N; Wiggins, J L; Mostofsky, S H; Milham, M P	June 2014	Not Determined
22677931	Create Study	Revisiting regression in autism: Heller''s dementia infantilis. Includes a translation of Über Dementia Infantilis.	Journal of autism and developmental disorders	Westphal, Alexander; Schelinski, Stefanie; Volkmar, Fred; Pelphrey, Kevin	February 2013	Not Determined

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Collection - Publications

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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	625	07/15/2013	769	11/15/2013	769	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
Genomics/omics	375	07/15/2013	282	11/15/2013	282	Approved
ADOS	80	01/15/2013	245	04/15/2013	245	Approved
ADI-R	250	07/15/2013	223	11/15/2013	223	Approved
Medical History	250	07/15/2013	225	11/15/2013	225	Approved
Social Responsiveness Scale (SRS)	625	12/27/2017	791	10/30/2018	791	Approved
Genetic Test	80	05/31/2016	151	09/30/2017	151	Approved
Child and Adolescent Symptom Inventory (CASI)	80	01/15/2013	400	04/15/2013	400	Approved
Social Communication Questionnaire (SCQ)	625	12/27/2017	486	10/30/2018	486	Approved
Broad Autism Phenotype Questionnaire (BAPQ)	80	01/15/2013	389	04/15/2013	389	Approved
Demographics	80	01/15/2013	415	04/15/2013	415	Approved
Child Behavior Checklist (CBCL)	80	01/15/2013	438	04/15/2013	438	Approved
Pubertal Development Scale (PDS)	625	07/15/2013	443	11/15/2013	443	Approved
DAS-II: Differential Ability Scales	80	01/15/2013	508	04/15/2013	508	Approved
Repetitive Behavior Scale - Revised (RBS-R)	625	12/27/2017	441	10/30/2018	441	Approved
Sensory Profile	625	07/15/2013	428	11/15/2013	428	Approved
Behavior Rating Inventory of Executive Function (BRIEF)	80	01/15/2013	438	04/15/2013	438	Approved
Clinical Evaluation of Language Fundamentals (CELF)	625	12/27/2017	480	10/30/2018	480	Approved
Vineland (Parent and Caregiver)	625	07/15/2013	479	11/15/2013	479	Approved
Imaging (Structural, fMRI, DTI, PET, microscopy)	625	07/15/2013	409	11/15/2013	409	Approved
EEG	625	12/27/2017	421	10/30/2018	421	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	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	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.	508/17423	Secondary Analysis	Shared
Prognostic early snapshot stratification of autism based on adaptive functioning	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.	132/3517	Secondary Analysis	Shared
Investigating autism etiology and heterogeneity by decision tree algorithm	Autism 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.	207/3382	Secondary Analysis	Shared
Imbalanced social-communicative and restricted repetitive behavior subtypes in autism spectrum disorder exhibit different neural circuitry	Social-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.	169/1708	Secondary Analysis	Shared
Age-dependent white matter microstructural disintegrity in autism spectrum disorder	There has been increasing evidence of White Matter (WM) microstructural disintegrity and connectome disruption in Autism Spectrum Disorder (ASD). We evaluated the effects of age on WM microstructure by examining Diffusion Tensor Imaging (DTI) metrics and connectome Edge Density (ED) in a large dataset of ASD and control patients from different age cohorts. N = 583 subjects from four studies from the National Database of Autism Research were included, representing four different age groups: (1) A Longitudinal MRI Study of Infants at Risk of Autism [infants, median age: 7 (interquartile range 1) months, n = 155], (2) Biomarkers of Autism at 12 months [toddlers, 32 (11)m, n = 102], (3) Multimodal Developmental Neurogenetics of Females with ASD [adolescents, 13.1 (5.3) years, n = 230], (4) Atypical Late Neurodevelopment in Autism [young adults, 19.1 (10.7)y, n = 96]. For each subject, we created Fractional Anisotropy (FA), Mean- (MD), Radial- (RD), and Axial Diffusivity (AD) maps as well as ED maps. We performed voxel-wise and tract-based analyses to assess the effects of age, ASD diagnosis and sex on DTI metrics and connectome ED. We also optimized, trained, tested, and validated different combinations of machine learning classifiers and dimensionality reduction algorithms for prediction of ASD diagnoses based on tract-based DTI and ED metrics. There is an age-dependent increase in FA and a decline in MD and RD across WM tracts in all four age cohorts, as well as an ED increase in toddlers and adolescents. After correction for age and sex, we found an ASD-related decrease in FA and ED only in adolescents and young adults, but not in infants or toddlers. While DTI abnormalities were mostly limited to the corpus callosum, connectomes showed a more widespread ASD-related decrease in ED. Finally, the best performing machine-leaning classification model achieved an area under the receiver operating curve of 0.70 in an independent validation cohort. Our results suggest that ASD-related WM microstructural disintegrity becomes evident in adolescents and young adults—but not in infants and toddlers. The ASD-related decrease in ED demonstrates a more widespread involvement of the connectome than DTI metrics, with the most striking differences being localized in the corpus callosum.	409/1362	Secondary Analysis	Shared
Reconciling Dimensional and Categorical Models of Autism Heterogeneity: A Brain Connectomics and Behavioral Study	Background Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide individuals with ASD into nonoverlapping (categorical) subgroups. However, continuous interindividual variation in ASD suggests that there is a need for a dimensional approach. Methods A Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of individuals with ASD into multiple abnormal RSFC patterns, i.e., categorical subtypes, henceforth referred to as “factors.” Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 individuals with ASD (5.2–57 years of age) from two multisite repositories. Post hoc analyses associated factors with symptoms and demographics. Results Analyses yielded three factors with dissociable whole-brain hypo- and hyper–RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default mode network, but the directionality (hypo- or hyper–RSFC) differed across factors. Factor 1 was associated with core ASD symptoms. Factors 1 and 2 were associated with distinct comorbid symptoms. Older male participants preferentially expressed factor 3. Factors were robust across control analyses and were not associated with IQ or head motion. Conclusions There exist at least three ASD factors with dissociable whole-brain RSFC patterns, behaviors, and demographics. Heterogeneous default mode network hypo- and hyper–RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms—a less appreciated domain of heterogeneity in ASD. These factors are coexpressed in individuals with ASD with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.	850/850	Secondary Analysis	Shared
Investigating possible biomarkers of autism in resting EEG	There 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.	332/771	Secondary Analysis	Shared
Brain-based sex differences in autism spectrum disorder across the lifespan: A systematic review of structural MRI, fMRI, and DTI findings	Females with autism spectrum disorder (ASD) have been long overlooked in neuroscience research, but emerging evidence suggests they show distinct phenotypic trajectories and age-related brain differences. Sex-related biological factors (e.g., hormones, genes) may play a role in ASD etiology and have been shown to influence neurodevelopmental trajectories. Thus, a lifespan approach is warranted to understand brain-based sex differences in ASD. This systematic review on MRI-based sex differences in ASD was conducted to elucidate variations across the lifespan and inform biomarker discovery of ASD in females. We identified articles through two database searches. Fifty studies met criteria and underwent integrative review. We found that regions expressing replicable sex-by-diagnosis differences across studies overlapped with regions showing sex differences in neurotypical (NT) cohorts, in particular regions showing NT male>female volumes. Furthermore, studies investigating age-related brain differences across a broad age-span suggest distinct neurodevelopmental patterns in females with ASD. Qualitative comparison across youth and adult studies also supported this hypothesis. However, many studies collapsed across age, which may mask differences. Furthermore, accumulating evidence supports the female protective effect in ASD, although only one study examined brain circuits implicated in “protection.” When synthesized with the broader literature, brain-based sex differences in ASD may come from various sources, including genetic and endocrine processes involved in brain “masculinization” and “feminization” across early development, puberty, and other lifespan windows of hormonal transition. Furthermore, sex-related biology may interact with peripheral processes, in particular the stress axis and brain arousal system, to produce distinct neurodevelopmental patterns in males and females with ASD. Future research on neuroimaging-based sex differences in ASD would benefit from a lifespan approach in well-controlled and multivariate studies. Possible relationships between behavior, sex hormones, and brain development in ASD remain largely unexamined.	79/759	Secondary Analysis	Shared
Identification of differentially methylated regions (DMRs) and cytosine sites (DMCs) in DNA methylation data of autism cases and unaffected siblings	We compared blood-based DNA methylation profiles between children with autism spectrum disorder (ASD) and carefully matched, unrelated neurotypical control children. Using sequencing-based method, we identified ASD-specific differentially methylated regions (DMRs) and cytosine sites (DMCs). We carried out comparative analyses with datasets from the NDA Collection 1650 (SFARI - DNA Methylation Analysis Cohort) that measured blood DNA methylation in ASD using microarray technology. We also identified DMRs and DMCs using metilene and minfi pipelines in the DNAm datasets from the NDA Collection 1650.	3/728	Secondary Analysis	Shared
Phenotypic subtyping and re-analysis of existing methylation data from autistic probands in simplex families reveal ASD subtype-associated differentially methylated genes and biological functions	Autism spectrum disorder (ASD) describes a group of neurodevelopmental disorders with core deficits in social communication and manifestation of restricted, repetitive, and stereotyped behaviors. Despite the core symptomatology, ASD is extremely heterogeneous with respect to the severity of symptoms and behaviors. This heterogeneity presents an inherent challenge to all large-scale genome-wide 'omics analyses. In the present study, we address this heterogeneity by stratifying ASD probands from simplex families according to severity of behavioral scores on the Autism Diagnostic Interview-Revised diagnostic instrument, followed by re-analysis of existing DNA methylation data from individuals in three ASD subphenotypes in comparison to that of their respective unaffected siblings. We demonstrate that subphenotyping of cases enables the identification of over 1.6 times the number of statistically significant differentially methylated genes (DMGs) between cases and controls, compared to that identified when all cases are combined. Our analyses also reveal ASD-related neurological functions and comorbidities that are enriched among DMGs in each phenotypic subgroup but not in the combined case group. These findings may aid in the development of subtype-directed diagnostics and therapeutics.	1/584	Secondary Analysis	Shared
Development of EEG dynamics throughout the lifespan	Combining 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.	179/551	Secondary Analysis	Shared
Face-processing performance is an independent predictor of social affect as measured by the Autism Diagnostic Observation Schedule across large-scale datasets	Face-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.	18/445	Secondary Analysis	Shared
comparing EEG metrics during eyes closed versus eyes open rest in autism	Understanding 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.	336/336	Secondary Analysis	Shared
Cortico-Basal Ganglia Brain Structure and Links to Restricted, Repetitive Behavior in Autism Spectrum Disorder	Restricted 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.	192/192	Secondary Analysis	Shared
A Midsagittal-View Magnetic Resonance Imaging Study of the Growth and Involution of the Adenoid Mass and Related Changes in Selected Velopharyngeal Structures	Purpose: The adenoids, or pharyngeal tonsils, consist of a pad of lymphoid tissue, located on the posterior pharyngeal wall of the nasopharynx. During childhood, the adenoid pad serves as a contact site for the soft palate to assist with velopharyngeal closure during oral speech. During adenoidal involution, most children are able to maintain appropriate velopharyngeal closure necessary for normal speech resonance. The purpose of this study is to determine age related trends of normal adenoid growth and involution from infancy through adulthood. Methods/Description: Lateral view magnetic resonance imaging (MRI) was used to analyze velopharyngeal variables among 270 participants, between 3 months and 34 years of age. The velopharyngeal measures of interest included velar length, effective velar length, pharyngeal depth, adenoid height, adenoid thickness, adenoid depth, and adenoid area. Participants were divided into four age groups for statistical comparison. Results: There was a statistically significant difference (p<.05) in all linear and area measurements between the four age groups. Adenoid depth reached peak growth at age 4, whereas adenoid height and adenoid thickness peaked at 8 years of age. Qualitatively, adenoid growth progresses in an anterior and inferior direction whereas involution occurs in a posterior and superior direction. Conclusions: This study contributes to the knowledge of time specific changes across an age span for adenoid growth and involution and presents a visualization of the shape and growth trends of adenoids. A new sequence of involution is reported beginning first with adenoid depth, followed by adenoid height at a slightly faster rate than adenoid thickness.	19/42	Secondary Analysis	Shared
Effective Velopharyngeal Ratio: A More Clinically Relevant Measure of Velopharyngeal Function	Purpose: Velopharyngeal (VP) ratios are commonly used to study normal VP anatomy and normal VP function. An effective VP (EVP) ratio may be a more appropriate indicator of normal parameters for speech. The aims of this study are to examine if the VP ratio is preserved across the age span or if it varies with changes in the VP portal and to analyze if the EVP ratio is more stable across the age span. Methods: Magnetic resonance imaging (MRI) was used to analyze VP variables of 270 participants. For statistical analysis, the participants were divided into the following groups based on age: infants, children, adolescents and adults. ANOVAs and a Games Howell Post Hoc Test were used to compare variables between groups. Results: There was a statistically significant difference (p < .05) in all measurements between the age groups. Pairwise comparisons reported statistically significant adjacent group differences (p < .05) for velar length, VP ratio, effective velar length, adenoid depth, and pharyngeal depth. No statistically significant differences between adjacent age groups was reported for the EVP ratio. Conclusions: Results from this study report the EVP ratio was not statistically significant between adjacent age groups, while the VP ratio was statistically significant between adjacent age groups. This study suggests that the EVP ratio is more correlated to VP function than the VP ratio and provides a more stable and consistent ratio of VP function across the age span.	19/42	Secondary Analysis	Shared
Growth Effects on Velopharyngeal Anatomy From Childhood to Adulthood	Purpose: The observed sexual dimorphism of velopharyngeal structures among adult populations has not been observed in the young child (4- to 9-year-old) population. The purpose of this study was to examine the age at which sexual dimorphism of velopharyngeal structures become apparent and to examine how growth trends vary between boys and girls. Method: Static 3-dimensional magnetic resonance imaging velopharyngeal data were collected among 202 participants ranging from 4 to 21 years of age. Participants were divided into 3 groups based on age, including Group 1: 4–10 years of age, Group 2: 11–17 years of age, and Group 3: 18–21 years of age. Nine velopharyngeal measures were obtained and compared between groups. Results: Significant sex effects were evident for levator length (p = .011), origin to origin (p = .018), and velopharyngeal ratio (p = .036) for those in Group 2 (11–17 years of age). Sex effects became increasingly apparent with age, with 7 of 9 variables becoming significantly different between male and female participants in Group 3. Boys, in general, displayed a delayed growth peak in velopharyngeal growth compared to girls. Conclusion: Results from this study demonstrate the growth of velopharyngeal anatomy with sexual dimorphism becoming apparent predominantly after 18 years of age. However, velopharyngeal variables displayed variable growth trends with some variables presenting sexual dimorphism at an earlier age compared to other velopharyngeal variables.	19/42	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.

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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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