NIMH Data Archive - Data

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¹ Numbers reported are subjects by age

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

Collection - Use Existing Experiment

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

The table search feature is case insensitive and targets the experiment id, experiment name and experiment type columns. The experiment id is searched only when the search term entered is a number, and filtered using a startsWith comparison. When the search term is not numeric the experiment name is used to filter the results.

Select	Experiment Id	Experiment Name	Experiment Type	Created On

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

Collection - Add Experiment

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Harmonizing multi-site diffusion MRI acquisitions for neuroscientific analysis across ages and brain disorders #3371

General
Experiments (0)
Shared Data
Publications (64)
Data Expected (4)
Associated Studies (3)

Collection Title	Collection Investigators	Collection Description
Collection Title:	Harmonizing multi-site diffusion MRI acquisitions for neuroscientific analysis across ages and brain disorders
Collection Investigators:	Yogesh Rathi
Collection Description:	Diffusion MRI (dMRI) is the only non-invasive method that can map the living human brains connections and is critical for understanding mental disorders. Several large studies such as the Human Connectome Project (HCP) and the Adolescent Brain Cognitive Development (ABCD) have collected or are poised to collect diffusion MRI data from over 30,000 subjects. However, an important challenge is that these datasets collected from different scanners cannot be pooled for joint analysis due to large inter-scanner (inter-site) differences, caused by differences in vendor specific software for data reconstruction, the sensitivity of head coils etc. These scanner differences are often larger than the effect sizes observed between groups in psychiatric disorders. A second challenge for large-scale data analysis is the lack of a single consistent ontology-based definition and automated extraction of white matter connections across the lifespan (including neonates and children). A third challenge is the sheer size of the combined dMRI datasets (several terabytes), limiting the ability of researchers to test hypotheses as this requires expertise and complex computational resources for processing, storing, and visualizing such large volumes of data. In this grant, we propose to address these challenges to enable large- scale data-intensive analysis of dMRI data. Specifically, in Aim 1, we propose to develop novel mathematical algorithms to remove scanner-specific differences from data acquired at multiple sites. We will harmonize 10,000 subjects from the ABCD study acquired at 21 different sites, another 10,000 subjects from the HCP initiative spanning the entire lifespan and numerous disease indications and 10,000 subjects from the Healthy Brain Network. All the harmonized datasets (30,000 subjects), will be shared with the community using the NIMH data archive (NDA). In Aim 2, we will develop a formal ontology-based system for defining 189 white matter fascicles using neuroanatomical landmarks known from human and monkey literature on brain connectivity. Our main focus will be to develop novel algorithms for automated and consistent clustering and extraction of these fiber bundles spanning the entire human lifespan including neonates. To enable widespread use without the need for demanding computational resources and technical knowledge, in Aim 3, we will develop a web-based system for real-time 3D viewing and querying of the harmonized data and fascicles (integrating with NIMH data archive infrastructure) for a user-defined selection of subjects from the entire cohort of subjects across different diagnostic categories. Overall, the potential impact of this framework is significant, as it will, for the first time, allow a large-scale data-intensive analysis of dMRI data to study neurodevelopment as well as mental disorders cutting across diagnostic boundaries.
Data Repository:	NIMH Data Archive
Permission Group:
Collection Creation Date:	10/15/2019
Collection Phase:	Funding Completed
Collection Sub-Phase:	Close Out
Blinded Clinical Trial:	No
Total Funded Amount:	$3,970,680.00
Subjects Shared:	9,345
Collection DOI:	10.15154/z6z9-pk66

{"values":[]}

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Funding Sources:

Funding Source Name	Funding Source URL
NIH - Extramural	None

Supporting Documentation:

Grant Information:

Project Number	Title	Start Date	Original End Date	End Date	Planned Enrollment	Actual Enrollment	Organization	Funds Obligated
R01MH119222-01	Harmonizing multi-site diffusion MRI acquisitions for neuroscientific analysis across ages and brain disorders	04/01/2019	01/31/2024	01/31/2026	Not Reported	Not Reported	BRIGHAM AND WOMENS HOSPITAL	$3,970,680.00

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.
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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.

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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.
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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.

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ID	Name	Created Date	Status	Type
No records found.

helpcenter.collection.experiments-tab

Collection - Experiments

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

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

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

Frequently Asked Questions

Can an Experiment be associated with more than one Collection?
Yes -see the “Copy” button in the bottom left when viewing an experiment. There are two actions that can be performed via this button:
1. Copy the experiment with intent for modifications.
2. Associate the experiment to the collection. No modifications can be made to the experiment.

Glossary

Experiment Status

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

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

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Shared Data:

Title	Type	Number of Subjects
Diffusion MRI Measure	Imaging	9345
Processed MRI Data	Imaging	9345

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.

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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
41451239	Create Study	Introducing QuantConn: Overcoming challenging diffusion acquisitions with harmonization.	Computational diffusion MRI. CDMRI (Workshop)	Newlin, Nancy R; Schilling, Kurt; Koudoro, Serge; Chandio, Bramsh Qamar; Kanakaraj, Praitayini; Moyer, Daniel; Kelly, Claire E; Genc, Sila; Yang, Joseph Yuan-Mou; Wu, Ye; Adluru, Nagesh; Nath, Vishwesh; Pathak, Sudhir; Schneider, Walter; Gade, Anurag; Consagra, William; Rathi, Yogesh; Hendriks, Tom; Vilanova, Anna; Chamberland, Maxime; Pieciak, Tomasz; Ciupek, Dominika; Vega, Antonio Tristán; Aja-Fernández, Santiago; Malawski, Maciej; Ouedraogo, Gani; Machnio, Julia; Thompson, Paul M; Jahanshad, Neda; Garyfallidis, Eleftherios; Landman, Bennett	January 1, 2025	Not Determined
41256884	Create Study	Millennium Pathways for Tractography: 40 grand challenges to shape the future of tractography.	ArXiv	Descoteaux, Maxime; Schilling, Kurt G; Aydogan, Dogu Baran; Beaulieu, Christian; Borra, Elena; Chamberland, Maxime; Daducci, Alessandro; Luca, Alberto De; Dell'Acqua, Flavio; Dubois, Jessica; Dyrby, Tim B; Farquharson, Shawna; Forkel, Stephanie; Froeling, Martijn; Griffa, Alessandra; Grotheer, Mareike; Guevara, Pamela; Haber, Suzanne N; Jangir, Vinod Kumar; Leemans, Alexander; Lefebvre, Joël; Lin, Ching-Po; Little, Graham; Zac Lo, Chun-Yi; Maffei, Chiara; Mayberg, Helen S; McNab, Jennifer A; Mukherjee, Pratik; O'Donnell, Lauren J; Parent, Martin; Pierpaoli, Carlo; Rheault, Francois; Rockland, Kathleen S; Roebroeck, Alard; Rokem, Ariel; Rushmore, R Jarrett; Sarubbo, Silvio; Schiavi, Simona; Sotiropoulos, Stamatios N; Szczupak, Diego; de Schotten, Michel Thiebaut; Tournier, J-Donald; Vergani, Francesco; Yuan-Mou Yang, Joseph; Zhang, Fan; Jones, Derek; Petit, Laurent	September 30, 2025	Not Determined
41104693	Create Study	Altered Cortical Gyrification Is Associated with Cortical and White Matter Microstructure in Individuals with Early Psychosis: A Multimodal Neuroimaging Study.	Schizophrenia bulletin	Sasabayashi, Daiki; Seitz-Holland, Johanna; Rathi, Yogesh; Kim, Nicholas; Cho, Kang Ik K; Mohandass, Dheshan; Billah, Tashrif; Haidar, Anastasia; Kotler, Elana; Cetin-Karayumak, Suheyla; Jacobs, Grace R; Berberich, Cornelius; Lewandowski, Kathryn E; Mesholam-Gately, Raquelle I; Wojcik, Joanne; Haaf, Moritz; Koike, Shinsuke; Hirano, Yoji; Takahashi, Tsutomu; Suzuki, Michio; Pasternak, Ofer; Keshavan, Matcheri S; Holt, Daphne; Öngür, Dost; Breier, Alan; Coleman, Michael J; Bouix, Sylvain; Shenton, Martha E; Kubicki, Marek	October 17, 2025	Not Determined
41040237	Create Study	Study of Sex Differences in the Whole Brain White Matter Using Diffusion MRI Tractography and Suprathreshold Fiber Cluster Statistics.	bioRxiv : the preprint server for biology	Zhang, Fan; Rushmore, Jarrett; Li, Yijie; Cetin-Karayumak, Suheyla; Song, Yang; Cai, Weidong; Westin, Carl-Fredrik; Levitt, James J; Makris, Nikos; Rathi, Yogesh; O'Donnell, Lauren J	September 28, 2025	Not Determined
40800747	Create Study	Fiber microstructure quantile (FMQ) regression: A novel statistical approach for analyzing white matter bundles from periphery to core.	Imaging neuroscience (Cambridge, Mass.)	Lan, Zhou; Chen, Yuqian; Rushmore, Jarrett; Zekelman, Leo; Makris, Nikos; Rathi, Yogesh; Golby, Alexandra J; Zhang, Fan; O'Donnell, Lauren J	January 1, 2025	Not Determined
40776551	Create Study	Towards an Informed Choice of Diffusion MRI Image Contrasts for Cerebellar Segmentation.	Human brain mapping	Legarreta, Jon Haitz; Lan, Zhou; Chen, Yuqian; Zhang, Fan; Yeterian, Edward H; Makris, Nikos; Rushmore, Richard J; Rathi, Yogesh; O'Donnell, Lauren J	August 1, 2025	Not Determined
40766497	Create Study	The superficial white matter in language processing: Broca''s area connections are bilaterally associated with individual performance in children and adults.	bioRxiv : the preprint server for biology	Hassanzadeh-Behbahani, Shiva; Lan, Zhou; Zekelman, Leo; Rushmore, R Jarrett; Chen, Yuqian; Xue, Tengfei; Cetin-Karayumak, Suheyla; Pieper, Steve; Tie, Yanmei; Yeterian, Edward; Golby, Alexandra J; Makris, Nikos; Zhang, Fan; Rathi, Yogesh; O'Donnell, Lauren J	August 1, 2025	Not Determined
40522497	Create Study	Think deep in the tractography game: deep learning for tractography computing and analysis.	Brain structure & function	Zhang, Fan; Théberge, Antoine; Jodoin, Pierre-Marc; Descoteaux, Maxime; O'Donnell, Lauren J	June 16, 2025	Not Determined
40193105	Create Study	TractCloud-FOV: Deep Learning-Based Robust Tractography Parcellation in Diffusion MRI With Incomplete Field of View.	Human brain mapping	Chen, Yuqian; Zekelman, Leo; Lo, Yui; Cetin-Karayumak, Suheyla; Xue, Tengfei; Rathi, Yogesh; Makris, Nikos; Zhang, Fan; Cai, Weidong; O'Donnell, Lauren J	April 1, 2025	Not Determined
40161663	Create Study	Towards an informed choice of diffusion MRI image contrasts for cerebellar segmentation.	bioRxiv : the preprint server for biology	Legarreta, Jon Haitz; Lan, Zhou; Chen, Yuqian; Zhang, Fan; Yeterian, Edward; Makris, Nikos; Rushmore, Jarrett; Rathi, Yogesh; O'Donnell, Lauren J	March 11, 2025	Not Determined
40143640	Create Study	The Shape of the Brain''s Connections Is Predictive of Cognitive Performance: An Explainable Machine Learning Study.	Human brain mapping	Lo, Yui; Chen, Yuqian; Liu, Dongnan; Liu, Wan; Zekelman, Leo; Rushmore, Jarrett; Zhang, Fan; Rathi, Yogesh; Makris, Nikos; Golby, Alexandra J; Cai, Weidong; O'Donnell, Lauren J	April 1, 2025	Not Determined
39974921	Create Study	Consistent cerebellar pathway-cognition associations across pre-adolescents & young adults: a diffusion MRI study of 9000+ participants.	bioRxiv : the preprint server for biology	Zekelman, Leo R; Cetin-Karayumak, Suheyla; Chen, Yuqian; Almeida, Melyssa; Legarreta, Jon Haitz; Rushmore, Jarrett; Pieper, Steve; Lan, Zhou; Desmond, John E; Baird, Lissa C; Makris, Nikos; Rathi, Yogesh; Zhang, Fan; Golby, Alexandra J; O'Donnell, Lauren J	February 6, 2025	Not Determined
39787735	Create Study	DDEvENet: Evidence-based ensemble learning for uncertainty-aware brain parcellation using diffusion MRI.	Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society	Li, Chenjun; Yang, Dian; Yao, Shun; Wang, Shuyue; Wu, Ye; Zhang, Le; Li, Qiannuo; Cho, Kang Ik Kevin; Seitz-Holland, Johanna; Ning, Lipeng; Legarreta, Jon Haitz; Rathi, Yogesh; Westin, Carl-Fredrik; O'Donnell, Lauren J; Sochen, Nir A; Pasternak, Ofer; Zhang, Fan	March 1, 2025	Not Determined
39606717	Create Study	MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI.	ArXiv	Newlin, Nancy R; Schilling, Kurt; Koudoro, Serge; Chandio, Bramsh Qamar; Kanakaraj, Praitayini; Moyer, Daniel; Kelly, Claire E; Genc, Sila; Chen, Jian; Yang, Joseph Yuan-Mou; Wu, Ye; He, Yifei; Zhang, Jiawei; Zeng, Qingrun; Zhang, Fan; Adluru, Nagesh; Nath, Vishwesh; Pathak, Sudhir; Schneider, Walter; Gade, Anurag; Rathi, Yogesh; Hendriks, Tom; Vilanova, Anna; Chamberland, Maxime; Pieciak, Tomasz; Ciupek, Dominika; Vega, Antonio Tristán; Aja-Fernández, Santiago; Malawski, Maciej; Ouedraogo, Gani; Machnio, Julia; Ewert, Christian; Thompson, Paul M; Jahanshad, Neda; Garyfallidis, Eleftherios; Landman, Bennett A	November 14, 2024	Not Determined
39564727	Create Study	Tractography-Based Automated Identification of Retinogeniculate Visual Pathway With Novel Microstructure-Informed Supervised Contrastive Learning.	Human brain mapping	Li, Sipei; Zhang, Wei; Yao, Shun; He, Jianzhong; Gao, Jingjing; Xue, Tengfei; Xie, Guoqiang; Chen, Yuqian; Torio, Erickson F; Feng, Yuanjing; Bastos, Dhiego C A; Rathi, Yogesh; Makris, Nikos; Kikinis, Ron; Bi, Wenya Linda; Golby, Alexandra J; O'Donnell, Lauren J; Zhang, Fan	December 1, 2024	Not Determined
39484397	Create Study	Fiber Microstructure Quantile (FMQ) Regression: A Novel Statistical Approach for Analyzing White Matter Bundles from Periphery to Core.	bioRxiv : the preprint server for biology	Lan, Zhou; Chen, Yuqian; Rushmore, Jarrett; Zekelman, Leo; Makris, Nikos; Rathi, Yogesh; Golby, Alexandra J; Zhang, Fan; O'Donnell, Lauren J	April 16, 2025	Not Determined
39392220	Create Study	Assessment of the Depiction of Superficial White Matter Using Ultra-High-Resolution Diffusion MRI.	Human brain mapping	Zhang, Fan; Chen, Yuqian; Ning, Lipeng; Rushmore, Jarrett; Liu, Qiang; Du, Mubai; Hassanzadeh-Behbahani, Shiva; Legarreta, Jon Haitz; Yeterian, Edward; Makris, Nikos; Rathi, Yogesh; O'Donnell, Lauren J	October 1, 2024	Not Determined
39234825	Create Study	Facial Nerve Tractography Using Diffusion MRI: A Comparison of Acquisition b -Values and Single- and Multifiber Tracking Strategies.	Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology	Epprecht, Lorenz; Zekelman, Leo; Reinshagen, Katherine L; Xie, Guoqiang; Norton, Isaiah; Kikinis, Ron; Makris, Nikos; Piccirelli, Marco; Huber, Alexander; Lee, Daniel J; Zhang, Fan; O'Donnell, Lauren J	October 1, 2024	Not Determined
39185598	Create Study	Deep multimodal saliency parcellation of cerebellar pathways: Linking microstructure and individual function through explainable multitask learning.	Human brain mapping	Tchetchenian, Ari; Zekelman, Leo; Chen, Yuqian; Rushmore, Jarrett; Zhang, Fan; Yeterian, Edward H; Makris, Nikos; Rathi, Yogesh; Meijering, Erik; Song, Yang; O'Donnell, Lauren J	August 15, 2024	Not Determined
39019877	Create Study	A diffusion MRI tractography atlas for concurrent white matter mapping across Eastern and Western populations.	Scientific data	Li, Yijie; Zhang, Wei; Wu, Ye; Yin, Li; Zhu, Ce; Chen, Yuqian; Cetin-Karayumak, Suheyla; Cho, Kang Ik K; Zekelman, Leo R; Rushmore, Jarrett; Rathi, Yogesh; Makris, Nikos; O'Donnell, Lauren J; Zhang, Fan	July 17, 2024	Not Determined
38458095	Create Study	TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance.	Medical image analysis	Chen, Yuqian; Zekelman, Leo R; Zhang, Chaoyi; Xue, Tengfei; Song, Yang; Makris, Nikos; Rathi, Yogesh; Golby, Alexandra J; Cai, Weidong; Zhang, Fan; O'Donnell, Lauren J	May 1, 2024	Not Determined
38413633	Create Study	Harmonized diffusion MRI data and white matter measures from the Adolescent Brain Cognitive Development Study.	Scientific data	Cetin-Karayumak, Suheyla; Zhang, Fan; Zurrin, Ryan; Billah, Tashrif; Zekelman, Leo; Makris, Nikos; Pieper, Steve; O'Donnell, Lauren J; Rathi, Yogesh	February 27, 2024	Not Determined
37943635	Create Study	DDParcel: Deep Learning Anatomical Brain Parcellation From Diffusion MRI.	IEEE transactions on medical imaging	Zhang, Fan; Cho, Kang Ik Kevin; Seitz-Holland, Johanna; Ning, Lipeng; Legarreta, Jon Haitz; Rathi, Yogesh; Westin, Carl-Fredrik; O'Donnell, Lauren J; Pasternak, Ofer	March 1, 2024	Not Determined
37792280	Create Study	Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods.	Human brain mapping	He, Jianzhong; Zhang, Fan; Pan, Yiang; Feng, Yuanjing; Rushmore, Jarrett; Torio, Erickson; Rathi, Yogesh; Makris, Nikos; Kikinis, Ron; Golby, Alexandra J; O'Donnell, Lauren J	December 1, 2023	Not Determined
37469213	Create Study	Exploring the impact of hippocampal sclerosis on white matter tracts and memory in individuals with mesial temporal lobe epilepsy.	Epilepsia open	Zanao, Tamires A; Seitz-Holland, Johanna; O'Donnell, Lauren J; Zhang, Fan; Rathi, Yogesh; Lopes, Tátila M; Pimentel-Silva, Luciana Ramalho; Yassuda, Clarissa L; Makris, Nikos; Shenton, Martha E; Bouix, Sylvain; Lyall, Amanda E; Cendes, Fernando	September 1, 2023	Not Determined

helpcenter.collection.publications-tab

Collection - Publications

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

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

Frequently Asked Questions

How can I determine if a publication is relevant?

Publications are considered relevant to a collection when the data shared is directly related to the project or collection.
Where does the NDA get the publications?

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

Glossary

Create Study

A link to the Create an NDA Study page that can be clicked to start creating an NDA Study with information such as the title, journal and authors automatically populated.
Not Determined Publication

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

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

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

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

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

Contact NDA Help Desk

Data Expected List: Mandatory Data Structures

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

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

Data Expected	Targeted Enrollment	Initial Submission	Subjects Submitted	Initial Share	Subjects Shared	Status
Research Subject and Pedigree	1	02/15/2021	0	12/17/2021	0	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
Processed MRI Data	9,345	10/25/2022	9,345	02/25/2023	9,345	Approved
Diffusion MRI	9,345	06/06/2022	0	01/01/2025	0	Approved
ABCD_DiffusionMeasures	9,345	07/15/2022	9,345	11/15/2022	9,345	Approved

Structure not yet defined

No Status history for this Data Expected has been recorded yet

helpcenter.collection.data-expected-tab

Collection - Data Expected

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

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

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

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

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

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

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

Frequently Asked Questions

What is an NDA Data Structure?

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

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

Glossary

Analyzed Data

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

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

A defined organization and group of Data Elements to represent an electronic definition of a measure, assessment, questionnaire, or collection of data points. Data structures that have been defined in the NDA Data Dictionary are available at https://nda.nih.gov/general-query.html?q=query=data-structure
Data Structure Category

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

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

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

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

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

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

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

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

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

Contact NDA Help Desk

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

Associated Studies

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

Study NameFilter by Study Name	DOIFilter by DOI	AbstractFilter by Abstract	Collection/Study SubjectsFilter by Collection/Study Subjects	Data UsageFilter by Data Usage	StateFilter by State
Prenatal substance exposure and child health: Understanding the role of environmental factors, genetics, and brain development	10.15154/1528317	This current study examined the interactions of 4 most common prenatal substance exposures (PSE), which are coffee, alcohol, tobacco and cannabis with poly-environmental and genetic factors and is the first to establish the comprehensive pathway map of the PSE in the context of both poly-environmental and genetic factors and adolescent brain structure. Using the large cohort from the ABCD study, this study not only demonstrates that PSE is widely associated with offspring health, but also elucidates the existence of possible modifiable factors for those who have already had the PSE. Associations of prenatal alcohol exposure with more physical and psychological impairment, impulsivity, and better cognitive performance, and associations of prenatal coffee exposure with more externalizing and total problems remained significant after adjustment for poly-environmental and -genetic risks while associations of prenatal marijuana/tobacco exposure diminished. While prenatal alcohol exposure was associated with a larger total cortical volume and regional volumes, prenatal tobacco exposure was associated with a smaller total cortical volume and surface area, smaller regional volumes and surface areas. Prenatal coffee exposure was associated with larger postcentral gyrus volume, smaller regional volume and surface area in the pericalcarine cortex, thinner superior frontal gyrus and rostral middle frontal gyrus, thicker right lingual gyrus and isthmus-cingulate cortex.Of the four PSE, environmental factors contributed to more health associations of prenatal tobacco exposure via moderation and mediation, while genetic factors confounded more health associations of prenatal marijuana exposure. The brain mediation analysis found that at baseline, cortical volume in the right middle temporal gyrus mediated the association of prenatal alcohol exposure with externalizing problems, whereas cortical volume in the right postcentral gyrus mediated the association of prenatal coffee exposure with externalizing problems.	9345/11878	Secondary Analysis	Shared
Comparison Between Gradients and Parcellations for Functional Connectivity Prediction of Behavior	10.15154/1528046	Resting-state functional connectivity (RSFC) is widely used to predict behavioral measures. To predict behavioral measures, representing RSFC with parcellations and gradients are the two most popular approaches. Here, we compare parcellation and gradient approaches for RSFC-based prediction of a broad range of behavioral measures in the Human Connectome Project (HCP) and Adolescent Brain Cognitive Development (ABCD) datasets. Among the parcellation approaches, we consider group-average “hard” parcellations (Schaefer et al., 2018), individual-specific “hard” parcellations (Kong et al., 2021a), and an individual-specific “soft” parcellation (spatial independent component analysis with dual regression; Beckmann et al., 2009). For gradient approaches, we consider the well-known principal gradients (Margulies et al., 2016) and the local gradient approach that detects local RSFC changes (Laumann et al., 2015). Across two regression algorithms, individual-specific hard-parcellation performs the best in the HCP dataset, while the principal gradients, spatial independent component analysis and group-average “hard” parcellations exhibit similar performance. On the other hand, principal gradients and all parcellation approaches perform similarly in the ABCD dataset. Across both datasets, local gradients perform the worst. Finally, we find that the principal gradient approach requires at least 40 to 60 gradients to perform as well as parcellation approaches. While most principal gradient studies utilize a single gradient, our results suggest that incorporating higher order gradients can provide significant behaviorally relevant information. Future work will consider the inclusion of additional parcellation and gradient approaches for comparison.	1409/1476	Secondary Analysis	Shared
Lifestyle Factors Counteract the Neurodevelopmental Impact of Genetic Risk for Accelerated Brain Aging in Adolescence	10.15154/exqx-wm52	Background The transition from childhood to adolescence is characterised by enhanced neural plasticity and a consequent susceptibility to both beneficial and adverse aspects of one’s milieu. Methods To understand the implications of the interplay between protective and risk-enhancing factors, we analysed longitudinal data from the Adolescent Brain and Cognitive Development study (N = 834; 394 female). We probed the maturational correlates of positive lifestyle variables (friendships, parental warmth, school engagement, physical exercise, healthy nutrition) and of genetic vulnerability to neuropsychiatric disorders (Major Depressive Disorder, Alzheimer’s Disease, Anxiety Disorders, Bipolar Disorder, Schizophrenia), and further sought to elucidate their implications for psychological well-being. Results Genetic risk factors and lifestyle buffers showed divergent relationships with later attentional and interpersonal problems. These effects were mediated by distinguishable functional neurodevelopmental deviations spanning the limbic, default mode, visual and control systems. Specifically, greater genetic vulnerability was associated with alterations in the normative maturation of areas rich in dopamine (D2), glutamate and serotonin receptors, and of areas with stronger expression of astrocytic and microglial genes, a molecular signature implicated in the brain disorders discussed here. Greater availability of lifestyle buffers predicted deviations in the normative functional development of higher density GABA-ergic receptor regions. The two profiles of neurodevelopmental alterations showed complementary roles in protection against psychopathology, which varied with environmental stress levels. Conclusions Our results underscore the importance of educational involvement and healthy nutrition in attenuating the neurodevelopmental sequelae of genetic risk factors. They also underscore the importance of characterising early life biomarkers associated with adult-onset pathologies.	834/843	Secondary Analysis	Shared

* Data not on individual level

helpcenter.collection.associated-studies-tab

Collection - Associated Studies

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

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

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

Frequently Asked Questions

How do I associate a study to my collection?

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

Glossary

Associated Studies Tab

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

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