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.

Use/Modify Existing Data Structure

Request New Data Structure

Targeted Enrollment:

Initial Submission Date:

Initial Share Date:

Data Structure Search:

Data Structures:

Submit

Request Submission Exemption

Not Eligible

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

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

Collection Updated

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

[CMS] Error

[CMS]

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

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

Data Expected Item	Original Sharing Date	New Sharing Date

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

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DCAN Labs ABCD-BIDS Community Collection (ABCC) #3165

General
Experiments (4)
Shared Data
Publications (107)
Data Expected (2)
Associated Studies (42)

Collection Title	Collection Investigators	Collection Description
Collection Title:	DCAN Labs ABCD-BIDS Community Collection (ABCC)
Collection Investigators:	Damien Fair
Collection Description:	The ABCD-BIDS Community Collection (ABCC) from the Developmental Cognition and Neuroimaging (DCAN) Labs contains a regularly updated dataset of ABCD Brain Imaging Data Structure (BIDS) version 1.2.0 pipeline inputs and derivatives. Source data passed initial acquisition quality control from the ABCD Data Analysis and Informatics Resource Center (DAIRC) and were processed by DCAN Labs. The input DICOM data to this BIDS version 1.2.0 (https://www.nature.com/articles/sdata201644) data collection were retrieved from the NIMH Data Archive (NDA) share of ABCD fast-track data (https://nda.nih.gov/edit_collection.html?id=2573) BIDS input data were converted from DICOMs using Dcm2Bids (https://github.com/cbedetti/Dcm2Bids). BIDS derivatives data were derived from the DCAN Labs ABCD-BIDS MRI processing pipeline which outputs Human Connectome Project (HCP) Minimal Preprocessing Pipelines-style data in both volume and surface spaces (https://doi.org/10.5281/zenodo.2587210, https://doi.org/10.1016/j.neuroimage.2013.04.127). This collection is independent from ABCD Data Collection 2573. Users may access ABCD DICOM files via the ABCD fast-track imaging data release in Collection 2573. Read the live online documentation for details about data currently available at https://collection3165.readthedocs.io.
Data Repository:	Adolescent Brain Cognitive Development
Permission Group:
Collection Creation Date:	05/09/2019
Collection Phase:	Funding Completed
Collection Sub-Phase:	Close Out
Blinded Clinical Trial:	No
Total Funded Amount:	$1,618,893.00
Subjects Shared:	10,073

{"values":[]}

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Funding Sources:

Funding Source Name	Funding Source URL
NIH - Extramural	None

Supporting Documentation:

File Name	File Type	Description	Audience
derivatives_qc_v1.0.1.zip	Other	The BIDS Quality Control Files version 1.0.1. For full documentation, see here: https://collection3165.readthedocs.io/en/stable/recommendations/	Qualified Researchers
https://collection3165.readthedocs.io	Background	The online version of the documentation with built-in navigation and search.	General Public
participants_v1.0.3.zip	Other	The most up to date version of the BIDS Participants Files and Matched Groups. Brain Coverage information will be added in at a later date. For full documentation, see here: https://collection3165.readthedocs.io/en/stable/recommendations/	Qualified Researchers

Grant Information:

Project Number	Project Title	Start Date	End Date	Planned Enrollment	Actual Enrollment	Organization	Funds Obligated
R01MH113550-01	Longitudinal Mapping of Network Development Underlying Executive Dysfunction in Adolescence	06/01/2018	02/28/2023	140	141	UNIVERSITY OF PENNSYLVANIA	$1,618,893.00

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
648	ABCD MID	04/17/2017	Approved	fMRI
649	ABCD REST	04/18/2017	Approved	fMRI
650	ABCD SST	04/18/2017	Approved	fMRI
651	ABCD NBACK	04/18/2017	Approved	fMRI

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
Imaging Collection	Imaging	10038
Processed MRI Data	Imaging	9748

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
39417125	Create Study	Association of Anxiety with Uncinate Fasciculus Lesion Burden in Multiple Sclerosis.	medRxiv : the preprint server for health sciences	Baller, Erica B; Luo, Audrey C; Schindler, Matthew K; Cooper, Elena C; Pecsok, Margaret K; Cieslak, Matthew C; Martin, Melissa Lynne; Bar-Or, Amit; Elahi, Ameena; Perrone, Christopher M; Reid, Donovan; Spangler, Bailey C; Satterthwaite, Theodore D; Shinohara, Russell T	October 9, 2024	Not Determined
39416182	Create Study	Changes in brain connectivity and neurovascular dynamics during dexmedetomidine-induced loss of consciousness.	bioRxiv : the preprint server for biology	Fotiadis, Panagiotis; McKinstry-Wu, Andrew R; Weinstein, Sarah M; Cook, Philip A; Elliott, Mark; Cieslak, Matthew; Duda, Jeffrey T; Satterthwaite, Theodore D; Shinohara, Russell T; Proekt, Alexander; Kelz, Max B; Detre, John A; Bassett, Dani S	October 7, 2024	Not Determined
39399003	Create Study	Polygenic Risk Underlies Youth Psychopathology and Personalized Functional Brain Network Topography.	medRxiv : the preprint server for health sciences	Sun, Kevin Y; Schmitt, J Eric; Moore, Tyler M; Barzilay, Ran; Almasy, Laura; Schultz, Laura M; Mackey, Allyson P; Kafadar, Eren; Sha, Zhiqiang; Seidlitz, Jakob; Mallard, Travis T; Cui, Zaixu; Li, Hongming; Fan, Yong; Fair, Damien A; Satterthwaite, Theodore D; Keller, Arielle S; Alexander-Bloch, Aaron	September 27, 2024	Not Determined
39386637	Create Study	Reproducible Sex Differences in Personalized Functional Network Topography in Youth.	bioRxiv : the preprint server for biology	Keller, Arielle S; Sun, Kevin Y; Francisco, Ashley; Robinson, Heather; Beydler, Emily; Bassett, Dani S; Cieslak, Matthew; Cui, Zaixu; Davatzikos, Christos; Fan, Yong; Gardner, Margaret; Kishton, Rachel; Kornfield, Sara L; Larsen, Bart; Li, Hongming; Linder, Isabella; Pines, Adam; Pritschet, Laura; Raznahan, Armin; Roalf, David R; Seidlitz, Jakob; Shafiei, Golia; Shinohara, Russell T; Wolf, Daniel H; Alexander-Bloch, Aaron; Satterthwaite, Theodore D; Shanmugan, Sheila	September 29, 2024	Not Determined
39075309	Create Study	A network control theory pipeline for studying the dynamics of the structural connectome.	Nature protocols	Parkes, Linden; Kim, Jason Z; Stiso, Jennifer; Brynildsen, Julia K; Cieslak, Matthew; Covitz, Sydney; Gur, Raquel E; Gur, Ruben C; Pasqualetti, Fabio; Shinohara, Russell T; Zhou, Dale; Satterthwaite, Theodore D; Bassett, Dani S	July 29, 2024	Not Determined
38979274	Create Study	Mapping Individual Differences in Intermodal Coupling in Neurodevelopment.	bioRxiv : the preprint server for biology	Weinstein, Sarah M; Tu, Danni; Hu, Fengling; Pan, Ruyi; Zhang, Rongqian; Vandekar, Simon N; Baller, Erica B; Gur, Ruben C; Gur, Raquel E; Alexander-Bloch, Aaron F; Satterthwaite, Theodore D; Park, Jun Young	June 28, 2024	Not Determined
38915591	Create Study	A sensorimotor-association axis of thalamocortical connection development.	bioRxiv : the preprint server for biology	Sydnor, Valerie J; Bagautdinova, Joëlle; Larsen, Bart; Arcaro, Michael J; Barch, Deanna M; Bassett, Dani S; Alexander-Bloch, Aaron F; Cook, Philip A; Covitz, Sydney; Franco, Alexandre R; Gur, Raquel E; Gur, Ruben C; Mackey, Allyson P; Mehta, Kahini; Meisler, Steven L; Milham, Michael P; Moore, Tyler M; Müller, Eli J; Roalf, David R; Salo, Taylor; Schubiner, Gabriel; Seidlitz, Jakob; Shinohara, Russell T; Shine, James M; Yeh, Fang-Cheng; Cieslak, Matthew; Satterthwaite, Theodore D	June 14, 2024	Not Determined
38878300	Create Study	Network enrichment significance testing in brain-phenotype association studies.	Human brain mapping	Weinstein, Sarah M; Vandekar, Simon N; Li, Bin; Alexander-Bloch, Aaron F; Raznahan, Armin; Li, Mingyao; Gur, Raquel E; Gur, Ruben C; Roalf, David R; Park, Min Tae M; Chakravarty, Mallar; Baller, Erica B; Linn, Kristin A; Satterthwaite, Theodore D; Shinohara, Russell T	June 1, 2024	Not Determined
38814872	Create Study	In vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth.	Proceedings of the National Academy of Sciences of the United States of America	Zhang, Shaoshi; Larsen, Bart; Sydnor, Valerie J; Zeng, Tianchu; An, Lijun; Yan, Xiaoxuan; Kong, Ru; Kong, Xiaolu; Gur, Ruben C; Gur, Raquel E; Moore, Tyler M; Wolf, Daniel H; Holmes, Avram J; Xie, Yapei; Zhou, Juan Helen; Fortier, Marielle V; Tan, Ai Peng; Gluckman, Peter; Chong, Yap Seng; Meaney, Michael J; Deco, Gustavo; Satterthwaite, Theodore D; Yeo, B T Thomas	June 4, 2024	Not Determined
38664387	Create Study	Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy.	Nature communications	Luo, Audrey C; Sydnor, Valerie J; Pines, Adam; Larsen, Bart; Alexander-Bloch, Aaron F; Cieslak, Matthew; Covitz, Sydney; Chen, Andrew A; Esper, Nathalia Bianchini; Feczko, Eric; Franco, Alexandre R; Gur, Raquel E; Gur, Ruben C; Houghton, Audrey; Hu, Fengling; Keller, Arielle S; Kiar, Gregory; Mehta, Kahini; Salum, Giovanni A; Tapera, Tinashe; Xu, Ting; Zhao, Chenying; Salo, Taylor; Fair, Damien A; Shinohara, Russell T; Milham, Michael P; Satterthwaite, Theodore D	April 25, 2024	Not Determined
38586012	Create Study	In-vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth.	bioRxiv : the preprint server for biology	Zhang, Shaoshi; Larsen, Bart; Sydnor, Valerie J; Zeng, Tianchu; An, Lijun; Yan, Xiaoxuan; Kong, Ru; Kong, Xiaolu; Gur, Ruben C; Gur, Raquel E; Moore, Tyler M; Wolf, Daniel H; Holmes, Avram J; Xie, Yapei; Zhou, Juan Helen; Fortier, Marielle V; Tan, Ai Peng; Gluckman, Peter; Chong, Yap Seng; Meaney, Michael J; Deco, Gustavo; Satterthwaite, Theodore D; Yeo, B T Thomas	March 28, 2024	Not Determined
38520359	Create Study	A practical evaluation of measures derived from compressed sensing diffusion spectrum imaging.	Human brain mapping	Radhakrishnan, Hamsanandini; Zhao, Chenying; Sydnor, Valerie J; Baller, Erica B; Cook, Philip A; Fair, Damien A; Giesbrecht, Barry; Larsen, Bart; Murtha, Kristin; Roalf, David R; Rush-Goebel, Sage; Shinohara, Russell T; Shou, Haochang; Tisdall, M Dylan; Vettel, Jean M; Grafton, Scott T; Cieslak, Matthew; Satterthwaite, Theodore D	April 1, 2024	Not Determined
38460580	Create Study	Generalizable Links Between Borderline Personality Traits and Functional Connectivity.	Biological psychiatry	Shafiei, Golia; Keller, Arielle S; Bertolero, Maxwell; Shanmugan, Sheila; Bassett, Dani S; Chen, Andrew A; Covitz, Sydney; Houghton, Audrey; Luo, Audrey; Mehta, Kahini; Salo, Taylor; Shinohara, Russell T; Fair, Damien; Hallquist, Michael N; Satterthwaite, Theodore D	September 15, 2024	Not Determined
38339908	Create Study	Diffusion MRI head motion correction methods are highly accurate but impacted by denoising and sampling scheme.	Human brain mapping	Cieslak, Matthew; Cook, Philip A; Shafiei, Golia; Tapera, Tinashe M; Radhakrishnan, Hamsanandini; Elliott, Mark; Roalf, David R; Oathes, Desmond J; Bassett, Dani S; Tisdall, M Dylan; Rokem, Ariel; Grafton, Scott T; Satterthwaite, Theodore D	February 1, 2024	Not Determined
38110396	Create Study	Personalized functional brain network topography is associated with individual differences in youth cognition.	Nature communications	Keller, Arielle S; Pines, Adam R; Shanmugan, Sheila; Sydnor, Valerie J; Cui, Zaixu; Bertolero, Maxwell A; Barzilay, Ran; Alexander-Bloch, Aaron F; Byington, Nora; Chen, Andrew; Conan, Gregory M; Davatzikos, Christos; Feczko, Eric; Hendrickson, Timothy J; Houghton, Audrey; Larsen, Bart; Li, Hongming; Miranda-Dominguez, Oscar; Roalf, David R; Perrone, Anders; Shetty, Alisha; Shinohara, Russell T; Fan, Yong; Fair, Damien A; Satterthwaite, Theodore D	December 18, 2023	Not Determined
38045258	Create Study	XCP-D: A Robust Pipeline for the post-processing of fMRI data.	bioRxiv : the preprint server for biology	Mehta, Kahini; Salo, Taylor; Madison, Thomas; Adebimpe, Azeez; Bassett, Danielle S; Bertolero, Max; Cieslak, Matthew; Covitz, Sydney; Houghton, Audrey; Keller, Arielle S; Luo, Audrey; Miranda-Dominguez, Oscar; Nelson, Steve M; Shafiei, Golia; Shanmugan, Sheila; Shinohara, Russell T; Sydnor, Valerie J; Feczko, Eric; Fair, Damien A; Satterthwaite, Theodore D	November 21, 2023	Not Determined
38014137	Create Study	Network Enrichment Significance Testing in Brain-Phenotype Association Studies.	bioRxiv : the preprint server for biology	Weinstein, Sarah M; Vandekar, Simon N; Alexander-Bloch, Aaron F; Raznahan, Armin; Li, Mingyao; Gur, Raquel E; Gur, Ruben C; Roalf, David R; Park, Min Tae M; Chakravarty, Mallar; Baller, Erica B; Linn, Kristin A; Satterthwaite, Theodore D; Shinohara, Russell T	November 13, 2023	Not Determined
37995188	Create Study	Development of white matter fiber covariance networks supports executive function in youth.	Cell reports	Bagautdinova, Joëlle; Bourque, Josiane; Sydnor, Valerie J; Cieslak, Matthew; Alexander-Bloch, Aaron F; Bertolero, Maxwell A; Cook, Philip A; Gur, Raquel E; Gur, Ruben C; Hu, Fengling; Larsen, Bart; Moore, Tyler M; Radhakrishnan, Hamsanandini; Roalf, David R; Shinohara, Russel T; Tapera, Tinashe M; Zhao, Chenying; Sotiras, Aristeidis; Davatzikos, Christos; Satterthwaite, Theodore D	December 26, 2023	Not Determined
37981178	Create Study	Mapping the Relationship of White Matter Lesions to Depression in Multiple Sclerosis.	Biological psychiatry	Baller, Erica B; Sweeney, Elizabeth M; Cieslak, Matthew; Robert-Fitzgerald, Timothy; Covitz, Sydney C; Martin, Melissa L; Schindler, Matthew K; Bar-Or, Amit; Elahi, Ameena; Larsen, Bart S; Manning, Abigail R; Markowitz, Clyde E; Perrone, Christopher M; Rautman, Victoria; Seitz, Madeleine M; Detre, John A; Fox, Michael D; Shinohara, Russell T; Satterthwaite, Theodore D	June 15, 2024	Not Determined
37963017	Create Study	The molecular genetic landscape of human brain size variation.	Cell reports	Seidlitz, Jakob; Mallard, Travis T; Vogel, Jacob W; Lee, Younga H; Warrier, Varun; Ball, Gareth; Hansson, Oskar; Hernandez, Leanna M; Mandal, Ayan S; Wagstyl, Konrad; Lombardo, Michael V; Courchesne, Eric; Glessner, Joseph T; Satterthwaite, Theodore D; Bethlehem, Richard A I; Bernstock, Joshua D; Lifespan Brain Chart Consortium; Tasaki, Shinya; Ng, Bernard; Gaiteri, Chris; Smoller, Jordan W; Ge, Tian; Gur, Raquel E; Gandal, Michael J; Alexander-Bloch, Aaron F	November 28, 2023	Not Determined
37777569	Create Study	Myelination and excitation-inhibition balance synergistically shape structure-function coupling across the human cortex.	Nature communications	Fotiadis, Panagiotis; Cieslak, Matthew; He, Xiaosong; Caciagli, Lorenzo; Ouellet, Mathieu; Satterthwaite, Theodore D; Shinohara, Russell T; Bassett, Dani S	September 30, 2023	Not Determined
37696094	Create Study	Evaluation of a new intrinsic and extrinsic motivation scale in youth with psychosis spectrum symptoms.	Comprehensive psychiatry	Didier, Paige R; Moore, Tyler M; Calkins, Monica E; Prettyman, Greer; Levinson, Tess; Savage, Chloe; de Moraes Leme, Luis Fernando Viegas; Kohler, Christian G; Kable, Joseph; Satterthwaite, Theodore; Gur, Ruben C; Gur, Raquel E; Wolf, Daniel H	November 1, 2023	Not Determined
37662395	Create Study	Using network control theory to study the dynamics of the structural connectome.	bioRxiv : the preprint server for biology	Parkes, Linden; Kim, Jason Z; Stiso, Jennifer; Brynildsen, Julia K; Cieslak, Matthew; Covitz, Sydney; Gur, Raquel E; Gur, Ruben C; Pasqualetti, Fabio; Shinohara, Russell T; Zhou, Dale; Satterthwaite, Theodore D; Bassett, Dani S	August 24, 2023	Not Determined
37662311	Create Study	Generalizable links between symptoms of borderline personality disorder and functional connectivity.	bioRxiv : the preprint server for biology	Shafiei, Golia; Keller, Arielle S; Bertolero, Maxwell; Shanmugan, Sheila; Bassett, Dani S; Chen, Andrew A; Covitz, Sydney; Houghton, Audrey; Luo, Audrey; Mehta, Kahini; Salo, Taylor; Shinohara, Russell T; Fair, Damien; Hallquist, Michael N; Satterthwaite, Theodore D	August 21, 2023	Not Determined
37645999	Create Study	A reproducible and generalizable software workflow for analysis of large-scale neuroimaging data collections using BIDS Apps.	bioRxiv : the preprint server for biology	Zhao, Chenying; Jarecka, Dorota; Covitz, Sydney; Chen, Yibei; Eickhoff, Simon B; Fair, Damien A; Franco, Alexandre R; Halchenko, Yaroslav O; Hendrickson, Timothy J; Hoffstaedter, Felix; Houghton, Audrey; Kiar, Gregory; Macdonald, Austin; Mehta, Kahini; Milham, Michael P; Salo, Taylor; Hanke, Michael; Ghosh, Satrajit S; Cieslak, Matthew; Satterthwaite, Theodore D	August 18, 2023	Not Determined
37643932	Create Study	A critical period plasticity framework for the sensorimotor-association axis of cortical neurodevelopment.	Trends in neurosciences	Larsen, Bart; Sydnor, Valerie J; Keller, Arielle S; Yeo, B T Thomas; Satterthwaite, Theodore D	October 1, 2023	Not Determined
37503017	Create Study	Regression and Alignment for Functional Data and Network Topology.	bioRxiv : the preprint server for biology	Tu, Danni; Wrobel, Julia; Satterthwaite, Theodore D; Goldsmith, Jeff; Gur, Ruben C; Gur, Raquel E; Gertheiss, Jan; Bassett, Dani S; Shinohara, Russell T	February 18, 2024	Not Determined
37398183	Create Study	Mapping the relationship of white matter lesions to depression in multiple sclerosis.	medRxiv : the preprint server for health sciences	Baller, Erica B; Sweeney, Elizabeth M; Cieslak, Matthew C; Robert-Fitzgerald, Timothy; Covitz, Sydney C; Martin, Melissa L; Schindler, Matthew K; Bar-Or, Amit; Elahi, Ameena; Larsen, Bart S; Manning, Abigail R; Markowitz, Clyde E; Perrone, Christopher M; Rautman, Victoria; Seitz, Madeleine M; Detre, John A; Fox, Michael D; Shinohara, Russell T; Satterthwaite, Theodore D	June 12, 2023	Not Determined
37353585	Create Study	Alprazolam modulates persistence energy during emotion processing in first-degree relatives of individuals with schizophrenia: a network control study.	Molecular psychiatry	Mahadevan, Arun S; Cornblath, Eli J; Lydon-Staley, David M; Zhou, Dale; Parkes, Linden; Larsen, Bart; Adebimpe, Azeez; Kahn, Ari E; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Wolf, Daniel H; Bassett, Dani S	August 1, 2023	Not Determined
37327696	Create Study	Individual differences in delay discounting are associated with dorsal prefrontal cortex connectivity in children, adolescents, and adults.	Developmental cognitive neuroscience	Mehta, Kahini; Pines, Adam; Adebimpe, Azeez; Larsen, Bart; Bassett, Danielle S; Calkins, Monica E; Baller, Erica B; Gell, Martin; Patrick, Lauren M; Shafiei, Golia; Gur, Raquel E; Gur, Ruben C; Roalf, David R; Romer, Daniel; Wolf, Daniel H; Kable, Joseph W; Satterthwaite, Theodore D	August 1, 2023	Not Determined
37146760	Create Study	Development of Iron Status Measures during Youth: Associations with Sex, Neighborhood Socioeconomic Status, Cognitive Performance, and Brain Structure.	The American journal of clinical nutrition	Larsen, Bart; Baller, Erica B; Boucher, Alexander A; Calkins, Monica E; Laney, Nina; Moore, Tyler M; Roalf, David R; Ruparel, Kosha; Gur, Ruben C; Gur, Raquel E; Georgieff, Michael K; Satterthwaite, Theodore D	July 1, 2023	Not Determined
37084926	Create Study	Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization.	NeuroImage	Hu, Fengling; Chen, Andrew A; Horng, Hannah; Bashyam, Vishnu; Davatzikos, Christos; Alexander-Bloch, Aaron; Li, Mingyao; Shou, Haochang; Satterthwaite, Theodore D; Yu, Meichen; Shinohara, Russell T	July 1, 2023	Not Determined
37019760	Create Study	Activation of Internal Correctness Monitoring Circuitry in Youths With Psychosis Spectrum Symptoms.	Biological psychiatry. Cognitive neuroscience and neuroimaging	Levinson, Tess; Prettyman, Greer; Savage, Chloe; White, Lauren; Moore, Tyler M; Calkins, Monica E; Ruparel, Kosha; Gur, Raquel E; Gur, Ruben C; Satterthwaite, Theodore D; Wolf, Daniel H	May 1, 2023	Not Determined
37017074	Create Study	Combining mixed effects hidden Markov models with latent alternating recurrent event processes to model diurnal active-rest cycles.	Biometrics	Ren, Benny; Barnett, Ian	December 1, 2023	Not Determined
36973514	Create Study	Intrinsic activity development unfolds along a sensorimotor-association cortical axis in youth.	Nature neuroscience	Sydnor, Valerie J; Larsen, Bart; Seidlitz, Jakob; Adebimpe, Azeez; Alexander-Bloch, Aaron F; Bassett, Dani S; Bertolero, Maxwell A; Cieslak, Matthew; Covitz, Sydney; Fan, Yong; Gur, Raquel E; Gur, Ruben C; Mackey, Allyson P; Moore, Tyler M; Roalf, David R; Shinohara, Russell T; Satterthwaite, Theodore D	April 1, 2023	Not Determined
36931330	Create Study	ModelArray: An R package for statistical analysis of fixel-wise data.	NeuroImage	Zhao, Chenying; Tapera, Tinashe M; Bagautdinova, Joëlle; Bourque, Josiane; Covitz, Sydney; Gur, Raquel E; Gur, Ruben C; Larsen, Bart; Mehta, Kahini; Meisler, Steven L; Murtha, Kristin; Muschelli, John; Roalf, David R; Sydnor, Valerie J; Valcarcel, Alessandra M; Shinohara, Russell T; Cieslak, Matthew; Satterthwaite, Theodore D	May 1, 2023	Not Determined
36803653	Create Study	Development of top-down cortical propagations in youth.	Neuron	Pines, Adam; Keller, Arielle S; Larsen, Bart; Bertolero, Maxwell; Ashourvan, Arian; Bassett, Dani S; Cieslak, Matthew; Covitz, Sydney; Fan, Yong; Feczko, Eric; Houghton, Audrey; Rueter, Amanda R; Saggar, Manish; Shafiei, Golia; Tapera, Tinashe M; Vogel, Jacob; Weinstein, Sarah M; Shinohara, Russell T; Williams, Leanne M; Fair, Damien A; Satterthwaite, Theodore D	April 19, 2023	Not Determined
36798354	Create Study	Development of White Matter Fiber Covariance Networks Supports Executive Function in Youth.	bioRxiv : the preprint server for biology	Bagautdinova, Joëlle; Bourque, Josiane; Sydnor, Valerie J; Cieslak, Matt; Alexander-Bloch, Aaron F; Bertolero, Max A; Cook, Phil A; Gur, Raquel C; Gur, Ruben E; Larsen, Bart; Moore, Tyler M; Radhakrishnan, Hamsi; Roalf, David R; Shinohara, Russel T; Tapera, Tinashe M; Zhao, Chenying; Sotiras, Aristeidis; Davatzikos, Christos; Satterthwaite, Theodore D	February 10, 2023	Not Determined
36747838	Create Study	Individual Differences in Delay Discounting are Associated with Dorsal Prefrontal Cortex Connectivity in Youth.	bioRxiv : the preprint server for biology	Mehta, Kahini; Pines, Adam; Adebimpe, Azeez; Larsen, Bart; Bassett, Dani S; Calkins, Monica E; Baller, Erica; Gell, Martin; Patrick, Lauren M; Gur, Raquel E; Gur, Ruben C; Roalf, David R; Romer, Daniel; Wolf, Daniel H; Kable, Joseph W; Satterthwaite, Theodore D	January 26, 2023	Not Determined
36728904	Create Study	Within-Person Temporal Associations Among Self-Reported Physical Activity, Sleep, and Well-Being in College Students.	Psychosomatic medicine	McGowan, Amanda L; Boyd, Zachary M; Kang, Yoona; Bennett, Logan; Mucha, Peter J; Ochsner, Kevin N; Bassett, Dani S; Falk, Emily B; Lydon-Staley, David M	February 1, 2023	Not Determined
36605890	Create Study	Network controllability mediates the relationship between rigid structure and flexible dynamics.	Network neuroscience (Cambridge, Mass.)	Gu, Shi; Fotiadis, Panagiotis; Parkes, Linden; Xia, Cedric H; Gur, Ruben C; Gur, Raquel E; Roalf, David R; Satterthwaite, Theodore D; Bassett, Dani S	February 1, 2022	Not Determined
36595675	Create Study	Mindful attention promotes control of brain network dynamics for self-regulation and discontinues the past from the present.	Proceedings of the National Academy of Sciences of the United States of America	Zhou, Dale; Kang, Yoona; Cosme, Danielle; Jovanova, Mia; He, Xiaosong; Mahadevan, Arun; Ahn, Jeesung; Stanoi, Ovidia; Brynildsen, Julia K; Cooper, Nicole; Cornblath, Eli J; Parkes, Linden; Mucha, Peter J; Ochsner, Kevin N; Lydon-Staley, David M; Falk, Emily B; Bassett, Dani S	January 10, 2023	Not Determined
36437189	Create Study	Hierarchical functional system development supports executive function.	Trends in cognitive sciences	Keller, Arielle S; Sydnor, Valerie J; Pines, Adam; Fair, Damien A; Bassett, Dani S; Satterthwaite, Theodore D	February 1, 2023	Not Determined
36309332	Create Study	Spatially-enhanced clusterwise inference for testing and localizing intermodal correspondence.	NeuroImage	Weinstein, Sarah M; Vandekar, Simon N; Baller, Erica B; Tu, Danni; Adebimpe, Azeez; Tapera, Tinashe M; Gur, Ruben C; Gur, Raquel E; Detre, John A; Raznahan, Armin; Alexander-Bloch, Aaron F; Satterthwaite, Theodore D; Shinohara, Russell T; Park, Jun Young	December 1, 2022	Not Determined
36305770	Create Study	Caregiver monitoring, but not caregiver warmth, is associated with general cognition in two large sub-samples of youth.	Developmental science	Keller, Arielle S; Mackey, Allyson P; Pines, Adam; Fair, Damien; Feczko, Eric; Hoffmann, Mauricio S; Salum, Giovanni A; Barzilay, Ran; Satterthwaite, Theodore D	May 1, 2023	Not Determined
36242852	Create Study	Decision value signals in the ventromedial prefrontal cortex and motivational and hedonic symptoms across mood and psychotic disorders.	NeuroImage. Clinical	Souther, Min K; Wolf, Daniel H; Kazinka, Rebecca; Lee, Sangil; Ruparel, Kosha; Elliott, Mark A; Xu, Anna; Cieslak, Matthew; Prettyman, Greer; Satterthwaite, Theodore D; Kable, Joseph W	January 1, 2022	Not Determined
36192151	Create Study	The Age of Reason: Functional Brain Network Development during Childhood.	The Journal of neuroscience : the official journal of the Society for Neuroscience	Tooley, Ursula A; Park, Anne T; Leonard, Julia A; Boroshok, Austin L; McDermott, Cassidy L; Tisdall, Matthew D; Bassett, Dani S; Mackey, Allyson P	November 2, 2022	Not Determined
36064140	Create Study	Curation of BIDS (CuBIDS): A workflow and software package for streamlining reproducible curation of large BIDS datasets.	NeuroImage	Covitz, Sydney; Tapera, Tinashe M; Adebimpe, Azeez; Alexander-Bloch, Aaron F; Bertolero, Maxwell A; Feczko, Eric; Franco, Alexandre R; Gur, Raquel E; Gur, Ruben C; Hendrickson, Timothy; Houghton, Audrey; Mehta, Kahini; Murtha, Kristin; Perrone, Anders J; Robert-Fitzgerald, Tim; Schabdach, Jenna M; Shinohara, Russell T; Vogel, Jacob W; Zhao, Chenying; Fair, Damien A; Milham, Michael P; Cieslak, Matthew; Satterthwaite, Theodore D	November 1, 2022	Not Determined
35963892	Create Study	Neuroimaging of plasticity mechanisms in the human brain: from critical periods to psychiatric conditions.	Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology	Sydnor, Valerie J; Satterthwaite, Theodore D	January 1, 2023	Not Determined
35939696	Create Study	Sex differences in the functional topography of association networks in youth.	Proceedings of the National Academy of Sciences of the United States of America	Shanmugan, Sheila; Seidlitz, Jakob; Cui, Zaixu; Adebimpe, Azeez; Bassett, Danielle S; Bertolero, Maxwell A; Davatzikos, Christos; Fair, Damien A; Gur, Raquel E; Gur, Ruben C; Larsen, Bart; Li, Hongming; Pines, Adam; Raznahan, Armin; Roalf, David R; Shinohara, Russell T; Vogel, Jacob; Wolf, Daniel H; Fan, Yong; Alexander-Bloch, Aaron; Satterthwaite, Theodore D	August 16, 2022	Not Determined
35927072	Create Study	Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youth.	Biological psychiatry	Cui, Zaixu; Pines, Adam R; Larsen, Bart; Sydnor, Valerie J; Li, Hongming; Adebimpe, Azeez; Alexander-Bloch, Aaron F; Bassett, Dani S; Bertolero, Max; Calkins, Monica E; Davatzikos, Christos; Fair, Damien A; Gur, Ruben C; Gur, Raquel E; Moore, Tyler M; Shanmugan, Sheila; Shinohara, Russell T; Vogel, Jacob W; Xia, Cedric H; Fan, Yong; Satterthwaite, Theodore D	December 15, 2022	Not Determined
35730989	Create Study	Voxel-wise intermodal coupling analysis of two or more modalities using local covariance decomposition.	Human brain mapping	Hu, Fengling; Weinstein, Sarah M; Baller, Erica B; Valcarcel, Alessandra M; Adebimpe, Azeez; Raznahan, Armin; Roalf, David R; Robert-Fitzgerald, Timothy E; Gonzenbach, Virgilio; Gur, Ruben C; Gur, Raquel E; Vandekar, Simon; Detre, John A; Linn, Kristin A; Alexander-Bloch, Aaron; Satterthwaite, Theodore D; Shinohara, Russell T	October 15, 2022	Not Determined
35689029	Create Study	ASLPrep: a platform for processing of arterial spin labeled MRI and quantification of regional brain perfusion.	Nature methods	Adebimpe, Azeez; Bertolero, Maxwell; Dolui, Sudipto; Cieslak, Matthew; Murtha, Kristin; Baller, Erica B; Boeve, Bradley; Boxer, Adam; Butler, Ellyn R; Cook, Phil; Colcombe, Stan; Covitz, Sydney; Davatzikos, Christos; Davila, Diego G; Elliott, Mark A; Flounders, Matthew W; Franco, Alexandre R; Gur, Raquel E; Gur, Ruben C; Jaber, Basma; McMillian, Corey; ALLFTD Consortium; Milham, Michael; Mutsaerts, Henk J M M; Oathes, Desmond J; Olm, Christopher A; Phillips, Jeffrey S; Tackett, Will; Roalf, David R; Rosen, Howard; Tapera, Tinashe M; Tisdall, M Dylan; Zhou, Dale; Esteban, Oscar; Poldrack, Russell A; Detre, John A; Satterthwaite, Theodore D	June 1, 2022	Not Determined
35660803	Create Study	Mobile footprinting: linking individual distinctiveness in mobility patterns to mood, sleep, and brain functional connectivity.	Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology	Xia, Cedric Huchuan; Barnett, Ian; Tapera, Tinashe M; Adebimpe, Azeez; Baker, Justin T; Bassett, Danielle S; Brotman, Melissa A; Calkins, Monica E; Cui, Zaixu; Leibenluft, Ellen; Linguiti, Sophia; Lydon-Staley, David M; Martin, Melissa Lynne; Moore, Tyler M; Murtha, Kristin; Piiwaa, Kayla; Pines, Adam; Roalf, David R; Rush-Goebel, Sage; Wolf, Daniel H; Ungar, Lyle H; Satterthwaite, Theodore D	August 1, 2022	Not Determined
35560117	Create Study	Structural imaging studies of patients with chronic pain: an anatomical likelihood estimate meta-analysis.	Pain	Henn, Alina T; Larsen, Bart; Frahm, Lennart; Xu, Anna; Adebimpe, Azeez; Scott, J Cobb; Linguiti, Sophia; Sharma, Vaishnavi; Basbaum, Allan I; Corder, Gregory; Dworkin, Robert H; Edwards, Robert R; Woolf, Clifford J; Habel, Ute; Eickhoff, Simon B; Eickhoff, Claudia R; Wagels, Lisa; Satterthwaite, Theodore D	January 1, 2023	Not Determined
35551181	Create Study	Dissociable multi-scale patterns of development in personalized brain networks.	Nature communications	Pines, Adam R; Larsen, Bart; Cui, Zaixu; Sydnor, Valerie J; Bertolero, Maxwell A; Adebimpe, Azeez; Alexander-Bloch, Aaron F; Davatzikos, Christos; Fair, Damien A; Gur, Ruben C; Gur, Raquel E; Li, Hongming; Milham, Michael P; Moore, Tyler M; Murtha, Kristin; Parkes, Linden; Thompson-Schill, Sharon L; Shanmugan, Sheila; Shinohara, Russell T; Weinstein, Sarah M; Bassett, Danielle S; Fan, Yong; Satterthwaite, Theodore D	May 12, 2022	Not Determined
35354053	Create Study	Developmental coupling of cerebral blood flow and fMRI fluctuations in youth.	Cell reports	Baller, Erica B; Valcarcel, Alessandra M; Adebimpe, Azeez; Alexander-Bloch, Aaron; Cui, Zaixu; Gur, Ruben C; Gur, Raquel E; Larsen, Bart L; Linn, Kristin A; O'Donnell, Carly M; Pines, Adam R; Raznahan, Armin; Roalf, David R; Sydnor, Valerie J; Tapera, Tinashe M; Tisdall, M Dylan; Vandekar, Simon; Xia, Cedric H; Detre, John A; Shinohara, Russell T; Satterthwaite, Theodore D	March 29, 2022	Not Determined
35119918	Create Study	A developmental reduction of the excitation:inhibition ratio in association cortex during adolescence.	Science advances	Larsen, Bart; Cui, Zaixu; Adebimpe, Azeez; Pines, Adam; Alexander-Bloch, Aaron; Bertolero, Max; Calkins, Monica E; Gur, Raquel E; Gur, Ruben C; Mahadevan, Arun S; Moore, Tyler M; Roalf, David R; Seidlitz, Jakob; Sydnor, Valerie J; Wolf, Daniel H; Satterthwaite, Theodore D	February 4, 2022	Not Determined
34826797	Create Study	Multi-Class ASD Classification via Label Distribution Learning with Class-Shared and Class-Specific Decomposition.	Medical image analysis	Wang, Jun; Zhang, Fengyexin; Jia, Xiuyi; Wang, Xin; Zhang, Han; Ying, Shihui; Wang, Qian; Shi, Jun; Shen, Dinggang	January 1, 2022	Not Determined
34818611	Create Study	Multi-scale semi-supervised clustering of brain images: Deriving disease subtypes.	Medical image analysis	Wen, Junhao; Varol, Erdem; Sotiras, Aristeidis; Yang, Zhijian; Chand, Ganesh B; Erus, Guray; Shou, Haochang; Abdulkadir, Ahmed; Hwang, Gyujoon; Dwyer, Dominic B; Pigoni, Alessandro; Dazzan, Paola; Kahn, Rene S; Schnack, Hugo G; Zanetti, Marcus V; Meisenzahl, Eva; Busatto, Geraldo F; Crespo-Facorro, Benedicto; Rafael, Romero-Garcia; Pantelis, Christos; Wood, Stephen J; Zhuo, Chuanjun; Shinohara, Russell T; Fan, Yong; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Koutsouleris, Nikolaos; Wolf, Daniel H; Davatzikos, Christos; Alzheimer's Disease Neuroimaging Initiative	January 1, 2022	Not Determined
34686764	Create Study	Altered functional brain dynamics in chromosome 22q11.2 deletion syndrome during facial affect processing.	Molecular psychiatry	Cornblath, Eli J; Mahadevan, Arun; He, Xiaosong; Ruparel, Kosha; Lydon-Staley, David M; Moore, Tyler M; Gur, Ruben C; Zackai, Elaine H; Emanuel, Beverly; McDonald-McGinn, Donna M; Wolf, Daniel H; Satterthwaite, Theodore D; Roalf, David R; Gur, Raquel E; Bassett, Dani S	February 1, 2022	Not Determined
34667261	Create Study	Effect of mGluR2 positive allosteric modulation on frontostriatal working memory activation in schizophrenia.	Molecular psychiatry	Wolf, Daniel H; Zheng, David; Kohler, Christian; Turetsky, Bruce I; Ruparel, Kosha; Satterthwaite, Theodore D; Elliott, Mark A; March, Mary E; Cross, Alan J; Smith, Mark A; Zukin, Stephen R; Gur, Ruben C; Gur, Raquel E	February 1, 2022	Not Determined
34625567	Create Study	Relationship of ventral striatum activation during effort discounting to clinical amotivation severity in schizophrenia.	NPJ schizophrenia	Prettyman, Greer E; Kable, Joseph W; Didier, Paige; Shankar, Sheila; Satterthwaite, Theodore D; Davatzikos, Christos; Bilker, Warren B; Elliott, Mark A; Ruparel, Kosha; Wolf, Daniel H	October 8, 2021	Not Determined
34519385	Create Study	A simple permutation-based test of intermodal correspondence.	Human brain mapping	Weinstein, Sarah M; Vandekar, Simon N; Adebimpe, Azeez; Tapera, Tinashe M; Robert-Fitzgerald, Timothy; Gur, Ruben C; Gur, Raquel E; Raznahan, Armin; Satterthwaite, Theodore D; Alexander-Bloch, Aaron F; Shinohara, Russell T	November 1, 2021	Not Determined
34270921	Create Study	Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology.	Neuron	Sydnor, Valerie J; Larsen, Bart; Bassett, Danielle S; Alexander-Bloch, Aaron; Fair, Damien A; Liston, Conor; Mackey, Allyson P; Milham, Michael P; Pines, Adam; Roalf, David R; Seidlitz, Jakob; Xu, Ting; Raznahan, Armin; Satterthwaite, Theodore D	September 15, 2021	Not Determined
34239433	Create Study	FlywheelTools: Data Curation and Manipulation on the Flywheel Platform.	Frontiers in neuroinformatics	Tapera, Tinashe M; Cieslak, Matthew; Bertolero, Max; Adebimpe, Azeez; Aguirre, Geoffrey K; Butler, Ellyn R; Cook, Philip A; Davila, Diego; Elliott, Mark A; Linguiti, Sophia; Murtha, Kristin; Tackett, William; Detre, John A; Satterthwaite, Theodore D	January 1, 2021	Not Determined
34155395	Create Study	QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data.	Nature methods	Cieslak, Matthew; Cook, Philip A; He, Xiaosong; Yeh, Fang-Cheng; Dhollander, Thijs; Adebimpe, Azeez; Aguirre, Geoffrey K; Bassett, Danielle S; Betzel, Richard F; Bourque, Josiane; Cabral, Laura M; Davatzikos, Christos; Detre, John A; Earl, Eric; Elliott, Mark A; Fadnavis, Shreyas; Fair, Damien A; Foran, Will; Fotiadis, Panagiotis; Garyfallidis, Eleftherios; Giesbrecht, Barry; Gur, Ruben C; Gur, Raquel E; Kelz, Max B; Keshavan, Anisha; Larsen, Bart S; Luna, Beatriz; Mackey, Allyson P; Milham, Michael P; Oathes, Desmond J; Perrone, Anders; Pines, Adam R; Roalf, David R; Richie-Halford, Adam; Rokem, Ariel; Sydnor, Valerie J; Tapera, Tinashe M; Tooley, Ursula A; Vettel, Jean M; Yeatman, Jason D; Grafton, Scott T; Satterthwaite, Theodore D	July 1, 2021	Not Determined
34099190	Create Study	Network Controllability in Transmodal Cortex Predicts Positive Psychosis Spectrum Symptoms.	Biological psychiatry	Parkes, Linden; Moore, Tyler M; Calkins, Monica E; Cieslak, Matthew; Roalf, David R; Wolf, Daniel H; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Bassett, Danielle S	September 15, 2021	Not Determined
33242721	Create Study	Towards precise resting-state fMRI biomarkers in psychiatry: synthesizing developments in transdiagnostic research, dimensional models of psychopathology, and normative neurodevelopment.	Current opinion in neurobiology	Parkes, Linden; Satterthwaite, Theodore D; Bassett, Danielle S	December 1, 2020	Not Determined
33119049	Create Study	Structural and Functional Brain Parameters Related to Cognitive Performance Across Development: Replication and Extension of the Parieto-Frontal Integration Theory in a Single Sample.	Cerebral cortex (New York, N.Y. : 1991)	Gur, Ruben C; Butler, Ellyn R; Moore, Tyler M; Rosen, Adon F G; Ruparel, Kosha; Satterthwaite, Theodore D; Roalf, David R; Gennatas, Efstathios D; Bilker, Warren B; Shinohara, Russell T; Port, Allison; Elliott, Mark A; Verma, Ragini; Davatzikos, Christos; Wolf, Daniel H; Detre, John A; Gur, Raquel E	February 5, 2021	Not Determined
33007777	Create Study	Neurocognitive and functional heterogeneity in depressed youth.	Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology	Baller, Erica B; Kaczkurkin, Antonia N; Sotiras, Aristeidis; Adebimpe, Azeez; Bassett, Danielle S; Calkins, Monica E; Chand, Ganesh B; Cui, Zaixu; Gur, Raquel E; Gur, Ruben C; Linn, Kristin A; Moore, Tyler M; Roalf, David R; Varol, Erdem; Wolf, Daniel H; Xia, Cedric H; Davatzikos, Christos; Satterthwaite, Theodore D	March 1, 2021	Not Determined
32563173	Create Study	Impact of childhood adversity on network reconfiguration dynamics during working memory in hypogonadal women.	Psychoneuroendocrinology	Shanmugan, Sheila; Cao, Wen; Satterthwaite, Theodore D; Sammel, Mary D; Ashourvan, Arian; Bassett, Danielle S; Ruparel, Kosha; Gur, Ruben C; Epperson, C Neill; Loughead, James	September 1, 2020	Not Determined
32553194	Create Study	Parsing Psychiatric Heterogeneity Through Common and Unique Circuit-Level Deficits.	Biological psychiatry	Satterthwaite, Theodore D; Feczko, Eric; Kaczkurkin, Antonia N; Fair, Damien A	July 1, 2020	Not Determined
32541774	Create Study	Multimodal network dynamics underpinning working memory.	Nature communications	Murphy, Andrew C; Bertolero, Maxwell A; Papadopoulos, Lia; Lydon-Staley, David M; Bassett, Danielle S	June 15, 2020	Not Determined
32510347	Create Study	Leveraging multi-shell diffusion for studies of brain development in youth and young adulthood.	Developmental cognitive neuroscience	Pines, Adam R; Cieslak, Matthew; Larsen, Bart; Baum, Graham L; Cook, Philip A; Adebimpe, Azeez; Dávila, Diego G; Elliott, Mark A; Jirsaraie, Robert; Murtha, Kristin; Oathes, Desmond J; Piiwaa, Kayla; Rosen, Adon F G; Rush, Sage; Shinohara, Russell T; Bassett, Danielle S; Roalf, David R; Satterthwaite, Theodore D	June 1, 2020	Not Determined
32444827	Create Study	Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands.	Communications biology	Cornblath, Eli J; Ashourvan, Arian; Kim, Jason Z; Betzel, Richard F; Ciric, Rastko; Adebimpe, Azeez; Baum, Graham L; He, Xiaosong; Ruparel, Kosha; Moore, Tyler M; Gur, Ruben C; Gur, Raquel E; Shinohara, Russell T; Roalf, David R; Satterthwaite, Theodore D; Bassett, Danielle S	May 22, 2020	Not Determined
32441854	Create Study	On the Nature of Explanations Offered by Network Science: A Perspective From and for Practicing Neuroscientists.	Topics in cognitive science	Bertolero, Maxwell A; Bassett, Danielle S	October 1, 2020	Not Determined
32278095	Create Study	Finding the needle in a high-dimensional haystack: Canonical correlation analysis for neuroscientists.	NeuroImage	Wang, Hao-Ting; Smallwood, Jonathan; Mourao-Miranda, Janaina; Xia, Cedric Huchuan; Satterthwaite, Theodore D; Bassett, Danielle S; Bzdok, Danilo	August 1, 2020	Not Determined
32216874	Create Study	Optimization of energy state transition trajectory supports the development of executive function during youth.	eLife	Cui, Zaixu; Stiso, Jennifer; Baum, Graham L; Kim, Jason Z; Roalf, David R; Betzel, Richard F; Gu, Shi; Lu, Zhixin; Xia, Cedric H; He, Xiaosong; Ciric, Rastko; Oathes, Desmond J; Moore, Tyler M; Shinohara, Russell T; Ruparel, Kosha; Davatzikos, Christos; Pasqualetti, Fabio; Gur, Raquel E; Gur, Ruben C; Bassett, Danielle S; Satterthwaite, Theodore D	March 27, 2020	Not Determined
32216125	Create Study	Multi-scale network regression for brain-phenotype associations.	Human brain mapping	Xia, Cedric Huchuan; Ma, Zongming; Cui, Zaixu; Bzdok, Danilo; Thirion, Bertrand; Bassett, Danielle S; Satterthwaite, Theodore D; Shinohara, Russell T; Witten, Daniela M	July 1, 2020	Not Determined
32103250	Create Study	Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning.	Brain : a journal of neurology	Chand, Ganesh B; Dwyer, Dominic B; Erus, Guray; Sotiras, Aristeidis; Varol, Erdem; Srinivasan, Dhivya; Doshi, Jimit; Pomponio, Raymond; Pigoni, Alessandro; Dazzan, Paola; Kahn, Rene S; Schnack, Hugo G; Zanetti, Marcus V; Meisenzahl, Eva; Busatto, Geraldo F; Crespo-Facorro, Benedicto; Pantelis, Christos; Wood, Stephen J; Zhuo, Chuanjun; Shinohara, Russell T; Shou, Haochang; Fan, Yong; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Koutsouleris, Nikolaos; Wolf, Daniel H; Davatzikos, Christos	March 1, 2020	Not Determined
32087950	Create Study	Approaches to Defining Common and Dissociable Neurobiological Deficits Associated With Psychopathology in Youth.	Biological psychiatry	Kaczkurkin, Antonia N; Moore, Tyler M; Sotiras, Aristeidis; Xia, Cedric Huchuan; Shinohara, Russell T; Satterthwaite, Theodore D	July 1, 2020	Not Determined
32078800	Create Study	Individual Variation in Functional Topography of Association Networks in Youth.	Neuron	Cui, Zaixu; Li, Hongming; Xia, Cedric H; Larsen, Bart; Adebimpe, Azeez; Baum, Graham L; Cieslak, Matt; Gur, Raquel E; Gur, Ruben C; Moore, Tyler M; Oathes, Desmond J; Alexander-Bloch, Aaron F; Raznahan, Armin; Roalf, David R; Shinohara, Russell T; Wolf, Daniel H; Davatzikos, Christos; Bassett, Danielle S; Fair, Damien A; Fan, Yong; Satterthwaite, Theodore D	April 22, 2020	Not Determined
31988059	Create Study	Longitudinal Development of Brain Iron Is Linked to Cognition in Youth.	The Journal of neuroscience : the official journal of the Society for Neuroscience	Larsen, Bart; Bourque, Josiane; Moore, Tyler M; Adebimpe, Azeez; Calkins, Monica E; Elliott, Mark A; Gur, Ruben C; Gur, Raquel E; Moberg, Paul J; Roalf, David R; Ruparel, Kosha; Turetsky, Bruce I; Vandekar, Simon N; Wolf, Daniel H; Shinohara, Russell T; Satterthwaite, Theodore D	February 26, 2020	Not Determined
31968320	Create Study	A practical guide to methodological considerations in the controllability of structural brain networks.	Journal of neural engineering	Karrer, Teresa M; Kim, Jason Z; Stiso, Jennifer; Kahn, Ari E; Pasqualetti, Fabio; Habel, Ute; Bassett, Danielle S	April 9, 2020	Not Determined
31917325	Create Study	Functional brain network architecture supporting the learning of social networks in humans.	NeuroImage	Tompson, Steven H; Kahn, Ari E; Falk, Emily B; Vettel, Jean M; Bassett, Danielle S	April 15, 2020	Not Determined
31896669	Create Study	A Multidimensional Neural Maturation Index Reveals Reproducible Developmental Patterns in Children and Adolescents.	The Journal of neuroscience : the official journal of the Society for Neuroscience	Truelove-Hill, Monica; Erus, Guray; Bashyam, Vishnu; Varol, Erdem; Sako, Chiharu; Gur, Ruben C; Gur, Raquel E; Koutsouleris, Nikolaos; Zhuo, Chuanjun; Fan, Yong; Wolf, Daniel H; Satterthwaite, Theodore D; Davatzikos, Christos	February 5, 2020	Not Determined
31874926	Create Study	Development of structure-function coupling in human brain networks during youth.	Proceedings of the National Academy of Sciences of the United States of America	Baum, Graham L; Cui, Zaixu; Roalf, David R; Ciric, Rastko; Betzel, Richard F; Larsen, Bart; Cieslak, Matthew; Cook, Philip A; Xia, Cedric H; Moore, Tyler M; Ruparel, Kosha; Oathes, Desmond J; Alexander-Bloch, Aaron F; Shinohara, Russell T; Raznahan, Armin; Gur, Raquel E; Gur, Ruben C; Bassett, Danielle S; Satterthwaite, Theodore D	January 7, 2020	Not Determined
31815502	Create Study	Within-person variability in sensation-seeking during daily life: Positive associations with alcohol use and self-defined risky behaviors.	Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors	Lydon-Staley, David M; Falk, Emily B; Bassett, Danielle S	March 1, 2020	Not Determined
31690494	Create Study	Neurostructural Heterogeneity in Youths With Internalizing Symptoms.	Biological psychiatry	Kaczkurkin, Antonia N; Sotiras, Aristeidis; Baller, Erica B; Barzilay, Ran; Calkins, Monica E; Chand, Ganesh B; Cui, Zaixu; Erus, Guray; Fan, Yong; Gur, Raquel E; Gur, Ruben C; Moore, Tyler M; Roalf, David R; Rosen, Adon F G; Ruparel, Kosha; Shinohara, Russell T; Varol, Erdem; Wolf, Daniel H; Davatzikos, Christos; Satterthwaite, Theodore D	March 1, 2020	Not Determined
31650093	Create Study	Digital phenotyping for psychiatry: Accommodating data and theory with network science methodologies.	Current opinion in biomedical engineering	Lydon-Staley, D M; Barnett, I; Satterthwaite, T D; Bassett, D S	March 1, 2019	Not Determined
31519052	Create Study	Within-person variability in curiosity during daily life and associations with well-being.	Journal of personality	Lydon-Staley, David M; Zurn, Perry; Bassett, Danielle S	August 1, 2020	Not Determined
31504253	Create Study	Unifying the Notions of Modularity and Core-Periphery Structure in Functional Brain Networks during Youth.	Cerebral cortex (New York, N.Y. : 1991)	Gu, Shi; Xia, Cedric Huchuan; Ciric, Rastko; Moore, Tyler M; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Bassett, Danielle S	March 14, 2020	Not Determined
31476764	Create Study	Accelerated cortical thinning within structural brain networks is associated with irritability in youth.	Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology	Jirsaraie, Robert J; Kaczkurkin, Antonia N; Rush, Sage; Piiwia, Kayla; Adebimpe, Azeez; Bassett, Danielle S; Bourque, Josiane; Calkins, Monica E; Cieslak, Matthew; Ciric, Rastko; Cook, Philip A; Davila, Diego; Elliott, Mark A; Leibenluft, Ellen; Murtha, Kristin; Roalf, David R; Rosen, Adon F G; Ruparel, Kosha; Shinohara, Russell T; Sotiras, Aristeidis; Wolf, Daniel H; Davatzikos, Christos; Satterthwaite, Theodore D	December 1, 2019	Not Determined
31291606	Create Study	The community structure of functional brain networks exhibits scale-specific patterns of inter- and intra-subject variability.	NeuroImage	Betzel, Richard F; Bertolero, Maxwell A; Gordon, Evan M; Gratton, Caterina; Dosenbach, Nico U F; Bassett, Danielle S	November 15, 2019	Not Determined
31230463	Create Study	Evidence for Dissociable Linkage of Dimensions of Psychopathology to Brain Structure in Youths.	The American journal of psychiatry	Kaczkurkin, Antonia N; Park, Sophia Seonyeong; Sotiras, Aristeidis; Moore, Tyler M; Calkins, Monica E; Cieslak, Matthew; Rosen, Adon F G; Ciric, Rastko; Xia, Cedric Huchuan; Cui, Zaixu; Sharma, Anup; Wolf, Daniel H; Ruparel, Kosha; Pine, Daniel S; Shinohara, Russell T; Roalf, David R; Gur, Ruben C; Davatzikos, Christos; Gur, Raquel E; Satterthwaite, Theodore D	December 1, 2019	Not Determined
31220218	Create Study	Associations between Neighborhood SES and Functional Brain Network Development.	Cerebral cortex (New York, N.Y. : 1991)	Tooley, Ursula A; Mackey, Allyson P; Ciric, Rastko; Ruparel, Kosha; Moore, Tyler M; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Bassett, Danielle S	January 10, 2020	Not Determined
30988437	Create Study	Network constraints on learnability of probabilistic motor sequences.	Nature human behaviour	Kahn, Ari E; Karuza, Elisabeth A; Vettel, Jean M; Bassett, Danielle S	December 1, 2018	Not Determined
30723287	Create Study	Alterations in white matter microstructure in individuals at persistent risk for psychosis.	Molecular psychiatry	Roalf, David R; de la Garza, Angel Garcia; Rosen, Adon; Calkins, Monica E; Moore, Tyler M; Quarmley, Megan; Ruparel, Kosha; Xia, Cedric Huchuan; Rupert, Petra E; Satterthwaite, Theodore D; Shinohara, Russell T; Elliott, Mark A; Gur, Ruben C; Gur, Raquel E	October 1, 2020	Not Determined
30508681	Create Study	Sex differences in network controllability as a predictor of executive function in youth.	NeuroImage	Cornblath, Eli J; Tang, Evelyn; Baum, Graham L; Moore, Tyler M; Adebimpe, Azeez; Roalf, David R; Gur, Ruben C; Gur, Raquel E; Pasqualetti, Fabio; Satterthwaite, Theodore D; Bassett, Danielle S	March 1, 2019	Not Determined
30446748	Create Study	Mitigating head motion artifact in functional connectivity MRI.	Nature protocols	Ciric, Rastko; Rosen, Adon F G; Erus, Guray; Cieslak, Matthew; Adebimpe, Azeez; Cook, Philip A; Bassett, Danielle S; Davatzikos, Christos; Wolf, Daniel H; Satterthwaite, Theodore D	December 1, 2018	Not Determined
30333998	Create Study	Knowledge gaps in the early growth of semantic feature networks.	Nature human behaviour	Sizemore, Ann E; Karuza, Elisabeth A; Giusti, Chad; Bassett, Danielle S	September 1, 2018	Not Determined
30068943	Create Study	Linked dimensions of psychopathology and connectivity in functional brain networks.	Nature communications	Xia, Cedric Huchuan; Ma, Zongming; Ciric, Rastko; Gu, Shi; Betzel, Richard F; Kaczkurkin, Antonia N; Calkins, Monica E; Cook, Philip A; García de la Garza, Angel; Vandekar, Simon N; Cui, Zaixu; Moore, Tyler M; Roalf, David R; Ruparel, Kosha; Wolf, Daniel H; Davatzikos, Christos; Gur, Ruben C; Gur, Raquel E; Shinohara, Russell T; Bassett, Danielle S; Satterthwaite, Theodore D	August 1, 2018	Not Determined
30002509	Create Study	On the nature and use of models in network neuroscience.	Nature reviews. Neuroscience	Bassett, Danielle S; Zurn, Perry; Gold, Joshua I	September 1, 2018	Not Determined
29930385	Create Study	Sex differences in the developing brain: insights from multimodal neuroimaging.	Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology	Kaczkurkin, Antonia N; Raznahan, Armin; Satterthwaite, Theodore D	January 1, 2019	Not Determined
29729890	Create Study	Understanding the Emergence of Neuropsychiatric Disorders With Network Neuroscience.	Biological psychiatry. Cognitive neuroscience and neuroimaging	Bassett, Danielle S; Xia, Cedric Huchuan; Satterthwaite, Theodore D	September 1, 2018	Not Determined
29688290	Create Study	Gestational Age is Dimensionally Associated with Structural Brain Network Abnormalities Across Development.	Cerebral cortex (New York, N.Y. : 1991)	Nassar, Rula; Kaczkurkin, Antonia N; Xia, Cedric Huchuan; Sotiras, Aristeidis; Pehlivanova, Marieta; Moore, Tyler M; Garcia de La Garza, Angel; Roalf, David R; Rosen, Adon F G; Lorch, Scott A; Ruparel, Kosha; Shinohara, Russell T; Davatzikos, Christos; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D	May 1, 2019	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
No Mandatory Data Expected

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	9,647	07/09/2019	10,727	11/15/2019	9,748	Approved
Imaging (Structural, fMRI, DTI, PET, microscopy)	10,038	07/15/2019	10,038	11/15/2019	10,038	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
A mega-analytic study of white matter differences in attention deficit hyperactivity disorder seen across multiple cohorts	Context: Previous research has explored the relationship between attention-deficit/hyperactivity disorder (ADHD) and variations in the brain's white matter tract connections, as observed through structural differences. However, these investigations have produced inconsistent outcomes, which may be attributed to the relatively small participant groups in these studies. Consequently, we embarked on a comprehensive analysis involving over 6000 participants from five distinct cohorts. We aimed to examine white matter microstructure using diffusion tensor imaging in vivo. Approach: Employing a mega-analysis approach, we employed linear mixed models to investigate potential links between ADHD traits and diagnosis with the fractional anisotropy of 42 white matter tracts. We also contrasted these associations against measurements of mood, anxiety, and other outward behavioral issues. Findings: Our study encompassed a total of 6993 participants, aged 6 to 18 years, with a mean age of 10.62 years (standard deviation 1.99). This group included 3368 girls and 3625 boys from diverse racial and ethnic backgrounds, including 764 African American individuals, 4146 non-Hispanic White individuals, and 2083 from other racial/ethnic groups. Among these participants, data was available for ADHD and other emotional/behavioral symptoms (N = 6933). Additionally, clinical information was adequate for the diagnosis of ADHD (n = 951) or the absence of such a diagnosis (n = 4884). Our analysis revealed that both ADHD diagnosis and traits were linked to decreased fractional anisotropy in the inferior longitudinal and left uncinate fasciculi (at a statistically adjusted false discovery rate of p < .05). Notably, the observed effect sizes were modest (the most robust association with ADHD traits had a partial r effect size of -0.14, while the most significant difference between cases and controls had a d effect size of -0.3). Conversely, no similar microstructural irregularities were observed in relation to anxiety, mood, or externalizing issues. These findings persisted even when ADHD cases and control subjects were matched based on their in-scanner motion. Conclusion: Although the microstructural distinctions associated with ADHD were evident across the various cohorts, their effects were minor. This underscores the limited clinical usefulness of relying solely on this imaging technique in isolation.	10073/12537	Secondary Analysis	Shared
Environmental Risk Factors and Psychotic-like Symptoms in Children Aged 9-11	Objective: Research implicates environmental risk factors, including correlates of urbanicity, deprivation, and environmental toxins, in psychotic-like experiences (PLEs). The current study examined associations between several types of environmental risk factors and PLEs in school-age children, whether these associations were specific to PLEs or generalized to other psychopathology, and examined possible neural mechanisms for significant associations. Method: The current study used data from 10,328 9-11-year-olds from the Adolescent Brain Cognitive Development (ABCD) study. Hierarchical linear models examined associations between PLEs and geocoded environmental risk factors, and whether associations generalized to internalizing/externalizing symptoms. Mediation models examined whether structural MRI abnormalities (e.g., intracranial volume) mediated associations between PLEs and environmental risk factors. Results: The results found specific types of environmental risk factors, namely measures of urbanicity (i.e., drug offense exposure, less perception of neighborhood safety), deprivation (including overall deprivation, rate of poverty, fewer years at residence), and lead exposure risk, were associated with PLEs. These associations showed evidence of stronger associations with PLEs than internalizing/externalizing symptoms (especially overall deprivation, poverty, drug offense exposure, and lead exposure risk). There was evidence that brain volume mediated between 11-25% of the associations between poverty, perception of neighborhood safety, and lead exposure risk with PLEs. Conclusions: These results are the first to find support for neural measures partially mediating the association between PLEs and environmental exposures. Furthermore, the current study replicated and extended recent findings of the association between PLEs and environmental exposures, finding evidence for specific associations with correlates of urbanicity, deprivation, and lead exposure risk.	9701/11898	Secondary Analysis	Shared
Longitudinally stable, brain-based predictive models mediate the relationships between childhood cognition and socio-demographic, psychological and genetic factors.	Cognitive abilities are one of the major transdiagnostic domains in the National Institute of Mental Health's Research Domain Criteria (RDoC). Following RDoC's integrative approach, we aimed to develop brain-based predictive models for cognitive abilities that (a) are developmentally stable over years during adolescence and (b) account for the relationships between cognitive abilities and socio-demographic, psychological and genetic factors. For this, we leveraged the unique power of the large-scale, longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study (n ~ 11 k) and combined MRI data across modalities (task-fMRI from three tasks: resting-state fMRI, structural MRI and DTI) using machine-learning. Our brain-based, predictive models for cognitive abilities were stable across 2 years during young adolescence and generalisable to different sites, partially predicting childhood cognition at around 20% of the variance. Moreover, our use of ‘opportunistic stacking’ allowed the model to handle missing values, reducing the exclusion from around 80% to around 5% of the data. We found fronto-parietal networks during a working-memory task to drive childhood-cognition prediction. The brain-based, predictive models significantly, albeit partially, accounted for variance in childhood cognition due to (1) key socio-demographic and psychological factors (proportion mediated = 18.65% [17.29%–20.12%]) and (2) genetic variation, as reflected by the polygenic score of cognition (proportion mediated = 15.6% [11%–20.7%]). Thus, our brain-based predictive models for cognitive abilities facilitate the development of a robust, transdiagnostic research tool for cognition at the neural level in keeping with the RDoC's integrative framework.	9724/11878	Secondary Analysis	Shared
Prenatal substance exposure and child health: Understanding the role of environmental factors, genetics, and brain development	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.	10829/11878	Secondary Analysis	Shared
Prevalence of anhedonia and related risk and protective factors in the general population: results from UK Biobank and ABCD study	Background Anhedonia (defined as the capacity to experience pleasure) is present in healthy people and in mental disorders but its prevalence and predictors are largely unknown in the general population. We aimed to estimate the prevalence of anhedonia and identify risk and protective factors within two large population-based samples, UK Biobank (UKB) and the US Adolescent Brain and Cognitive Development (ABCD) study. Methods A total of 487,631 adults from UKB (mean age = 56.56 years, 54.39% female) and 9,829 early adolescents from ABCD (mean age = 9.9 years, 47.64% female) were included. The prevalence of anhedonia and common mental disorders were estimated at baseline in both cohorts separately. Multiple factors were assessed, including demographics, family history, early life factors, lifestyle, physical factors, mental health conditions, and family, school and social environments. We conducted bivariate analyses, multinomial logistic regression, Poisson regression and logistic regression in subsamples with complete data to identify factors associated with current or future anhedonia. Results In UKB, 21.47% [95% CI, 21.36-21.59%] had state anhedonia during the preceding two weeks and 36.92% [95% CI, 36.68-37.15%] endorsed lifetime severe anhedonia. Risk factors associated with state anhedonia and lifetime severe anhedonia included parental depression history, sleeplessness, poor overall health, any lifetime mental disorders, childhood trauma, and adulthood traumatic life events, whereas social support was a protective factor. In ABCD, youth report and parent report revealed a prevalence of 10.11% (95% CI, 9.44-10.82%) for state anhedonia and 8.70% (95% CI, 8.07-9.37%) for lifetime severe anhedonia. Contributing risk factors included Black and Hispanic race/ethnicity, high family conflict, any lifetime mental disorders, high school disengagement and high impact of adverse life experiences. High parent acceptance and higher parental educational degree were protective. Conclusions Anhedonia is common in the general population and multiple risk factors are implicated during early adolescence and rom middle to later adulthood. These risk factors are largely consistent with previous findings for diagnoses such as depression and bipolar disorder and may represent promising prevention targets for addressing anhedonia in the general population.	10059/11876	Primary Analysis	Shared
Auditory Cortex Asymmetry Associations with Individual Differences in Language and Cognition	A longstanding cerebral lateralization hypothesis predicts that disrupted development of typical leftward structural asymmetry of auditory cortex explains why children have problems learning to read. Small sample sizes and small effects, potential sex-specific effects, and associations that are limited to specific dimensions of language are thought to have contributed inconsistent results. The large ABCD study dataset (baseline visit: N = 11,859) was used to test the hypothesis of significant associations between surface area asymmetry of auditory cortex and receptive vocabulary performance across boys and girls, as well as an oral word reading effect that was specific to boys. The results provide modest support (Cohen’s d effect sizes ≤ 0.10) for the cerebral lateralization hypothesis.	10050/11859	Secondary Analysis	Shared
Integrating large-scale genomic data CNV Calling with MRI data in the ABCD Cohort	Childhood represents a crucial developmental phase for mental health and cognitive function, both of which are implicated in psychiatric disorders. This neurodevelopmental trajectory is shaped by a complex interplay of genetic and environmental factors. While common genetic variants account for a large proportion of inherited genetic risk, rare genetic variations, particularly copy number variants (CNVs), play a significant role in the genetic architecture of neurodevelopmental disorders. Despite their importance, the relevance of CNVs to child psychopathology and cognitive function in the general population remains underexplored. In this study, we utilized PennCNV and QuantiSNP algorithms to identify duplications and deletions larger than 50Kb across a cohort of 11,088 individuals from the Adolescent Brain Cognitive Development (ABCD) study. CNVs meeting quality control standards were subjected to a genome-wide association scan to identify regions associated with psychopathological and cognitive outcomes. Additionally, a CNV risk score, reflecting the aggregated burden of genetic intolerance to inactivation and dosage sensitivity, was calculated to assess its impact on variability in overall and dimensional child psychiatric and cognitive phenotypes. In a final sample of 8,564 individuals passing quality control, we identified 4,111 individuals carrying 5,760 autosomal CNVs. Our results revealed significant associations between specific CNVs and psychopathology and cognitive function. For instance, a duplication at 10q26.3 was associated with total psychopathology, and somatic complaints in particular. Additionally, deletions at 1q12.1, along with duplications at 14q11.2 and 10q26.3, were linked to total cognitive function, with particular contributions from fluid intelligence, working memory, and reading ability. Moreover, individuals carrying CNVs previously associated with neurodevelopmental disorders exhibited greater impairment in social functioning and cognitive performance across multiple domains, in particular working memory. Notably, a higher deletion CNV risk score was significantly correlated with increased total psychopathology (especially in dimensions of social functioning, thought disorder, and attention) as well as cognitive impairment across various domains. In summary, our findings shed light on the contribution of CNV to interindividual variability in complex traits related to neurocognitive development and child psychopathology.	9878/11665	Primary Analysis	Shared
Neuroanatomical correlates of impulsive traits in children aged 9 to 10	Impulsivity refers to a set of traits that are generally negatively related to critical domains of adaptive functioning and are core features of numerous psychiatric disorders. The current study examined the gray and white matter correlates of five impulsive traits measured using an abbreviated version of the UPPS-P (Urgency, (lack of) Premeditation, (lack of) Perseverance, Sensation-Seeking, Positive Urgency) impulsivity scale in children aged 9 to 10 (N = 11,052) from the Adolescent Brain and Cognitive Development (ABCD) study. Linear mixed effect models and elastic net regression were used to examine features of regional gray matter and white matter tractography most associated with each UPPS-P scale; intraclass correlations were computed to examine the similarity of the neuroanatomical correlates among the scales. Positive Urgency showed the most robust association with neuroanatomy, with similar but less robust associations found for Negative Urgency. Perseverance showed little association with neuroanatomy. Premeditation and Sensation Seeking showed intermediate associations with neuroanatomy. Critical regions across measures include the dorsolateral prefrontal cortex, lateral temporal cortex, and orbitofrontal cortex; critical tracts included the superior longitudinal fasciculus and inferior fronto-occipital fasciculus. Negative Urgency and Positive Urgency showed the greatest neuroanatomical similarity. Some UPPS-P traits share neuroanatomical correlates, while others have distinct correlates or essentially no relation to neuroanatomy. Neuroanatomy tended to account for relatively little variance in UPPS-P traits (i.e., Model R2 < 1%) and effects were spread throughout the brain, highlighting the importance of well powered samples.	9595/11051	Secondary Analysis	Shared
Association of Mental Health Burden With Prenatal Cannabis Exposure From Childhood to Early Adolescence: Longitudinal Findings From the Adolescent Brain Cognitive Development (ABCD) Study	Dramatic increases in cannabis use during pregnancy are alarming because of evidence that prenatal exposure may be associated with a host of adverse outcomes.1 We previously found that prenatal cannabis exposure (PCE) following maternal knowledge of pregnancy is associated with increased psychopathology during middle childhood using baseline data from the Adolescent Brain Cognitive Development (ABCD) study.2 Here, leveraging longitudinal ABCD study data (data release 4.0), we examined whether associations with psychopathology persist into early adolescence.	9043/10640	Secondary Analysis	Shared
Effect of exposure to maternal diabetes during pregnancy on offspring’s brain cortical thickness and neurocognitive functioning	OBJECTIVE: Maternal diabetes may affect the developing brain of the fetus, which may adversely affect the neurocognitive functioning (NCF) of diabetes-exposed children. We examined the effect of prenatal exposure to maternal diabetes (DP) on brain structure and neurocognition in preadolescent children, ages 9-10. RESEARCH DESIGN AND METHODS: This secondary data analysis study used cross-sectional structural neuroimaging and NCF data from the Adolescent Brain and Cognitive Development (ABCD) study (N=9,963). Differences in brain cortical thickness (CTh) and five cognitive abilities (executive function, working and episodic memory, processing speed, and language abilities) between diabetes-exposed and unexposed children were examined. Generalized linear models were used to adjust for the effect of confounding variables. Indirect effect of CTh into the relationship between maternal DP and NCF were also examined. RESULTS: The average age of the children was 9.9 years (SD 7.5); half of them were male and non-Hispanic White. Diabetes-exposed children (n=714) had lower CTh of the whole-brain (2.744mm VS 2.756mm; p 0.008) and lower scores in processing speed task (85.97 VS 87.28; p=0.021 compared to unexposed children (n=9249) after adjusting for demographic and other confounding variables. Diabetes-exposed children also had lower score in fluid intelligence [β (95%CI): -0.837 (-1.604, -0.171)]) and total cognition [β (95%CI): -0.728 (-1.338,-0.119)]. CTh partially mediated [Direct effect=β (95%CI): -3.239 (-5.834, -0.644); indirect effect=β (95%CI): -3.239 (-5.834, -0.644)] the effect of maternal DP on offspring’s processing speed. CONCLUSION: Diabetes-exposed children have reduced CTh and NCF during preadolescence age, which may have implications for psychomotor development during later life. Prospective studies are needed to confirm our findings	8372/10218	Secondary Analysis	Shared
Effect of maternal hypertensive disorder on their children’s neurocognitive functioning	Objective: The aim of the study was to examine the effect of prenatal exposure to maternal HDP on brain structure and NCF in singleton children aged between 9-10 years the baseline wave of the Adolescent Brain and Cognitive Development (ABCD) Study. Methods: The ABCD Study® interviewed each child (and their parents), measured NCF, and performed neuroimaging. Exposure to maternal high blood pressure (HBP) and preeclampsia or eclampsia (PE/EL) were extracted from the developmental history questionnaire. Differences in cortical thickness (CTh) and five cognitive abilities (executive function, working and episodic memory, processing speed, and language abilities) between exposed and unexposed children were examined using generalized linear models. The mediating effects of CTh, birthweight, and BMI on the relationship between maternal HDP on NCF were also examined. Result: A total of 584-children exposed to HBP, 387-children exposed to PE/EL, and 5,877 unexposed children were included in the analysis. Neither CTh nor NCF differed between the exposed and unexposed children with or without adjusting for the confounders including the child’s age, sex, race, education, and birth histories. The whole-brain CTh did not mediate any of the relationships between HDP and NCF. However, the relationship between HDP and most of the NCF was mediated by birthweight and BMI. Conclusions: Our results do not support maternal HDP, in comparison to other perinatal risk factors, as a direct risk factor for later-life cognitive functions. Prospective longitudinal studies, following up from infancy, are needed to further delineate the effect of HDP on children’s cognitive abilities.	8619/10183	Secondary Analysis	Shared
Prenatal cannabis exposure, the brain, and psychopathology during early adolescence	Prenatal cannabis exposure (PCE) is associated with mental health problems in early adolescence, but the possible neurobiological mechanisms remain unknown. In a large longitudinal sample of adolescents (ages 9-12, n=9,322-10,186), we find that PCE is associated with localized differences in gray and white matter of the frontal and parietal cortices, their associated white matter tracts, and with striatal resting state connectivity, even after accounting for potential pregnancy, familial, and child confounds. Variability in forceps minor and pars triangularis diffusion metrics partially longitudinally mediate associations of PCE with attention problems and attention-deficit/hyperactivity disorder (ADHD) symptoms. PCE-related differences in brain development may confer vulnerability to worse mental health in early adolescence. Analyses used the 5.0 ABCD release: https://dx.doi.org/10.15154/8873-zj65	8712/10159	Secondary Analysis	Shared
Hierarchical Individual Variation and Socioeconomic Impact on Personalized Functional Network Topography in ABCD Children	The spatial topography of large-scale functional networks on the cerebral cortex varies substantially across individuals, particularly in the higher-order association cortices. Childhood functional organization has been linked to academical performance, quality of life and mental health outcomes throughout adolescence and adulthood. However, the individual variability of personalized functional network topography and its relationship with socioeconomic status (SES) during childhood remain unclear. Here, we delineated 17 personalized functional networks for children aged 9–10 years using 20 minutes of high-quality functional MRI data from the Adolescent Brain Cognitive Development study. We found that individual variations in personalized functional network topography increase along a hierarchical sensorimotor-association axis across the cortex. Furthermore, we observed that functional network topography significantly predicts unseen individuals’ SES, which was defined as the family income-to-needs ratio. Moreover, the association between topography and SES is hierarchically organized along the sensorimotor-association cortical axis, with stronger positive associations at the higher-order association cortex. Finally, we have publicly released children’s functional networks at https://nda.nih.gov/study.html?id=2484. These findings highlight a hierarchically organized cortical plasticity of childhood functional neuroanatomy in humans.	10073/10073	Secondary Analysis	Shared
Limited generalizability of multivariate brain-based dimensions of child psychiatric symptoms	Multivariate machine learning techniques are a promising set of tools for identifying complex brain-behavior associations. However, failure to replicate results from these methods across samples has hampered their clinical relevance. Here we aimed to delineate dimensions of brain functional connectivity that are associated with child psychiatric symptoms in two large and independent cohorts: the Adolescent Brain Cognitive Development (ABCD) Study and the Generation R Study (total n = 6935). Using sparse canonical correlations analysis, we identified two brain-behavior dimensions in ABCD: attention problems and aggression/rule-breaking behaviors. Importantly, out-of-sample generalizability of these dimensions was consistently observed in ABCD, suggesting robust multivariate brain-behavior associations. Despite this, out-of-study generalizability in Generation R was limited. These results highlight that the degrees of generalizability can vary depending on the external validation methods employed as well as the datasets used, emphasizing that biomarkers will remain elusive until models generalize better in true external settings.	10073/10073	Secondary Analysis	Shared
Polygenic risk scores for alcohol involvement relate to brain structure in substance‐naïve children: results from the ABCD Study	Brain imaging-derived structural correlates of alcohol involvement have largely been speculated to arise as a consequence of alcohol exposure. However, they may also reflect predispositional risk. In substance naïve children of European ancestry who completed the baseline session of the Adolescent Brain Cognitive Development (ABCD) Study (n = 3013), mixed-effects models estimated whether polygenic risk scores (PRS) for problematic alcohol use (PAU-PRS) and drinks per week (DPW-PRS) are associated with magnetic resonance imaging-derived brain structure phenotypes (i.e., total and regional: cortical thickness, surface area and volume; subcortical volume; white matter volume, fractional anisotropy, mean diffusivity). Follow-up analyses evaluated whether any identified regions were also associated with polygenic risk among substance naïve children of African ancestry (n = 898). After adjustment for multiple testing correction, polygenic risk for PAU was associated with lower volume of the left frontal pole and greater cortical thickness of the right supramarginal gyrus (\|βs\| > 0.009; ps < 0.001; psfdr < 0.046; r2s < 0.004). PAU PRS and DPW PRS showed nominally significant associations with a host of other regional brain structure phenotypes (e.g., insula surface area and volume). None of these regions showed any, even nominal association among children of African ancestry. Genomic liability to alcohol involvement may manifest as variability in brain structure during middle childhood prior to alcohol use initiation. Broadly, alcohol-related variability in brain morphometry may partially reflect predisposing genomic influence. Larger discovery genome-wide association studies and target samples of diverse ancestries are needed to determine whether observed associations may generalize across ancestral origins.	8413/10054	Secondary Analysis	Shared
BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks	Mapping the connectome of the human brain using structural or functional connectivity has become one of the most pervasive paradigms for neuroimaging analysis. Recently, Graph Neural Networks (GNNs) motivated from geometric deep learning have attracted broad interest due to their established power for modeling complex networked data. Despite their established performance in other fields, there has not yet been a systematic study of how to design effective GNNs for brain network analysis. To bridge this gap, we present BrainGB, a benchmark for brain network analysis with GNNs. BrainGB standardizes the process by 1) summarizing brain network construction pipelines for both functional and structural neuroimaging modalities and 2) modularizing the implementation of GNN designs. We conduct extensive experiments on datasets across cohorts and modalities and recommend a set of general recipes for effective GNN designs on brain networks.	9748/9748	Secondary Analysis	Shared
Neural correlates of obesity across the lifespan	Associations between brain and obesity are bidirectional: changes in brain structure and function can underpin over-eating, while chronic adiposity might lead to brain atrophy. Consequently, investigating brain-BMI associations across the lifespan can help to understand causality of those relationships. This study, conducted using multiple large-scale datasets, delves into the dynamic interplay between obesity and cortical morphometry across distinct age groups, encompassing children, young adults, adults, and older adults. Additionally, we investigate the genetic, neurochemical, and cognitive correlates of these alterations. Our findings reveal a consistent pattern of lower cortical thickness in fronto-temporal brain regions associated with obesity across all age cohorts. Moreover, in adults and older adults, obesity correlates with neurochemical changes and differential gene expression related to inflammation and mitochondrial function. In addition, in children and older adults, elevated body mass index corresponds to modifications in brain regions involved in emotional and attentional processes implicated in feeding regulation. In summary, obesity might originate from cognitive changes during early adolescence, subsequently leading to neurodegeneration in later life through mitochondrial and inflammatory mechanisms.	2891/9186	Secondary Analysis	Shared
Differentiating distinct and converging neural correlates of types of systemic environmental exposures	Background: Systemic environmental disadvantage relates to a host of health and functional outcomes. Specific structural factors have seldom been linked to neural structure, however, clouding understanding of putative mechanisms. Examining relations during childhood/preadolescence, a dynamic period of neurodevelopment, could aid bridge this gap. Methods: A total of 10,213 youth were recruited from the Adolescent Brain and Cognitive Development study. Self-report and objective measures (Census and Federal bureau of investigation metrics extracted using geocoding) of environmental exposures were used, including stimulation indexing lack of safety and high attentional demands, discrepancy indexing social exclusion/lack of belonging, and deprivation indexing lack of environmental enrichment. Environmental measures were related to cortical thickness, surface area and subcortical volume regions, controlling for other environmental exposures and accounting for other brain regions. Results: Self-report (\|β\|=0.04-0.09) and objective (\|β\|=0.02-0.06) environmental domains related to area/thickness in overlapping (e.g. insula, caudal anterior cingulate), and unique regions (e.g. for discrepancy, rostral anterior and isthmus cingulate, implicated in socioemotional functions; for stimulation, precuneus, critical for cue reactivity and integration of environmental cues, and for deprivation, superior frontal, integral to executive functioning). For stimulation and discrepancy exposures, self-report and objective measures showed similarities in correlate regions, while deprivation exposures evidenced distinct correlates for self-report and objective measures. Conclusions: Results represent a necessary step toward broader work aimed at establishing mechanisms and correlates of structural disadvantage, highlighting the relevance of going beyond aggregate models by considering types of environmental factors, and the need to incorporate both subjective and objective measurements in these efforts.	7824/9043	Primary Analysis	Shared
A multi-cohort study of resting-state connectivity alterations in attention-deficit/hyperactivity disorder	Most studies examining connectomic abnormalities associated with ADHD have used small, underpowered samples and thus produced inconsistent findings. Here we combined data from the Adolescent Brain Cognitive Development (ABCD) and Lifespan Human Connectome Project Development (HCP-D) cohorts (NDAR collections #2573, #2846 and #3165), as well as datasets from non-NDAR sources including the ADHD-200, Healthy Brain Network (HBN), National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) and Neurobehavioral Clinical Research (NCR) cohorts. We aimed to identify network-level resting-state features associated ADHD diagnosis and traits in this large multi-cohort sample. We applied the same 36-parameter+despiking pipeline to subjects from all datasets, and combined data using mega-analytic mixed models, which included nested random intercepts for study, site and family ID. In the group comparison, we compared 1301 subjects with diagnosed ADHD against 1301 unaffected controls (total N=2,602; 1710 males (65.72%); mean age=10.86 years, sd=2.05). Patients and controls were 1:1 nearest neighbor matched on in-scanner motion and key demographic variables. Associations between ADHD-traits and resting-state connectivity were assessed in a large multi-cohort sample (N=10,113). ADHD diagnosis was associated with less anticorrelation between the default mode and salience/ventral attention (B=0.009, t=3.45, p-FDR=0.004, d=0.14, 95% CI=0.004, 0.014), somatomotor (B=0.008, t=3.49, p-FDR=0.004, d=0.14, 95% CI=0.004, 0.013), and dorsal attention networks (B=0.01, t=4.28, p-FDR<0.001, d=0.17, 95% CI=0.006, 0.015). These results were robust to sensitivity analyses considering comorbid internalizing problems, externalizing problems and psychostimulant medication. Similar findings were observed when examining ADHD traits. Finding associations between ADHD and connectivity of the default mode to task-positive networks is consistent with default mode network models of disorder, although all effect sizes were small.	7283/8817	Secondary Analysis	Shared
Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study	Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits, including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R2 = 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R2 = 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task.	6708/7999	Secondary Analysis	Shared
Intra-individual variability in task performance after cognitive training is associated with long-term outcomes in children	The potential benefits and mechanistic effects of working memory training in children are the subject of much research and debate. The cumulative evidence indicates that training can alter brain structure and function in the short term and have lasting effects on behaviour. We show that five weeks of school-based, adaptive working memory training led to greater activity in prefrontal and striatal brain regions, higher task accuracy, and reduced intra-individual variability in response times. Using a sequential sampling decision model, we demonstrate that this reduction in intra-individual variability can be explained by changes to the evidence accumulation rates and thresholds. Critically, intra-individual variability was more closely associated with academic skills and mental health 6-12 months after the end of training than task accuracy. Taken together, our results suggest that improvements in attention control are the initial mechanism that leads to the long-run benefits from adaptive working memory training. Improvements in selective and sustained attention after the training might serve as a scaffold for subsequent changes in higher cognitive processes, academic skills, and general well-being. Furthermore, these results highlight that the selection of outcome measures and the timing of the assessments play a crucial role in detecting training efficacy. Intra-individual variability appears to be useful in quantifying the immediate impact of cognitive training interventions and predicting the future emergence of academic and socioemotional skills. Thus, evaluating intra-individual variability, during or directly after training could allow for the early tailoring of training interventions in terms of duration or content to maximise their impact.	1/7844	Primary Analysis	Shared
Human cortex development is shaped by molecular and cellular brain systems	Human brain morphology undergoes complex developmental changes with diverse regional trajectories. Various biological factors influence cortical thickness development, but human data are scarce. Building on methodological advances in neuroimaging of large cohorts, we show that population-based developmental trajectories of cortical thickness unfold along patterns of molecular and cellular brain organization. During childhood and adolescence, distributions of dopaminergic receptors, inhibitory neurons, glial cell populations as well as features of brain metabolism explain up to 50% of variance associated with regional cortical thickness trajectories. Cortical maturation patterns in later life are best explained by distributions of cholinergic and glutamatergic systems. These observations are validated in longitudinal data from over 8,000 adolescents, explaining up to 59% of developmental change at population- and 18% at single-subject level. Integrating multilevel brain atlases with normative modeling and population neuroimaging provides a biologically and clinically meaningful path to understand typical and atypical brain development in living humans.	5827/7209	Secondary Analysis	Shared
Stability of polygenic scores across discovery genome-wide association studies	Polygenic scores (PGS) are commonly evaluated in terms of their predictive accuracy at the population level by the proportion of phenotypic variance they explain. To be useful for precision medicine applications, they also need to be evaluated at the individual level when phenotypes are not necessarily already known. We investigated the stability of PGS in European American (EUR) and African American (AFR)-ancestry individuals from the Philadelphia Neurodevelopmental Cohort and the Adolescent Brain Cognitive Development study using different discovery genome-wide association study (GWAS) results for post-traumatic stress disorder (PTSD), type 2 diabetes (T2D), and height. We found that pairs of EUR-ancestry GWAS for the same trait had genetic correlations >0.92. However, PGS calculated from pairs of same-ancestry and different-ancestry GWAS had correlations that ranged from <0.01 to 0.74. PGS stability was greater for height than for PTSD or T2D. A series of height GWAS in the UK Biobank suggested that correlation between PGS is strongly dependent on the extent of sample overlap between the discovery GWAS. Focusing on the upper end of the PGS distribution, different discovery GWAS do not consistently identify the same individuals in the upper quantiles, with the best case being 60% of individuals above the 80th percentile of PGS overlapping from one height GWAS to another. The degree of overlap decreases sharply as higher quantiles, less heritable traits, and different-ancestry GWAS are considered. PGS computed from different discovery GWAS have only modest correlation at the individual level, underscoring the need to proceed cautiously with integrating PGS into precision medicine applications.	4701/5962	Secondary Analysis	Shared
A Phenome-Wide Association Study (PheWAS) of Late Onset Alzheimer Disease Genetic Risk in Children of European Ancestry at Middle Childhood: Results from the ABCD Study	Genetic risk for Late Onset Alzheimer Disease (AD) has been associated with lower cognition and smaller hippocampal volume in healthy young adults. However, whether these and other associations are present during childhood remains unclear. Using data from 5556 genomically-confirmed European ancestry youth who completed the baseline session of the ongoing the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®), our phenome-wide association study estimating associations between four indices of genetic risk for late-onset AD (i.e., AD polygenic risk scores (PRS), APOE rs429358 genotype, AD PRS with the APOE region removed (ADPRS-APOE), and an interaction between ADPRS-APOE and APOE genotype) and 1687 psychosocial, behavioral, and neural phenotypes revealed no significant associations after correction for multiple testing (all ps > 0.0002; all pfdr > 0.07). These data suggest that AD genetic risk may not phenotypically manifest during middle-childhood or that effects are smaller than this sample is powered to detect.	4914/5556	Secondary Analysis	Shared
Changes in patterns of age-related network connectivity are associated with risk for schizophrenia	Alterations in fMRI-based brain functional network connectivity (FNC) are associated with schizophrenia (SCZ) and the genetic risk or subthreshold clinical symptoms preceding the onset of SCZ, which often occurs in early adulthood. Thus, age-sensitive FNC changes may be relevant to SCZ risk-related FNC. We used independent component analysis to estimate FNC from childhood to adulthood in 9,236 individuals. To capture individual brain features more accurately than single-session fMRI, we studied an average of three fMRI scans per individual. To identify potential familial risk-related FNC changes, we compared age-related FNC in unaffected siblings (SIB) and first-degree relatives (FHR) of SCZ patients with neurotypical controls (NC) at the same age-stage. Then, we examined how polygenic risk scores for SCZ influenced risk-related FNC patterns. Finally, we investigated the same risk-related FNC patterns in adult SCZ patients (oSCZ) and young individuals with subclinical psychotic symptoms (PSY). Age-sensitive risk-related FNC patterns emerge during adolescence and early adulthood, but not before. Young SIB always followed older NC patterns, with decreased FNC in a cerebellar-occipitoparietal circuit and increased FNC in two prefrontal-sensorimotor circuits when compared to young NC. Some of these FNC alterations were also found in oSCZ, with one exhibiting reversed pattern. All were linked to polygenic risk for SCZ in unrelated individuals (R2 varied from 0.02 to 0.09). Young PSY showed FNC alterations in the same direction as SIB when compared to NC. These results suggest that age-related neurotypical FNC correlate with genetic risk for SCZ and are detectable with MRI in young participants.	4280/4936	Secondary Analysis	Shared
Overlapping brain correlates of superior cognition among children at genetic risk for Alzheimer’s disease and/ or major depressive disorder	Early life adversity (ELA) tends to accelerate neurobiological ageing, which, in turn, is thought to heighten vulnerability to both Major Depressive Disorder (MDD) and Alzheimer’s Disease (AD). The two conditions are putatively related, with MDD representing either a risk factor or early symptom of AD. Given the substantial environmental susceptibility of both disorders, timely identification of their neurocognitive markers could facilitate interventions to prevent clinical onset. To this end, we analysed multimodal data from the Adolescent Brain and Cognitive Development study (ages 9-10 years). To disentangle genetic from correlated genetic-environmental influences, while also probing gene-adversity interactions, we compared adoptees, a group generally exposed to substantial ELA, with children raised by their biological families via genetic risk scores (GRS) from genome-wide association studies. AD and MDD GRSs predicted overlapping and widespread neurodevelopmental alterations associated with superior fluid cognition. Specifically, among adoptees only, greater AD GRS were related to accelerated structural maturation (i.e., cortical thinning) and higher MDD GRS were linked to delayed functional neurodevelopment, as reflected in compensatory brain activation on an inhibitory control task. Our study identifies compensatory mechanisms linked to MDD risk and highlights the potential cognitive benefits of accelerated maturation linked to AD vulnerability in late childhood.	3969/4499	Secondary Analysis	Shared
Shared heritability of human face and brain shape	Evidence from model organisms and clinical genetics suggests coordination between the developing brain and face, but the role of this link in common genetic variation remains unknown. We performed a multivariate genome-wide association study of cortical surface morphology in 19,644 individuals of European ancestry, identifying 472 genomic loci influencing brain shape, of which 76 are also linked to face shape. Shared loci include transcription factors involved in craniofacial development, as well as members of signaling pathways implicated in brain-face cross-talk. Brain shape heritability is equivalently enriched near regulatory regions active in either forebrain organoids or facial progenitors. However, we do not detect significant overlap between shared brain-face genome-wide association study signals and variants affecting behavioral-cognitive traits. These results suggest that early in embryogenesis, the face and brain mutually shape each other through both structural effects and paracrine signaling, but this interplay may not impact later brain development associated with cognitive function.	3938/4470	Secondary Analysis	Shared
Associations among household and neighborhood socioeconomic disadvantages, resting-state frontoamygdala connectivity, and internalizing symptoms in youth	Exposure to socioeconomic disadvantages (SED) can have negative impacts on mental health, yet SED is a multifaceted construct and the precise processes by which SED confer deleterious effects are less clear. Using a large and diverse sample of preadolescents (ages 9-10 at baseline; N = 4,038; 49% female) from the Adolescent Brain Cognitive Development Study, we examined associations among SED at both household (i.e., income-to-needs and material hardship) and neighborhood (i.e., area deprivation and neighborhood unsafety) levels, frontoamygdala resting-state functional connectivity, and internalizing symptoms at baseline and 1-year follow-up. SED were positively associated with internalizing symptoms at baseline, and indirectly predicted symptoms one year later through elevated symptoms at baseline. At the household level, youth in households characterized by higher disadvantage (i.e., lower income-to-needs ratio) exhibited more strongly negative frontoamygdala coupling, particularly between the bilateral amygdala and medial orbitofrontal (mOFC) regions within the Frontoparietal Network. While more strongly positive amygdala-mOFC coupling was associated with higher levels of internalizing symptoms at baseline and 1-year follow-up, it did not mediate the association between income-to-needs ratio and internalizing symptoms. However, at the neighborhood level, amygdala-mOFC functional coupling moderated the effect of neighborhood deprivation on internalizing symptoms. Specifically, higher neighborhood deprivation was associated with higher internalizing symptoms for youth with more strongly positive connectivity, but not for youth with more strongly negative connectivity, suggesting a potential buffering effect. Findings highlight the importance of capturing multileveled socioecological contexts in which youth develop to identify youth who are most likely to benefit from early interventions. Exposure to socioeconomic disadvantages (SED) can have negative impacts on mental health, yet SED is a multifaceted construct and the precise processes by which SED confer deleterious effects are less clear. Using a large and diverse sample of preadolescents (ages 9-10 at baseline; N = 4,038; 49% female) from the Adolescent Brain Cognitive Development Study, we examined associations among SED at both household (i.e., income-to-needs and material hardship) and neighborhood (i.e., area deprivation and neighborhood unsafety) levels, frontoamygdala resting-state functional connectivity, and internalizing symptoms at baseline and 1-year follow-up. SED were positively associated with internalizing symptoms at baseline, and indirectly predicted symptoms one year later through elevated symptoms at baseline. At the household level, youth in households characterized by higher disadvantage (i.e., lower income-to-needs ratio) exhibited more strongly negative frontoamygdala coupling, particularly between the bilateral amygdala and medial orbitofrontal (mOFC) regions within the Frontoparietal Network. While more strongly positive amygdala-mOFC coupling was associated with higher levels of internalizing symptoms at baseline and 1-year follow-up, it did not mediate the association between income-to-needs ratio and internalizing symptoms. However, at the neighborhood level, amygdala-mOFC functional coupling moderated the effect of neighborhood deprivation on internalizing symptoms. Specifically, higher neighborhood deprivation was associated with higher internalizing symptoms for youth with more strongly positive connectivity, but not for youth with more strongly negative connectivity, suggesting a potential buffering effect. Findings highlight the importance of capturing multileveled socioecological contexts in which youth develop to identify youth who are most likely to benefit from early interventions.	4000/4163	Secondary Analysis	Shared
Neuroanatomical correlates of genetic risk for obesity in children	Obesity has a strong genetic component, with up to 20% of variance in body mass index (BMI) being accounted for by common polygenic variation. Most genetic polymorphisms associated with BMI are related to genes expressed in the central nervous system. At the same time, higher BMI is associated with neurocognitive changes. However, the direct link between genetics of obesity and neurobehavioral mechanisms related to weight gain is missing. Here, we use a large sample of participants (n > 4000) from the Adolescent Brain Cognitive Development cohort to investigate how genetic risk for obesity, expressed as polygenic risk score for BMI (BMI-PRS), is related to brain and behavioral measures in adolescents. In a series of analyses, we show that BMI-PRS is related to lower cortical volume and thickness in the frontal and temporal areas, relative to age-expected values. Relatedly, using structural equation modeling, we find that lower overall cortical volume is associated with higher impulsivity, which in turn is related to an increase in BMI 1 year later. In sum, our study shows that obesity might partially stem from genetic risk as expressed in brain changes in the frontal and temporal brain areas, and changes in impulsivity.	3709/4157	Secondary Analysis	Shared
Relating neighborhood deprivation to childhood obesity in the ABCD Study®: evidence for theories of neuroinflammation and neuronal stress	Objective: We evaluated whether relationships between area deprivation (ADI), body mass index (BMI) and brain structure (e.g., cortical thickness, subcortical volume) during pre-adolescence supported the immunologic model of self-regulation failure (NI) and/or neuronal stress (NS) theories of overeating. The NI theory proposes that ADI causes structural alteration in the brain due to the neuroinflammatory effects of overeating unhealthy foods. The NS theory proposes that ADI-related stress negatively impacts brain structure, which causes stress-related overeating and subsequent obesity. Methods: Data were gathered from the Adolescent Brain Cognitive DevelopmentSM Study® (9-12-years-old; n=3,087, 51% male). Linear mixed-effects models identified brain regions that were associated with both ADI and BMI; longitudinal associations were evaluated with mediation models. The NI model included ADI and BMI at 9/10-years-old and brain data at 11/12-years-old. The NS model included ADI and brain data at 9/10-years-old and BMI at 11/12-years-old. Results: BMI at 9/10-years-old partially mediated the relationship between ADI and Ventral DC volume at 11/12-years-old. Additionally, the Ventral DC at 9/10-years-old partially mediated the relationship between ADI and BMI at 11/12-years-old, even in youth who at baseline, were of a healthy weight. Results were unchanged when controlling for differences in brain structure and weight across the two-years. Conclusion: Greater area deprivation may indicate fewer access to resources that support healthy development, like nutritious food and nonstressful environments. Our findings provide evidence in support of the NI and NS theories of overeating, specifically, with greater ADI influencing health outcomes of obesity via brain structure alterations.	2732/3087	Secondary Analysis	Shared
What Is the Link Between Attention-Deficit/Hyperactivity Disorder and Sleep Disturbance? A Multimodal Examination of Longitudinal Relationships and Brain Structure Using Large-Scale Population-Based Cohorts	Background: Attention-deficit/hyperactivity disorder (ADHD) comorbid with sleep disturbances can produce profound disruption in daily life and negatively impact quality of life of both the child and the family. However, the temporal relationship between ADHD and sleep impairment is unclear, as are underlying common brain mechanisms. Methods: This study used data from the Quebec Longitudinal Study of Child Development (n = 1601, 52% female) and the Adolescent Brain Cognitive Development Study (n = 3515, 48% female). Longitudinal relationships between symptoms were examined using cross-lagged panel models. Gray matter volume neural correlates were identified using linear regression. The transcriptomic signature of the identified brain-ADHD-sleep relationship was characterized by gene enrichment analysis. Confounding factors, such as stimulant drugs for ADHD and socioeconomic status, were controlled for. Results: ADHD symptoms contributed to sleep disturbances at one or more subsequent time points in both cohorts. Lower gray matter volumes in the middle frontal gyrus and inferior frontal gyrus, amygdala, striatum, and insula were associated with both ADHD symptoms and sleep disturbances. ADHD symptoms significantly mediated the link between these structural brain abnormalities and sleep dysregulation, and genes were differentially expressed in the implicated brain regions, including those involved in neurotransmission and circadian entrainment. Conclusions: This study indicates that ADHD symptoms and sleep disturbances have common neural correlates, including structural changes of the ventral attention system and frontostriatal circuitry. Leveraging data from large datasets, these results offer new mechanistic insights into this clinically important relationship between ADHD and sleep impairment, with potential implications for neurobiological models and future therapeutic directions.	2948/3075	Secondary Analysis	Shared
Investigation of Psychiatric and Neuropsychological Correlates of Default Mode Network and Dorsal Attention Network Anticorrelation in Children.	The default mode network (DMN) and dorsal attention network (DAN) demonstrate an intrinsic "anticorrelation" in healthy adults, which is thought to represent the functional segregation between internally and externally directed thought. Reduced segregation of these networks has been proposed as a mechanism for cognitive deficits that occurs in many psychiatric disorders, but this association has rarely been tested in pre-adolescent children. The current analysis used data from the Adolescent Brain Cognitive Development study to examine the relationship between the strength of DMN/DAN anticorrelation and psychiatric symptoms in the largest sample to date of 9- to 10-year-old children (N = 6543). The relationship of DMN/DAN anticorrelation to a battery of neuropsychological tests was also assessed. DMN/DAN anticorrelation was robustly linked to attention problems, as well as age, sex, and socioeconomic factors. Other psychiatric correlates identified in prior reports were not robustly linked to DMN/DAN anticorrelation after controlling for demographic covariates. Among neuropsychological measures, the clearest correlates of DMN/DAN anticorrelation were the Card Sort task of executive function and cognitive flexibility and the NIH Toolbox Total Cognitive Score, although these did not survive correction for socioeconomic factors. These findings indicate a complicated relationship between DMN/DAN anticorrelation and demographics, neuropsychological function, and psychiatric problems.	2558/3004	Secondary Analysis	Shared
Different patterns of intrinsic functional connectivity at the default mode and attentional networks predict crystallized and fluid abilities in childhood	Crystallized abilities are skills used to solve problems based on experience, while fluid abilities are linked to reasoning without prior knowledge. To what extent crystallized and fluid abilities involve dissociated or overlapping neural systems is debatable. Due to often deployed small sample sizes or different study settings in prior work, the neural basis of crystallized and fluid abilities in childhood remains largely unknown. Here we analyzed within and between network connectivity patterns from resting-state functional MRI of 2707 children from the ABCD study. We hypothesized that differences in functional connectivity at the default mode network (DMN) and ventral and dorsal attentional networks (VAN, DAN) explain differences in fluid and crystallized abilities. We found that stronger between-network connectivity of the DMN and VAN, DMN and DAN, and VAN and DAN predicted crystallized abilities. Within-network connectivity of the DAN predicted both crystallized and fluid abilities. Our findings reveal that crystallized abilities rely on the functional coupling between attentional networks and the DMN, whereas fluid abilities are associated with a focal connectivity configuration at the DAN. Our study provides new evidence into the neural basis of child intelligence and calls for future comparative research in adulthood during neuropsychiatric diseases.	2417/2707	Secondary Analysis	Shared
A pattern of cognitive resource disruptions in childhood psychopathology	The Hurst exponent ( H ) isolated in fractal analyses of neuroimaging time-series is implicated broadly in cognition. Within this literature, H is associated with multiple mental disorders, suggesting that H is transdimensionally associated with psychopathology. Here, we unify these results and demonstrate a pattern of decreased H with increased general psychopathology and attention-deficit/hyperactivity factor scores during a working memory task in 1,839 children. This pattern predicts current and future cognitive performance in children and some psychopathology in 703 adults. This pattern also defines psychological and functional axes associating psychopathology with an imbalance in resource allocation between fronto-parietal and sensory-motor regions, driven by reduced resource allocation to fronto-parietal regions. This suggests the hypothesis that impaired working memory function in psychopathology follows from a reduced cognitive resource pool and a reduction in resources allocated to the task at hand.	1667/1839	Secondary Analysis	Shared
Comparison Between Gradients and Parcellations for Functional Connectivity Prediction of Behavior	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.	1333/1476	Secondary Analysis	Shared
A morphometrics approach for inclusion of localised characteristics from medical imaging studies into genome-wide association studies	Medical images, such as magnetic resonance or computed tomography, are increasingly being used to investigate the genetic architecture of neurological diseases like Alzheimer's disease, or psychiatric disorders like attention-deficit hyperactivity disorder. The quantified global or regional brain imaging measures are commonly known as imaging-specific or -derived phenotypes (IDPs) when conducting genotype-phenotype association studies. Inclusion of whole medical images rather than derived tabular data as IDPs has been done by either a voxel-wise approach or a global approach of whole medical images via principal component analysis. Limitations with multiple testing and inability to isolate high variation regions within the principal components arise with either of these approaches. This work proposes a principal component analysis-like localised approach of dimensionality reduction using diffeomorphic morphometry allowing for the selection of distances to model more regional effects.The main benefit of the proposed method is that it can can reduce the dimensionality of the problem considerably in comparison to the medical image's variability it is describing while grouping spatial information potentially lost in dimensionality reduction techniques like principal component analyses. Moreover, the approach not only allows to include locality in the analysis but can also be used as a generative model to explore the morphometric changes across an axis of particular components of interest. To demonstrate the feasibility of this pipeline for inclusion in a multivariate genome-wide association study, it was applied to 1,359 subjects from the Adolescent Brain Cognitive Development Study for traits related to attention-deficit disorder. The results show that the proposed method can identify more specific morphometric features associated with genome regions.	1207/1359	Secondary Analysis	Shared
Predicting multilingual effects on executive function and individual connectomes in children: An ABCD study	While there is a substantial amount of work studying multilingualism’s effect on cognitive functions, little is known about how the multilingual experience modulates the brain as a whole. In this study, we analyzed data of over 1,000 children from the Adolescent Brain Cognitive Development (ABCD) Study to examine whether monolinguals and multilinguals differ in executive function, functional brain connectivity, and brain–behavior associations. We observed significantly better performance from multilingual children than monolinguals in working-memory tasks. In one finding, we were able to classify multilinguals from monolinguals using only their whole-brain functional connectome at rest and during an emotional n-back task. Compared to monolinguals, the multilingual group had different functional connectivity mainly in the occipital lobe and subcortical areas during the emotional n-back task and in the occipital lobe and prefrontal cortex at rest. In contrast, we did not find any differences in behavioral performance and functional connectivity when performing a stop-signal task. As a second finding, we investigated the degree to which behavior is reflected in the brain by implementing a connectome-based behavior prediction approach. The multilingual group showed a significant correlation between observed and connectome-predicted individual working-memory performance scores, while the monolingual group did not show any correlations. Overall, our observations suggest that multilingualism enhances executive function and reliably modulates the corresponding brain functional connectome, distinguishing multilinguals from monolinguals even at the developmental stage.	1024/1075	Secondary Analysis	Shared
Tuber locations associated with infantile spasms map to a common brain network	Objective: Approximately 50% of patients with Tuberous Sclerosis Complex develop infantile spasms, a sudden-onset epilepsy syndrome associated with poor neurological outcomes. While an increased burden of tubers confers an elevated risk of infantile spasms, it remains unknown whether some tuber locations confer higher risk than others. Here, we test whether tuber location and connectivity are associated with infantile spasms. Methods: We segmented tubers from 123 children with (n=74) and without (n=49) infantile spasms from a prospective observational cohort. We used voxel-wise lesion symptom mapping to test for an association between spasms and tuber location. We then used lesion network mapping to test for an association between spasms and connectivity with tuber locations. Finally, we tested the discriminability of identified associations with logistic regression and cross validation as well as statistical mediation. Results: Tuber locations associated with infantile spasms were heterogenous, and no single location was significantly associated with spasms. However, >95% of tuber locations associated with spasms were functionally connected to the globus pallidi and cerebellar vermis. These connections were specific compared to tubers in patients without spasms. Logistic regression found that globus pallidus connectivity was a stronger predictor of spasms (OR 1.96, 95%CI [1.10, 3.50], p=0.02) than tuber burden (OR 1.65, 95%CI [0.90, 3.04], p=0.11), with a mean ROC area under the curve of 0.73 (+/-0.1) during repeated cross validation. Interpretation: Connectivity between tuber locations and the bilateral globus pallidus is associated with infantile spasms. Our findings lend insight into spasm pathophysiology and may identify patients at risk.	1000/1000	Secondary Analysis	Shared
Brain structural associations with depression in a large early adolescent sample (the ABCD Study)	Background: Depression is the leading cause of disability worldwide with >50% of cases emerging before the age of 25 years. Large-scale neuroimaging studies in depression implicate robust structural brain differences in the disorder. However most studies have been conducted in adults and therefore, the temporal origins of depression-related imaging features remain largely unknown. This has important implications for understanding aetiology and informing timings of potential intervention. Methods: Here, we examine associations between brain structure (cortical metrics and white matter microstructural integrity) and depression ratings (from caregiver and child), in a large sample of early adolescents from the Adolescent Brain and Cognitive Development (ABCD) Study (N=9981, 9-11-year-olds). Findings: We report significantly decreased global cortical and white matter metrics, and regionally in frontal, limbic and temporal areas in adolescent depression (Cohen’s d = -0.018 to -0041, β = -0·019 to -0.057). Further, we report consistently stronger imaging associations for caregiver-reported compared to child-reported depression ratings. Divergences between reports (caregiver vs child) were found to significantly relate to negative socio-environmental factors (e.g., family conflict, absolute β=0.048 to 0.169). Interpretation: Depression ratings in early adolescence were associated with similar imaging findings to those seen in adult depression samples, suggesting neuroanatomical abnormalities may be present early in the disease course, arguing for the importance of early intervention. Associations between socio-environmental factors and reporter discrepancy warrant further consideration, both in the wider context of the assessment of adolescent psychopathology, and in relation to their role in aetiology. Funding: Wellcome Trust, Mental Health Research UK.	855/999	Secondary Analysis	Shared
Lifestyle Factors Counteract the Neurodevelopmental Impact of Genetic Risk for Accelerated Brain Aging in Adolescence	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.	810/843	Secondary Analysis	Shared
Longitudinal assessment of brain structure and behavior in youth with rapid weight gain: Potential contributing causes and consequences	Objective: Independent of weight status, rapid weight gain has been associated with underlying brain structure variation in regions associated with food intake and impulsivity among pre-adolescents. Yet, we lack clarity on how developmental maturation coincides with rapid weight gain and weight stability. Methods: We identified brain predictors of two-year rapid weight gain and its longitudinal effects on brain structure and impulsivity in the Adolescent Brain Cognitive DevelopmentSM Study®. Youth were categorized as Healthy Weight/Weight Stable (WSHW, n=527) or Weight Gainers (WG, n=221, >38lbs); 63% of the WG group were healthy weight at 9-to-10-years-old. Results: A five-fold cross-validated logistic elastic-net regression revealed that rapid weight gain was associated with structural variation amongst 39 brain features at 9-to-10-years-old in regions involved with executive functioning, appetitive control, and reward sensitivity. Two years later, WG youth showed differences in change over time in several of these regions and performed worse on measures of impulsivity. Conclusions: These findings suggest that brain structure in pre-adolescence may predispose some to rapid weight gain and that weight gain itself may alter maturational brain change in regions important for food intake and impulsivity. Behavioral interventions that target inhibitory control may improve trajectories of brain maturation and facilitate healthier behaviors.	696/748	Secondary Analysis	Shared
Latent Profiles of Sleep Patterns in Adolescence: Associations with Behavioral Health Risk	Purpose: The present study characterized sleep profiles in a national longitudinal sample of early adolescents and examined whether profiles predicted later behavioral problems. Methods: Three waves of data (2016-2021) were obtained from the Adolescent Behavior and Cognitive Development study, including 3,326 participants with both weekday and weekend sleep data measured by Fitbit wearables (age range 10.58 to 13.67; 49.3% female). Latent profile analysis was utilized to identify sleep profiles using multiple sleep indicators (duration, latency, efficiency, wake minutes, wake counts, midpoint). We then explored whether demographic predictors predicted profile membership and tested the latent sleep profiles’ predictive utility of internalizing and externalizing symptoms. Results: Four profiles were identified: average sleep (40.39%), high duration & high wakefulness (28.58%), high efficiency, low duration & low wakefulness (16.86%), and low duration & low efficiency (14.17%). Participants with older age, males, higher BMI, and advanced pubertal status were more likely to be classified in the low duration & low efficiency profile than average group. Participants with lower income, minority identification, older age, and higher BMI were more likely to be classified in the high efficiency, low duration & low wakefulness than the average group. Participants with lower parental education and males were more likely to be in the high sleep duration & high wakefulness than the average group. The low duration & low efficiency group had the highest attention problems, social problems, and rule-breaking behaviors. Conclusion: Our findings highlight unique sleep patterns in early adolescence and their prospective links with internalizing and externalizing problems. Keywords: sleep, risk, internalizing problems, externalizing problems, latent profile	469/500	Secondary Analysis	Shared

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