NIMH Data Archive - Data

Genomics

Neuroimaging

Phenotype¹

New Trial
Clinical Trial

¹ Numbers reported are subjects by age

New Project
Grant/Project Number

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

Collection - Use Existing Experiment

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

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

Select	Experiment Id	Experiment Name	Experiment Type	Created On

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

Collection - Add Experiment

Add Supporting Documentation

Funding Source:
URL:

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

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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

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Human Connectome Project for Early Psychosis #2914

General
Experiments (1)
Shared Data
Publications (48)
Data Expected (48)
Associated Studies (16)

Collection Title	Collection Investigators	Collection Description
Collection Title:	Human Connectome Project for Early Psychosis
Collection Investigators:	Martha Shenton
Collection Description:	The Human Connectome Project HCP was initiated to accelerate progress in understanding the organization of the human brain. To accomplish this goal, the original HCP Washington-University-Minnesota and MGH Harvard-UCLA Projects have focused on acquiring and sharing data relevant to structural and functional connectivity in 1200 healthy twins and their siblings. The main aims have been to use advanced 3T imaging to develop advanced data acquisition and scanning sequences, to develop novel algorithms for post-processing of white matter fiber structure and brain connectivity, and to develop novel graphical techniques for brain connectomes. The purpose of the new funding opportunity announcement, PAR-14-281 for Connectomes Related to Human Diseases U01, is to build upon the original HCP by extending it to the study of human brain diseases in order to acquire the same high quality data as in the original HCP, but with the goal of accelerating knowledge of brain diseases in a manner heretofore not possible. Importantly, progress has been slow and frustrating in translating knowledge of the brain to new and more effective treatments for human brain diseases such as severe mental disorders. In fact, severe mental disorders, which include psychotic disorders, are brain diseases that are not only devastating because they result in severe disruptions that occur early in life, but, for many, the course of illness is progressive, leading to chronic debilitation and early mortality. Thus the need to accelerate knowledge of dysfunctions in structural and functional brain connectivity in these disorders, and to translate this knowledge to treatment, is critical. The primary goal of the proposed Human Connectome Project on Early Psychosis is to acquire high quality data consistent with data acquired by the original HCP. To this end, we will acquire imaging data on Prisma 3T magnets at two sites, one in Boston and one in Indianapolis, using the HCP Lifespan Prisma protocol. This imaging protocol was developed to be of similar high quality to the original HCP, but with reduced scan time, the latter important in a psychosis cohort. We will also use behavioral measures from the HCP as well as additional measures specific to early psychosis. We will acquire blood to be stored at the Rutgers University Cell and DNA Repository RUCDR Aim 1, and we will use the Washington University HCP post-processing pipeline to process imaging data Aim 2. Additionally, we will include new imaging tools for signal drop detection, multi-tensor tractography, diffusion magnetic resonance imaging dMRI models, i.e., free-water imaging, and a new harmonization protocol for diffusion images Aim 3. We will also perform, as a representative example, a study comparing brain networks of affective and non-affective psychosis groups with controls Aim 4. The main goals are thus to acquire high quality imaging, behavioral, cognitive, and genetic data on an important cohort of early psychosis patients, in a manner consistent with the HCP, which will be made available to the research community for future studies. Such data will provide a unique opportunity to characterize the pathological substrates of early psychosis.
Data Repository:	Connectome Coordination Facility
Permission Group:
Collection Creation Date:	05/03/2018
NIH Research Initiatives:	Human Connectome Project (HCP), NIMH Repository & Genomics Resource (NRGR)
Collection Phase:	Funding Completed
Collection Sub-Phase:	Close Out
Blinded Clinical Trial:	No
Total Funded Amount:	$2,954,138.00
Subjects Shared:	253
Collection DOI:	10.15154/s25n-tm53

{"values":[]}

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Funding Sources:

Funding Source Name	Funding Source URL
NIH - Extramural	None

Supporting Documentation:

File Name	File Type	Description	Audience
Appendix_1_HCP-EP_Release_Imaging_Protocols.pdf	Methods	HCP Early Psychosis 1.0 Data Release: Reference Manual Appendix 1 – Imaging Protocols	General Public
Appendix_2_HCP-EP_Release_Files_Directory_Structure.pdf	Methods	HCP Early Psychosis 1.0 Data Release: Reference Manual Appendix 2 – File Names and Directory Structure	General Public
Appendix_3_HCP-EP_Release_1.1_Change_Log.pdf	Software	HCP Early Psychosis Release 1.1: Reference Manual Appendix 3 - Change Log	General Public
Appendix_2_HCP-EP_Release_1.1_Files_Directory_Stucture.pdf	Software	HCP Early Psychosis Release 1.1: Reference Manual Appendix 2 - File Names and Directory Structure	General Public
HCP-EP_Release_1.1_Manual.pdf	Software	HCP Early Psychosis Release 1.1: Reference Manual	General Public
HCP-EP_Release_1.0_Manual.pdf	Methods	HCP Early Psychosis 1.0 Data Release: Reference Manual	General Public

Grant Information:

Project Number	Title	Start Date	Original End Date	End Date	Planned Enrollment	Actual Enrollment	Organization	Funds Obligated
U01MH109977-01	Human Connectome Project for Early Psychosis	05/17/2016	02/29/2020	02/29/2020	0	391	BRIGHAM AND WOMENS HOSPITAL	$2,954,138.00

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
1563	Resting State	06/03/2020	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
Auditory Continuous Performance Test	Clinical Assessments	251
Clinical Assessment Interview for Negative Symptoms -CAINS	Clinical Assessments	177
Clinical Global Impression (CGI)	Clinical Assessments	251
Cognition Composite Scores	Clinical Assessments	234
Delay Discounting Task	Clinical Assessments	238
Dimensional Change Card Sort Test (DCCS)	Clinical Assessments	234
Family Medical History	Clinical Assessments	251
Flanker Task	Clinical Assessments	234
Hollingshead Socioeconomic Rating Scale	Clinical Assessments	251
Image	Imaging	183
Imaging Collection	Imaging	183
Medication History	Clinical Assessments	251
Montgomery-Asberg Depression Rating Scale	Clinical Assessments	180
NIH Toolbox Emotion Domain - Emotional Support Survey	Clinical Assessments	234
NIH Toolbox Emotion Domain - Fear Surveys	Clinical Assessments	3
NIH Toolbox Emotion Domain - Friendship Survey	Clinical Assessments	234
NIH Toolbox Emotion Domain - Peer Rejection and Perceived Rejection Surveys	Clinical Assessments	234
NIH Toolbox Emotion Domain - Perceived Hostility Surveys	Clinical Assessments	234
NIH Toolbox Emotion Domain - Psychological Well-Being	Clinical Assessments	234
NIH Toolbox Emotion Domain - Sadness Surveys	Clinical Assessments	3
NIH Toolbox Emotion Domain - Self-Efficacy Survey	Clinical Assessments	234
NIH Toolbox List Sorting Working Memory Test	Clinical Assessments	234
NIH Toolbox Motor Domain	Clinical Assessments	234
NIH Toolbox Oral Reading Recognition Test	Clinical Assessments	234
NIH Toolbox Picture Vocabulary Test	Clinical Assessments	234
NIH Toolbox Sensation Domain	Clinical Assessments	234
PROMIS Anger	Clinical Assessments	234
PROMIS Emotional Distress - Depression	Clinical Assessments	231
PROMIS Emotional Distress-Anxiety	Clinical Assessments	231
PROMIS General Life Satisfaction	Clinical Assessments	194
PROMIS Social Isolation	Clinical Assessments	234
Pattern Comparison Processing Speed	Clinical Assessments	233
Penn Emotion Recognition Task	Clinical Assessments	170
Perceived Stress Scale	Clinical Assessments	234
Picture Sequence Memory	Clinical Assessments	234
Pre-Session Questionnaire	Clinical Assessments	251
Processed MRI Data	Imaging	169
Psychosocial Interview	Clinical Assessments	245
Research Subject	Clinical Assessments	251
SCID-V Diagnosis	Clinical Assessments	184
Seidman Olfactory Questionnaire	Clinical Assessments	251
Sociodemographics	Clinical Assessments	251
Structured Clinical Interview for the Positive and Negative Syndrome Scale	Clinical Assessments	181
Traumatic Brain Injury	Clinical Assessments	251
WASI-2	Clinical Assessments	251
Young Mania Rating Scale	Clinical Assessments	184

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
42786188	Create Study	Reduced amplitude of low frequency fluctuation in the sensorimotor cortex in early psychosis: association with motor dexterity and hyperconnectivity.	Schizophrenia (Heidelberg, Germany)	Smucny, Jason; Wylie, Korey P; Tregellas, Jason R; Hare, Stephanie M	July 29, 2026	Not Determined
42401715	Create Study	Diagnostic and sex effects on frontostriatal brain wiring structural organization in early psychosis affective subjects compared to healthy controls.	Molecular psychiatry	Levitt, J J; Zhang, F; Vangel, M; Nestor, P G; Rathi, Y; Cetin-Karayumak, S; Kubicki, M; Pasternak, O; Coleman, M J; Lewandowski, K E; Holt, D J; Keshavan, M; Bouix, S; Öngür, D; Breier, A; Shenton, M E; O'Donnell, L J	July 4, 2026	Not Determined
42094566	Create Study	Linking human brain functional connectivity to underlying neurotransmission.	bioRxiv : the preprint server for biology	Lotter, Leon D; Shafiei, Golia; Larabi, Daouia; Koushik, Abhay; Dipasquale, Ottavia; Mehta, Mitul; Cercignani, Mara; Sethi, Arjun; Harrison, Neil; Holiga, Štefan; Umbricht, Daniel; Yakushev, Igor; Muthukumaraswamy, Suresh; Forsyth, Anna; Hipp, Joerg F; Misic, Bratislav; Caspers, Svenja; Koenig, Julian; Patil, Kaustubh R; Paquola, Casey; Eickhoff, Simon B; Dukart, Juergen	May 5, 2026	Not Determined
41279850	Create Study	Global organisation of structural covariance networks derived from parcellated cortical surface area in atypical populations.	bioRxiv : the preprint server for biology	Roseby, William; Racey, Chris; Ward, Jamie	October 30, 2025	Not Determined
41104693	Create Study	Altered Cortical Gyrification Is Associated with Cortical and White Matter Microstructure in Individuals with Early Psychosis: A Multimodal Neuroimaging Study.	Schizophrenia bulletin	Sasabayashi, Daiki; Seitz-Holland, Johanna; Rathi, Yogesh; Kim, Nicholas; Cho, Kang Ik K; Mohandass, Dheshan; Billah, Tashrif; Haidar, Anastasia; Kotler, Elana; Cetin-Karayumak, Suheyla; Jacobs, Grace R; Berberich, Cornelius; Lewandowski, Kathryn E; Mesholam-Gately, Raquelle I; Wojcik, Joanne; Haaf, Moritz; Koike, Shinsuke; Hirano, Yoji; Takahashi, Tsutomu; Suzuki, Michio; Pasternak, Ofer; Keshavan, Matcheri S; Holt, Daphne; Öngür, Dost; Breier, Alan; Coleman, Michael J; Bouix, Sylvain; Shenton, Martha E; Kubicki, Marek	October 17, 2025	Not Determined
40896904	Create Study	Microstructural alterations of the corpus callosum in affective and non-affective early psychosis: A diffusion magnetic resonance imaging study.	Schizophrenia research	Sanjari Moghaddam, Hossein; Aarabi, Mohammad Hadi; Kiani, Iman; Cattarinussi, Giulia; Khodadadi, Shiva; Delavari, Sahar; Sambataro, Fabio	October 1, 2025	Not Determined
40851911	Create Study	CICADA: An automated and flexible tool for comprehensive fMRI noise reduction.	Imaging neuroscience (Cambridge, Mass.)	Dodd, Keith; McHugo, Maureen; Sarabia, Lauren; Wylie, Korey P; Legget, Kristina T; Cornier, Marc-Andre; Tregellas, Jason R	January 1, 2025	Not Determined
40777274	Create Study	Charting structural brain asymmetry across the human lifespan.	bioRxiv : the preprint server for biology	Dorfschmidt, Lena; White, Simon; Gardner, Margaret; Bedford, Saashi; Ball, Gareth; Edwards, A David; Gu, Yuanjun; He, Yuankai; Huang, Hao; Karandikar, Shivaram; Kyriakopoulou, Vanessa; Ouyuang, Minhui; Pulli, Elmo P; Raznahan, Armin; Robinson, Emma C; Romero-García, Rafael; Satterthwaite, Theodore D; Schabdach, Jenna; Sebenius, Isaac; Sha, Zhiqiang; Shinohara, Russell T; Tuulari, Jetro; Vaghi, Matilde M; Vogel, Jacob; Váša, František; Williams, Logan; Zimmerman, Dabriel; Lifespan Brain Chart Consortium; Warrier, Varun; Wagstyl, Konrad; Bullmore, Edward T; Bethlehem, Richard A I; Seidlitz, Jakob; Alexander-Bloch, Aaron	July 24, 2025	Not Determined
40661622	Create Study	Multivariate Resting-State Functional Connectivity Features Linked to Transdiagnostic Psychopathology in Early Psychosis.	bioRxiv : the preprint server for biology	Wang, Haley R; Liu, Zhen-Qi; Nomi, Jason S; Schleifer, Charles H; Bearden, Carrie E; Misic, Bratislav; Uddin, Lucina Q; Karlsgodt, Katherine H	June 9, 2025	Not Determined
40657322	Create Study	Early psychosis is characterized by white matter abnormalities in fiber structures supporting local connectivity.	medRxiv : the preprint server for health sciences	Saito, Yoshito; Syeda, Warda T; Wannan, Cassandra M J; Gurleyen, Yasmin; Rapado-Castro, Marta; Di Biase, Maria A; Mito, Remika; Pantelis, Christos	May 14, 2025	Not Determined
40617381	Create Study	Mapping Cerebellar Connectivity to Cognition in Psychosis: Convergent Evidence From Functional Magnetic Resonance Imaging and Transcranial Magnetic Stimulation.	Biological psychiatry	Cao, Hengyi; Argyelan, Miklos; Yan, Joanna; Velioglu, Halil Aziz; Fang, Franky; Joanlanne, Andrea; Kang, Simran; Prizgint, Lara; Schugart, Jenna; Brown, Kadeem; Cholewa, John; Watson, Philip; Tang, Sunny X; Carrion, Ricardo; Rubio, Jose; Foroughi, Moein; Lencz, Todd; Malhotra, Anil K	January 15, 2026	Not Determined
40556454	Create Study	Grip Strength as a Marker of Resting-State Network Integrity and Well-Being in Early Psychosis.	The American journal of psychiatry	Ward, Heather Burrell; Beermann, Adam; Manzanarez Felix, Karlos; Narisetti, Lipika; Lewandowski, Kathryn E; Coleman, Michael; Bouix, Sylvain; Holt, Daphne; Öngür, Dost; Breier, Alan; Shenton, Martha E; Brady Jr, Roscoe O; Moussa-Tooks, Alexandra B	September 1, 2025	Not Determined
40527079	Create Study	Characterising grey-white matter relationships in recent-onset psychosis and its association with cognitive function.	NeuroImage. Clinical	Saito, Yoshito; Pantelis, Christos; Cropley, Vanessa; Laskaris, Liliana; Wannan, Cassandra M J; Syeda, Warda T	January 1, 2025	Not Determined
40435586	Create Study	Negative symptoms, cognition, and community functioning in early psychosis.	Schizophrenia research	Blotner, Julia; Hechinger, Rachel; Shenton, Martha E; Coleman, Michael J; Öngür, Dost; Lewandowski, Kathryn E	July 1, 2025	Not Determined
39966957	Create Study	A Latent Profile Analysis of Psychosis Symptoms to Examine Distress and Depression as Pathways to Suicide Ideation Among Individuals in an Early Phase of Psychosis Illness.	Early intervention in psychiatry	Bornheimer, Lindsay A; Brdar, Nicholas M; Lapidos, Adrienne; Kelter, Alexandra N; Miner, Chloe; Grogan-Kaylor, Andrew	February 1, 2025	Not Determined
39223185	Create Study	Cognitive subgroups of affective and non-affective psychosis show differences in medication and cortico-subcortical brain networks.	Scientific reports	Bracher, Katharina M; Wohlschlaeger, Afra; Koch, Kathrin; Knolle, Franziska	September 2, 2024	Not Determined
39208481	Create Study	Diverging functional connectivity timescales: Capturing distinct aspects of cognitive performance in early psychosis.	NeuroImage. Clinical	Hirsch, Fabian; Bumanglag, Ângelo; Zhang, Yifei; Wohlschlaeger, Afra	January 1, 2024	Not Determined
39182722	Create Study	Normative Modeling of Thalamic Nuclear Volumes and Characterization of Lateralized Volume Alterations in Alzheimer''s Disease Versus Schizophrenia.	Biological psychiatry. Cognitive neuroscience and neuroimaging	Young, Taylor R; Kumar, Vinod Jangir; Saranathan, Manojkumar	July 1, 2025	Not Determined
39036958	Create Study	An Introduction to the Human Connectome Project for Early Psychosis.	Schizophrenia bulletin	Jacobs, Grace R; Coleman, Michael J; Lewandowski, Kathryn E; Pasternak, Ofer; Cetin-Karayumak, Suheyla; Mesholam-Gately, Raquelle I; Wojcik, Joanne; Kennedy, Leda; Knyazhanskaya, Evdokiya; Reid, Benjamin; Swago, Sophia; Lyons, Monica G; Rizzoni, Elizabeth; John, Omar; Carrington, Holly; Kim, Nicholas; Kotler, Elana; Veale, Simone; Haidar, Anastasia; Prunier, Nicholas; Haaf, Moritz; Levitt, James J; Seitz-Holland, Johanna; Rathi, Yogesh; Kubicki, Marek; Keshavan, Matcheri S; Holt, Daphne J; Seidman, Larry J; Öngür, Dost; Breier, Alan; Bouix, Sylvain; Shenton, Martha E	May 8, 2025	Not Determined
39032726	Create Study	Robust Brain Correlates of Cognitive Performance in Psychosis and Its Prodrome.	Biological psychiatry	Ward, Heather Burrell; Beermann, Adam; Xie, Jing; Yildiz, Gulcan; Felix, Karlos Manzanarez; Addington, Jean; Bearden, Carrie E; Cadenhead, Kristin; Cannon, Tyrone D; Cornblatt, Barbara; Keshavan, Matcheri; Mathalon, Daniel; Perkins, Diana O; Seidman, Larry; Stone, William S; Tsuang, Ming T; Walker, Elaine F; Woods, Scott; Coleman, Michael J; Bouix, Sylvain; Holt, Daphne J; Öngür, Dost; Breier, Alan; Shenton, Martha E; Heckers, Stephan; Halko, Mark A; Lewandowski, Kathryn E; Brady Jr, Roscoe O	January 15, 2025	Not Determined
38908657	Create Study	Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated With Psychopathology Across Independent Cohorts.	Biological psychiatry	Wang, Haley R; Liu, Zhen-Qi; Nakua, Hajer; Hegarty, Catherine E; Thies, Melanie Blair; Patel, Pooja K; Schleifer, Charles H; Boeck, Thomas P; McKinney, Rachel A; Currin, Danielle; Leathem, Logan; DeRosse, Pamela; Bearden, Carrie E; Misic, Bratislav; Karlsgodt, Katherine H	January 15, 2025	Not Determined
38503924	Create Study	Data-driven, connectome-wide analysis identifies psychosis-specific brain correlates of fear and anxiety.	Molecular psychiatry	Feola, Brandee; Beermann, Adam; Manzanarez Felix, Karlos; Coleman, Michael; Bouix, Sylvain; Holt, Daphne J; Lewandowski, Kathryn E; Öngür, Dost; Breier, Alan; Shenton, Martha E; Heckers, Stephan; Brady Jr, Roscoe O; Blackford, Jennifer Urbano; Ward, Heather Burrell	September 1, 2024	Not Determined
38496426	Create Study	Normative modeling of thalamic nuclear volumes.	medRxiv : the preprint server for health sciences	Young, Taylor; Kumar, Vinod Jangid; Saranathan, Manojkumar	March 8, 2024	Not Determined
38452884	Create Study	Isolation of Distinct Networks Driving Action and Cognition in Psychomotor Processes.	Biological psychiatry	Moussa-Tooks, Alexandra B; Beermann, Adam; Manzanarez Felix, Karlos; Coleman, Michael; Bouix, Sylvain; Holt, Daphne; Lewandowski, Kathryn E; Öngür, Dost; Breier, Alan; Shenton, Martha E; Heckers, Stephan; Walther, Sebastian; Brady Jr, Roscoe O; Ward, Heather Burrell	September 1, 2024	Not Determined
38270836	Create Study	More organized white matter is associated with positivity bias in older adults.	Brain imaging and behavior	Viher, Petra V; Seitz-Holland, Johanna; Schulz, Marc S; Kensinger, Elizabeth A; Karmacharya, Sarina; Swisher, Talis; Lyall, Amanda E; Makris, Nikos; Bouix, Sylvain; Shenton, Martha E; Kubicki, Marek; Waldinger, Robert J	June 1, 2024	Not Determined

helpcenter.collection.publications-tab

Collection - Publications

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

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

Frequently Asked Questions

How can I determine if a publication is relevant?

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

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

Glossary

Create Study

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

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

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

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

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

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

Contact NDA Help Desk

Data Expected List: Mandatory Data Structures

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

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

Data Expected	Targeted Enrollment	Initial Submission	Subjects Submitted	Initial Share	Subjects Shared	Status
Research Subject and Pedigree	400	07/15/2019	308	11/15/2019	251	Approved

To create your project's Data Expected list, use the "+New Data Expected" to add or request existing structures and to request new Data Structures that are not in the NDA Data Dictionary.

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

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

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

Please visit the Completing Your Data Expected Tutorial for more information.

Data Expected List: Data Structures per Research Aims

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

Data Expected	Targeted Enrollment	Initial Submission	Subjects Submitted	Initial Share	Subjects Shared	Status
Perceived Stress Scale	17	08/31/2019	282	11/15/2019	234	Approved
Penn Emotion Recognition Task-40	400	08/31/2019	306	09/01/2019	170	Approved
Mania Rating Scale	400	08/31/2019	307	09/01/2019	184	Approved
Medical History	400	08/31/2019	308	09/01/2019	251	Approved
Wechsler Abbreviated Scale of Intelligence (WASI)	400	08/31/2019	308	09/01/2019	251	Approved
Demographics	400	08/31/2019	308	09/01/2019	251	Approved
Clinical Global Impression (CGI)	400	08/31/2019	308	09/01/2019	251	Approved
Processed MRI Data	400	08/31/2019	219	08/31/2020	169	Approved
Structured Clinical Interview for DSM (SCID)	400	08/31/2019	307	09/01/2019	184	Approved
Positive and Negative Syndrome Scale (PANSS)	400	08/31/2019	305	09/01/2019	181	Approved
Picture Sequence Memory	400	08/31/2019	282	09/09/2020	234	Approved
Cognition Composite Scores	400	08/31/2019	281	09/09/2020	234	Approved
Pattern Comparison Processing Speed	400	08/31/2019	281	09/09/2020	233	Approved
List Sorting Working Memory Test	400	08/31/2019	281	08/31/2020	234	Approved
Imaging (Structural, fMRI, DTI, PET, microscopy)	400	08/31/2019	291	08/31/2020	183	Approved
Auditory CPT	400	08/31/2019	305	09/01/2019	251	Approved
Psychological Well-Being Summary	17	08/31/2019	282	11/15/2019	234	Approved
Dimensional Change Card Sort Test	17	08/31/2019	282	11/15/2019	234	Approved
Emotional Distress-Anxiety	17	08/31/2019	278	11/15/2019	231	Approved
Emotional Distress - Depression	17	08/31/2019	278	11/15/2019	231	Approved
Social Isolation	17	08/31/2019	282	11/15/2019	234	Approved
Psychosocial Interview	400	08/31/2019	308	09/01/2019	245	Approved
Montgomery-Asberg Depression Rating Scale	400	08/31/2019	305	09/01/2019	180	Approved
Delay Discounting Task	400	08/31/2019	305	09/01/2019	238	Approved
Flanker Task	17	08/31/2019	282	11/15/2019	234	Approved
Anger	17	08/31/2019	282	11/15/2019	234	Approved
Traumatic Brain Injury	400	08/31/2019	308	09/01/2019	251	Approved
NIH Toolbox Oral Reading Recognition Test	17	08/31/2019	280	11/15/2019	234	Approved
Picture Vocabulary Test	17	08/31/2019	282	11/15/2019	234	Approved
Self Efficacy Survey	17	08/31/2019	282	11/15/2019	234	Approved
NIH Toolbox Fear Anxiety Surveys	400	08/31/2019	4	09/09/2020	3	Approved
NIH Toolbox Motor Domain	17	08/31/2019	282	11/15/2019	234	Approved
Sadness Survey	400	08/31/2019	4	09/09/2020	3	Approved
NIH Toolbox Sensation Domain	17	08/31/2019	284	11/15/2019	234	Approved
NIH Toolbox Rejection Surveys	17	08/31/2019	282	11/15/2019	234	Approved
NIH Toolbox Emotional Support Survey	17	08/31/2019	282	11/15/2019	234	Approved
NIH Toolbox Friendship Survey	17	08/31/2019	282	11/15/2019	234	Approved
NIH Toolbox Perceived Hostility	17	08/31/2019	282	11/15/2019	234	Approved
Clinical Assessment Interview for Negative Symptoms	400	08/31/2019	303	09/01/2019	177	Approved
Medication History	400	08/31/2019	308	08/31/2020	251	Approved
Brief Negative Symptom Scale	400	02/29/2020	303	02/28/2021	0	Approved
PROMIS General Life Satisfaction	1	08/31/2019	241	11/15/2019	194	Approved
Olfactory Questionnaire	400	08/31/2019	308	09/01/2019	251	Approved
Pre-session Questionnaire	400	08/31/2019	308	09/01/2019	251	Approved
NRGR Demographics and Diagnostic Form	205	08/24/2026	205	09/06/2026	0	Approved
NRGR Alternate ID	205	08/24/2026	205	09/06/2026	0	Approved
NRGR Extended Clinical Diagnosis	201	08/24/2026	201	09/06/2026	0	Approved

Structure not yet defined

No Status history for this Data Expected has been recorded yet

helpcenter.collection.data-expected-tab

Collection - Data Expected

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

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

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

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

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

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

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

Frequently Asked Questions

What is an NDA Data Structure?

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

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

Glossary

Analyzed Data

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

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

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

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

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

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

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

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

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

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

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

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

Contact NDA Help Desk

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

Associated Studies

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

Study NameFilter by Study Name	DOIFilter by DOI	AbstractFilter by Abstract	Collection/Study SubjectsFilter by Collection/Study Subjects	Data UsageFilter by Data Usage	StateFilter by State
Perception of social experiences and cortical thickness change together throughout early adolescence: findings from the ABCD cohort	10.15154/1524763	Early adolescence is a dynamic period of social and cortical development amidst rapid hormonal and puberty changes. We examined how differences and changes in positive social experiences and cortical thickness co-develop from age 9-11 and 11-13 years in the ABCD cohort (N~12,000). We used Bivariate Latent Change Score Models to capture cortical development (modelling mean whole-brain cortical thickness) and positive social experiences (modelling caregiver monitoring, family cohesion, prosocial behaviour, number of friends, school engagement, school involvement, and neighborhood safety). We found that positive social experiences decreased between age 9-11 years (baseline) and 11-13 years (2-year-follow-up), indicating that social experiences were perceived as less positive over time. We found evidence for correlated change, such that a greater reduction in positive social experiences was associated with a greater reduction in cortical thickness (est=5.23, SE=1.31, p<.001, standardized coefficient=.08), which did not differ between males and females in early and late puberty stages. We found mixed evidence for sex-specific relationships between puberty stage and social experiences. The evidence supports a transactional model of development, in that positive social experiences and cortical thickness change together throughout early adolescence. The findings also highlight the importance of supporting youth in early adolescence through school transitions.	169/13803	Secondary Analysis	Shared
Lifespan development of brain asymmetry	10.15154/3er3-dc69	Lateralization is a fundamental principle of structural brain organization. In vivo imaging of brain asymmetry is essential for deciphering lateralized brain functions and their disruption in neurodevelopmental and neurodegenerative disorders. Here, we present a normative framework for benchmarking brain asymmetry across the lifespan, developed from an aggregated sample of 128 primary neuroimaging studies, including 177,701 scans from 138,231 individuals, jointly spanning the age range from 20 post menstrual weeks to 102 years. This resource includes comprehensive, hemisphere-specific brain growth charts for multiple neuroimaging phenotypes: regional cortical grey matter volume, thickness, surface area, and subcortical volumes. Our findings reveal distinct spatial patterns of asymmetry, with early leftward asymmetry observed in association cortices and late rightward asymmetry in sensory regions. These trajectories support theories of the neuroplasticity of asymmetry and the role of both genetic and environmental factors in shaping brain lateralization. Additionally, we provide tools to generate asymmetry centile scores, which allow the quantification of individual deviations from typical asymmetry throughout the lifespan and can be applied to unseen data or clinical populations. We demonstrate the utility of these models by highlighting group-level differences in asymmetry in autism spectrum disorder, schizophrenia, and Alzheimer’s disease, and exploring genetic correlations with hemispheric specialization. To facilitate further research, we have made this normative framework freely available as an interactive open-access resource (upon publication), offering an essential tool to advance both basic and clinical neuroscience.	183/8552	Secondary Analysis	Shared
Functional Brain Network Dynamics Mediate the Relationship between Female Reproductive Aging and Perceived Hostility: Relevance to Neuropsychiatric Disorders	10.15154/g3hb-nf28	Premature reproductive aging is linked to heightened stress sensitivity and psychological maladjustment across the life course. However, the brain dynamics underlying this relationship are poorly understood. To address this issue, we analysed multimodal data from female participants in the Adolescent Brain and Cognitive Development (longitudinal, N=441; aged 9-12 years) and Human Connectome-Aging (cross-sectional, N =130; aged 36-60 years) studies. Age-specific intrinsic functional brain network dynamics mediated the link between reproductive aging and perceptions of greater interpersonal adversity. The adolescent profile overlapped areas of greater glutamatergic and dopaminergic receptor density, while the middle-aged profile was concentrated in visual, attentional and default mode networks. The two profiles showed opposite relationships with patterns of functional neural network variability and cortical atrophy observed in psychosis vs major depressive disorder. Our findings underscore the divergent patterns of brain aging linked to reproductive maturation vs senescence, which may explain developmentally specific vulnerability to distinct disorders.	178/849	Secondary Analysis	Shared
Sex-differential markers of psychiatric risk and treatment response based on premature aging of functional brain network dynamics and peripheral physiology	10.15154/9wfk-qa89	Background Aging is a multilevel process of gradual decline that predicts morbidity and mortality. Independent investigations have implicated senescence of brain and peripheral physiology in psychiatric risk, but it is unclear whether these effects stem from unique or shared mechanisms. Methods To address this question, we analyzed clinical, blood chemistry and resting state functional neuroimaging data in a healthy aging cohort (N= 427; age 36-100 years) and two disorder-specific samples encompassing patients with early psychosis (100 patients, 16-35 years) and major depressive disorder (MDD) (104 patients, 20-76 years). Results We identified sex-dependent coupling between blood chemistry markers of metabolic senescence (i.e., homeostatic dysregulation), functional brain network aging, and psychiatric risk. In females, premature aging of frontoparietal and somatomotor networks was linked to greater homeostatic dysregulation. It also predicted the severity and treatment resistance of mood symptoms (depression/anxiety [all three samples], anhedonia [MDD]) and social withdrawal/behavioral inhibition (avoidant personality disorder [healthy aging]; negative symptoms [early psychosis]). In males, premature aging of the default mode, cingulo-opercular, and visual networks was linked to reduced homeostatic dysregulation and predicted severity and treatment resistance of symptoms relevant to hostility/aggression (antisocial personality disorder [healthy aging]; mania/positive symptoms [early psychosis]), impaired thought processes (early psychosis, MDD) and somatic problems (healthy aging, MDD). Conclusions Our findings identify sexually dimorphic relationships between brain dynamics, peripheral physiology, and risk for psychiatric illness, suggesting that the specificity of putative risk biomarkers and precision therapeutics may be improved by considering sex and other relevant personal characteristics.	100/631	Secondary Analysis	Shared
Characterising grey-white matter relationships in recent-onset psychosis and its association with cognitive function.	10.15154/dbr7-8e09	Individuals with recent-onset psychosis (ROP) present widespread grey matter (GM) reductions and white matter (WM) abnormalities. While prior studies used univariate approaches, understanding how multiple GM regions relate to WM tracts is important, as psychosis involves network-level brain dysfunction. Understanding characteristic GM-WM patterns may also clarify the basis of cognitive impairments, which are potentially linked to network dysfunction in psychosis. Using multivariate analysis, we examined whole-brain GM-WM relationships and their association with cognitive abilities in ROP. We used T1 and diffusion-weighted images from 71 non-affective ROP individuals (age 22.09 ± 3.08) and 71 matched controls (age 22.05 ± 3.21). We performed multiblock partial least squares correlation (MB-PLS-C) to identify GM-WM patterns based on GM thickness or surface area and WM fractional anisotropy (FA), and examined their associations with cognitive abilities. MB-PLS-C identified a 'GM thickness'-'WM FA' pattern representing group differences, explaining 12.38 % of the variance and associated with frontal and temporal GM regions and seven WM tracts around subcortical structures. MB-PLS-C also identified a 'GM surface area'-'WM FA' pattern showing group differences, explaining 18.92 % and related with cingulate, frontal, temporal, and parietal GM regions and 15 WM tracts, including the inferior cerebellar peduncle and corona radiata. The 'GM thickness'-'WM FA' pattern describing group differences was significantly correlated with processing speed in ROP. MB-PLS-C identified differential whole-brain GM-WM relationships, indicating a potential signature of brain alterations in ROP. Our findings of a relationship between processing speed and GM-WM patterns for GM thickness have implications for our understanding of brain-behaviour relationships in psychosis.	236/466	Primary Analysis	Shared
Preserved white matter structure at the grey matter–white matter interface despite widespread cortical thinning in early psychosis	10.15154/fweb-pv54	Background Early psychosis is characterized by widespread cortical grey matter (GM) reductions. White matter (WM) alterations have also been reported. The GM–WM interface may represent a link between cortical GM and WM alterations that remains understudied. As the interface matures later in development than deep WM, it may be particularly vulnerable to neurodevelopmental disruptions in schizophrenia-spectrum disorders. However, its complex fiber architecture and proximity to the cortex pose challenges for conventional diffusion tensor imaging. Methods We applied an advanced diffusion MRI approach to assess fiber density (FD) in the GM–WM interface of 78 individuals with early psychosis (age 22.0 ± 3.0, 29.5% female) and 78 controls (age 21.8 ± 3.2, 29.5% female). We examined group differences in FD at the GM–WM interface and cortical measures, and assessed spatial correlations between regional effect sizes of FD and cortical measures. Results Widespread cortical thinning was observed, whereas no significant group differences were identified in FD at the GM–WM interface. This finding remained robust after accounting for partial-volume effects and was consistent with the template-space analysis. The spatial distribution of FD effect sizes showed significant positive correlations with those of cortical thickness and surface area. Conclusions Despite widespread cortical GM alterations, WM microstructure at the GM–WM interface was relatively preserved in early psychosis, while spatial correspondence between GM and WM measures at the interface was observed. These findings suggest that cortical alterations are pronounced in early psychosis, whereas WM changes may manifest later in the course of illness.	174/404	Primary Analysis	Shared
Data-driven, connectome-wide analysis identifies psychosis-specific brain correlates of fear and anxiety	10.15154/k76g-8542	Decades of psychosis research highlight the prevalence and the clinical significance of negative emotions, such as fear and anxiety. Translational evidence demonstrates the pivotal role of the amygdala in fear and anxiety. However, most of these approaches have used hypothesis-driven analyses with predefined regions of interest. A data-driven analysis may provide a complimentary, unbiased approach to identifying brain correlates of fear and anxiety. The aim of the current study was to identify the brain basis of fear and anxiety in early psychosis and controls using a data-driven approach. We analyzed data from the Human Connectome Project for Early Psychosis, a multi-site study of 125 people with psychosis and 58 controls with resting-state fMRI and clinical characterization. Multivariate pattern analysis of whole-connectome data was used to identify shared and psychosis-specific brain correlates of fear and anxiety using the NIH Toolbox Fear-Affect and Fear-Somatic Arousal scales. We then examined clinical correlations of Fear-Affect scores and connectivity patterns. Individuals with psychosis had higher levels of Fear-Affect scores than controls (p < 0.05). The data-driven analysis identified a cluster encompassing the amygdala and hippocampus where connectivity was correlated with Fear-Affect score (p < 0.005) in the entire sample. The strongest correlate of Fear-Affect was between this cluster and the anterior insula and stronger connectivity was associated with higher Fear-Affect scores (r = 0.31, p = 0.0003). The multivariate pattern analysis also identified a psychosis-specific correlate of Fear-Affect score between the amygdala/hippocampus cluster and a cluster in the ventromedial prefrontal cortex (VMPFC). Higher Fear-Affect scores were correlated with stronger amygdala/hippocampal-VMPFC connectivity in the early psychosis group (r = 0.33, p = 0.002), but not in controls (r = -0.15, p = 0.28). The current study provides evidence for the transdiagnostic role of the amygdala, hippocampus, and anterior insula in the neural basis of fear and anxiety and suggests a psychosis-specific relationship between fear and anxiety symptoms and amygdala/hippocampal-VMPFC connectivity. Our novel data-driven approach identifies novel, psychosis-specific treatment targets for fear and anxiety symptoms and provides complimentary evidence to decades of hypothesis-driven approaches examining the brain basis of threat processing.	253/253	Secondary Analysis	Shared
Isolation of Distinct Networks Driving Action and Cognition in Psychomotor Processes	10.15154/21mk-ce04	Background: Psychomotor disturbances are observed across psychiatric disorders and often manifest as psychomotor slowing, agitation, disorganized behavior, or catatonia. Psychomotor function includes both cognitive and motor components, but the neural circuits driving these subprocesses and how they relate to symptoms have remained elusive for centuries. Methods: We analyzed data from the HCP-EP (Human Connectome Project for Early Psychosis), a multisite study of 125 participants with early psychosis and 58 healthy participants with resting-state functional magnetic resonance imaging and clinical characterization. Psychomotor function was assessed using the 9-hole pegboard task, a timed motor task that engages mechanical and psychomotor components of action, and tasks assessing processing speed and task switching. We used multivariate pattern analysis of whole-connectome data to identify brain correlates of psychomotor function. Results: We identified discrete brain circuits driving the cognitive and motor components of psychomotor function. In our combined sample of participants with psychosis (n = 89) and healthy control participants (n = 52), the strongest correlates of psychomotor function (pegboard performance) (p < .005) were between a midline cerebellar region and left frontal region and presupplementary motor area. Psychomotor function was correlated with both cerebellar-frontal connectivity (r = 0.33) and cerebellar-presupplementary motor area connectivity (r = 0.27). However, the cognitive component of psychomotor performance (task switching) was correlated only with cerebellar-frontal connectivity (r = 0.19), whereas the motor component (processing speed) was correlated only with cerebellar-presupplementary motor area connectivity (r = 0.15), suggesting distinct circuits driving unique subprocesses of psychomotor function. Conclusions: We identified cerebellar-cortical circuits that drive distinct subprocesses of psychomotor function. Future studies should probe relationships between cerebellar connectivity and psychomotor performance using neuromodulation.	253/253	Secondary Analysis	Shared
Robust Brain Correlates of Cognitive Performance in Psychosis and Its Prodrome	10.15154/6229-wj80	Background: Neurocognitive impairment is a well-known phenomenon in schizophrenia that begins prior to psychosis onset. Connectome-wide association studies have inconsistently linked cognitive performance to resting-state functional magnetic resonance imaging. We hypothesized that a carefully selected cognitive instrument and refined population would allow identification of reliable brain-behavior associations with connectome-wide association studies. To test this hypothesis, we first identified brain-cognition correlations via a connectome-wide association study in early psychosis. We then asked, in an independent dataset, if these brain-cognition relationships would generalize to individuals who develop psychosis in the future. Methods: The Seidman Auditory Continuous Performance Task (ACPT) effectively differentiates healthy participants from those with psychosis. Our connectome-wide association study used the HCP-EP (Human Connectome Project for Early Psychosis) (n = 183) to identify links between connectivity and ACPT performance. We then analyzed data from the NAPLS2 (North American Prodrome Longitudinal Study 2) (n = 345), a multisite prospective study of individuals at risk for psychosis. We tested the connectome-wide association study-identified cognition-connectivity relationship in both individuals at risk for psychosis and control participants. Results: Our connectome-wide association study in early-course psychosis identified robust associations between better ACPT performance and higher prefrontal-somatomotor connectivity (p < .005). Prefrontal-somatomotor connectivity was also related to ACPT performance in at-risk individuals who would develop psychosis (n = 17). This finding was not observed in nonconverters (n = 196) or control participants (n = 132). Conclusions: This connectome-wide association study identified reproducible links between connectivity and cognition in separate samples of individuals with psychosis and at-risk individuals who would later develop psychosis. A carefully selected task and population improves the ability of connectome-wide association studies to identify reliable brain-phenotype relationships.	253/253	Secondary Analysis	Shared
Human Connectome Project for Early Psychosis -- Release 1.1	10.15154/1522899	The HCP-EP Release 1.1 contains behavioral data for 252 subjects (69 subjects added since the 1.0 release). In addition to the added subjects for the Clinical Assessments and Procedures, corrections were made to behavioral data for a few subjects. Cohort assignment is as follows: 57 affective, 126 non-affective psychotic patients and 68 matched healthy controls. Updated MRI data (several data files were missing from the preprocessed Structural imaging data in the 1.0 release) is provided for 183 of these subjects, 169 with preprocessed structural data (the same group of subjects as in HCP-EP Release 1.0). Modalities include structural MRI, resting state fMRI, and diffusion MRI. For details of all the measures included in this release and access instructions see the 1.1 Release documentation at https://www.humanconnectome.org/study/human-connectome-project-for-early-psychosis/document/hcp-ep.	251/251	Primary Analysis	Shared
Human Connectome Project for Early Psychosis	10.15154/1503722	The Human Connectome Project (HCP) was initiated to accelerate progress in understanding the organization of the human brain. To accomplish this goal, the original HCP Washington-University-Minnesota and MGH/Harvard-UCLA Projects have focused on acquiring and sharing data relevant to structural and functional connectivity in 1200 healthy twins and their siblings. The main aims have been to use advanced 3T imaging to develop advanced data acquisition and scanning sequences, to develop novel algorithms for post-processing of white matter fiber structure and brain connectivity, and to develop novel graphical techniques for brain connectomes. The purpose of the new funding opportunity announcement, PAR-14-281 for Connectomes Related to Human Diseases (U01), is to build upon the original HCP by extending it to the study of human brain diseases in order to acquire the same high quality data as in the original HCP, but with the goal of accelerating knowledge of brain diseases in a manner heretofore not possible. Importantly, progress has been slow and frustrating in translating knowledge of the brain to new and more effective treatments for human brain diseases such as severe mental disorders. In fact, severe mental disorders, which include psychotic disorders, are brain diseases that are not only devastating because they result in severe disruptions that occur early in life, but, for many, the course of illness is progressive, leading to chronic debilitation and early mortality. Thus the need to accelerate knowledge of dysfunctions in structural and functional brain connectivity in these disorders, and to translate this knowledge to treatment, is critical. The primary goal of the proposed Human Connectome Project on Early Psychosis is to acquire high quality data consistent with data acquired by the original HCP. To this end, we will acquire imaging data on Prisma 3T magnets at two sites, one in Boston and one in Indianapolis, using the HCP Lifespan Prisma protocol. This imaging protocol was developed to be of similar high quality to the original HCP, but with reduced scan time, the latter important in a psychosis cohort. We will also use behavioral measures from the HCP as well as additional measures specific to early psychosis. We will acquire blood to be stored at the Rutgers University Cell and DNA Repository (RUCDR)(Aim 1), and we will use the Washington University HCP post-processing pipeline to process imaging data (Aim 2). Additionally, we will include new imaging tools for signal drop detection, multi-tensor tractography, diffusion magnetic resonance imaging (dMRI) models, i.e., free-water imaging, and a new harmonization protocol for diffusion images (Aim 3). We will also perform, as a representative example, a study comparing brain networks of affective and non-affective psychosis groups with controls (Aim 4). The main goals are thus to acquire high quality imaging, behavioral, cognitive, and genetic data on an important cohort of early psychosis patients, in a manner consistent with the HCP, which will be made available to the research community for future studies. Such data will provide a unique opportunity to characterize the pathological substrates of early psychosis.	183/183	Primary Analysis	Shared
Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology	10.15154/1528359	The disconnection hypothesis of schizophrenia proposes that symptoms of the disorder arise as a result of aberrant functional integration between segregated areas of the brain. The concept of metastability characterizes the coexistence of competing tendencies for functional integration and functional segregation in the brain, and is therefore well suited for the study of schizophrenia. In this study, we investigate metastability as a candidate neuromechanistic biomarker of schizophrenia pathology, including a demonstration of reliability and face validity. Group-level discrimination, individual-level classification, pathophysiological relevance, and explanatory power were assessed using two independent case-control studies of schizophrenia, the Human Connectome Project Early Psychosis (HCPEP) study (controls n=82, non-affective psychosis n=53) and the Cobre study (controls n=71, cases n=59). In this work we extend Leading Eigenvector Dynamic Analysis (LEiDA) to capture specific features of dynamic functional connectivity and then implement a novel approach to estimate metastability. We used non-parametric testing to evaluate group-level differences and a naïve Bayes classifier to discriminate cases from controls. Our results show that our new approach is capable of discriminating cases from controls with elevated effect sizes relative to published literature, reflected in an up to 76% area under the curve (AUC) in out-of-sample classification analyses. Additionally, our new metric showed explanatory power of between 81-92% for measures of integration and segregation. Furthermore, our analyses demonstrated that patients with early psychosis exhibit intermittent disconnectivity of subcortical regions with frontal cortex and cerebellar regions, introducing new insights about the mechanistic bases of these conditions. Overall, these findings demonstrate reliability and face validity of metastability as a candidate neuromechanistic biomarker of schizophrenia pathology.	183/183	Secondary Analysis	Shared
Cortical and Subcortical Structural Morphometric Profiles in Individuals with Non-Affective and Affective Early Illness Psychosis	10.15154/1524263	Research has found strong evidence for common and distinct morphometric brain abnormality profiles in nonaffective psychosis (NAff-P) and affective psychosis (Aff-P). Due to chronicity and prolonged medication exposure confounds, it is critical to examine structural morphometry early in the course of psychosis. Using Human Connectome Project Early Psychosis data, multivariate profile analyses were implemented to examine regional profiles for cortical thickness, cortical surface area, subcortical volume, and ventricular volume in healthy control (HC; n=56) and early illness NAff-P (n=83) and Aff-P (n=30) groups after accounting for normal aging effects. Associations with symptom severity, functioning, and cognition were also examined. Group regional profiles were significantly non-parallel and differed in overall level for cortical thickness (ps<.002), with NAff-P having widespread cortical thinning relative to HC and Aff-P and some regions showing greater deficits than others. Significant non-parallelism of group regional profiles was also evident for cortical surface area (ps<.018), with Aff-P and N-Aff-P differing from HC but not from each other. For subcortical volume, there was significant profile non-parallelism with NAff-P having an enlarged left pallidum and smaller accumbens and hippocampus (ps<.050), and Aff-P having a smaller accumbens and amygdala (ps<.017), relative to HC. Further, NAff-P had enlarged ventricular volumes (ps<.037) compared to HC and Aff-P. Regional morphometric measures were not significantly correlated with clinical and cognitive measures within groups. Overall, this study found common and distinct regional morphometric profile abnormalities in early illness NAff-P and Aff-P, providing evidence for both shared and disease-specific pathophysiological processes.	169/169	Secondary Analysis	Shared
Global Thickness	10.15154/kgg6-yf92	Importance: Recent magnetic resonance imaging (MRI) studies and publicly disseminated analytic tools advocate that regional morphometric analyses covary for global whole-brain measures (e.g., global mean thickness) to support conclusions about regional specificity of disease effects. We challenge the conceptual basis for this approach and empirically demonstrate that this approach severely underestimates regional cortical thickness dysmorphology in psychiatric disorders. Objective: Demonstrate the detrimental impact of covarying global mean thickness on regional thickness in psychiatric disorders, such as schizophrenia, characterized by widespread thinning. Hypotheses: 1) covarying global thickness attenuates/eliminates patient group regional thickness abnormalities, 2) especially, when there are disorder-related abnormalities in global thickness and when global and regional thickness are highly correlated. Design: Studies 1 and 2 are cross-sectional MRI studies. Setting: Study 1 was conducted at the University of California San Francisco. Study 2 was part of the multicenter Human Connectome Project-Early Psychosis. Participants: Study 1 included 90 healthy controls (HC), 51 clinical high-risk for psychosis (CHR-P), and 78 early illness schizophrenia participants. 10 CHR-P individuals converted to a psychotic disorder, and 23 did not convert for ≥24 months. Study 2 included 56 HC, 83 non-affective psychosis (NAff-P), and 30 affective psychosis (Aff-P) participants. Main Outcome(s) and Measure(s): Primary outcome measurements planned before data collection included structural and functional brain metrics. In this paper, we measured regional cortical thickness and global mean thickness across regions. We examined global and regional thickness correlations, global thickness group differences, and regional thickness group differences with/without covarying for global thickness. Hypotheses were formulated after data collection in order to challenge the emerging practice of covarying for global thickness in regional thickness analyses. Results: Global and regional thickness were strongly correlated across groups. Global thickness was lower in schizophrenia-spectrum groups versus other groups. Regional thickness deficits in schizophrenia-spectrum groups, relative to HC and NAff-P groups, were attenuated/eliminated with global thickness covariation. Conclusions and Relevance: Depriving regional thickness of the variance it shares with global thickness removes disease-related effects, particularly when widespread cortical deficits are characteristic of the disease. Resulting in erroneous conclusions that regional cortical thickness is normal in disorders like schizophrenia or CHR-P syndrome.	169/169	Secondary Analysis	Shared
Spatially localized fMRI metrics as predictive and highly distinct state-independent fingerprints	10.15154/1528137	Precision medicine and the investigation of brain-behavior associations require biomarkers that are stable (low intraindividual variability) and unique (high interindividual variability) at the same time, hence calling them "fingerprints". The functional connectome (FC) has good "fingerprint properties", as individuals can be accurately identified in a database based on their FC. Importantly, research has shown lower intraindividual variability of more localized measures of brain function such as regional homogeneity (ReHo) and (fractional) amplitude of low-frequency fluctuations ((f)ALFF), compared to the FC. Here, with fMRI data from two publicly available datasets we demonstrate that individuals can be identified with near-perfect accuracies using local functional fingerprints, and especially the regional homogeneity (ReHo) fingerprint. Further analyses reveal that the dorsal attention network contributes most to the individual "uniqueness" of the ReHo fingerprint. Moreover, using a machine-learning setup, we show that the small intraindividual ReHo fingerprint variability across sessions is meaningful for explaining individual-level intelligence. Last, using two other publicly available datasets, clinical applicability is shown with high fingerprint accuracies and a significant correlation between fingerprint stability and intelligence in individuals with schizophrenia. Altogether, our findings suggest that the ReHo fingerprint is a good candidate for further exploration of applicability in precision medicine.	123/123	Secondary Analysis	Shared
CICADA: An automated and flexible tool for comprehensive fMRI noise reduction	10.15154/dnre-4576	Independent component analysis (ICA) denoising methods can be highly effective for reducing functional magnetic resonance imaging (fMRI) noise. ICA denoising method success heavily depends, however, on the accurate classification of fMRI data ICs as either neural signal or noise. While manual IC classification (“manual ICA denoising”) is a current gold-standard, it requires extensive time and training. Automated methods of IC classification (“automated ICA denoising”), meanwhile, are less accurate and effective, especially in clinical populations where motion artifacts are more common. To address these challenges, a novel denoising method, Comprehensive Independent Component Analysis Denoising Assistant (CICADA), was developed. Uniquely, CICADA uses manual classification guidelines to automatically, comprehensively, and accurately capture most common sources of fMRI noise. As such, we hypothesized that CICADA would perform similarly to manual ICA denoising and outperform other current automated denoising methods. CICADA was evaluated against two well-established automated ICA denoising methods (FIX and ICA-AROMA) across three fMRI datasets. The datasets included high-motion resting-state (N = 57) and visual-task data (N = 53), both from individuals with schizophrenia, as well as low-motion resting-state healthy control data from an openly available dataset (N = 56). IC classification accuracy was first evaluated against manual IC classification in a subset (N = 30) of each dataset. Denoising performance efficacy was then evaluated with commonly used quality control (QC) benchmarks and correlations with fMRI noise profiles across all data. With a 97.9% mean overall accuracy in IC classification, CICADA performed nearly as well as manual IC classification and was significantly more accurate than FIX (92.9% mean overall accuracy; all p-values < 0.01) and ICA-AROMA (83.8% mean overall accuracy; all p-values < 0.001). CICADA also matched or outperformed FIX and ICA-AROMA across most QC and noise profile metrics across all data. Furthermore, CICADA greatly eased implementation of manual ICA denoising by decreasing the number of ICs a user must inspect by an average of 75%. Overall, CICADA is a novel, accurate, comprehensive, and automated ICA denoising tool for use in both resting-state and task-based fMRI. It performed similarly to the labor-intensive manual IC classification gold-standard and, in some datasets, outperformed current automated ICA denoising methods. Finally, CICADA may facilitate more efficient manual ICA denoising without reducing efficacy.	56/56	Secondary Analysis	Shared

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