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NDAR provides a single access to de-identified autism research data. For permission to download data, you will need an NDAR account with approved access to NDAR or a connected repository (AGRE, IAN, or the ATP). For NDAR access, you need to be a research investigator sponsored by an NIH recognized institution with federal wide assurance. See Request Access for more information.

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The filters you have selected from various query interfaces will be stored here, in the 'Filter Cart'. The database will be queried using filters added to your 'Filter Cart', when multiple filters are defined, each will be executed using 'AND' logic, so with each filter that is applied the result set gets smaller.

From the 'Filter Cart' you can inspect each of the filters that have been defined, and you also have the option to remove filters. The 'Filter Cart' itself will display the number of filters applied along with the number of subjects that are identified by the combination of those filters. For example a GUID filter with two subjects, followed by a GUID filter for just one of those subjects would return only data for the subject that is in both GUID filters.

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

Please select an experiment type below

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SelectExperiment IdExperiment NameExperiment Type
  • Select One
  • EEG
  • EGG
  • Eye Tracking
  • Omics
  • fMRI
Created On
949Resting StatefMRI06/18/2018
943Emotional Face TaskfMRI06/13/2018
941Meridians localizerfMRI06/07/2018
940V1 localizer movingDotsfMRI06/07/2018
939movingDotsfMRI06/07/2018
938MT localizer dots movingDotsfMRI06/07/2018
937MT localizer gratings movingDotsfMRI06/07/2018
936V1 localizer peripheryfMRI06/07/2018
935Contrast peripheryfMRI06/07/2018
934MT localizer peripheryfMRI06/07/2018
933Pilot01: Posner Cueing with st-tACSEye Tracking06/06/2018
932Social- Theory of Mind Localizer TaskfMRI06/01/2018
931Faces TaskfMRI05/31/2018
930Go_NogofMRI05/30/2018
929Moral RatingfMRI05/30/2018
928Pain Detection fMRI05/30/2018
927Reward TaskfMRI05/30/2018
926Go no Go TaskfMRI05/30/2018
924EARLI Placenta WGBSOmics05/24/2018
923Anxiety-CBT fMRI (pre-post) - Version 4 BlockfMRI05/15/2018
922Anxiety-CBT fMRI (pre-post) - Version 3 BlockfMRI05/15/2018
921Anxiety-CBT fMRI (pre-post) - Version 2 BlockfMRI05/15/2018
920Anxiety-CBT fMRI (pre-post) - Version 1 BlockfMRI05/15/2018
919Neural overlap in item representations across episodes impairs context memoryfMRI05/11/2018
918ReferenceTissue: U01MH106892_Brain_Amplicon_SeqOmics05/08/2018
917Virginia_single_cell_HiSeq3000Omics05/03/2018
916Virginia_single_cell_HiSeq2500Omics05/03/2018
915Virginia_single_cell_MiSeqOmics05/03/2018
914PFC analysis in bloodOmics04/27/2018
913Task and emotional content driven visual competitionfMRI04/27/2018
912Task and emotional content driven visual competitionEEG04/23/2018
911Resting StatefMRI04/20/2018
910Modified Monetary Incentive Delay fMRI04/20/2018
908Resting State Pre-Stress Visit 1fMRI04/20/2018
907Montreal Imaging Stress Task Visit 1fMRI04/18/2018
9062-back Post-Stress Visit 1fMRI04/18/2018
9051-back Post-Stress Visit 1fMRI04/18/2018
9040-back Post-Stress Visit 1fMRI04/18/2018
9032-back Pre-Stress Visit 1fMRI04/18/2018
9021-back Pre-Stress Visit 1fMRI04/18/2018
9010-back Pre-Stress Visit 1fMRI04/18/2018
900DTIfMRI04/11/2018
899Investigating a Neurobehavioral Mechanism of Paranoia - Resting State ScansfMRI04/06/2018
898FAST-POMAfMRI04/03/2018
897parvizi_eeg_109EEG03/19/2018
896parvizi_eeg_107EEG03/19/2018
895parvizi_eeg_106EEG03/19/2018
893Startle Habituation and Shock Sensitivity EvaluationEEG03/03/2018
892NPU EEG Task EEG03/03/2018
891Duke ACE ETEye Tracking03/02/2018
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Please enter the name of the data structure to search or if your definition does not exist, please upload that definition so that it can be appropriately defined for submission. Multiple data structures may be associated with a single Data Expected entry. Please add only one data structure per assessment.

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

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

General

Title, investigators, and Collection Description may be edited along with the Collection Phase. For Collection Phase, the options Pre-enrollment, Enrollment, and Completed can be chosen allowing the Collection Owner to indicate the stage of data collection.

Funding Source

The ability to associate the funding source for the project is provided. For NIH funded grants, linkage to Project Reporter information (e.g. R01MH123456) is supported. Projects funded by others, including the URL of the project, are listed. Non NIH funded projects will become available here to link that data with the appropriate funding agency.

Supporting Documentation

Any documents related to the project may be uploaded clarifying the data or acquisition methods used may be uploaded and made available here. The default is to share these documents to the general public. An option to share only to qualified Researchers is also an option.

Clinical Trials

For clinical trials, the option to link to the clinical trial in clinicaltrials.gov is optionally provided.

Collection Summary Collection Charts
Collection Title Collection Investigators Collection Description
Mapping the Human Connectome During Typical Aging (HCP-A)
Beau Ances, Susan Bookheimer, Randy Buckner, David Salat, Stephen Smith, Melissa Terpstra, Kamil Ugurbil, David Van Essen, Roger Woods 
The major technological and analytical advances in human brain imaging achieved as part of the Human Connectome Projects (HCP) enable examination of structural and functional brain connectivity at unprecedented levels of spatial and temporal resolution. This information is proving invaluable for enhancing our understanding of normative variation in young adult brain connectivity. It is now timely to use the tools and analytical approaches developed by the HCP to understand how structural and functional wiring of the brain changes during the aging process. Using state-of-the art HCP imaging approaches will allow investigators to push our currently limited understanding of normative brain aging to new levels. We propose an effort involving a consortium of five sites (Massachusetts General Hospital, University of California at Los Angeles, University of Minnesota, Washington University in St. Louis, and Oxford University), with extensive complementary expertise in human brain imaging and aging and including many investigators associated with the original adult and pilot lifespan HCP efforts. This synergistic integration of advances from the MGH and WU-MINN-OXFORD HCPs with cutting-edge expertise in aging provides an unprecedented opportunity to advance our understanding of the normative changes in human brain connectivity with aging. Aim 1 will be to optimize existing HCP Lifespan Pilot project protocols to respect practical constraints in studying adults over a wide age range, including the very old (80+ years). Aim 2 will be to collect high quality neuroimaging, behavioral, and other datasets on 1200 individuals in the age range of 36 - 100+ years, using matched protocols across sites. This will enable robust cross-sectional analyses of age-related changes in network properties including metrics of connectivity, network integrity, response properties during tasks, and behavior. Aim 3 will be to collect and analyze longitudinal data on a subset of 300 individuals in three understudied and scientifically interesting groups: ages 36-44 (when late maturational and early aging processes may co-occur); ages 45-59 (perimenopausal, when rapid hormonal changes can affect cognition and the brain); and ages 80 - 100+ (the `very old', whose brains may reflect a `healthy survivor' state). The information gained relating to these important periods will enhance our understanding of how important phenomena such as hormonal changes affect the brain and will provide insights into factors that enable cognitively intact function into advanced aging. Aim 4 will capitalize on our success in sharing data in the Human Connectome Project (HCP), and will use these established tools, platforms, and procedures to make this data publicly available through the Connectome Coordination Facility.
RDoCdb
Pre-Enrollment
Private
$13,522,953.00
0
1212
715
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U01AG052564-01 Mapping the Human Connectome During Typical Aging 08/19/2016 05/31/2020 1212 715 WASHINGTON UNIVERSITY $13,522,953.00

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

Experiments

To create a new Omics, eye tracking, fMRI, or EEG experiment, press the "+ New Experiment" button. Once an experiment is created, then raw files for these types of experiments should be provided, associating the experiment – through Experiment_ID – with the metadata defined in the experiments interface.

IDNameCreated DateStatusType
No records found.

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

Shared Data

Data structures with the number of subjects submitted and shared are provided.

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 NDAR 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 IDStudyTitleJournalAuthorsDateStatus
29112194Create StudyGenome-wide association study identifies a novel locus for cannabis dependence.Molecular psychiatryAgrawal A, Chou YL, Carey CE, Baranger DAA, Zhang B, Sherva R, Wetherill L, Kapoor M, Wang JC, Bertelsen S, Anokhin AP, Hesselbrock V, Kramer J, Lynskey MT, Meyers JL, Nurnberger JI, Rice JP, Tischfield J, Bierut LJ, Degenhardt L, Farrer LA, Gelernter J, Hariri AR, Heath AC, Kranzler HR, et al.May 2018Not Determined
28749606Create StudyPerceived stress is associated with increased rostral middle frontal gyrus cortical thickness: a family-based and discordant-sibling investigation.Genes, brain, and behaviorMichalski LJ, Demers CH, Baranger DAA, Barch DM, Harms MP, Burgess GC, Bogdan RNovember 2017Not Determined
28739213Create StudyAssociation Between Substance Use Disorder and Polygenic Liability to Schizophrenia.Biological psychiatryHartz SM, Horton AC, Oehlert M, Carey CE, Agrawal A, Bogdan R, Chen LS, Hancock DB, Johnson EO, Pato CN, Pato MT, Rice JP, Bierut LJNovember 2017Not Determined
28645098Create StudyThe behavioral economics of social anxiety disorder reveal a robust effect for interpersonal traits.Behaviour research and therapyRodebaugh TL, Tonge NA, Weisman JS, Lim MH, Fernandez KC, Bogdan RAugust 2017Not Determined
28283186Create StudyImaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential.Biological psychiatryBogdan R, Salmeron BJ, Carey CE, Agrawal A, Calhoun VD, Garavan H, Hariri AR, Heinz A, Hill MN, Holmes A, Kalin NH, Goldman DAugust 2017Not Determined
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Relevant Publications
PubMed IDStudyTitleJournalAuthorsDate
No records found.
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Data Expected
Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
No records found.
Structure not yet defined

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 NameAbstractCollection/Study SubjectsData UsageState
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