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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.

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

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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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Shared

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

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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
UNC/UMN Baby Connectome Project
Jed Elison, Weili Lin 
This application is in response to the RFA-MH-16-160, entitled Lifespan Human Connectome Project (HCP): Baby Connectome. Investigators at The University of North Carolina at Chapel Hill (UNC) and The University of Minnesota (UMN) will join forces to accomplish the goals outlined by this RFA. The team at UNC has over 10 years of experience in recruiting and imaging typically developing and at-risk children, scanning over 1000 children from birth to five years1-40. Well established infrastructure at the Biomedical Research Imaging Center (BRIC) at UNC and Center for Magnetic Resonance Research (CMRR) at UMN are in place to recruit and retain pediatric subjects and facilitate the coordination of pediatric imaging studies. Our past and ongoing studies for imaging children (birth five years of age) without sedation have achieved an overall success rate of 81% and attrition rate of 29.3%. Our track record demonstrates that we possess the critical and essential components to successfully conduct longitudinal pediatric imaging studies focusing on early brain development, a critically-important aspect of this RFA. Our ability to recruit, retain, and image non-sedated, typically developing children is further strengthened by our image analysis team, which has developed novel image analysis tools specifically for early brain development. The expertise at UNC is complementary to and strengthened by the expertise of the team at UMN. The CMRR at UMN has been one of the leading groups in the HCP project and has developed novel MR imaging approaches to dramatically shorten data acquisition time. Furthermore, the team at UMN has extensive experience in behavioral and cognitive studies of early child development. Together, our combined team is well positioned to accomplish the goals of this RFA. To this end, a total of 500 typically developing children between birth and five years of age will be recruited across two data collection sites in a sequential cohort, accelerated longitudinal study design. The participants are divided into two main groups, longitudinal (n=285) and cross-sectional (n=215) groups, respectively. This hybrid longitudinal and cross-sectional design enables detailed characterization of early brain development from both brain structural/functional using MRI and behavioral aspects using behavioral assessments. All of the acquired images and behavioral assessments will undergo extensive quality assurance and control processes to ensure that high quality data is obtained and transferred to the Central Connectome Facility at Washington University. In addition, we will integrate novel image analysis tools, developed by our team onto the existing HCP pipelines.
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Pre-Enrollment
Shared
$3,087,495.00
0
500
274
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NIH - Extramural None


U01MH110274-01 UNC/UMN Baby Connectome Project 09/01/2016 05/31/2020 500 274 UNIV OF NORTH CAROLINA CHAPEL HILL $3,087,495.00

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
29578031Create StudyThe UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development.NeuroImageHowell BR, Styner MA, Gao W, Yap PT, Wang L, Baluyot K, Yacoub E, Chen G, Potts T, Salzwedel A, Li G, Gilmore JH, Piven J, Smith JK, Shen D, Ugurbil K, Zhu H, Lin W, Elison JTMarch 2018Not Determined
29574033Create StudyComputational neuroanatomy of baby brains: A review.NeuroImageLi G, Wang L, Yap PT, Wang F, Wu Z, Meng Y, Dong P, Kim J, Shi F, Rekik I, Lin W, Shen DMarch 2018Not Determined
29568823Create StudyGraph-Constrained Sparse Construction of Longitudinal Diffusion-Weighted Infant Atlases.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted InterventionKim J, Chen G, Lin W, Yap PT, Shen DSeptember 2017Not Determined
29317597Create StudyPreliminary evidence for genetic overlap between body mass index and striatal reward response.Translational psychiatryLancaster TM, Ihssen I, Brindley LM, Linden DEJanuary 2018Not Determined
29124254Create StudyDevelopmental Patterns Based Individualized Parcellation of Infant Cortical Surface.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted InterventionLi G, Wang L, Lin W, Shen DSeptember 2017Not Determined
29124253Create StudyExploring Gyral Patterns of Infant Cortical Folding based on Multi-view Curvature Information.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted InterventionDuan D, Xia S, Meng Y, Wang L, Lin W, Gilmore JH, Shen D, Li GSeptember 2017Not Determined
28902466Create StudyLearning-based deformable registration for infant MRI by integrating random forest with auto-context model.Medical physicsWei L, Cao X, Wang Z, Gao Y, Hu S, Wang L, Wu G, Shen DDecember 2017Not Determined
28819140Create StudyEnhancement of Perivascular Spaces in 7 T MR Image using Haar Transform of Non-local Cubes and Block-matching Filtering.Scientific reportsHou Y, Park SH, Wang Q, Zhang J, Zong X, Lin W, Shen DAugust 2017Not Determined
28665045Create StudyExtraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification.Human brain mappingChen X, Zhang H, Zhang L, Shen C, Lee SW, Shen DOctober 2017Not Determined
28624881Create StudyDiscriminative self-representation sparse regression for neuroimaging-based alzheimer's disease diagnosis.Brain imaging and behaviorZhu X, Suk HI, Lee SW, Shen DJune 2017Not Determined
28603790Create StudyDual-Layer Groupwise Registration for Consistent Labeling of Longitudinal Brain Images.Machine learning in medical imaging. MLMI (Workshop)Kim M, Wu G, Rekik I, Shen DOctober 2016Not Determined
28358032Create StudyA Hierarchical Feature and Sample Selection Framework and Its Application for Alzheimer's Disease Diagnosis.Scientific reportsAn L, Adeli E, Liu M, Zhang J, Lee SW, Shen DMarch 2017Not Determined
28295833Create StudyCan we predict subject-specific dynamic cortical thickness maps during infancy from birth?Human brain mappingMeng Y, Li G, Rekik I, Zhang H, Gao Y, Lin W, Shen DJune 2017Not Determined
28284800Create StudyJoint prediction of longitudinal development of cortical surfaces and white matter fibers from neonatal MRI.NeuroImageRekik I, Li G, Yap PT, Chen G, Lin W, Shen DMay 2017Not Determined
28102945Create StudyLearning-based deformable image registration for infant MR images in the first year of life.Medical physicsHu S, Wei L, Gao Y, Guo Y, Wu G, Shen DJanuary 2017Not Determined
27798142Create StudyLongitudinal Study of the Emerging Functional Connectivity Asymmetry of Primary Language Regions during Infancy.The Journal of neuroscience : the official journal of the Society for NeuroscienceEmerson RW, Gao W, Lin WOctober 2016Not Determined
27668065Create StudyFULLY CONVOLUTIONAL NETWORKS FOR MULTI-MODALITY ISOINTENSE INFANT BRAIN IMAGE SEGMENTATION.Proceedings. IEEE International Symposium on Biomedical ImagingNie D, Wang L, Gao Y, Shen D2016Not Determined
27380969Create StudyLearning-based subject-specific estimation of dynamic maps of cortical morphology at missing time points in longitudinal infant studies.Human brain mappingMeng Y, Li G, Gao Y, Lin W, Shen DNovember 2016Not Determined
26874184Create StudyStructural and Maturational Covariance in Early Childhood Brain Development.Cerebral cortex (New York, N.Y. : 1991)Geng X, Li G, Lu Z, Gao W, Wang L, Shen D, Zhu H, Gilmore JHMarch 2017Not Determined
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Relevant Publications
PubMed IDStudyTitleJournalAuthorsDate
No records found.
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Data Expected
Data ExpectedTargeted EnrollmentInitial SubmissionSubjects SharedStatus
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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.

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