Tools   Select Another Resource Report Type

http://www.nitrc.org/projects/pediatric_mri

A database which contains longitudinal structural MRIs, spectroscopy, DTI and correlated clinical/behavioral data from approximately 500 healthy, normally developing children, ages newborn to young adult.

Proper citation: NIH Pediatric MRI Data Repository (RRID:SCR_014149) Copy   

•   Source: SciCrunch Registry
  

https://nda.nih.gov/

The National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains. Research data repository for data sharing and collaboration among investigators. Used to accelerate scientific discovery through data sharing across all of mental health and other research communities, data harmonization and reporting of research results. Infrastructure created by National Database for Autism Research (NDAR), Research Domain Criteria Database (RDoCdb), National Database for Clinical Trials related to Mental Illness (NDCT), and NIH Pediatric MRI Repository (PedsMRI).

Proper citation: NIMH Data Archive (RRID:SCR_004434) Copy   

•   Source: SciCrunch Registry
  

http://www.nitrc.org/projects/nusdast

A repository of schizophrenia neuroimaging data collected from over 450 individuals with schizophrenia, healthy controls and their respective siblings, most with 2-year longitudinal follow-up. The data include neuroimaging data, cognitive data, clinical data, and genetic data.

Proper citation: Northwestern University Schizophrenia Data and Software Tool (NUSDAST) (RRID:SCR_014153) Copy   

•   Source: SciCrunch Registry
  

https://www.nitrc.org/projects/fmridatacenter/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 25, 2013 Public curated repository of peer reviewed fMRI studies and their underlying data. This Web-accessible database has data mining capabilities and the means to deliver requested data to the user (via Web, CD, or digital tape). Datasets available: 107 NOTE: The fMRIDC is down temporarily while it moves to a new home at UCLA. Check back again in late Jan 2013! The goal of the Center is to help speed the progress and the understanding of cognitive processes and the neural substrates that underlie them by: * Providing a publicly accessible repository of peer-reviewed fMRI studies. * Providing all data necessary to interpret, analyze, and replicate these fMRI studies. * Provide training for both the academic and professional communities. The Center will accept data from those researchers who are publishing fMRI imaging articles in peer-reviewed journals. The goal is to serve the entire fMRI community.

Proper citation: fMRI Data Center (RRID:SCR_007278) Copy   

•   Source: SciCrunch Registry
  

http://www.pediatricmri.nih.gov/

Data sets of clinical / behavioral and image data are available for download by qualified researchers from a seven year, multi-site, longitudinal study using magnetic resonance technologies to study brain maturation in healthy, typically-developing infants, children, and adolescents and to correlate brain development with cognitive and behavioral development. The information obtained in this study is expected to provide essential data for understanding the course of normal brain development as a basis for understanding atypical brain development associated with a variety of developmental, neurological, and neuropsychiatric disorders affecting children and adults. This study enrolled over 500 children, ranging from infancy to young adulthood. The goal was to study each participant at least three times over the course of the project at one of six Pediatric Centers across the United States. Brain MR and clinical/behavioral data have been compiled and analyzed at a Data Coordinating Center and Clinical Coordinating Center. Additionally, MR spectroscopy and DTI data are being analyzed. The study was organized around two objectives corresponding to two age ranges at the time of enrollment, each with its own protocols. * Objective 1 enrolled children ages 4 years, 6 months through 18 years (total N = 433). This sample was recruited across the six Pediatric Study Centers using community based sampling to reflect the demographics of the United States in terms of income, race, and ethnicity. The subjects were studied with both imaging and clinical/behavioral measures at two year intervals for three time points. * Objective 2 enrolled newborns, infants, toddlers, and preschoolers from birth through 4 years, 5 months, who were studied three or more times at two Pediatric Study Centers at intervals ranging from three months for the youngest subjects to one year as the children approach the Objective 1 age range. Both imaging and clinical/behavioral measures were collected at each time point. Participant recruitment used community based sampling that included hospital venues (e.g., maternity wards and nurseries, satellite physician offices, and well-child clinics), community organizations (e.g., day-care centers, schools, and churches), and siblings of children participating in other research at the Pediatric Study Centers. At timepoint 1, of those enrolled, 114 children had T1 scans that passed quality control checks. Staged data release plan: The first data release included structural MR images and clinical/behavioral data from the first assessments, Visit 1, for Objective 1. A second data release included structural MRI and clinical/behavioral data from the second visit for Objective 1. A third data release included structural MRI data for both Objective 1 and 2 and all time points, as well as preliminary spectroscopy data. A fourth data release added cortical thickness, gyrification and cortical surface data. Yet to be released are longitudinally registered anatomic MRI data and diffusion tensor data. A collaborative effort among the participating centers and NIH resulted in age-appropriate MR protocols and clinical/behavioral batteries of instruments. A summary of this protocol is available as a Protocol release document. Details of the project, such as study design, rationale, recruitment, instrument battery, MRI acquisition details, and quality controls can be found in the study protocol. Also available are the MRI procedure manual and Clinical/Behavioral procedure manuals for Objective 1 and Objective 2.

Proper citation: NIH MRI Study of Normal Brain Development (RRID:SCR_003394) Copy   

•   Source: SciCrunch Registry
  

http://www.brainimagelibrary.org

Public, NIH-funded repository and analysis ecosystem for brain microscopy data, designed to store, share, and process massive volumetric datasets. It enables researchers to access whole-brain images, neuron morphologies, and spatial data without needing to download, fostering collaborative discovery. Used to deposit, analyze, mine, share and interact with large brain image datasets.

Proper citation: Brain Image Library (RRID:SCR_017272) Copy   

•   Source: SciCrunch Registry
  

https://bams1.org/

Knowledge management system designed to handle neurobiological information at different levels of organization of vertebrate nervous system. Database and repository for information about neural circuitry, storing and analyzing data concerned with nomenclature, taxonomy, axonal connections, and neuronal cell types. Handles data and metadata collated from original literature, or inserted by scientists that is associated to four levels of organization of vertebrate nervous system. Data about expressed molecules, neuron types and classes, brain regions, and networks of brain regions.

Proper citation: Brain Architecture Management System (RRID:SCR_007251) Copy   

•   Source: SciCrunch Registry
  

http://headit.ucsd.edu

Platform for sharing, download, and re-analysis or meta-analysis of sophisticated, fully annotated, human electrophysiological data sets. It uses EEG Study Schema (ESS) files to provide task, data collection, and subject metadata, including Hierarchical Event Descriptor (HED) tag descriptions of all identified experimental events. Visospatial task data also available from, http://sccn.ucsd.edu/eeglab/data/headit.html: A 238-channel, single-subject EEG data set recorded at the Swartz Center, UCSD, by Arnaud Delorme, Julie Onton, and Scott Makeig is al.

Proper citation: HeadIT (RRID:SCR_005657) Copy   

•   Source: SciCrunch Registry
  

http://senselab.med.yale.edu/modeldb/

Curated database of published models so that they can be openly accessed, downloaded, and tested to support computational neuroscience. Provides accessible location for storing and efficiently retrieving computational neuroscience models.Coupled with NeuronDB. Models can be coded in any language for any environment. Model code can be viewed before downloading and browsers can be set to auto-launch the models. The model source code has to be available from publicly accessible online repository or WWW site. Original source code is used to generate simulation results from which authors derived their published insights and conclusions.

Proper citation: ModelDB (RRID:SCR_007271) Copy   

•   Source: SciCrunch Registry
  

https://nemoarchive.org/

Data repository specifically focused on storage and dissemination of omic data generated from BRAIN Initiative and related brain research projects. Data repository and archive for BCDC and BICCN project, among others. NeMO data include genomic regions associated with brain abnormalities and disease, transcription factor binding sites and other regulatory elements, transcription activity, levels of cytosine modification, histone modification profiles and chromatin accessibility.

Proper citation: NeMOarchive (RRID:SCR_016152) Copy   

•   Source: SciCrunch Registry
  

http://openneuro.org

Open platform for analyzing and sharing neuroimaging data from human brain imaging research studies. Brain Imaging Data Structure ( BIDS) compliant database. Formerly known as OpenfMRI. Data archives to hold magnetic resonance imaging data. Platform for sharing MRI, MEG, EEG, iEEG, and ECoG data.

Proper citation: OpenNeuro (RRID:SCR_005031) Copy   

•   Source: SciCrunch Registry
  

http://humanconnectome.org/connectome/connectomeDB.html

Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.

Proper citation: ConnectomeDB (RRID:SCR_004830) Copy   

•   Source: SciCrunch Registry
  

http://marmosetbrain.org/

Brain connectivity atlas to create systematic, digital repository for data on connections between different cortical areas, in primate species. Data repository for connections between different cortical areas in marmoset monkeys. Allows access to data set and enables other interpretations of data, in light of future evolution of knowledge about marmoset cortex.

Proper citation: Marmoset Brain Connectivity Atlas (RRID:SCR_015964) Copy   

•   Source: SciCrunch Registry
  

https://bossdb.org/

BossDB (Brain Observatory Storage Service and Database) is a cloud-based ecosystem for the storage and management of public large-scale volumetric neuroimaging and connectomics datasets. This includes volumetric Electron Microscopy and X-Ray Micro/Nanotomography data with support for multi-channel image data, segmentations, annotations, meshes, and connectomes. BossDB integrates with community resources for data access, processing, visualization, and analysis, and includes an API that enables metadata management, rendering, datatype conversions, and ingest.

Proper citation: Brain Observatory Storage Service and Database (BossDB) (RRID:SCR_017273) Copy   

•   Source: SciCrunch Registry
  

http://sumsdb.wustl.edu/sums/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 11, 2016. Repository of brain-mapping data (surfaces and volumes; structural and functional data) derived from studies including fMRI and MRI from many laboratories, providing convenient access to a growing body of neuroimaging and related data. WebCaret is an online visualization tool for viewing SumsDB datasets. SumsDB includes: * data on cerebral cortex and cerebellar cortex * individual subject data and population data mapped to atlases * data from FreeSurfer and other brainmapping software besides Caret SumsDB provides multiple levels of data access and security: * Free (public) access (e.g., for data associated with published studies) * Data access restricted to collaborators in different laboratories * Owner-only access for work in progress Data can be downloaded from SumsDB as individual files or as bundles archived for offline visualization and analysis in Caret WebCaret provides online Caret-style visualization while circumventing software and data downloads. It is a server-side application running on a linux cluster at Washington University. WebCaret "scenes" facilitate rapid visualization of complex combinations of data Bi-directional links between online publications and WebCaret/SumsDB provide: * Links from figures in online journal article to corresponding scenes in WebCaret * Links from metadata in WebCaret directly to relevant online publications and figures

Proper citation: SumsDB (RRID:SCR_002759) Copy   

•   Source: SciCrunch Registry
  

http://humanconnectome.org/

Consortium to comprehensively map long-distance brain connections and their variability. It is acquiring data and developing analysis pipelines for several modalities of neuroimaging data plus behavioral and genetic data from healthy adults.

Proper citation: Human Connectome Coordination Facility (RRID:SCR_008749) Copy   

•   Source: SciCrunch Registry
  

http://national_databank.mclean.org

THIS RESOURCE IS NO LONGER IN SERVICE, documented September 6, 2016. A publicly accessible data repository to provide neuroscience investigators with secure access to cohort collections. The Databank collects and disseminates gene expression data from microarray experiments on brain tissue samples, along with diagnostic results from postmortem studies of neurological and psychiatric disorders. All of the data that is derived from studies of the HBTRC collection is being incorporated into the National Brain Databank. This data is available to the general public, although strict precautions are undertaken to maintain the confidentiality of the brain donors and their family members. The system is designed to incorporate MIAME and MAGE-ML based microarray data sharing standards. Data from various types of studies conducted on brain tissue in the HBTRC collection will be available from studies using different technologies, such as gene expression profiling, quantitative RT-PCR, situ hybridization, and immunocytochemistry and will have the potential for providing powerful insights into the subregional and cellular distribution of genes and/or proteins in different brain regions and eventually in specific subregions and cellular subtypes.

Proper citation: National Brain Databank (RRID:SCR_003606) Copy   

•   Source: SciCrunch Registry
  

http://brainmaps.org

An interactive multiresolution brain atlas that is based on over 20 million megapixels of sub-micron resolution, annotated, scanned images of serial sections of both primate and non-primate brains and integrated with a high-speed database for querying and retrieving data about brain structure and function. Currently featured are complete brain atlas datasets for various species, including Macaca mulatta, Chlorocebus aethiops, Felis catus, Mus musculus, Rattus norvegicus, Tyto alba and many other vertebrates. BrainMaps is currently accepting histochemical, immunocytochemical, and tracer connectivity data, preferably whole-brain. In addition, they are interested in EM, MRI, and DTI data.

Proper citation: BrainMaps.org (RRID:SCR_006878) Copy   

•   Source: SciCrunch Registry
  

http://hbatlas.org

A data repository containing transcriptome and associated metadata for the developing and adult human brain. It provides genome-wide, exon-level transcriptome data from both sexes and multiple ethnicities.

Proper citation: Human Brain Transcriptome (RRID:SCR_013742) Copy   

•   Source: SciCrunch Registry
  

https://terra.bio

Open ecosystem of data repositories hosted by various partner organizations, who work together to ensure that their data can be federated across participating platforms. Open source platform for biomedical researchers to access data, run analysis tools, and collaborate. Terra powers important scientific projects including AnVIL, BioData Catalyst, Human Cell Atlas, BICCN, and many others. Easily access both open and access-controlled datasets hosted in cloud repositories. Explore, analyze, and visualize data using Jupyter Notebooks, RStudio, RShinyApps, and Galaxy.

Proper citation: Terra (RRID:SCR_021648) Copy   

•   Source: SciCrunch Registry