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http://aimlab.cs.uoregon.edu/NEMO/web/

THIS RESOURCE IS NO LONGER IN SERVICE. NIH tombstone webpage lists Project Period : 2009 - 2013. NIH funded project to create EEG and MEG ontologies and ontology based tools. These resources will be used to support representation, classification, and meta-analysis of brain electromagnetic data. Three pillars of NEMO are: DATA, ONTOLOGY, and DATABASE. NEMO data consist of raw EEG, averaged EEG (ERPs), and ERP data analysis results. NEMO ontologies include concepts related to ERP data (including spatial and temporal features of ERP patterns), data provenance, and cognitive and linguistic paradigms that were used to collect data. NEMO database portal is large repository that stores NEMO consortium data, data analysis results, and data provenance. EEG and MEG ontologies and ontology-based tools to support representation, classification, and meta-analysis of brain electromagnetic data. Raw EEG and ERP data may be uploaded to the NEMO FTP site., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Neural ElectroMagnetic Ontologies (NEMO) Project (RRID:SCR_002001) Copy   

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http://www.genepaint.org/MapE15_5_01.htm

Abbreviated reference atlas for the Embryonic 15.5 post conception day mouse. All sections were nissl stained and digitized. To assist in the initial identification of sites of gene expression sites, maps of brains are available for E15.5, P7 and the adult. These maps depict the boundaries of major brain regions (cortex, thalamus, striatum, globus pallidus, ventral striatum, septum, basal forebrain, hippocampus, midbrain, pons, medulla, cerebellum) and also show the more prominent nerve tracts. Maps are most efficiently used by placing the window depicting the map of interest next to the gene expression image. Browsing between planes of sectioning is permitted thus allowing the most appropriate plane to be selected. The annotation of anatomical details such as brain nuclei is currently beyond the scope of the GenePaint database. Hence, such information on the anatomy of the brain and embryo should be obtained from published atlases of mouse anatomy (Kaufman, 1995; Paxinos and Franklin, 2001; Jacobowitz and Abbott, 1997; Schambra et al., 1992; Valverde1998).

Proper citation: GenePaint E15 Atlas (RRID:SCR_002786) Copy   

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http://www.nitrc.org/projects/sri24/

An MRI-based atlas of normal adult human brain anatomy, generated by template-free nonrigid registration from images of 24 normal control subjects. The atlas comprises T1, T2, and PD weighted structural MRI, tissue probability maps (GM, WM, CSF), maximum-likelihood tissue segmentation, DTI-based measures (FA, MD, longitudinal and transversal diffusivity), and two labels maps of cortical regions and subcortical structures. The atlas is provided at 1mm isotropic image resolution in Analyze, NIFTI, and Nrrd format. We are also providing an experimental packaging for use with SPM8.

Proper citation: SRI24 Atlas: Normal Adult Brain Anatomy (RRID:SCR_002551) Copy   

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http://neuromab.ucdavis.edu/

A national mouse monoclonal antibody generating resource for biochemical and immunohistochemical applications in mammalian brain. NeuroMabs are generated from mice immunized with synthetic and recombinant immunogens corresponding to components of the neuronal proteome as predicted from genomic and other large-scale cloning efforts. Comprehensive biochemical and immunohistochemical analyses of human, primate and non-primate mammalian brain are incorporated into the initial NeuroMab screening procedure. This yields a subset of mouse mAbs that are optimized for use in brain (i.e. NeuroMabs): for immunocytochemical-based imaging studies of protein localization in adult, developing and pathological brain samples, for biochemical analyses of subunit composition and post-translational modifications of native brain proteins, and for proteomic analyses of native brain protein networks. The NeuroMab facility was initially funded with a five-year U24 cooperative grant from NINDS and NIMH. The initial goal of the facility for this funding period is to generate a library of novel NeuroMabs against neuronal proteins, initially focusing on membrane proteins (receptors/channels/transporters), synaptic proteins, other neuronal signaling molecules, and proteins with established links to disease states. The scope of the facility was expanded with supplements from the NIH Blueprint for Neuroscience Research to include neurodevelopmental targets, the NIH Roadmap for Medical Research to include epigenetics targets, and NIH Office of Rare Diseases Research to include rare disease targets. These NeuroMabs will then be produced on a large scale and made available to the neuroscience research community on an inexpensive basis as tissue culture supernatants or purified immunoglobulin by Antibodies Inc. The UC Davis/NIH NeuroMab Facility makes NeuroMabs available directly to end users and is unable to accommodate sales to distributors for third party distribution. Note, NeuroMab antibodies are now offered through antibodiesinc.

Proper citation: NeuroMab (RRID:SCR_003086) Copy   

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http://www.genepaint.org/MapP7_01.htm

Abbreviated reference atlas for the P56 mouse. All sections were nissl stained and digitized. To assist in the initial identification of sites of gene expression sites, maps of brains are available for E15.5, P7 and the adult. These maps depict the boundaries of major brain regions (cortex, thalamus, striatum, globus pallidus, ventral striatum, septum, basal forebrain, hippocampus, midbrain, pons, medulla, cerebellum) and also show the more prominent nerve tracts. Maps are most efficiently used by placing the window depicting the map of interest next to the gene expression image. Browsing between planes of sectioning is permitted thus allowing the most appropriate plane to be selected. The annotation of anatomical details such as brain nuclei is currently beyond the scope of the GenePaint database. Hence, such information on the anatomy of the brain and embryo should be obtained from published atlases of mouse anatomy (Kaufman, 1995; Paxinos and Franklin, 2001; Jacobowitz and Abbott, 1997; Schambra et al., 1992; Valverde1998).

Proper citation: GenePaint P7 Atlas (RRID:SCR_002787) Copy   

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http://sleep.alleninstitute.org

Collection of gene expression data in mouse brain for five different conditions of sleep and wakefulness to understand sleep deprivation and dynamic changes underlying sleep and wake cycles. Platform to generate cellular resolution expression data.

Proper citation: Allen Institute for Brain Science Sleep Study (RRID:SCR_002983) Copy   

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http://www.virtualflybrain.org

An interactive tool for neurobiologists to explore the detailed neuroanatomy, neuron connectivity and gene expression of the adult Drosophila melanogaster brain.

Proper citation: Virtual Fly Brain (RRID:SCR_004229) Copy   

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

Human brain atlases for adult, pediatric and elderly populations, by iterative joint deformable registration of training datasets into a single unbiased average image. Atlases packages include T1-weighted images, tissue priors (WM,GM,CSF), lobar parcellation maps and subcortical structures. Current available atlases: * Adult atlas: Symmetric atlas generated from 50+ healthy adult subjects (20-59 year old). * UNC-MNI Pediatric 1-year-old atlas: Symmetric atlas generated from 104 1-year-old subjects, combining children at high familial risk of autism and controls. * Pediatric 4-year-old atlas: Symmetric atlas generated from 10 4-year-old healthy subjects. * Elderly atlas: Atlas generated from 27 healthy elderly subjects (60+ years old). Additional information and acknowledgment for their usage can be found by clicking on the release notes.

Proper citation: UNC Human Brain Atlas (RRID:SCR_002606) Copy   

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http://cvr.yorku.ca/home/

The Centre for Vision Research focuses on interdisciplinary research into human and machine vision and visual processes, into vision's interactions with other senses and with motor and cognitive processes, and in applications such as visually-guided robotics or clinical diagnosis and treatment. The Centre for Vision Research includes the following major research themes: - Human Visual Performance - Visual Human-Computer Interaction, Graphics and Virtual Reality - Visual Psychophysics - Eye Movements and Hand-Eye Coordination - Computational Modeling and Computer Vision - Electrophysiology - Clinical and Developmental Studies - Brain Imaging

Proper citation: Centre for Vision Research (RRID:SCR_002879) Copy   

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http://senselab.med.yale.edu

The SenseLab Project is a long-term effort to build integrated, multidisciplinary models of neurons and neural systems. It was founded in 1993 as part of the original Human Brain Project, which began the development of neuroinformatics tools in support of neuroscience research. It is now part of the Neuroscience Information Framework (NIF) and the International Neuroinformatics Coordinating Facility (INCF). The SenseLab project involves novel informatics approaches to constructing databases and database tools for collecting and analyzing neuroscience information, using the olfactory system as a model, with extension to other brain systems. SenseLab contains seven related databases that support experimental and theoretical research on the membrane properties: CellPropDB, NeuronDB, ModelDB, ORDB, OdorDB, OdorMapDB, BrainPharmA pilot Web portal that successfully integrates multidisciplinary neurocience data.

Proper citation: SenseLab (RRID:SCR_007276) Copy   

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https://www.msu.edu/~brains/brains/human/index.html

A labeled three-dimensional atlas of the human brain created from MRI images. In conjunction are presented anatomically labeled stained sections that correspond to the three-dimensional MRI images. The stained sections are from a different brain than the one which was scanned for the MRI images. Also available the major anatomical features of the human hypothalamus, axial sections stained for cell bodies or for nerve fibers, at six rostro-caudal levels of the human brain stem; images and Quicktime movies. The MRI subject was a 22-year-old adult male. Differing techniques used to study the anatomy of the human brain all have their advantages and disadvantages. Magnetic resonance imaging (MRI) allows for the three-dimensional viewing of the brain and structures, precise spatial relationships and some differentiation between types of tissue, however, the image resolution is somewhat limited. Stained sections, on the other hand, offer excellent resolution and the ability to see individual nuclei (cell stain) or fiber tracts (myelin stain), however, there are often spatial distortions inherent in the staining process. The nomenclature used is from Paxinos G, and Watson C. 1998. The Rat Brain in Stereotaxic Coordinates, 4th ed. Academic Press. San Diego, CA. 256 pp

Proper citation: Human Brain Atlas (RRID:SCR_006131) Copy   

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http://www.nih.gov/science/brain/

Project aimed at revolutionizing understanding of human brain, to show how individual cells and complex neural circuits interact, enable rapid progress in development of new technologies and data analysis tools to treat and prevent brain disorders. BRAIN Initiative encourages collaborations between neurobiologists and scientists from disciplines such as statistics, physics, mathematics, engineering, and computer and information sciences. Institutes and centers contributing to NIH BRAIN Initiative support those research efforts.

Proper citation: BRAIN Initiative (RRID:SCR_006770) Copy   

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http://www.cs.tau.ac.il/~shlomito/tissue-net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Network visualizations in which the expression and predicted flux data are projected over the global human network. These network visualizations are accessible through the supplemental website using the publicly available Cytoscape software (Cline, Smoot et al. 2007). Since many high degree nodes exist in the network, special layouts are required to produce network visualizations that are readily interpretable. To this end we produced network visualizations in which hub nodes are repeated multiple times and hence layouts with a small number of edge crossings can be generated. Contains entries for brain compartments and brain pathways.

Proper citation: Network-based Prediction of Human Tissue-specific Metabolism (RRID:SCR_007392) Copy   

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https://confluence.crbs.ucsd.edu/display/NIF/StemCellInfo

Data tables providing an overview of information about stem cells that have been derived from mice and humans. The tables summarize published research that characterizes cells that are capable of developing into cells of multiple germ layers (i.e., multipotent or pluripotent) or that can generate the differentiated cell types of another tissue (i.e., plasticity) such as a bone marrow cell becoming a neuronal cell. The tables do not include information about cells considered progenitor or precursor cells or those that can proliferate without the demonstrated ability to generate cell types of other tissues. The tables list the tissue from which the cells were derived, the types of cells that developed, the conditions under which differentiation occurred, the methods by which the cells were characterized, and the primary references for the information.

Proper citation: National Institutes of Health Stem Cell Tables (RRID:SCR_008359) Copy   

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

A free collection of MRI brain images for testing segmentation algorithms. It is available for download to assess the accuracy, reproducibility and sensitivity of MRI segmentation software. It includes data from infants and adults as well as patients with Alzheimer's disease.

Proper citation: Brain Segmentation Testing Protocol (RRID:SCR_009445) Copy   

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http://coins.mrn.org/

A web-based neuroimaging and neuropsychology software suite that offers versatile, automatable data upload/import/entry options, rapid and secure sharing of data among PIs, querying and export all data, real-time reporting, and HIPAA and IRB compliant study-management tools suitable to large institutions as well as smaller scale neuroscience and neuropsychology researchers. COINS manages over over 400 studies, more than 265,000 clinical neuropsychological assessments, and 26,000 MRI, EEG, and MEG scan sessions collected from 18,000 participants at over ten institutions on topics related to the brain and behavior. As neuroimaging research continues to grow, dynamic neuroinformatics systems are necessary to store, retrieve, mine and share the massive amounts of data. The Collaborative Informatics and Neuroimaging Suite (COINS) has been created to facilitate communication and cultivate a data community. This tool suite offers versatile data upload/import/entry options, rapid and secure sharing of data among PIs, querying of data types and assessments, real-time reporting, and study-management tools suitable to large institutions as well as smaller scale researchers. It manages studies and their data at the Mind Research Network, the Nathan Kline Institute, University of Colorado Boulder, the Olin Neuropsychiatry Research Center (at) Hartford Hospital, and others. COINS is dynamic and evolves as the neuroimaging field grows. COINS consists of the following collaboration-centric tools: * Subject and Study Management: MICIS (Medical Imaging Computer Information System) is a centralized PostgreSQL-based web application that implements best practices for participant enrollment and management. Research site administrators can easily create and manage studies, as well as generate reports useful for reporting to funding agencies. * Scan Data Collection: An automated DICOM receiver collects, archives, and imports imaging data into the file system and COINS, requiring no user intervention. The database also offers scan annotation and behavioral data management, radiology review event reports, and scan time billing. * Assessment Data Collection: Clinical data gathered from interviews, questionnaires, and neuropsychological tests are entered into COINS through the web application called Assessment Manager (ASMT). ASMT's intuitive design allows users to start data collection with little or no training. ASMT offers several options for data collection/entry: dual data entry, for paper assessments, the Participant Portal, an online tool that allows subjects to fill out questionnaires, and Tablet entry, an offline data entry tool. * Data Sharing: De-identified neuroimaging datasets with associated clinical-data, cognitive-data, and associated meta-data are available through the COINS Data Exchange tool. The Data Exchange is an interface that allows investigators to request and share data. It also tracks data requests and keeps an inventory of data that has already been shared between users. Once requests for data have been approved, investigators can download the data directly from COINS.

Proper citation: Mind Research Network - COINS (RRID:SCR_000805) Copy   

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http://www.loni.ucla.edu/~thompson/thompson.html

The UCLA laboratory of neuroimaging is working in several areas to enhance knowledge of anatomy, including brain mapping in large human populations, HIV, Schizophrenia, methamphetamine, tumor growth and 4d brain mapping, genetics and detection of abnormalities.

Proper citation: University of California at Los Angeles, School of Medicine: Neuro Imaging Lab of Thompson (RRID:SCR_001924) Copy   

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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   

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http://neurobureau.projects.nitrc.org/BrainArt/Competition.html

An annual Brain-Art Competition to recognize the beauty and creativity of artistic renderings emerging from the neuroimaging community. Submission deadline: June 1st, 2012. Awards will be announced on June 11th during the OHBM conference in Beijing. (You need not be present to win) Countless hours are devoted to creation of informative visualizations for communicating neuroscientific findings. This competition once again aims to recognize the artistic creativity of our community that often goes underappreciated in the publication process. We are inviting researchers to submit their favorite unpublished works for entry. Both team and single-person entries are welcomed. The competition will have five award categories: # Best Representation of the Human Connectome # Best Abstract Brain Illustration # Best Educational Brain Illustration # Best Humorous Brain Illustration # Best Video Illustration of the Brain Submissions will be evaluated based on their aesthetic merit

Proper citation: Brain-Art Competition (RRID:SCR_005360) Copy   

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http://braincanada.ca/

Brain Canada is a national non-profit organization that develops and supports collaborative, multidisciplinary, multi-institutional research across the neurosciences. Through partnering with the public, private and voluntary sectors, Brain Canada connects the knowledge and resources available in this area to accelerate neuroscience research and funding and maximize the output of Canada''s world-class scientists and researchers. Brain Canada was created to address the twin challenges of increasing the scale of brain research funding in Canada and widening its scope to encourage interdisciplinary collaboration to produce insights for treating multiple disorders. Brain Canada is built on the successes and model of NeuroScience Canada (NSC). Established in 1999, NSC raised more than $11.5 million, leveraged over $20 million with partnered funding, and funded 100 individual and teams of researchers in Canada. Brain Canada is the new vision for Canadian brain researchthe voice for the brain and the grouping of brain disorders, raising awareness about their prevalence and impact on individuals, families, the economy and society. But most important, through the research we are funding, we are giving hope to the millions of Canadians who are directly or indirectly touched by diseases, disorders, and injuries of the brain, spinal cord and nervous system.

Proper citation: Brain Canada (RRID:SCR_005053) Copy   

•   Source: SciCrunch Registry