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http://bluebrain.epfl.ch/

A Swiss-led project with the aim of reverse engineering the mammalian brain and achieving a complete virtual human brain. The researchers have demonstrated the validity of their method by developing a realistic model of a rat cortical column, consisting of about 10,000 neurons. The eventual goal is to simulate systems of millions and hundreds of millions of neurons. The virtual brain will be an exceptional tool giving neuroscientists a new understanding of the brain and a better understanding of neurological diseases. In five years of work, Henry Markram's team has perfected a facility that can create realistic models of one of the brain's essential building blocks. This process is entirely data driven and essentially automatically executed on the supercomputer. Meanwhile the generated models show a behavior already observed in years of neuroscientific experiments. These models will be basic building blocks for larger scale models leading towards a complete virtual brain.

Proper citation: Blue Brain Project (RRID:SCR_002994) Copy   

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https://www.synapse.org/

Sage Bionetworks, Mount Sinai School of Medicine (MSSM), University of Pennsylvania (Penn), the National Institute of Mental Health (NIMH), and Takeda Pharmaceuticals Company Limited (TAKEDA) have launched a Public-Private Pre-Competitive Consortium, the CommonMind Consortium, to generate and analyze large-scale genomic data from human subjects with neuropsychiatric disease and to make this data and the associated analytical results broadly available to the public. This collaboration brings together disease area expertise, large scale and well curated brain sample collections, and data management and analysis expertise from the respective institutions. As many as 450 million people worldwide are believed to be living with a mental or behavioral disorder: schizophrenia and bipolar disorder are two of the top six leading causes of years lived with disability according to the World Health Organization. The burden on the individual as well as on society is significant with estimates for the health care costs for these individuals as high as four percent GNP. This highlights a grave need for new therapies to alleviate this suffering. Researchers from MSSM including Dr. Pamela Sklar, Dr. Joseph Buxbaum and Dr. Eric Schadt will join with Dr. Raquel Gur and Dr. Chang-Gyu Hahn from Penn to combine their extensive brain bank collections for the generation of whole genome scale RNA and DNA sequence data. Dr.Pamela Sklar, Professor of Psychiatry and Neuroscience at MSSM commented this is an exciting opportunity for us to use the newest genomic methods to really expand our understanding of the molecular underpinnings of neuropsychiatric disease, while Dr Raquel Gur, Professor of Psychiatry from Penn observed this will be a great complement to some of the large-scale genetic analyses that have been carried out to date because it will give a more complete mechanistic picture. The CommonMind Consortium is committed to generating an open resource for the community and invites others with common goals to contact us at info (at) CommonMind.org.

Proper citation: CommonMind Consortium (RRID:SCR_000139) Copy   

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http://www.thebrainproject.org/

The Mission of the Sarah Jane Brain Project is to create a model system of care for children and young adults suffering from all Pediatric Acquired Brain Injuries in order to advance our knowledge of the brain fifty years over the next five years! As a father of a child suffering from a Pediatric Acquired Brain Injury (PABI), I have spent countless hours searching the internet and speaking with Sarah Jane's development team (doctors, therapists and other professionals) trying to improve the development of my daughter. What I found was that while there are a countless number of wonderful and informative prevention sites for Shaken Baby Syndrome and advocacy sites for brain injuries, there is no one centralized resource for research and rehabilitation for PABI. Furthermore, many of the issues families and children face are the same whether the brain injury was caused by a car crash, a sports-related concussion, an assault or by a tumor. No one person or organization has all the answers to the questions that parents of children suffering from PABI face. Yet through my own experience, I learned that the coordination and dissemination of Sarah Jane's medical and therapy records and data in an orderly manner greatly helps her development team better help her. These wonderful individuals are constantly looking for additional ways to improve Sarah Jane's progress by speaking with their colleagues, reading literature on brain injury, and collaborating with other parents. But they all admit there is a considerable amount that still needs to be learned about the human brain, particularly the developing brain. The field of neuroscience today is similar to the computer science field of the 1950s and 1960s: you have a diverse group of very smart people working independently of one another throughout the United States and the world, yet few know what the others are doing behind closed doors. Fast- forward 50 years and many of the breakthroughs in the computer industry have been made utilizing the principles of open source a research method that promotes free and open access to the design and production of goods and knowledge. Its use was made well-known through the creation of the Linux computer operating system, in which professionals share knowledge to make corrections and fix problems. Open source is commonly used by millions of people today through the Wikipedia online free encyclopedia, a collection of public entries on established subjects that allows anyone to make additions or corrections. The National Institute of Mental Health launched The Human Brain Project in 1993 to develop and support the new science of neuro-informatics. From this initiative, it became obvious what needed to be done. That's why we created the Sarah Jane Brain Virtual Center of Excellence an ecosystem for professionals and families dealing with PABI around the world and a vehicle to help implement the PABI Plan by establishing a model system for PABI.

Proper citation: Sarah Jane Brain Project (RRID:SCR_000620) Copy   

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http://isc.temple.edu/neuroanatomy/lab/atlas/S5/

Sectional atlas featuring sections of the spinal cord and brain for a neuroanatomy course offered by Temple University. Labels may be turned on and off.

Proper citation: Sectional Atlas of Human Brain and Spinal Cord (RRID:SCR_000799) Copy   

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https://github.com/TonnesenLab/Diffusion-Model/

Software code for simulating diffusion in brain extracellular space images.

Proper citation: Diffusion-Model (RRID:SCR_027942) Copy   

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http://udn.nichd.nih.gov/brainatlas_home.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 1, 2019. The first brain atlas for the common marmoset to be made available since a printed atlas by Stephan, Baron and Schwerdtfeger published in 1980. It is a combined histological and magnetic resonance imaging (MRI) atlas constructed from the brains of two adult female marmosets. Histological sections were processed from Nissl staining and digitized to produce an atlas in a large format that facilitates visualization of structures with significant detail. Naming of identifiable brain structures was performed utilizing current terminology. For the present atlas, an adult female was perfused through the heart with PBS followed by 10% formalin. The brain was then sent to Neuroscience Associates of Knoxville, TN, who prepared the brain for histological analysis. The brain was cut in the coronal (frontal) plane at 40 microns, every sixth section stained for Nissl granules with thionine and every seventh section stained for myelinated fibers with the Weil technique. The mounted sections were photographed at the NIH (Medical Arts and Photography Branch). The equipment used was a Nikon Multiphot optical bench with Zeiss Luminar 100 mm lens, and scanned with a Better Light 6100 scan back driven by Better Light Viewfinder 5.3 software. The final images were saved as arrays of 6000x8000 pixels in Adobe Photoshop 6.0. A scale in mm provided with these images permitted construction of the final Nissl atlas files with a horizontal and vertical scale. Some additional re-touching (brightness and contrast) was done with Adobe Photoshop Elements 2.0. The schematic (labeled) atlas plates were created from the Nissl images. The nomenclature came almost exclusively from brainmaps.org, where a rhesus monkey brain with structures labeled can be found. The labels for the MRI images were placed by M. R. Zametkin, under supervision from Dr. Newman.

Proper citation: Brain atlas of the common marmoset (RRID:SCR_005135) Copy   

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http://centreforstrokerecovery.ca/our-research/research-structure/stroke-patient-recovery-research-database-spred

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 28,2025. The Stroke Patient Recovery Research Database (SPReD) initiative creates the infrastructure needed for the collection of a wide range of data related to stroke risk factors and to stroke recovery. It also promotes the analysis and management of large brain and vessel images. A major goal is to create a comprehensive electronic database Stroke Patient Recovery Research Database or SPReD and populate it with patient data, including demographic, biomarker, genetic and proteomic data and imaging data. SPReD will enable us to combine descriptions of our stroke patients from multiple projects that are geographically distributed. We will do this in a uniform fashion in order to enhance our ability to document rates of recovery; to study the effects of vascular risk factors and inflammatory biomarkers; and to use these data to improve their physical and cognitive recovery through innovative intervention programs. This comprehensive database will provide an integrated repository of data with which our researchers will investigate and test original ideas, ultimately leading to knowledge that can be applied clinically to benefit stroke survivors.

Proper citation: Stroke Patient Recovery Research Database (SPReD) (RRID:SCR_005508) Copy   

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http://www.geneatlas.org/gene/main.jsp

This website allows visitors to search for genes of interest based on their spatial expression patterns in the Postnatal Day 7 mouse brain. Geneatlas provides two searching tools: A graphical interface for customized spatial queries; A textual interface for querying annotated structures. Geneatlas is the product of a collaboration between researchers at Baylor College of Medicine, Rice University, and University of Houston.

Proper citation: Gene Atlas (RRID:SCR_008089) Copy   

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http://brainmap.wisc.edu/monkey.html

NO LONGER AVAILABLE. Documented on September 17, 2019. A set of multi-subject atlas templates to facilitate functional and structural imaging studies of the rhesus macaque. These atlases enable alignment of individual scans to improve localization and statistical power of the results, and allow comparison of results between studies and institutions. This population-average MRI-based atlas collection can be used with common brain mapping packages such as SPM or FSL.

Proper citation: Rhesus Macaque Atlases for Functional and Structural Imaging Studies (RRID:SCR_008650) Copy   

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http://phm.utoronto.ca/~jeffh/surgical.htm

3D interactive atlas of two mouse brains, 129S1/SvImJ and C57Bl/6J. The aim of this resource is to enhance comparative morphometric analyses and stereotactic surgical procedures in mice. These representations of the murine brain and skull, in conjunction with the resource''s development of a new, more dynamic master coordinate system, provide improved accuracy with respect to targeting CNS structures during surgery compared with previous systems. The interactive three-dimensional nature of these atlases also provide users with stereotactic information necessary to perform accurate off-axis surgical procedures, as is commonly required for experiments such as in vivo micro-electroporation. In addition, three-dimensional analysis of the brain and skull shape in C57Bl, 129Sv, CD1, and additional murine strains, suggests that a stereotactic coordinate system based upon the lambda and rostral confluence of the sinuses at the sagittal midline, provides improved accuracy compared with the traditional lambdabregma landmark system. These findings demonstrate the utility of developing highly accurate and robust three-dimensional representations of the murine brain and skull, in which experimental outputs can be directly compared using a unified coordinate system.

Proper citation: 3D surgical atlases of the murine head (RRID:SCR_008039) Copy   

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http://www.loni.usc.edu/ICBM/Downloads/Downloads_DTI-81.shtml

A stereotaxic probabilistic white matter atlas that fuses DTI-based white matter information with an anatomical template (ICBM-152). This atlas is based on probabilistic tensor maps obtained from 81 normal subjects acquired under an initiative of the International Consortium of Brain Mapping (ICBM). The subjects were normal right-handed adults ranging from 18 to 59 years of age. A hand-segmented white matter parcellation map was created from this averaged map. This map can be used for automated white matter parcellation. The precision of the affine-based image normalization and automated parcellation was measured for a group of normal subjects using manually defined anatomical landmarks. The raw diffusion-weighted images (DWIs) were first co-registered to one of the least diffusion-weighted images and corrected for subject motion with 6-mode rigid transformation with Automated Image Registgration (AIR). The average of all DWIs (aDWI) was calculated and used for a DTI-based anatomic image. For anatomical images to drive the normalization process, aDWIs were used. These images were normalized to the template (ICBM-152) using a 12-mode affine or 4th order polynomial non-linear transformation of AIR. The transformation matrix was then applied to the calculated diffusion tensor field. In the white matter parcellation map (WMPM), deep white matter regions were manually segmented into various anatomic structures based on fiber orientation information.

Proper citation: International Consortium of Brain Mapping DTI-81 Atlas (RRID:SCR_008066) Copy   

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http://vox.pharmacology.ucla.edu/home.html

Two-dimensional images of gene expression for 20,000 genes in a coronal slice of the mouse brain at the level of the striatum by using microarrays in combination with voxelation at a resolution of 1 cubic mm gene expression patterns in the brain obtained through voxelation. Voxelation employs high-throughput analysis of spatially registered voxels (cubes) to produce multiple volumetric maps of gene expression analogous to the images reconstructed in biomedical imaging systems.

Proper citation: Voxelation Map of Gene Expression in a Coronal Section of the Mouse Brain (RRID:SCR_008065) Copy   

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http://catlas.org/mousebrain/#!/

Atlas of gene regulatory elements in adult mouse cerebrum. Atlas of CIS elements, providing information on accessible chromatin in individual cells from regions of adult mouse isocortex, olfactory bulb, hippocampus and cerebral nuclei. Uses resulting data to define candidate cis-regulatory DNA elements in distinct cell groups. Many are linked to putative target genes expressed in diverse cerebral cell types and uncover transcriptional regulators involved in broad spectrum of molecular and cellular pathways in different neuronal and glial cell populations. Used for analysis of gene regulatory programs of mammalian brain and interpretation of non-coding risk variants associated with various neurological disease and traits in humans.

Proper citation: CATlas (RRID:SCR_018690) Copy   

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http://findlab.stanford.edu/functional_ROIs.html

Atlas of functional ROI's, including individual networks (auditory network, sensorimotor network, etc.). Atlases of individual networks and combined networks are available for download directly from the website.

Proper citation: 90 fROI atlas (RRID:SCR_014757) Copy   

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

Project that is a translation of the BraVa arterial vasculature database into the NIFTI MRI file format that can be applied to stroke studies, fMRI resting state imaging studies and other clinical neuroscience studies. Group artery region labels and arterial density maps are provided as well. Human Brain Major Artery Atlas 10.7490/f1000research.1114378.1

Proper citation: Bravissima (RRID:SCR_016229) Copy   

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

Atlas for studies of older adult brain. Includes T1-weighted template of older adult brain and tissue probability maps. Exhibits high image sharpness, provides higher inter-subject spatial normalization accuracy compared to other standardized templates and similar normalization accuracy to well-constructed study-specific templates.

Proper citation: MIITRA atlas (RRID:SCR_017566) Copy   

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http://www.pymvpa.org

A Python package intended to ease statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run. Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. This Python-based, cross-platform, open-source software toolbox software toolbox for the application of classifier-based analysis techniques to fMRI datasets makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages.

Proper citation: PyMVPA (RRID:SCR_006099) Copy   

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http://kesm.cs.tamu.edu

A web-based, light-weight 3D volume viewer that serves large volumes (typically the whole brain) of high-resolution mouse brain images (~1.5 TB per brain, ~1 um resolution) from the Knife-Edge Scanning Microscope (KESM), invented by Bruce H. McCormick. Currently, KESMBA serves the following data sets: * Mouse: Whole-brain-scale Golgi (acquired 2008 spring): neuronal morphology: Choe et al. (2009) * Mouse: Whole-brain India Ink (acquired 2008 spring): vascular network: Choe et al. (2009); Mayerich et al. (2011); * Mouse: Whole-brain Golgi (acquired 2011 summer): neuronal morphology: Choe et al. (2011); Chung et al. (2011); * Mouse: Whole-brain Nissl (acquired 2009-2010 winter): somata (Choe et al. 2010) (Coming soon) They will ship you the full data set on a hard drive if you provide them with the hard drive and shipping cost.

Proper citation: KESM brain atlas (RRID:SCR_001559) Copy   

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http://library.med.utah.edu/kw/hyperbrain/

An online tutorial for human neuroanatomy designed as a supplement to textbook and class learning or as a lab substitute when human specimens, slides and models are not available. HyperBrain includes thousand of images and hundreds of linked illustrated glossary terms, as well as movies, quizzes and interactive animations. Last updated 2012.

Proper citation: HyperBrain (RRID:SCR_001595) Copy   

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http://cmbn-approd01.uio.no/nesys/

Public neuroscience database providing a collection of published data describing structure and structure-function relationships in one of the largest projection systems of the brain: the cerebro-cerebellar system. It also gives access to a suite of tools that allow the user to visualize and analyze any selected combination of data sets. Contact them if you are interested in contributing data. The overall goal is to improve communication of results and permit re-use of previously published data in new contexts. FACCS is a part of the Rat Brain WorkBench, a new research and development project funded by The Research Council of Norway, the Centre for Molecular Biology and Neuroscience, and the European Union. The project is directed by Jan G. Bjaalie, Centre for Molecular Biology and Neuroscience & Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.

Proper citation: Functional Anatomy of the Cerebro-Cerebellar System (FACCS) (RRID:SCR_001661) Copy   

•   Source: SciCrunch Registry