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Collection of high resolution images and databases of brains from many genetically characterized strains of mice with aim to systematically map and characterize genes that modulate architecture of mammalian CNS. Includes detailed information on genomes of many strains of mice. Consists of images from approximately 800 brains and numerical data from just over 8000 mice. You can search MBL by strain, age, sex, body or brain weight. Images of slide collection are available at series of resolutions. Apple's QuickTime Plugin is required to view available MBL Movies.
Proper citation: Mouse Brain Library (RRID:SCR_001112) Copy
http://clarityresourcecenter.org/
Protocols and other training materials related to the CLARITY protocol, a technique for the transformation of intact tissue into a nanoporous hydrogel-hybridized form (crosslinked to a three-dimensional network of hydrophilic polymers) that is fully assembled but optically transparent and macromolecule-permeable.
Proper citation: Clarity resources (RRID:SCR_001387) Copy
http://users.loni.ucla.edu/~shattuck/brainsuite/
Suite of image analysis tools designed to process magnetic resonance images (MRI) of the human head. BrainSuite provides an automatic sequence to extract genus-zero cortical surface mesh models from the MRI. It also provides a set of viewing tools for exploring image and surface data. The latest release includes graphical user interface and command line versions of the tools. BrainSuite was specifically designed to guide its users through the process of cortical surface extraction. NITRC has written the software to require minimal user interaction and with the goal of completing the entire process of extracting a topologically spherical cortical surface from a raw MR volume within several minutes on a modern workstation. The individual components of BrainSuite may also be used for soft tissue, skull and scalp segmentation and for surface analysis and visualization. BrainSuite was written in Microsoft Visual C using the Microsoft Foundation Classes for its graphical user interface and the OpenGL library for rendering. BrainSuite runs under the Windows 2000 and Windows XP Professional operating systems. BrainSuite features include: * Sophisticated visualization tools, such as MRI visualization in 3 orthogonal views (either separately or in 3D view), and overlayed surface visualization of cortex, skull, and scalp * Cortical surface extraction, using a multi-stage user friendly approach. * Tools including brain surface extraction, bias field correction, voxel classification, cerebellum removal, and surface generation * Topological correction of cortical surfaces, which uses a graph-based approach to remove topological defects (handles and holes) and ensure a tessellation with spherical topology * Parameterization of generated cortical surfaces, minimizing a harmonic energy functional in the p-norm * Skull and scalp surface extraction
Proper citation: BrainSuite (RRID:SCR_006623) Copy
http://www.mitre.org/news/digest/archives/2002/neuroinformatics.html
This resource''s long-term goal is to develop informatics methodologies and tools that will increase the creativity and productivity of neuroscience investigators, as they work together to use shared human brain mapping data to generate and test ideas far beyond those pursued by the data''s originators. This resource currently has four major projects supporting this goal: * Database tools: The goal of the NeuroServ project is to provide neuroscience researchers with automated information management tools that reduce the effort required to manage, analyze, query, view, and share their imaging data. It currently manages both structural magnetic resonance image (MRI) datasets and diffusion tensor image (DTI) datasets. NeuroServ is fully web-enabled: data entry, query, processing, reporting, and administrative functions are performed by qualified users through a web browser. It can be used as a local laboratory repository, to share data on the web, or to support a large distributed consortium. NeuroServ is based on an industrial-quality query middleware engine MRALD. NeuroServ includes a specialized neuroimaging schema and over 40 custom Java Server Pages supporting data entry, query, and reporting to help manage and explore stored images. NeuroServ is written in Java for platform independence; it also utilizes several open source components * Data sharing: DataQuest is a collaborative forum to facilitate the sharing of neuroimaging data within the neuroscience community. By publishing summaries of existing datasets, DataQuest enables researchers to: # Discover what data is available for collaborative research # Advertise your data to other researchers for potential collaborations # Discover which researchers may have the data you need # Discover which researchers are interested in your data. * Image quality: The approach to assessing the inherent quality of an image is to measure how distorted the image is. Using what are referred to as no-reference or blind metrics, one can measure the degree to which an image is distorted. * Content-based image retrieval: NIRV (NeuroImagery Retrieval & Visualization) is a work environment for advanced querying over imagery. NIRV will have a Java-based front-end for users to issue queries, run processing algorithms, review results, visualize imagery and assess image quality. NIRV interacts with an image repository such as NeuroServ. Users can also register images and will soon be able to filter searches based on image quality.
Proper citation: MITRE Neuroinformatics (RRID:SCR_006508) Copy
Set of measures intended for use in large-scale genomic studies. Facilitate replication and validation across studies. Includes links to standards and resources in effort to facilitate data harmonization to legacy data. Measurement protocols that address wide range of research domains. Information about each protocol to ensure consistent data collection.Collections of protocols that add depth to Toolkit in specific areas.Tools to help investigators implement measurement protocols.
Proper citation: Phenotypes and eXposures Toolkit (RRID:SCR_006532) Copy
http://intramural.nimh.nih.gov/
The Division of Intramural Research Programs (DIRP) at the National Institute of Mental Health (NIMH) is the internal research division of the NIMH. NIMH DIRP scientists conduct research ranging from studies into mechanisms of normal brain function, conducted at the behavioral, systems, cellular, and molecular levels, to clinical investigations into the diagnosis, treatment and prevention of mental illness. Major disease entities studied throughout the lifespan include mood disorders and anxiety, schizophrenia, obsessive-compulsive disorder, attention deficit hyperactivity disorder, and pediatric autoimmune neuropsychiatric disorders. Because of its outstanding resources, unique funding mechanisms, and location in the nation''s capital, the DIRP is viewed as a national resource, providing unique opportunities in mental health research and research training. Training is conducted in all the Institute''s clinical branches and basic neuroscience laboratories located on the 305-acre National Institutes of Health campus in Bethesda, Maryland. In addition to individualized trainee/mentor-driven postdoctoral training opportunities in the clinical and basic sciences, the DIRP offers Postbaccalaureate Research Training Awards, a Clinical Electives Program, as well as a variety of Summer Research Fellowships and an Undergraduate Internship Program. The mission of the division is to plan and conduct basic, clinical, and translational research to advance understanding of the diagnosis, causes, treatment, and prevention of mental disorders through the study of brain function and behavior; conduct state-of-the-art research that, in part, complements extramural research activities and exploits the special resources of the National Institutes of Health; and provide an environment conducive to the training and development of clinical and basic scientists. In addition the DIRP fosters standards of excellence in the ethical treatment and the provision of clinical care to research subjects; serve as a resource to the NIMH in responding to requests made by the Administration, members of Congress, and citizens'' groups for information regarding mental disorders; and analyzes and evaluates national needs and research opportunities and provides advice to the Institute Director on matters of scientific interest. Core Facilities: * Functional MRI Core * Magnetic Resonance Core * Magnetoencephalography Core * Microarray Core * Neurophysiology Imaging Facility * Non-Human Primate Core * Scientific and Statistical Computing Core * Section on Instrumentation Core * Transgenic Core * Veterinary Medicine Resources
Proper citation: NIMH Division of Intramural Research Programs (RRID:SCR_006860) Copy
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
Web based gene set analysis toolkit designed for functional genomic, proteomic, and large-scale genetic studies from which large number of gene lists (e.g. differentially expressed gene sets, co-expressed gene sets etc) are continuously generated. WebGestalt incorporates information from different public resources and provides a way for biologists to make sense out of gene lists. This version of WebGestalt supports eight organisms, including human, mouse, rat, worm, fly, yeast, dog, and zebrafish.
Proper citation: WebGestalt: WEB-based GEne SeT AnaLysis Toolkit (RRID:SCR_006786) Copy
http://krasnow1.gmu.edu/cn3/index3.html
Multidisciplinary research team devoted to the study of basic neuroscience with a specific interest in the description and generation of dendritic morphology, and in its effect on neuronal electrophysiology. In the long term, they seek to create large-scale, anatomically plausible neural networks to model entire portions of a mammalian brain (such as a hippocampal slice, or a cortical column). Achievements by the CNG include the development of software for the quantitative analysis of dendritic morphology, the implementation of computational models to simulate neuronal structure, and the synthesis of anatomically accurate, large scale neuronal assemblies in virtual reality. Based on biologically plausible rules and biophysical determinants, they have designed stochastic models that can generate realistic virtual neurons. Quantitative morphological analysis indicates that virtual neurons are statistically compatible with the real data that the model parameters are measured from. Virtual neurons can be generated within an appropriate anatomical context if a system level description of the surrounding tissue is included in the model. In order to simulate anatomically realistic neural networks, axons must be grown as well as dendrites. They have developed a navigation strategy for virtual axons in a voxel substrate.
Proper citation: Computational Neuroanatomy Group (RRID:SCR_007150) Copy
http://brainatlas.mbi.ufl.edu/Database/
Comprehensive three-dimensional digital atlas database of the C57BL/6J mouse brain based on magnetic resonance microscopy images acquired on a 17.6-T superconducting magnet. This database consists of: Individual MRI images of mouse brains; three types of atlases: individual atlases, minimum deformation atlases and probabilistic atlases; the associated quantitative structural information, such as structural volumes and surface areas. Quantitative group information, such as variations in structural volume, surface area, magnetic resonance microscopy image intensity and local geometry, have been computed and stored as an integral part of the database. The database augments ongoing efforts with other high priority strains as defined by the Mouse Phenome Database focused on providing a quantitative framework for accurate mapping of functional, genetic and protein expression patterns acquired by a myriad of technologies and imaging modalities. You must register First (Mandatory) and then you may Download Images and Data.
Proper citation: MRM NeAt (Neurological Atlas) Mouse Brain Database (RRID:SCR_007053) Copy
http://brainml.org/goto.do?page=.home
Set of standards and practices for using XML to facilitate information exchange between user application software and neuroscience data repositories. It allows for common shared library routines to handle most of the data processing, but also supports use of structures specialized to the needs of particular neuroscience communities. This site also serves as a repository for BrainML models. (A BrainML model is an XML Schema and optional vocabulary files describing a data model for electronic representation of neuroscience data, including data types, formats, and controlled vocabulary. ) It focuses on layered definitions built over a common core in order to support community-driven extension. One such extension is provided by the new NIH-supported neuroinformatics initiative of the Society for Neuroscience, which supports the development of expert-derived terminology sets for several areas of neuroscience. Under a cooperative agreement, these term lists will be made available Open Source on this site.
The repository function of this site includes the following features:
* BrainML models are published in searchable, browsable form.
* Registered users may submit new models or new versions of existing models to accommodate data of interest. * BrainML model schema and vocabulary files are made available at fixed URLs to allow software applications to reference them.
* Users can check models and/or instance documents for correct format before submitting them using an online validation service.
To complement the BrainML modeling language, a set of protocols have been developed for BrainML document exchange between repositories and clients, for indexing of repositories, and for data query.
Proper citation: BrainML (RRID:SCR_007087) Copy
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
Trans-NIH project to assess the state of longitudinal and epidemiological research on demographic, social and biologic determinants of cognitive and emotional health in aging adults and the pathways by which cognitive and emotional health may reciprocally influence each other. A database of large scale longitudinal study relevant to healthy aging in 4 domains was created based on responses of investigators conducting these studies and is available for query. The four domains are: * Cognitive Health * Emotional Health * Demographic and Social Factors * Biomedical and Physiologic Factors
Proper citation: Cognitive and Emotional Health Project: The Healthy Brain (RRID:SCR_007390) Copy
Collects, stores, and distributes samples of nervous tissue, cerebrospinal fluid, blood, and other tissue from HIV-infected individuals. The NNTC mission is to bolster research on the effects of HIV infection on human brain by providing high-quality, well-characterized tissue samples from patients who died with HIV, and for whom comprehensive neuromedical and neuropsychiatric data were gathered antemortem. Researchers can request tissues from patients who have been characterized by: * degree of neurobehavioral impairment * neurological and other clinical diagnoses * history of drug use * antiretroviral treatments * blood and CSF viral load * neuropathological diagnosis The NNTC encourages external researchers to submit tissue requests for ancillary studies. The Specimen Query Tool is a web-based utility that allows researchers to quickly sort and identify appropriate NNTC specimens to support their research projects. The results generated by the tool reflect the inventory at a previous time. Actual availability at the local repositories may vary as specimens are added or distributed to other investigators.
Proper citation: National NeuroAIDS Tissue Consortium (RRID:SCR_007323) Copy
https://portal.brain-map.org/explore/classes/nomenclature
Framework for creating brain cell type nomenclature, and include examples using published datasets. System allows designation of cell types with or without hierarchical organization. Nomenclature convention initially applied to brain cells and types, is intended to encompass existing naming strategies used in publications across diverse research teams. Allows tracking of many different taxonomies, including those from different organ systems or across diverse areas of bioscience.
Proper citation: Common Cell Type Nomenclature (RRID:SCR_021124) Copy
Open source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.
Proper citation: ImageJ (RRID:SCR_003070) Copy
Database of mouse brain cell type-specific gene expression datasets. NeuroExpresso is able to demonstrate the use of marker genes for acquiring cell type specific information from whole tissue expression.
Proper citation: NeuroExpresso (RRID:SCR_015724) Copy
Platform for mediation and integration of schizophrenia neuroimaging-related databases. It provides access to federated databases, novel mediation software, and large-scale data-sharing features.
Proper citation: SchizConnect (RRID:SCR_015766) Copy
http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases
Probabilistic atlases covering 48 cortical and 21 subcortical structural areas, derived from structural data and segmentations kindly provided by the Harvard Center for Morphometric Analysis. T1-weighted images of 21 healthy male and 16 healthy female subjects (ages 18-50) were individually segmented by the CMA using semi-automated tools developed in-house. The T1-weighted images were affine-registered to MNI152 space using FLIRT (FSL), and the transforms then applied to the individual labels. Finally, these were combined across subjects to form population probability maps for each label. Segmentations used to create these atlases were provided by: David Kennedy and Christian Haselgrove, Centre for Morphometric Analysis, Harvard; Bruce Fischl, the Martinos Center for Biomedical Imaging, MGH; Janis Breeze and Jean Frazier from the Child and Adolescent Neuropsychiatric Research Program, Cambridge Health Alliance; Larry Seidman and Jill Goldstein from the Department of Psychiatry of Harvard Medical School.
Proper citation: Harvard - Oxford Cortical Structural Atlas (RRID:SCR_001476) Copy
http://www.nitrc.org/projects/frats/
Software for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. The resulting analysis pipeline can be used for understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles.
Proper citation: Functional Regression Analysis of DTI Tract Statistics (RRID:SCR_002293) Copy
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