Tools   Select Another Resource Report Type

http://www.nia.nih.gov/research/dn

A funding resource that supports the research and training for understanding the structure and function of the aging nervous system, with an emphasis on studies involving Alzheimer's disease and age-related dementia. There is an emphasis on brain-behavior relationships. This program is composed of three branches: Neurobiology, Neuropsychology, and Dementias of Aging. The overall aim of this program is to understand the aging nervous system to minimize mental decline and improve the lives of older patients. This resource also includes links to sites for Alzheimer's disease (AD) studies that include: specimen repositories, genetic materials, bio-markers, data, policies on NIA and AD genetics sharing plans, and additional aging or other AD related links.

Proper citation: National Institute on Aging, Division of Neuroscience (RRID:SCR_008257) Copy   

•   Source: SciCrunch Registry

http://brainconnection.positscience.com/

An educational site providing accessible information about how the brain works and how people learn

Proper citation: Brain Connection (RRID:SCR_008315) Copy   

•   Source: SciCrunch Registry

http://loni.usc.edu/Software/SVT

Software tool for determining the statistically significant regions of activation in single or multi-subject human brain functional studies. It can be also applied to structural brain data for analyzing developmental, dementia and other changes of anatomy over time. This package was originally developed to work on Sun SPARC and SGI stations using the "C" language compiler provided by Sun/SGI as part of the standard system software.

Proper citation: Sub-Volume Thresholding Analysis (RRID:SCR_008272) Copy   

•   Source: SciCrunch Registry

http://www.ohsu.edu/xd/research/centers-institutes/onprc/

Center that aims to develop biomedical technologies using nonhuman primate (NHP) models. Its goal is to uncover the root causes of various disease and disorders, unlock secrets of the brain, and unleash new methods of diagnostics and treatment.

Proper citation: Oregon National Primate Research Center (RRID:SCR_008291) Copy   

•   Source: SciCrunch Registry

http://www.jsmf.org/

Supports research and scholarship to improve the quality of life by providing funding for grants in three program areas: studying complex systems, understanding human cognition, and mathematical and complex systems approaches for brain cancer. Types of awards include Fellowship Awards, Scholar Awards, and Collaborative Awards. * Studying Complex Systems: This program supports scholarship and research directed toward the development of theoretical and mathematical tools that can be applied to the study of complex, adaptive, nonlinear systems. It is anticipated that research funded in this program will address issues in fields such as biology, biodiversity, climate, demography, epidemiology, technological change, economic development, governance, or computation. * Understanding Human Cognition: This program supports research studying how neural systems are linked to and support cognitive functions and how cognitive systems are related to an organism's (preferably human) observable behavior. Studies with model organisms should justify why such models were selected and how data obtained from models advances our understanding of human cognition. * Mathematical & Complex Systems Approaches for Brain Cancer: (Collaborative Activity Awards grant type only.) Despite some recent cause for optimism for advancing the clinical treatment of brain cancers, for many patients brain tumor remains a devastating diagnosis. Progress against this disease has been stymied by limited understandings of the molecular, metabolic, and physiological characteristics of human brain cancers across multiple temporal and spatial scales and by the failure of many preclinical models to predict patient responses.

Proper citation: James S. McDonnell Foundation (RRID:SCR_006341) Copy   

•   Source: SciCrunch Registry

http://www.callisto-science.org/NSI/Neuroscience_Image_Database/Images%20of%20the%20Human%20Nervous%20System%20-%20Neuroanatomy.html

Data set of images of the human nervous system focusing on neuroanatomy.

Proper citation: Human Nervous System Neuroanatomy (RRID:SCR_006371) Copy   

•   Source: SciCrunch Registry

http://vinovia.ncl.ac.uk/emagewebapp/pages/eadhb_home.jsf

Database of a set of standard 3D virtual models at different stages of development from Carnegie Stages (CS) 12-23 (approximately 26-56 days post conception) in which various anatomical regions have been defined with a set of anatomical terms at various stages of development (known as an ontology). Experimental data is captured and converted to digital format and then mapped to the appropriate 3D model. The ontology is used to define sites of gene expression using a set of standard descriptions and to link the expression data to an ''''anatomical tree''''. Human data from stages CS12 to CS23 can be submitted to the HUDSEN Gene Expression Database. The anatomy ontology currently being used is based on the Edinburgh Human Developmental Anatomy Database which encompasses all developing structures from CS1 to CS20 but is not detailed for developing brain structures. The ontology is being extended and refined (by Prof Luis Puelles, University of Murcia, Spain) and will be incorporated into the HUDSEN database as it is developed. Expression data is annotated using two methods to denote sites of expression in the embryo: spatial annotation and text annotation. Additionally, many aspects of the detection reagent and specimen are also annotated during this process (assignment of IDs, nucleotide sequences for probes etc). There are currently two main ways to search HUDSEN - using a gene/protein name or a named anatomical structure as the query term. The entire contents of the database can be browsed using the data browser. Results may be saved. The data in HUDSEN is generated from both from researchers within the HUDSEN project, and from the wider scientific community. The HUDSEN human gene expression spatial database is a collaboration between the Institute of Human Genetics in Newcastle, UK, and the MRC Human Genetics Unit in Edinburgh, UK, and was developed as part of the Electronic Atlas of the Developing Human Brain (EADHB) project (funded by the NIH Human Brain Project). The database is based on the Edinburgh Mouse Atlas gene expression database (EMAGE), and is designed to be an openly available resource to the research community holding gene expression patterns during early human development.

Proper citation: HUDSEN Human Gene Expression Spatial Database (RRID:SCR_006325) Copy   

•   Source: SciCrunch Registry

http://learn.genetics.utah.edu/content/addiction/drugs/mouse.html

Mouse Party is an interactive website that teaches how various drugs disrupt the synapse by taking a look inside the brains of mice on drugs! Every drug of abuse has its own unique molecular mechanism. Where applicable, this presentation primarily depicts how drugs interact with dopamine neurotransmitters because this website focuses on the brain''s reward pathway. Mouse Party is designed to provide a small glimpse into the chemical interactions at the synaptic level that cause the drug user to feel ''high''. The simplified mechanisms of drug action presented here are just a small part of the story. When drugs enter the body they elicit very complex effects in many different regions of the brain. Often they interact with many different types of neurotransmitters and may bind with a variety of receptor types in a variety of different locations. For example, THC in marijuana can bind with cannabinoid receptors located on the presynaptic and/or postsynaptic cell in a synapse.

Proper citation: Mouse Party (RRID:SCR_006438) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/functionalconnectivitytoolbox/

MATLAB toolbox for performing functional connectivity analyses includes many of the most commonly-used approaches researchers have utilized to date for the identification of condition-dependent functional interactions between fMRI time-series obtained from two or more brain regions. The approaches are either bivariate or multivariate methods defined in time or frequency domains that emphasize distinct features of relationships among the time-series.

Proper citation: Functional Connectivity Toolbox (RRID:SCR_006394) Copy   

•   Source: SciCrunch Registry

http://www.medschool.lsuhsc.edu/epilepsy_center/

The LSU Epilepsy Center of Excellence is dedicated to providing state-of-the-art, comprehensive epilepsy treatment, enhancing access to epilepsy education for patients and physicians, and promoting multidisciplinary epilepsy research in pharmacology, neuroelectrophysiology, neuroimaging, neurosurgery, neuropsychology, biomedical engineering and public health. The center''s team of professionals offers diagnostic and presurgical monitoring, the strategic use of antiepileptic medications, specialized epilepsy neuroimaging, vagus nerve stimulator implantation, ketogenic diet management, neuropsychological testing, psychiatric support and epilepsy surgery for adults and children. The Center also hosts several clinical research trials each year for investigational medications and devices. The following are the treatment methods currently available at this center: - Epilepsy Brain Implants - Responsive Neurostimulator (RNS) - Medications - Medication blood level monitoring - Vagus Nerve Stimulators (VNS) - Epilepsy Surgery - Ketogenic Diet - Psychiatric Services - Radiosurgery Epilepsy Center Sections: *Electrophysiology *Neuroimaging *Neuropsychology *Neuroscience *Neurosurgery *Pharmacology *Psychiatry *Research

Proper citation: Louisiana State University School of Medicine, Health Sciences Center: Epilepsy Center (RRID:SCR_006519) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.neuroinf.jp/

The Japan Node of the INCF coordinates neuroinformatics activities within Japan and represents Japanese efforts in INCF. This site provides information about Japanese neuroinformatics platforms (NI Platforms) and the techniques and tools available from the International Neuroinformatics Coordinating Facility (INCF). The Neuroinformatics Japan Center (NIJC) will also supply techniques and tools developed at RIKEN BSI and at other research groups in Japan. INCF expects each national node to: 1. Actively formulate and implement the INCF Work Programs, 2. Coordinate and facilitate local neuroinformatics research activities at the national level, 3. Encourage neuroinformatics data sharing that conforms with INCF standards, and 4. Promote neuroinformatics development that supports the goals of INCF. The Neuroinformatics Japan Center (NIJC) represents the Japan Node. Together with the Japan Node Committee and the Platform Subcommittees, we promote domestic activities of neuroinformatics. Platform Subcommittee members collaborate to develop databases that are available for use on the website. Standing at the intersection of neuroscience and information science, the field of neuroinformatics develops the tools to house, share and analyze neuroscientific data, and to create computational models of brain. NIJC supports researchers developing and maintaining neuroscience databases, provides a portal for these databases and Neuroinformatics, and is designing the infrastructure for Neuroinformatics. It is also developing database technologies, and facilitates cooperation and distribution of the information stored in those databases. The activities of the Japan Node * Shaping domestic neuroinformatics research and directions (Japan Node Committee) * Advising on Intellectual Property Rights and protecting experimental subjects (Japan Node Committee) * Developing and publishing brain science databases (Platform Subcommittee) * Coordinating database management (Platform Subcommittee) * Disseminating neuroinformatics information via the web portal * Developing the infrastructure for brain science information and neuroinformatics * Supporting the development and diffusion of neuroinformatics technology

Proper citation: INCF Japan Node (RRID:SCR_006569) Copy   

•   Source: SciCrunch Registry

http://www.behav.org/abcd/abcd.php

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 21, 2017.

Database developed for storing, retrieving and cross-referencing neuroscience information about the connectivity of the avian brain. It contains entries about the new and old terminology of the areas and their hierarchy and data on connections between brain regions, as well as a functional keyword system linked to brain regions and connections.

Proper citation: Avian Brain Circuitry Database (RRID:SCR_002401) Copy   

•   Source: SciCrunch Registry

http://www.jeiglesias.com

An automatic whole-brain extraction tool for T1-weighted MRI data (commonly known as skull stripping). Whole-brain segmentation is often the first component in neuroimage pipelines and therefore, its robustness is critical for the overall performance of the system. Many methods have been proposed in the literature, but they often: * work well on certain datasets but fail on others. * require case-specific parameter tuning ROBEX aims for robust skull-stripping across datasets with no parameter settings. It fits a triangular mesh, constrained by a shape model, to the probabilistic output of a supervised brain boundary classifier. Because the shape model cannot perfectly accommodate unseen cases, a small free deformation is subsequently allowed. The deformation is optimized using graph cuts.

Proper citation: ROBEX (RRID:SCR_002534) Copy   

•   Source: SciCrunch Registry

http://www.unidesign.ch/wiki/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on December 6, 2012. Connectome Wiki is a knowledge base for macro- and mesoscale brain region and brain structural connectivity information across species. Employing modern semantic wiki technology, it serves as collaborative platform as well. What can I get? * Brain Regions: Plenty of information, including links to relevant literature and much more. * Brain Connections: Well established neuronal connections based mainly on neuronal tracer studies from the literature. * Abbreviations: Look up abbreviations and corresponding English and Latin names * Partition Schemes: Foundational and more partitions with their corresponding delineation criteria and protocols. * Species: Information about different species is available, using their binomial name as identifier. * External: Enhance the ConnectomeViewer with Volume-To-Ontology mappings. * Data Source: You can download the raw data in RDF or JSON. How can I contribute? If your research is in particular brain regions, or model organisms not yet registered, feel free to act as domain expert and add your knowledge. If you do any tracer studies, add findings with appropriate published papers. Incrementally building a mesoscale skeleton wiring diagram. Complete anything that is missing. See also PapersToAdd. Register your own partition scheme and link it semantically against known schemes. Adding brain region pages for your particular research organisms. Use ConnectomeWiki as knowledge backend for your application concerned with gross neuroanatomy. The goals of this wiki are: * A collaborative platform to collect, collate, manage and disseminate mesoscale nervous system region and connectivity information across various species * Authority for Brain Region Abbreviations * Representation of Brain Region Homologies * Interrelation of Brain Partition Schemes * Information source for the ConnectomeViewer application

Proper citation: Connectome Wiki (RRID:SCR_002675) Copy   

•   Source: SciCrunch Registry

http://www.wellesley.edu/Neuroscience/

Neuroscience was implemented as a new interdisciplinary major in 1999, replacing the Psychobiology Program and providing a base of experiences in biology, chemistry and psychology. Our students benefit from being able to work in small classes and to experience investigative lab experiences even in their introductory courses. Wellesley's neuroscience majors graduate with a liberal arts background coupled with sufficient concentration in this specialized field to be competitive among students coming from exclusively research-oriented institutions. The best proofs of the success of this approach are its products: * 60% of our graduates proceed to medical school; * 15% of our graduates continue on with graduate work in neuroscience, psychology, or neuropsychology; * 10% of our graduates pursue careers that intersect with neuroscience - for example, patent law or work in the biotech industry. Neuroscience is the study of the structure and function of neurons and how they are assembled to produce behaviors. This topic uses a multidisciplinary approach that extends from the molecular, through the cellular, and to the behavioral level.

Proper citation: Wellesley College Neuroscience (RRID:SCR_002734) Copy   

•   Source: SciCrunch Registry

http://www.umc.edu/Administration/Centers_and_Institutes/Center_for_Psychiatric_Neuroscience/Core_Research_Resources.aspx

Core facility that provides access to psychiatrically characterized post-mortem brain specimens, state-of-the-art equipment, cutting-edge technologies and the technical advice of highly trained faculty members who serve as Core Directors. The sophisticated imaging systems and biotechnologically advanced molecular core resources are provided on a shared-use basis to CPN and UMMC researchers. The CPN Research Resources Cores include the Human Brain Collection Core, Animal Core, Imaging Core, Molecular Biology Core, and Information Technologies Core.

Proper citation: UMMC Center for Psychiatric Neuroscience Labs and Facilities (RRID:SCR_002688) Copy   

•   Source: SciCrunch Registry

http://www.gensat.org/

Gene expression data and maps of mouse central nervous system. Gene expression atlas of developing adult central nervous system in mouse, using in situ hybridization and transgenic mouse techniques. Collection of pictorial gene expression maps of brain and spinal cord of mouse. Provides tools to catalog, map, and electrophysiologically record individual cells. Application of Cre recombinase technologies allows for cell-specific gene manipulation. Transgenic mice created by this project are available to scientific community.

Proper citation: Gene Expression Nervous System Atlas (RRID:SCR_002721) Copy   

•   Source: SciCrunch Registry

http://www.ndgo.net/sfn/nerve/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. Society for Neuroscience (SfN) provides this Web site, Neuroscience Education Resources Virtual Encycloportal (NERVE), to advance neuroscience teaching and educational efforts. SfN is a nonprofit association of more than 38,000 researchers and professionals, believes K-12 educators and vital partners for engaging the next generation of researchers. NERVE gives access to information and tools for teaching about the nervous system and related health issues. The goal of NERVE is to provide a gateway to credible information from government, nonprofit and other respected sources. Society scientists and educators have reviewed information for appropriateness but responsibility for content remains that of the originating author or organizations. NERVE gives access to information and tools for teaching about the nervous system and related health issues.

Proper citation: Neuroscience Education Resources Virtual Encycloportal (RRID:SCR_002897) Copy   

•   Source: SciCrunch Registry

http://www.brainscape.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 23, 2013. Database for resting state functional connectivity studies. Functional connectivity has shown tremendous promise in mapping the intrinsic functional topography of the brain, evaluating neuroanatomical models, and investigating neurological and psychiatric disease. Brainscape includes a repository of public and private data and an analysis engine for exploring the correlation structure of spontaneous fluctuations in the fMRI BOLD signal. (DICOM data is the image format that can be uploaded.) With Brainscape you can upload, analyze, and share your own data. You can search for, download, and analyze studies in the repository of shared data. The analysis engine works by selecting one or more studies, typing in the coordinates of a brain region of interest, and the seed-region correlation engine computes the correlation structure across the whole brain. (T1, T2 and EPI data are the scan types Brainscape can process.) You decide who can access your data. You can keep it to yourself, share with select colleagues, or share it with everyone. The Brainscape database and analysis tools are open source and freely available.

Proper citation: Brainscape (RRID:SCR_002962) Copy   

•   Source: SciCrunch Registry