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http://afni.nimh.nih.gov/afni/

Set of (mostly) C programs that run on X11+Unix-based platforms (Linux, Mac OS X, Solaris, etc.) for processing, analyzing, and displaying functional MRI (FMRI) data defined over 3D volumes and over 2D cortical surface meshes. AFNI is freely distributed as source code plus some precompiled binaries.

Proper citation: Analysis of Functional NeuroImages (RRID:SCR_005927) Copy   

•   Source: SciCrunch Registry

https://www.braintest.org/brain_test/BrainTest

A portal of online studies that encourage community participation to tackle the most challenging problems in neuropsychiatry, including attention-deficit / hyperactivity disorder, schizophrenia, and bipolar disorder. Our approach is to engage the community and try to recruit tens of thousands of people to spend an hour of their time on our site. You folks will provide data in both brain tests and questionnaires, as well as DNA, and in return, we will provide some information about your brain and behavior. You will also be entered to win amazon.com gift cards. While large collaborative efforts were made in genetics in order to discover the secrets of the human genome, there are still many mysteries about the behaviors that are seen in complex neuropsychiatric syndromes and the underlying biology that gives rise to these behaviors. We know that it will require studying tens of thousands of people to begin to answer these questions. Having you, the public, as a research partner is the only way to achieve that kind of investment. This site will try to reach that goal, by combining high-throughput behavioral assessment using questionnaires and game-like cognitive tests. You provide the data and then we will provide information and feedback about why you should help us achieve our goals and how it benefits everyone in the world. We believe that through this online study, we can better understand memory and attention behaviors in the general population and their genetic basis, which will in turn allow us to better characterize how these behaviors go awry in people who suffer from mental illness. In the end, we hope this will provide better, more personalized treatment options, and ultimately prevention of these widespread and extremely debilitating brain diseases. We will use the data we collect to try to identify the genetic basis for memory and impulse control, for example. If we can achieve this goal, maybe we can then do more targeted research to understand how the biology goes awry in people who have problems with cognition, including memory and impulse control, like those diagnosed with ADHD, Schizophrenia, Bipolar Disorder, and Autism Spectrum Disorders. By participating in our research, you can learn about mental illness and health and help researchers tackle these complex problems. We can''t do it without your help.

Proper citation: Brain Test (RRID:SCR_006212) Copy   

•   Source: SciCrunch Registry

http://intramural.nimh.nih.gov/gcap/index.htm

Schizophrenia related portal that aims to solve the mystery of genetic predisposition to psychosis, develop new methods for early diagnosis and prevention, and discover new treatments that will cure people suffering from it. Our objectives are to fully characterize: # neurobiological mechanisms related to susceptibility genes for schizophrenia and related clinical disorders; # genetic variation in aspects of cognition and emotionality associated with schizophrenia; and # small molecular targets for novel therapies. A unique feature of this Program is that its diverse scientific resources will be focused on a highly specific scientific agenda, that is to acquire the critical biological information about the susceptibility genes associated with schizophrenia and related illnesses. Our mission and goal, to understand the basic mechanisms of serious mental illness, has again guided us into new areas of research and to new insights. We have found evidence of new genes implicated in the cause of schizophrenia and involved in brain functions related to cognition and emotion and we have begun to explore how genes interact with each other and with the environment to individualize risk for these conditions. We are working now with over 20 genes related to schizophrenia. One of the key developments in our research over the past year has been the emergence of some targets for the development of novel therapeutics. We have discovered a new schizophrenia susceptibility gene, KCNH2, which represents the first clear target for the development of novel treatments. Just in this past year, for example, we published the first extensive statistical analysis of how schizophrenia genes may vary in their risk effects based on different genetic background (Nicodemus et al Hum Gen 2006), the first studies of schizophrenia genes interacting in effecting gene expression in brain (Lipska et al Hum Mol Genetics 2006a, Lipska et al Hum Mol Gen 2006 b); the first evidence that the mechanism of genetic association of NRG1 with schizophrenia involves a novel isoform of the gene in human brain (Law et al PNAS 2006), and the first evidence that MAOA may be linked to mood and impulse control because it effects critical mood regulatory neural networks (Meyer-Lindenberg et al PNAS 2006).

Proper citation: Genes Cognition and Psychosis Program (RRID:SCR_006292) Copy   

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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   

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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   

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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

https://www.phenxtoolkit.org/

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   

•   Source: SciCrunch Registry

http://pubbrain.org/

A literature search and visualization tool that allows end users to enter any PubMed query and see that query rendered as a heatmap illustrating which regions of interest are most commonly mentioned within the search results. To use PubBrain, simply enter any valid PubMed search in the search box.

Proper citation: PubBrain (RRID:SCR_005387) Copy   

•   Source: SciCrunch Registry

http://neuromorphometrics.com

Neuromorphometrics provides brain labeling and measurement services. Given raw MRI brain scans, we make precise quantitative measurements of the volume, shape, and location of specific neuroanatomical structures. Web tool for brain measurement services. Used for modeling living human brain and make quantitative measurements of volume, shape, and location of specific neuroanatomical structures using given MRI brain scans. Automated analyses are manually guided, inspected and certified by a neuroanatomical expert. Resource of neuroanatomically labeled MRI brain scans database. Resource for neuroanatomical localization and identification: NeuAtlas.

Proper citation: Neuromorphometrics (RRID:SCR_005656) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/trials/index.shtml

NIMH supports research studies on mental health and disorders. Participate, refer a patient or learn about results of studies in ClinicalTrials.gov, the NIH/National Library of Medicine''''s registry of federally and privately funded clinical trials for all disease. Find NIH-funded studies currently recruiting participants in the following mental health topics: * Anxiety Disorders ** Generalized Anxiety Disorder ** Obsessive-Compulsive Disorder (OCD) ** Panic Disorder ** Post-traumatic Stress Disorder (PTSD) ** Social Phobia (Social Anxiety Disorder) * Attention Deficit Hyperactivity Disorder (ADHD, ADD) * Autism Spectrum Disorders (Pervasive Developmental Disorders) * Bipolar Disorder (Manic-Depressive Illness) * Borderline Personality Disorder * Depression * Eating Disorders * HIV/AIDS * Schizophrenia * Suicide Prevention Information Resources for NIMH Researchers Conducting Clinical Trials * Limited Access Datasets from NIMH-Supported Clinical Trials * NIMH Policy for Recruitment of Participants in Clinical Research * NIMH Policy on Data and Safety Monitoring in Extramural Investigator-Initiated Clinical Trials * Register a study with ClinicalTrials.gov

Proper citation: NIMH Clinical Trials (RRID:SCR_005613) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/educational-resources/neuroscience-and-psychiatry/neuroscience-and-psychiatry-module-1-translating-neural-circuits-into-novel-therapeutics.shtml

This is the first in a series of modules on neuroscience and psychiatry. This module explores research on cognitive deficits, a core feature of schizophrenia and the single best predictor of functional outcomes in this disorder for which we currently have no treatments. This module is an example of how translational neuroscience can provide clues for the development of promising novel therapeutics.

Proper citation: Neuroscience and Psychiatry Module 1: Translating Neural Circuits into Novel Therapeutics (RRID:SCR_005609) Copy   

•   Source: SciCrunch Registry

http://infocenter.nimh.nih.gov/il/public_il/

Database of photographs and illustrations of general biomedical research and research tools, mental health specific research, and treatment related images that are available, copyright free, to the public at no cost. Many images are available in low, medium, and high resolutions. Formats include jpg, gif, and png. NIMH images may not be used to state or imply the endorsement by NIMH or by an NIMH employee of a commercial product, service, or activity, or use in any other manner that might mislead. No fee is charged for using the images. However, credit must be given to the National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services unless otherwise instructed to give credit to the photographer or other source., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NIMH Image Library (RRID:SCR_005588) Copy   

•   Source: SciCrunch Registry

http://www.cnbc.cmu.edu/ibsc/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 07, 2013. A framework for understanding human cognition, grounded in principles specifying the character of human cognitive processes, and constrained by properties, of the underlying neural mechanisms. The Center will exploit this framework to guide formulation of explicit, testable models of normal and disordered cognition, including models of the development of cognitive functions and of their disintegration as a result of brain damage or disease. This site is intended as a public service and as a focal point for exchange of ideas among the participants in the Interdisciplinary Behavioral Science Center (IBSC). Public areas of the site provide information about the Center as a whole and about the various projects in the Center, as well as web-accessible documents and tools that we are making available as a public service. A fundamental tenet is that cognition is an emergent phenomenon, arising from the interactions of cooperating processing elements organized into specialized populations. One aim of the center will be to investigate the utility of explicit models that are formulated in terms of this approach, addressing many aspects of cognition including semantic knowledge, language processing, cognitive control, perception, learning and memory. A second aim will also investigate the principles that are embodied in the models, including principles of learning, processing and representation. Learning will be a central focus, since it plays a crucial role in cognitive development, acquisition of skills, formation of memories, and remediation of cognitive functions. A third aim of the Center will be to incorporate constraints from neuroscience. Findings from neuroscience will guide the specification of the principles and the formulation of domain-specific details of particular models, and will provide target experimental observations against which to assess the adequacy of the models. In addition, the Center will make use of neurophysiological methods in animals and functional brain imaging in humans to test predictions and generate additional data needed to constrain and inform model development. The Center will provide training funds for interdisciplinary research fellowships, to train junior scientists in the convergent use of behavioral, computational, and neuroscience methodologies. The outcome of the Centers efforts will be a fuller characterization of the nature of human cognitive processes, a clearer formulation of the underlying principles, and a more complete understanding of normal and disordered functions across many domains of cognition. This Center includes eight projects dedicated to various aspects of cognition and various general issues that arise in the effort to build explicit models that capture different aspects of cognition, and also includes an administrative core to help foster integration and provide computing resources. * Project 1: Functional and Neural Organization of Semantic Memory * Project 2: Interactive Processes in Language: Lexical Processing * Project 3: Interactive Processes in Language: Sentence Processing * Project 4: Mechanisms of Cognitive Control * Project 5: Interactive Processes in Perception: Neurophysiology of Figure-Ground Organization * Project 6: Basic Mechanisms and Cooperating Systems in Learning Memory * Project 7: Age and Experience Dependent Processes in Learning * Project 8: Theoretical Foundations * Core: Integration, Computational Resources, and Administration

Proper citation: NIMH Interdisciplinary Behavioral Science Center (RRID:SCR_008085) Copy   

•   Source: SciCrunch Registry

http://brainspan.org/

Atlas of developing human brain for studying transcriptional mechanisms involved in human brain development. Consists of RNA sequencing and exon microarray data profiling up to sixteen cortical and subcortical structures across full course of human brain development, high resolution neuroanatomical transcriptional profiles of about 300 distinct structures spanning entire brain for four midgestional prenatal specimens, in situ hybridization image data covering selected genes and brain regions in developing and adult human brain, reference atlas in full color with high resolution anatomic reference atlases of prenatal (two stages) and adult human brain along with supporting histology, magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) data.

Proper citation: Allen Human Brain Atlas: BrainSpan (Atlas of the Developing Brain) (RRID:SCR_008083) Copy   

•   Source: SciCrunch Registry

http://cbdb.nimh.nih.gov/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 07, 2013. A multidisciplinary neuroscience laboratory in which basic and clinical scientists work side by side exploring neural mechanisms and models of mental and cognitive function and of neuropsychiatric illness. Experiments are performed at many levels of inquiry, from basic molecular biology of the gene to clinical examinations of patients. A major area of investigation of this laboratory is the genetic mechanisms implicated in the pathogenesis of schizophrenia and its treatment. The laboratory is organized as a multi-disciplinary team of investigators with a common mission: to identify and fully characterize basic genetic and neurobiological mechanisms of schizophrenia and related cognitive and emotional disorders. The various components of this effort are centered various different units or divisions represented by groups of investigators, at various levels of training and experience, working on related experiments. The Director of the Branch and of the Genes, Cognition and Psychosis Program (GCAP) is Daniel R. Weinberger, M.D. The CBDB is the principle research laboratory in the created (2003) Genes, Cognition, and Psychosis Program (GCAP) of the NIMH. After twelve years of residing on the pastoral grounds of St. Elizabeths Hospital, in Southeast Washington, CBDB moved back to the main NIH campus in Bethesda, Maryland in 1998. While the unique setting of St. Elizabeths is irreplaceable, we have occupied beautiful new laboratories and clinic spaces that were created for us, and we are in the mainstream of NIH life., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NIMH Intramural Research Program Clinical Brain Disorders Branch (RRID:SCR_008728) Copy   

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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   

•   Source: SciCrunch Registry

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   

•   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://www.webgestalt.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry