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http://www.socr.ucla.edu/

A hierarchy of portable online interactive aids for motivating, modernizing probability and statistics applications. The tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials. The core SOCR educational and computational components include the following suite of web-based Java applets: * Distributions (interactive graphs and calculators) * Experiments (virtual computer-generated games and processes) * Analyses (collection of common web-accessible tools for statistical data analysis) * Games (interfaces and simulations to real-life processes) * Modeler (tools for distribution, polynomial and spectral model-fitting and simulation) * Graphs, Plots and Charts (comprehensive web-based tools for exploratory data analysis), * Additional Tools (other statistical tools and resources) * SOCR Java-based Statistical Computing Libraries * SOCR Wiki (collaborative Wiki resource) * Educational Materials and Hands-on Activities (varieties of SOCR educational materials), * SOCR Statistical Consulting In addition, SOCR provides a suite of tools for volume-based statistical mapping (http://wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials_AnalysesCommandLine) via command-line execution and via the LONI Pipeline workflows (http://www.nitrc.org/projects/pipeline). Course instructors and teachers will find the SOCR class notes and interactive tools useful for student motivation, concept demonstrations and for enhancing their technology based pedagogical approaches to any study of variation and uncertainty. Students and trainees may find the SOCR class notes, analyses, computational and graphing tools extremely useful in their learning/practicing pursuits. Model developers, software programmers and other engineering, biomedical and applied researchers may find the light-weight plug-in oriented SOCR computational libraries and infrastructure useful in their algorithm designs and research efforts. The three types of SOCR resources are: * Interactive Java applets: these include a number of different applets, simulations, demonstrations, virtual experiments, tools for data visualization and analysis, etc. All applets require a Java-enabled browser (if you see a blank screen, see the SOCR Feedback to find out how to configure your browser). * Instructional Resources: these include data, electronic textbooks, tutorials, etc. * Learning Activities: these include various interactive hands-on activities. * SOCR Video Tutorials (including general and tool-specific screencasts).

Proper citation: Statistics Online Computational Resource (RRID:SCR_003378) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/BIRN/Projects/Mouse/

Animal model data primarily focused on mice including high resolution MRI, light and electron microscopic data from normal and genetically modified mice. It also has atlases, and the Mouse BIRN Atlasing Toolkit (MBAT) which provides a 3D visual interface to spatially registered distributed brain data acquired across scales. The goal of the Mouse BIRN is to help scientists utilize model organism databases for analyzing experimental data. Mouse BIRN has ended. The next phase of this project is the Mouse Connectome Project (https://www.nitrc.org/projects/mcp/). The Mouse BIRN testbeds initially focused on mouse models of neurodegenerative diseases. Mouse BIRN testbed partners provide multi-modal, multi-scale reference image data of the mouse brain as well as genetic and genomic information linking genotype and brain phenotype. Researchers across six groups are pooling and analyzing multi-scale structural and functional data and integrating it with genomic and gene expression data acquired from the mouse brain. These correlated multi-scale analyses of data are providing a comprehensive basis upon which to interpret signals from the whole brain relative to the tissue and cellular alterations characteristic of the modeled disorder. BIRN's infrastructure is providing the collaborative tools to enable researchers with unique expertise and knowledge of the mouse an opportunity to work together on research relevant to pre-clinical mouse models of neurological disease. The Mouse BIRN also maintains a collaborative Web Wiki, which contains announcements, an FAQ, and much more.

Proper citation: Mouse Biomedical Informatics Research Network (RRID:SCR_003392) Copy   

•   Source: SciCrunch Registry

http://cng.gmu.edu:8080/Lm

A freely available software tool available for the Windows and Linux platform, as well as the Online version Applet, for the analysis, comparison and search of digital reconstructions of neuronal morphologies. For the quantitative characterization of neuronal morphology, LM computes a large number of neuroanatomical parameters from 3D digital reconstruction files starting from and combining a set of core metrics. After more than six years of development and use in the neuroscience community, LM enables the execution of commonly adopted analyses as well as of more advanced functions, including: (i) extraction of basic morphological parameters, (ii) computation of frequency distributions, (iii) measurements from user-specified subregions of the neuronal arbors, (iv) statistical comparison between two groups of cells and (v) filtered selections and searches from collections of neurons based on any Boolean combination of the available morphometric measures. These functionalities are easily accessed and deployed through a user-friendly graphical interface and typically execute within few minutes on a set of 20 neurons. The tool is available for either online use on any Java-enabled browser and platform or may be downloaded for local execution under Windows and Linux.

Proper citation: L-Measure (RRID:SCR_003487) Copy   

•   Source: SciCrunch Registry

http://neuroscienceblueprint.nih.gov/

Collaborative framework that includes the NIH Office of the Director and the 14 NIH Institutes and Centers that support research on the nervous system. By pooling resources and expertise, the Blueprint identifies cross-cutting areas of research, and confronts challenges too large for any single Institute or Center. The Blueprint makes collaboration a day-to-day part of how the NIH does business in neuroscience, complementing the basic missions of Blueprint partners. During each fiscal year, the partners contribute a small percentage of their funds to a common pool. Since the Blueprint's inception in 2004, this pool has comprised less than 1 percent of the total neuroscience research budget of the partners. In 2009, the Blueprint Grand Challenges were launched to catalyze research with the potential to transform our basic understanding of the brain and our approaches to treating brain disorders. * The Human Connectome Project is an effort to map the connections within the healthy brain. It is expected to help answer questions about how genes influence brain connectivity, and how this in turn relates to mood, personality and behavior. The investigators will collect brain imaging data, plus genetic and behavioral data from 1,200 adults. They are working to optimize brain imaging techniques to see the brain's wiring in unprecedented detail. * The Grand Challenge on Pain supports research to understand the changes in the nervous system that cause acute, temporary pain to become chronic. The initiative is supporting multi-investigator projects to partner researchers in the pain field with researchers in the neuroplasticity field. * The Blueprint Neurotherapeutics Network is helping small labs develop new drugs for nervous system disorders. The Network provides research funding, plus access to millions of dollars worth of services and expertise to assist in every step of the drug development process, from laboratory studies to preparation for clinical trials. Project teams across the U.S. have received funding to pursue drugs for conditions from vision loss to neurodegenerative disease to depression. Since its inception in 2004, the Blueprint has supported the development of new resources, tools and opportunities for neuroscientists. For example, the Blueprint supports several training programs to help students pursue interdisciplinary areas of neuroscience, and to bring students from underrepresented groups into the neurosciences. The Blueprint also funds efforts to develop new approaches to teaching neuroscience through K-12 instruction, museum exhibits and web-based platforms. From fiscal years 2007 to 2009, the Blueprint focused on three major themes of neuroscience - neurodegeneration, neurodevelopment, and neuroplasticity. These efforts enabled unique funding opportunities and training programs, and helped establish new resources including the Blueprint Non-Human Primate Brain Atlas.

Proper citation: NIH Blueprint for Neuroscience Research (RRID:SCR_003670) Copy   

•   Source: SciCrunch Registry

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

An end-to-end pipeline for corpus callosum processing that provides automated midsagittal alignment, CC segmentation with a quality control tool, and thickness profile generation. Groupwise analysis is facilitated by permutation testing with FWER and FDR multiple comparison correction. Results display is facilitated by a display script that shows p-values on a 3D pipe representation of a CC. This pipeline is implemented in MATLAB and requires the Image Processing Toolbox. There are plans to implement it completely in Python.

Proper citation: Corpus Callosum Thickness Profile Analysis Pipeline (RRID:SCR_003575) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/meshmetric3d/

Software visualization tool based on the VTK library. Its main feature is to measure and display surface-to-surface distance between two triangle meshes using user-specified uniform sampling. Offers all the basic tools to visualize meshes such as color, opacity, smoothing, down sampling or type of representation.

Proper citation: 3DMeshMetric (RRID:SCR_000043) Copy   

•   Source: SciCrunch Registry

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

The packaged tools perform Local Binary Pattern on Three Orthogonal Planes (LBP-TOP) analysis on MR brain images. One can use them to extract LBP texture features for machine learning applications or other advance analysis. Bash scripts performing simple preprocessing with FSL and AFNI as well as LBP mapping programs written by Java are both including in this package. The output is the histogram describing the brain morphology.

Proper citation: Local Binary Pattern Analysis Tools for MR Brain Images (RRID:SCR_000412) Copy   

•   Source: SciCrunch Registry

http://micro-manager.org

Software package for control of automated microscopes. Cross-platform desktop application, to control motorized microscopes, scientific cameras, stages, illuminators, and other microscope accessories.

Proper citation: uManager (RRID:SCR_000415) Copy   

•   Source: SciCrunch Registry

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

Scribe encodes papers to populate the BrainMap Database

Proper citation: Scribe (RRID:SCR_000423) Copy   

•   Source: SciCrunch Registry

http://cbrain.mcgill.ca/loris

A modular and extensible web-based data management system that integrates all aspects of a multi-center study, from heterogeneous data acquisition to storage, processing and ultimately dissemination, within a streamlined platform. Through a standard web browser, users are able to perform a wide variety of tasks, such as data entry, 3D image visualization and data querying. LORIS also stores data independently from any image processing pipeline, such that data can be processed by external image analysis software tools. LORIS provides a secure web-based and database-driven infrastructure to automate the flow of clinical data for complex multi-site neuroimaging trials and studies providing researchers with the ability to easily store, link, and access significant quantities of both scalar (clinical, psychological, genomic) and multi-dimensional (imaging) data. LORIS can collect behavioral, neurological, and imaging data, including anatomical and functional 3D/4D MRI models, atlases and maps. LORIS also functions as a project monitoring and auditing platform to oversee data acquisition across multiple study sites. Confidentiality during multi-site data sharing is provided by the Subject Profile Management System, which can perform automatic removal of confidential personal information and multiple real-time quality control checks. Additionally, web interactions with the LORIS portal take place over an encrypted channel via SSL, ensuring data security. Additional features such as Double Data Entry and Statistics and Data Query GUI are included.

Proper citation: LORIS - Longitudinal Online Research and Imaging System (RRID:SCR_000590) Copy   

•   Source: SciCrunch Registry

http://www.talairach.org/

Software automated coordinate based system to retrieve brain labels from the 1988 Talairach Atlas. Talairach Daemon database contains anatomical names for brain areas using x-y-z coordinates defined by the 1988 Talairach Atlas.

Proper citation: Talairach Daemon (RRID:SCR_000448) Copy   

•   Source: SciCrunch Registry

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

Autism research program that makes available post-mortem brain tissue to qualified scientists all over the world. Working directly with tissue banks, organ procurement agencies, medical examiners and the general public, this is the largest program dedicated to increasing and enhancing the availability of post-mortem brain tissue for basic research in autism. To date, the ATP has collected and stored more than 170 brains in their repositories at Harvard (US) and Oxford (UK). These brains are processed by formalin fixation and/or snap frozen to properly provide high quality tissue of all brain regions, in support of biological research in autism. The ATP is unique in that they diligently pursue all available clinical data (pre and post mortem) on tissue donors in order to create the most biologically relevant brain repository for autism research. These data, together with tissue resources from both banks and associated repositories, are presented to all interested researchers through their extensive web-based data portal (login required). The ATP is not a brain bank, but works directly with the Harvard Brain Tissue Resource Center in Boston (HBTRC), Massachusetts to serve as its tissue repository. This program augments brain bank functions by: * Creating the most biologically relevant brain tissue repository possible * Fully covering all costs associated with brain extraction and transfer to the repositories at Harvard (US and Canada) and Oxford (UK). * Providing scientific oversight of tissue distributions * Overseeing and managing all tissue grants * Clinically phenotyping and acquiring extensive medical data on all of their donors * Providing continuing family support and communication to all of their donors * Directly supporting researchers to facilitate autism research * Maintaining a robust web based data management and secure on-line global interface system * Developing and supporting ATP established scientific initiatives * Actively providing public outreach and education The ATP is not a clinical organ procurement agency, but rather they facilitate the wishes of donors and families to donate their tissue to autism research. Through the ATP's established international infrastructure, they work with any accredited tissue bank, organ procurement agency, or medical examiner that receives a family's request to donate their loved one's tissue to the program. Once contacted, the ATP will insure that the family's request to donate their loved one's tissue is faithfully met, covering all costs to the family and partnering agency as well as ensuring the tissues' proper and rapid transport to the ATP's repository at the Harvard Brain Tissue Resource Center (HBTRC) in Boston, Massachusetts.

Proper citation: Autism Tissue Program (RRID:SCR_000651) Copy   

•   Source: SciCrunch Registry

http://fcp-indi.github.io

A configurable, open-source, Nipype-based, automated processing pipeline for resting state functional MRI (R-fMRI) data, for use by both novice and expert users. C-PAC was designed to bring the power, flexibility and elegance of the Nipype platform to users in a plug and play fashion?without requiring the ability to program. Using an easy to read, text-editable configuration file, C-PAC can rapidly orchestrate automated R-fMRI processing procedures, including: - quality assurance measurements - image preprocessing based upon user specified preferences - generation of functional connectivity maps (e.g., correlation analyses) - customizable extraction of time-series data - generation of local R-fMRI metrics (e.g., regional homogeneity, voxel-matched homotopic connectivity, fALFF/ALFF) C-PAC makes it possible to use a single configuration file to launch a factorial number of pipelines differing with respect to specific processing steps.

Proper citation: C-PAC (RRID:SCR_000862) Copy   

•   Source: SciCrunch Registry

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

An I/O library for Matlab/Octave Matlab and Octave library for reading and writing Nifti-1 files. cbiNifti is intended to be a small, self-contained library that makes minimal assumptions about what Nifti files should look like and allow users easy access to the raw data. cbiNifti handles compressed file formats for reading and writing, using Unix pipes for compression and decompression. More information and code examples at: http://www.pc.rhul.ac.uk/staff/J.Larsson/software.html

Proper citation: cbiNifti: Matlab/Octave Nifti library (RRID:SCR_000860) Copy   

•   Source: SciCrunch Registry

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

Construct and analyse brain network is a brain network visualization tool, which can help researchers to visualize construct and analyse resting state functional brain networks from different levels in a quick, easy and flexible way. Entrance parameter of construct and analyse brain network is export parameters of dparsf software.It would be greatly appreciated if you have any suggestions about the package or manual.

Proper citation: BrainNetworkConstructionAnalysisPlatform (RRID:SCR_000854) Copy   

•   Source: SciCrunch Registry

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

Communnity project to help support the efforts of investigators using Philips Healthcare systems. This clearingsite helps users find forums, mailinglists, etc. that support this community. If you have suggestions for inclusion, let the project admin know!

Proper citation: Philips Users Community (RRID:SCR_001438) Copy   

•   Source: SciCrunch Registry

http://neuro.imm.dtu.dk/wiki/Main_Page

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 10, 2025. Semantic wiki with structured information, primarily from functional and molecular neuroimaging papers, but there are also other types of papers, e.g., from personality genetics. It lists results from neuroimaging studies, such as Talairach coordinates and brain volume measurements, as well as software packages and brain regions. SQL dumps of the structured information in the wiki is available so complex queries can be formed. The Brede Wiki templates store the structured information from neuroscience papers and editors may add free format text. Template definitions format the data so it is presented as tables on the formatted wiki-page. From a given PMID a web-service can format information from PubMed for inclusion in the Brede Wiki. A Matlab script can extract coordinates from SPM5 and format them in the Talairach coordinate template format.

Proper citation: Brede Wiki (RRID:SCR_001411) Copy   

•   Source: SciCrunch Registry

https://www.mristudio.org/

An image processing program running under Windows suitable for such tasks as tensor calculation, color mapping, fiber tracking, and 3D visualization. Most of operations can be done with only a few clicks. This tool evolved from DTI Studio. Tools in the program can be grouped in the following way: * Image Viewer * Diffusion Tensor Calculations * Fiber Tracking and Editing * 3D Visualization * Image File Management * Region of Interesting (ROI) Drawing and Statistics * Image Registration

Proper citation: MRI Studio (RRID:SCR_001398) Copy   

•   Source: SciCrunch Registry

http://www.thevirtualbrain.org/

Simulation software for modeling the entire human brain by combining structural and functional data from empirical neuroimaging data. It can generate local field potentials, EEG, MEG and fMRI BOLD data based on neural mass models. The user can also modify the model parameters to match clinical conditions from focal lesions or degenerative disorders.

Proper citation: Virtual brain (RRID:SCR_002249) Copy   

•   Source: SciCrunch Registry

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

Software package for brain image manipulation and analysis, focusing on fMRI and lesion analysis. VoxBo can be used independently or in conjunction with other packages. It provides GLM-based statistical tools, an architecture for interoperability with other tools (they encourage users to incorporate SPM and FSL into their processing pipelines), an automation system, a system for parallel distributed computing, numerous stand-alone tools, decent wiki-based documentation, and lots more.

Proper citation: VoxBo (RRID:SCR_002166) Copy   

•   Source: SciCrunch Registry