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http://humanconnectome.org/consortia/

Project to map the neural pathways that underlie human brain function for several modalities of neuroimaging data including fMRI. The purpose of the Project is to acquire and share data about the structural and functional connectivity of the human brain. It will greatly advance the capabilities for imaging and analyzing brain connections, resulting in improved sensitivity, resolution, and utility, thereby accelerating progress in the emerging field of human connectomics. Altogether, the Human Connectome Project will lead to major advances in the understanding of what makes us uniquely human and will set the stage for future studies of abnormal brain circuits in many neurological and psychiatric disorders. The sixteen institutes and centers of the NIH Blueprint for Neuroscience have funded two major grants that will take complementary approaches to deciphering the brain's amazingly complex wiring diagram. An 11-institution consortium led by Washington University in St. Louis and the University of Minnesota received a 5-year grant to enable development and utilization of advanced Magnetic Resonance Imaging (MRI) methods to chart brain circuitry. A consortium led by Massachusetts General Hospital and the University of California at Los Angeles received a grant to enable building and refining a next-generation 3T MR scanner that improves the quality and spatial resolution with which brain connectivity data can be acquired at this field strength.

Proper citation: NIH Human Connectome Project (RRID:SCR_006942) Copy   

•   Source: SciCrunch Registry

http://www.wholebraincatalog.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016. An open source, downloadable, 3d atlas of the mouse brain and its cellular constituents that allows multi-scale data to be visualized in a seamless way, similar to Google earth. Data within the Catalog is marked up with annotations and can link out to additional data sources via a semantic framework. This next generation open environment has been developed to connect members of the neuroscience community to facilitate solutions for today's intractable challenges in brain research through cooperation and crowd sourcing. The client-server platform provides rich 3-D views for researchers to zoom in, out, and around structures deep in a multi-scale spatial framework of the mouse brain. An open-source, 3-D graphics engine used in graphics-intensive computer gaming generates high-resolution visualizations that bring data to life through biological simulations and animations. Within the Catalog, researchers can view and contribute a wide range of data including: * 3D meshes of subcellular scenes or brain region territories * Large 2D image datasets from both electron and light level microscopy * NeuroML and Neurolucida neuronal reconstructions * Protein Database molecular structures Users of the Whole Brain Catalog can: * Fit data of any scale into the international standard atlas coordinate system for spatial brain mapping, the Waxholm Space. * View brain slices, neurons and their animation, neuropil reconstructions, and molecules in appropriate locations * View data up close and at a high resolution * View their own data in the Whole Brain Catalog environment * View data within a semantic environment supported by vocabularies from the Neuroscience Information Framework (NIF) at http://www.neuinfo.org. * Contribute code and connect personal tools to the environment * Make new connections with related research and researchers 5 Easy Ways to Explore: * Explore the datasets across multiple scales. * View data closely at high resolution. * Observe accurately simulated neurons. * Readily search for content. * Contribute your own research.

Proper citation: Whole Brain Catalog (RRID:SCR_007011) Copy   

•   Source: SciCrunch Registry

http://mcx.sourceforge.net/

A Monte Carlo simulation software for photon migration in 3D turbid media. It uses Graphics Processing Units (GPU) based massively parallel computing techniques and is extremely fast compared to the traditional single-threaded CPU-based simulations. Using an nVidia 8800GT graphics card (14MP/114Cores), the acceleration is about 300x~400x compared to a single core of Xeon 5120 CPU; this ratio can be as high as 700x with a GTX 280 GPU and 1400x with a GTX 470.

Proper citation: Monte Carlo eXtreme (RRID:SCR_007001) Copy   

•   Source: SciCrunch Registry

http://ncmir.ucsd.edu/downloads/manual_align_rts2000.shtm

Software program to adjust the alignment of two adjacent images. Allows to correct for any misalignment that may occur during auto-alignment step. Serves as a bootstrap to get the images in approximately the right place.

Proper citation: Manual Align RTS2000 (RRID:SCR_007107) Copy   

•   Source: SciCrunch Registry

http://www.birncommunity.org/collaborators/function-birn/

The FBIRN Federated Informatics Research Environment (FIRE) includes tools and methods for multi-site functional neuroimaging. This includes resources for data collection, storage, sharing and management, tracking, and analysis of large fMRI datasets. fBIRN is a national initiative to advance biomedical research through data sharing and online collaboration. BIRN provides data-sharing infrastructure, software tools, strategies and advisory services - all from a single source.

Proper citation: Function BIRN (RRID:SCR_007291) Copy   

•   Source: SciCrunch Registry

http://www.brainvisa.info/

BrainVISA is a modular an customizable software platform built to host heterogeneous tools dedicated to neuroimaging research. Many toolboxes have already been developed for BrainVISA (T1 MRI, sulcal identification and morphometry, cortical surface analysis, diffusion imaging and tractography, fMRI, nuclear imaging, EEG and MEG, TMS, histology and autoradiography, etc.). Anatomist is a software for interactive visualization of multimodal data and for manipulation of structured 3D objects. It allows to build scenes that merge or combine images, meshes, regions of interest, fibers, textures, color palettes, referential changes, etc. A user can interact in 3D and in real time with the objects of an Anatomist scene: change point of view, select objects, add/suppress objects, change colors, draw regions of interests, do manual registration, etc. BrainVISA main features are: * Harmonization of communications between different software. For instance, BrainVISA toolboxes are using home-made software but also third-party software such as FreeSurfer, FSL, SPM, nipy, R-project, Matlab, etc. * Ontology-based data organization allowing database sharing and automation of mass of data analysis. * Fusion and interactive visualization of multimodal data (using Anatomist software). * Automatic generation of graphical user interfaces. * Workflow monitoring and data quality checking. * Full customization possible. * Runs on Linux, Mac and Windows. * Programming Language: C++, Python * Supported Data Format: ANALYZE, DICOM, GIfTI, MINC, NIfTI-1, Other Format

Proper citation: BrainVISA / Anatomist (RRID:SCR_007354) Copy   

•   Source: SciCrunch Registry

http://fmri.wfubmc.edu/software/PickAtlas

A software toolbox that provides a method for generating Region of Interest (ROI) masks based on the Talairach Daemon database. The atlases include Brodmann area, Lobar, Hemisphere, Anatomic Label (gyral anatomy), and Tissue type. The atlases have been extended to the vertex in MNI space, and corrected for the precentral gyrus anomaly. Additional atlases (including non-human atlases) can be added without difficulty., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: WFU PickAtlas (RRID:SCR_007378) Copy   

•   Source: SciCrunch Registry

http://mipav.cit.nih.gov

A Java-based application that enables quantitative analysis and visualization of medical images of numerous modalities such as DTI, PET, MRI, CT, or microscopy. Using MIPAV's standard user-interface and analysis tools, researchers at remote sites (via the internet) can easily share research data and analyses, thereby enhancing their ability to research, diagnose, monitor, and treat medical disorders. MIPAV can be run on any Java-enabled platform such as Windows, UNIX, or Macintosh OS X. Functionality includes segmentation, inter- and intra multi-modality registration, surface rendering, volume rendering and reading and writing a large number of biomedical file formats including: DICOM 3.0, Analyze, NIFTI, SPM, MINC, Phillips, GE, Zeiss, Biorad, jpeg, png, tiff, mrc, fits, interfile, and many more.

Proper citation: MIPAV: Medical Image Processing and Visualization (RRID:SCR_007371) Copy   

•   Source: SciCrunch Registry

http://www.ant-neuro.com/products/asa

A highly flexible EEG/ERP and MEG analysis package with a variety of source reconstruction, signal analysis and MRI processing features. ASA combines functional brain imaging with the visualization and incorporation of morphological information obtained from MRI or CT. ASA is a highly interactive and flexible software tool that can be applied to neuro-physiological and clinical brain research. ASA gives a realistic impression of your experimental configuration together with topographical mapping of EEG and MEG and the results of your analysis. ASA is developed for and by people dedicated to brain research. The concept of flexibility and openness covers even most complex analysis demands. The ASA environment is particularly attractive for those that wish to develop their own methods in third party packages like Matlab and use ASA for pre-processing and visualization purposes.

Proper citation: ASA - Advanced Source Analysis (RRID:SCR_012867) Copy   

•   Source: SciCrunch Registry

https://github.com/BRAINSia/BRAINSTools/tree/master/BRAINSConstellationDetector

This program will find the mid-sagittal plane, the AC, PC, and mpj points in an image, and create an AC/PC aligned data set with the AC point at the center of the voxel lattice (la beled at the origin of the image physical space.) This work is an extention of the algorithms originally described by Dr. Babak A. Ardekani, Alvin H. Bachman, Model-based automatic detection of the anterior and posterior commissures on MRI scans, N euroImage, Volume 46, Issue 3, 1 July 2009, Pages 677-682, ISSN 1053-8119, DOI: 10.1016/j.neuroimage.2009.02.030. (http://www.sciencedirect.com/science/article/B6WNP-4VRP25C-4/2/8207b962a38aa83c822c6379bc43fe4c)

Proper citation: BRAINSConstellationDetector (RRID:SCR_012856) Copy   

•   Source: SciCrunch Registry

https://vpixx.com/products/viewpixx/

Research-grade, CRT-replacement LCD display system for vision science and psychophysics. It combines a 22.5″ 1920×1200 industrial LCD (wide 176°/176° viewing angles) with a custom panel/video controller engineered for deterministic stimulus timing and synchronized acquisition. The display supports 12-bit intensity resolution per RGB channel via custom video modes. It uses a scanning RGB LED backlight to improve temporal precision (e.g., crisp frame transitions and reduced motion artifacts) while bypassing consumer “enhancement” processing to keep output predictable for experiments. VIEWPixx also integrates microsecond-synchronized peripherals commonly needed in timing-sensitive paradigms—24-channel TTL I/O (triggers), stereo audio I/O, analog I/O, and a button-box interface—implemented on the same board as the video pipeline for tight hardware-to-video synchronization.

Proper citation: VPixx: VIEWPixx (RRID:SCR_013271) Copy   

•   Source: SciCrunch Registry

https://vpixx.com/hardware/projector/

Unique DLP LED projector which has been designed to be the most flexible display solution for vision research and neuroscience research. The PROPixx features a native resolution of 1920 x 1080, and can be driven with refresh rate up to 500Hz with deterministic timing. The PROPixx uses high brightness LEDs as a light source, giving a wide colour gamut and much longer lifetime than halogen light sources. It features high-bit depth, up to 12-bit per color for high-frequency full colour stimulation. For stereo vision applications, our high-speed ferro-electric circular polarizer can project stereoscopic stimuli with the use of passive glasses at up to 400Hz. In addition the PROPixx includes an array of peripherals which often need to be synchronized to video during an experiment, and with perfect microsecond precision.

Proper citation: VPixx: PROPixx (RRID:SCR_013299) Copy   

•   Source: SciCrunch Registry

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

The FP-CIT SPECT brain template has been created using a fully automatic procedure involving posterization of the source image to three levels: background, brain and striatum. We performed a spatial affine registration of these 40 posterized source images to a posterized reference image in the MNI space. The intensity values of the transformed images is normalized linearly, assuming that the histogram of the intensity values follows an alpha-stable distribution. Lastly, we built the [123I]FP-CIT SPECT template by the mean of the transformed and normalized images. More info: 1) Salas-Gonzalez et al. Building a FP-CIT SPECT brain template using a posterization approach. Accepted in Neuroinformatics. 2) Salas-Gonzalez et al. Linear intensity normalization of FP-CIT SPECT brain images using the alpha-stable distribution. NeuroImage, Volume 65, 2013, pp. 449-455. http://dx.doi.org/10.1016/j.neuroimage.2...

Proper citation: FP-CIT SPECT brain template in MNI space (RRID:SCR_013668) Copy   

•   Source: SciCrunch Registry

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

A toolbox that implements several EEG/MEG source localization techniques within the Maximum Entropy on the Mean (MEM) framework. These methods are particularly dedicated to estimate accurately the source of EEG/MEG generators together with their spatial extent along the cortical surface.

Proper citation: Brain Entropy in space and time (BEst) (RRID:SCR_014090) Copy   

•   Source: SciCrunch Registry

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

Brainnetome Atlas Viewer shows the anatomical connectivity-based parcellation results, including the maximum probabilistic maps, probabilistic maps and both the anatomical and functional connectivity patterns, which have been developed in Brainnetome Center, CASIA. The atlas is based on the analysis of connectional architecture with in vivo multi-modal MRI data.

Proper citation: Brainnetome Atlas Viewer (RRID:SCR_014091) Copy   

•   Source: SciCrunch Registry

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

A fast, scalable tool developed at the Johns Hopkins University to automatically segment the major anatomical fiber tracts within the human brain from clinical quality diffusion tensor MR imaging. With an atlas-based Markov Random Field representation, DOTS directly estimates the tract probabilities, bypassing tractography and associated issues. Overlapping and crossing fibers are modeled and DOTS can also handle white matter lesions. DOTS is released as a plug-in for the MIPAV software package and as a module for the JIST pipeline environment. They are therefore cross-platform and compatible with a wide variety of file formats.

Proper citation: DOTS WM tract segmentation (RRID:SCR_009459) Copy   

•   Source: SciCrunch Registry

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

A web enabled data and workflow management system extended from the HID codebase on NITRC specialized for Arterial Spin Labeling data management and analysis (including group analysis) in a centralized manner.

Proper citation: Cerebral Blood Flow Database and Analysis Pipeline (RRID:SCR_009454) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/c8c8/

A small, stand-alone MatLab toolbox that measures sagittal cross-section thickness and area of the human corpus callosum from high-resolution T1 in vivo MR images. C8 takes as input affine normalized white matter segmentations derived from high-resolution (in-plane) T1 images and outputs both regional callosal thicknesses in three different formats and geometrically-defined regional areas in three different configurations. It is a small package that is easily configurable and modifiable and it measures callosa at the rate of several per minute.

Proper citation: C8: Corpus Callosum Computations (RRID:SCR_009449) Copy   

•   Source: SciCrunch Registry

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

A tutorial that took place as part of MICCAI 2010 is the 13th International Conference on Medical Image Computing and Computer Assisted Intervention, September 20-24, 2010 in Beijing, China. See http://www.miccai2010.org/ This project supporedt community outreach and dialog between presenters and audience, both before and after the tutorial session, and is intended to engage the broader community in the deliberations on this important topic. ''Best Practices'' covered software engineering practices as well end-user installation and support practices.

Proper citation: Best Practices for Software Development (RRID:SCR_009441) Copy   

•   Source: SciCrunch Registry

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

Software toolkit developed for the fbrain project that consists of several image processing tools: image reconstruction, image denoising, image segmentation, tractography etc., for a better understanding of fetal brain development.

Proper citation: Baby Brain Toolkit (RRID:SCR_009440) Copy   

•   Source: SciCrunch Registry