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http://www.humanconnectomeproject.org/

A multi-center project comprising two distinct consortia (Mass. Gen. Hosp. and USC; and Wash. U. and the U. of Minn.) seeking to map white matter fiber pathways in the human brain using leading edge neuroimaging methods, genomics, architectonics, mathematical approaches, informatics, and interactive visualization. The mapping of the complete structural and functional neural connections in vivo within and across individuals provides unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve conclusions about the living human brain. The HCP is being developed to employ advanced neuroimaging methods, and to construct an extensive informatics infrastructure to link these data and connectivity models to detailed phenomic and genomic data, building upon existing multidisciplinary and collaborative efforts currently underway. Working with other HCP partners based at Washington University in St. Louis they will provide rich data, essential imaging protocols, and sophisticated connectivity analysis tools for the neuroscience community. This project is working to achieve the following: 1) develop sophisticated tools to process high-angular diffusion (HARDI) and diffusion spectrum imaging (DSI) from normal individuals to provide the foundation for the detailed mapping of the human connectome; 2) optimize advanced high-field imaging technologies and neurocognitive tests to map the human connectome; 3) collect connectomic, behavioral, and genotype data using optimized methods in a representative sample of normal subjects; 4) design and deploy a robust, web-based informatics infrastructure, 5) develop and disseminate data acquisition and analysis, educational, and training outreach materials.

Proper citation: MGH-USC Human Connectome Project (RRID:SCR_003490) Copy   

•   Source: SciCrunch Registry

http://neuromorpho.org/index.jsp

Centrally curated inventory of digitally reconstructed neurons associated with peer-reviewed publications that contains some of the most complete axonal arborizations digitally available in the community. Each neuron is represented by a unique identifier, general information (metadata), the original and standardized ASCII files of the digital morphological reconstruction, and a set of morphometric features. It contains contributions from over 100 laboratories worldwide and is continuously updated as new morphological reconstructions are collected, published, and shared. Users may browse by species, brain region, cell type or lab name. Users can also download morphological reconstructions for research and analysis. Deposition and distribution of reconstruction files ultimately prevents data loss. Centralized curation and annotation aims at minimizing the effort required by data owners while ensuring a unified format. It also provides a one-stop entry point for all available reconstructions, thus maximizing data visibility and impact.

Proper citation: NeuroMorpho.Org (RRID:SCR_002145) Copy   

•   Source: SciCrunch Registry

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

Based on JIST and MIPAV, this pipeline combines structural magnetic resonance data with diffusion tensor imaging to estimate a connectome, which is a comprehensive description of the wiring diagram of the brain.

Proper citation: MR Connectome Automated Pipeline (RRID:SCR_002252) Copy   

•   Source: SciCrunch Registry

http://www.incf.org/

Independent international facilitator catalyzing and coordinating global development of neuroinformatics aiming to advance data reuse and reproducibility in global brain research. Integrates and analyzes diverse data across scales, techniques, and species to understand brain function and positively impact the health and well being of society.

Proper citation: International Neuroinformatics Coordinating Facility (RRID:SCR_002282) Copy   

•   Source: SciCrunch Registry

http://cogpo.org

Ontology used to describe the experimental conditions within cognitive and behavioral experiments, primarily in humans for application and use in the functional neuroimaging community. CogPO has been developed through the integration of the Functional Imaging Biomedical Informatics Research Network (FBIRN) Human Imaging Database (HID) and the BrainMap Database. The design of CogPO concentrates on what can be observed directly: categorization of each paradigm in terms of (1) the stimulus presented to the subjects, (2) the requested instructions, and (3) the returned response.

Proper citation: Cognitive Paradigm Ontology (RRID:SCR_002235) Copy   

•   Source: SciCrunch Registry

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

An EEGLAB plugin which adaptively estimates and removes sinusoidal artifacts from independent component analysis (ICA) components or scalp channels using a frequency-domain (multi-taper) regression technique with a Thompson F-statistic for identifying significant sinusoidal artifacts. This approach has been advocated by Partha Mitra and Hemant Bokil (Observed Brain Dynamics, Chapter 7.3.4., 2007) and CleanLine utilizes modified routines from the Mitra Lab's Chronux Toolbox (www.chronux.org). Sinusoidal noise can be a prominent artifact in recorded electrophysiological data. This can stem from AC power line fluctuations (e.g. 50/60 Hz line noise + harmonics), power suppliers (e.g. in medical equipment), fluorescent lights, etc. Notch filtering is generally undesirable due to creation of band-holes, and significant distortion of frequencies around the notch frequency (as well as phase distortion at other frequencies and Gibbs rippling in the time-domain).

Proper citation: CleanLine (RRID:SCR_002233) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/niak/

Software library of modules and pipelines for fMRI processing with Octave or Matlab(r) that can run in parallel either locally or in a supercomputing environment. Linux OS and MINC file format are supported. NIAK currently includes a preprocessing, a region growing and a connectome pipelines. NIAK features powerful pipeline management capabilities, including parallel computing, generation of detailed logs and automatic handling of pipeline failures or updates.

Proper citation: NeuroImaging Analysis Kit (NIAK) (RRID:SCR_002497) Copy   

•   Source: SciCrunch Registry

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

Software tool that provides a convenient environment to simulate NMR diffusion in closed pores. It builds on the eigenfunction expansion of the magnetization.

Proper citation: Multiple Correlation Function Tool (RRID:SCR_002321) Copy   

•   Source: SciCrunch Registry

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

A powerful and modular medical image viewer/editor. It should be particularly useful to Undergraduates, Postdocs and Researchers in Medical Imaging to visualize data and to easily make attractive figures (for papers or presentations). It will also in a near future offer a number of advanced algorithms for medical image processing. Look at the video to get an idea ! http://www.benoitscherrer.com/MisterI/videos.html

Proper citation: MisterI (RRID:SCR_002317) Copy   

•   Source: SciCrunch Registry

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

A Matlab-based software library to perform independent component analysis on group white matter skeleton generated by FSL TBSS. The script produces stable estimates of the white matter tract or tract segments that resemble highly correlated variation profiles across a group of subjects.

Proper citation: Microstructural correlation toolbox (RRID:SCR_002316) Copy   

•   Source: SciCrunch Registry

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

Software toolkit that provides the following libraries and functions on linux platform: # Multi-resolution registration of MR images include T1, multimodality, and DTI images. # The registration model is B-spline, and users can custermize their own image similarity measures by writing a plugin function and recompile the program.

Proper citation: MIAS Registration Toolkit (RRID:SCR_002312) Copy   

•   Source: SciCrunch Registry

http://www.pstnet.com/hardware.cfm?ID=92

MRI Simulator that provides a realistic approximation of an actual MRI scanner to allow habituation and training of participants in an environment less daunting than a real scanner. Special populations such as children, the elderly, and psychiatric patients, are often prone to claustrophobia and anxiety in the bore of a magnet, and consequently have a much higher rate of terminating the experiment or scan session before its completion. Some centers that have dealt with these populations estimate a 50%-80% failure rate. With the use of the MRI Simulator this failure rate can often be reduced below 5%, improving cost effectiveness.

Proper citation: PSTNet: MRI Simulator (RRID:SCR_002460) Copy   

•   Source: SciCrunch Registry

http://www.brain.org.au/software/

A collection of tools that generate numerical fiber structures with the complexity of human white matter and simulate Diffusion-Weighted MR images that would arise from them. Its primary use is to enable the testing of tracking algorithms

Proper citation: Numerical Fibre Generator (RRID:SCR_002457) Copy   

•   Source: SciCrunch Registry

http://sccn.ucsd.edu/wiki/NFT

A MATLAB Toolbox for generating realistic head models from available data (MRI and/or electrode locations), for computing numerical solutions for the forward problem of electromagnetic source imaging and for single dipole source localization. The NFT includes tools for segmenting scalp, skull, cerebrospinal fluid (CSF) and brain tissues from T1-weighted magnetic resonance (MR) images. The Boundary Element Method (BEM) and Finite Element Method (FEM) are used for the numerical solution of the forward problem. When a subject MR image is not available a template head model can be warped to measured electrode locations to obtain an individualized head model. Toolbox functions may be called either from a graphic user interface compatible with EEGLAB or from the MATLAB command line.

Proper citation: NFT (RRID:SCR_002450) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/ncanda-datacore/

Manuals, training materials, and computational tools developed by the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) Data Component. The NCANDA consortium consists of an Administrative Component at UC San Diego, the Data Integration Component at SRI International, and five data collection sites, Duke University, Oregon Health & Sciences University, SRI International, University of Pittsburgh, and UC San Diego. Each collection site will collect data from about 150 adolescents, each of them seen for one baseline and three annual follow-up visits.

Proper citation: NCANDA: Data Integration Component (RRID:SCR_002447) Copy   

•   Source: SciCrunch Registry

http://nipy.org/nipy

A complete Python environment for the analysis of structural and functional neuroimaging data. It currently has a full system for general linear modeling of functional magnetic resonance imaging (fMRI).

Proper citation: NIPY (RRID:SCR_002489) Copy   

•   Source: SciCrunch Registry

http://www.pstnet.com/hardware.cfm?ID=90

MRI Digital Projection System that uses Digital Light Processing (DLP) technology providing microsecond pixel rise times, outstanding contrast with all-digital fiber optic control that allows you to project crystal clear, sharp images. Includes: * High resolution (1024x768) DLP Projector with RF filtered enclosure, custom lens assembly, digital video (DVI) over fiber, high flow fans, internal thermal sensor * Control room device to perform DVI to Fiber conversion, remotely power down the projector, and allow use of projector remote control from control room * 30 meter fiber optic cable that runs between the projector and projector control station * Heavy duty, magnet compatible, projector stand (assembly required) * Heavy duty, magnet compatible mirror stand with mirror (assembly required) * High resolution, lenticular pitch rear projection screen for high quality image reproduction * Optional VGA to DVI converter (native DVI video cards on Windows or Macintosh recommended)

Proper citation: MRI Digital Projection System (RRID:SCR_002486) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/parser_4d/

A tool for analyzing 4D images with pathology. Originally developed for processing longitudinal images of patients with traumatic brain injury, the tool contains new image analysis algorithms that combine registration and segmentation in a coherent framework, accounting for extreme changes due to extensive tissue damage.

Proper citation: 4D-PARSeR Pathological Anatomy Regression via Segmentation and Registration (RRID:SCR_002480) Copy   

•   Source: SciCrunch Registry

http://mialab.mrn.org/software/eegift/index.html

Implements multiple algorithms for independent component analysis and blind source separation of group (and single subject) EEG data. This MATLAB toolbox is compatible with MATLAB 6.5 and higher.

Proper citation: Group ICA Of EEG Toolbox (RRID:SCR_002478) Copy   

•   Source: SciCrunch Registry

http://brainproducts.com/productdetails.php?id=17

Software to manage the daily work of analyzing various neurophysiological data. Features include a history tree, automated analysis, various data format readers, and more.

Proper citation: BrainVision Analyzer (RRID:SCR_002356) Copy   

•   Source: SciCrunch Registry