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

An fMRI toolkit which contains a large selection of complex network measures in Matlab GUI. These measures are increasingly used to characterize structural and functional brain connectivity datasets.

Proper citation: Brainnetome fMRI toolkit (RRID:SCR_014092) Copy   

•   Source: SciCrunch Registry

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

A Matlab toolbox that allows computation of task-related functional connectivity between multiple pairs of regions. Task-related functional connectivity is computed using the correlational psychophysiological interaction (cPPI) methodology described in Fornito et al. (2012) PNAS, 109: 12788-12793. The toolbox assumes that first-level design matrices have been specified and estimated using SPM5 or later. It takes as input these design matrices as well as user-extracted regional time courses and returns a matrix of pair-wise, task-related functional connectivity for each participant. The method is scalable to large networks comprising hundreds of regions and is well-suited to graph theoretic analyses and functional connectomics. One modifiable script, cPPI_master.m, can be used to run the analysis for an entire sample of participants.

Proper citation: cPPI Toolbox for fMRI (RRID:SCR_009518) Copy   

•   Source: SciCrunch Registry

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

A reference for modifications, extensions, and utilities for the FMRIB Software Library (FSL).

Proper citation: FSL extensions (RRID:SCR_009472) Copy   

•   Source: SciCrunch Registry

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

A MATLAB toolbox for denoising task-based fMRI data. It derives noise regressors from voxels unrelated to the experimental paradigm and uses these regressors in a general linear model (GLM) analysis of the data. The technique only requires a design matrix indicating the experimental design and an fMRI dataset.

Proper citation: GLMdenoise: a fast, automated technique for denoising task-based fMRI data (RRID:SCR_014116) Copy   

•   Source: SciCrunch Registry

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

A software tool (with GUI) for investigating inter-regional functional connectivity in event-related fMRI data and allows the user to assess the modulation of functional connectivity by an experimental condition.

Proper citation: BetA-Series COrrelation (RRID:SCR_014086) Copy   

•   Source: SciCrunch Registry

http://www.uzh.ch/keyinst/loreta

Software package for functional imaging of human brain. Used to compute three dimensional distribution of electric neuronal activity from non-invasive measurements of scalp electric potential differences with high time resolution in millisecond range. Non-invasive intracranial time series are used for studying functional dynamic connectivity.. Current software version includes two new, improved variants of the original method: standardized (sLORETA) and exact (eLORETA). The new methods are characterized by exact localization when tested with point sources. Due to the fact that these methods are multivariate tomographies that are solutions to the inverse EEG problem, and that they are linear in nature, they will produce a low spatial resolution image for any distribution of activity. This property is not shared by naive one-at-a-time single dipole techniques.

Proper citation: Low Resolution Electromagnetic Tomography (RRID:SCR_007077) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/gig-ica/

Software toolbox for group-information guided Independent Component Analysis (ICA). In GIG-ICA, group information captured by standard Independent Component Analysis (ICA) on the group level is used as guidance to compute individual subject specific Independent Components (ICs) using a multi-objective optimization strategy. For computing subject specific ICs, GIG-ICA is applicable to subjects that are involved or not involved in the computation of the group information. Besides the group ICs, group information captured from other imaging modalities and meta analysis could be used as the guidance in GIG-ICA too.

Proper citation: Group Information Guided ICA (RRID:SCR_009491) Copy   

•   Source: SciCrunch Registry

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

A comprehensive and open-source library of analysis tools for multi-parametric MRI of the spinal cord. The toolbox includes a template and several atlases, along with state-of-the-art methods to register any data to the template. It also includes useful scripts for data preprocessing: extraction of centerline, automatic segmentation, slice-wise motion correction, etc.

Proper citation: Spinal Cord Toolbox (RRID:SCR_014170) Copy   

•   Source: SciCrunch Registry

http://caid.cs.uga.edu/?name=software

A software toolbox to predict 358 DICCCOL landmarks (Dense Individualized and Common Connectivity-based Cortical landmarks (http://dicccol.cs.uga.edu) ) on a new brain given b0, brain surface data and DTI derived fiber data (vtk format). Each DICCCOL landmark is defined by group-wise consistent white-matter fiber connection patterns derived from diffusion tensor imaging (DTI) data. DICCCOL aims to provide large-scale cortical landmarks with finer granularity, better functional homogeneity, more accurate functional localization, and automatically-established cross-subjects correspondence.

Proper citation: DICCCOL predictor (RRID:SCR_009554) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/cudasphere/

A CUDA C based toolkit which provides a GPU based implementation of the spherical model forward solution for the 306 channel Elekta Neuromag MEG system and the EEG. The 1-Sphere forward solution for the MEG and the 4-Sphere forward solution for the EEG is implemented in CUDA C and an accelerated solution is obtained using the NVIDIA GPU when the solution is calculated for a large number of dipoles (on the order of 15000 and above) and sensor location. Speedup by a factor of 22 and 32 is obtained for the EEG and MEG solution respectively when compared to the fastest CPU implementation available in the public domain. The complete source code and pre-compiled binaries are also made available via an open source license (GPL Version 3). A CUDA enabled NVIDIA graphics card is required to use the software.

Proper citation: CUDA-SPHERE-FWD-MEEG (RRID:SCR_013225) Copy   

•   Source: SciCrunch Registry

http://www.calatk.org/

An open-source toolkit for cross-sectional and longitudinal atlas building. The CalaTK project develops innovative methods and tools for longitudinal atlases with a focus on neurodevelopment. The computational toolbox is developed with the objective to analyze the neural developmental patterns observed in human and non-human primate structural and diffusion tensor magnetic resonance (MR) images.

Proper citation: CalaTK (RRID:SCR_009547) Copy   

•   Source: SciCrunch Registry

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

A multi-day event hosted by the Organization for Human Brain Mapping which features collaborative and open neuroscience projects in data analysis and methods development. Locations change annually.

Proper citation: HBM Hackathon (RRID:SCR_014119) Copy   

•   Source: SciCrunch Registry

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

An international symposium held initially to assess the new technology and innovation in the various established fields of genetics and imaging, and to facilitate the transdisciplinary fusion needed to optimize the development of the emerging field of Imaging Genetics. This annual conference features presentations from investigators world-wide and places emphasis on facilitating in-depth discussions among the participants and presenters.

Proper citation: International Imaging Genetics Conference (RRID:SCR_014125) Copy   

•   Source: SciCrunch Registry

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

An on-line tutorial on how to use MATLAB for Diffusion-Weighted MRI processing. The following subjects are covered in this tutorial: Generation of Synthetic Diffusion-Weighted MRI datasets, Diffusion Tensor (DTI) Estimation from DW-MRI, DTI Visualization as a field of ellipsoids, Higher-order Diffusion Tensor Estimation from DW-MRI, Computing of Tensor Orientation Distribution Functions (Tensor ODF), Computing of Fiber Orientations, Higher-order Diffusion Tensor Image Visualization as fields of spherical functions, Multi-fiber reconstruction etc. The tutorial contains numerous illustrations, figures and Matlab scripts embedded in the text. The reader/user can automatically generate Matlab script for a self-designed DW-MRI experiment by selecting which steps needs to be followed. The code that corresponds to the selected steps is then appropriately merged in the Matlab Script Generator, and the user can easily copy and paste the produced code directly to the Matlab command prompt.

Proper citation: MATLAB Tutorial on Diffusion Tensor MRI (RRID:SCR_009507) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/maps4mipav/

The exploratory development tree of Java Image Science Toolkit (JIST), an extension to the MIPAV (Medical Image Processing, Analysis, and Visualization) plug-in framework that allows the user to design and execute pipelines, which are multi-stage processing tasks.. New features and designs are tested here before general release into the JIST project. JIST was formerly known as the MedIC Automated Pipeline Scheduler (MAPS).

Proper citation: Maps4Mipav (Exploratory JIST) (RRID:SCR_000613) Copy   

•   Source: SciCrunch Registry

http://www.nirx.net

Commercial technology solutions for NIRS neuroscience imaging applications.

Proper citation: NIRx NIRS Neuroimaging (RRID:SCR_002491) Copy   

•   Source: SciCrunch Registry

http://biodev.ece.ucsb.edu/projects/bisquik/wiki

A scalable web-based system for biological image analysis, management and exploration. The Bisque system incorporates many features useful to imaging researchers from image capture to extensible image analysis and querying. At the core, bisque maintains a flexible database of images and experimental metadata. Image analyses can be incorporated into the system and deployed on clusters and desktops. Search and comparison of datasets by image data and content is supported. Novel semantic analyses are integrated into the system allowing high level semantic queries and comparison of image content. New features and testing of Bisque version: 0.5.1, among many others are: # Parallel execution of datasets # Rich interfaces for autogenerated module UI # Abstracted storage system for local, irods, etc.. They are using Mercurial for their source control system. This should be installed before proceeding. Browse source on-line, http://biodev.ece.ucsb.edu/projects/bisquik/browser Bisque Installation, http://biodev.ece.ucsb.edu/projects/bisquik/wiki/InstallationInstructions05 Bisque DOWNLOAD, http://biodev.ece.ucsb.edu/projects/bisquik/wiki/download, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Bisque (RRID:SCR_005564) Copy   

•   Source: SciCrunch Registry

http://www.hitachi-medical.co.jp/english/

An instrumental supplier which provides researchers and clinicians with sophisticated All-in-One solutions in the field of neuroscience.

Proper citation: Hitachi Optical Topography System (RRID:SCR_000865) Copy   

•   Source: SciCrunch Registry

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

Graphical user interface that has been implemented as a 3D Slicer plugin (scripted module). It serves to display a corresponding set of cortical regions from functional connectivity matrix in an explorable 3D scene that represents brain anatomical environment. In addition to grey matter regions, MultiXplore automatically finds and extracts deterministic fiber bundles which exist between selected region(s) and adds them to the 3D environment. This feature helps in generating region-based fiber bundles given a desired whole-brain tractography data.

Proper citation: MultiXplore (RRID:SCR_014814) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/projects/atpp

Integrated pipeline for tractography-based brain parcellation with automatic processing and massive parallel computing. ATPP offers a CLI version for parcellating multiple brain regions and a GUI version for parcellating a specific brain region. " ATPP completely follows the scientific cultural shift to open science, which aims at making scientific research including journal papers, lab notes, data, and, of course, workflow tools, accessible and transparent to all levels of society. ATPP is publicly accessible in Neuroimaging Informatics Tools and Resources Clearinghouse8 (NITRC) (https://www.nitrc.org/projects/atpp). Its source codes are hosted in GitHub9 (https://github.com/haililihai/ATPP_CLI; https://github.com/haililihai/ATPP_GUI), under the GNU generic purpose license version 310 (GPLv3), and are welcome to download and fork. The Digital Object Identifiers (DOIs) providing a persistent way to make digital data easily and uniquely citable was created from Zenodo11 platform with those GitHub repositories (ATPP CLI v2.0.0, doi: https://doi.org/10.5281/zenodo.239702; ATPP GUI v2.0.0, doi: https://doi.org/10.5281/zenodo.239705). "

Proper citation: Automatic Tractography-based Parcellation Pipeline (RRID:SCR_014815) Copy   

•   Source: SciCrunch Registry