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https://compumedicsneuroscan.com/products/by-name/curry/

Processing software for multimodal neuroimaging centered on combining functional data such as EEG and MEG with imaging data from MRI and CT to optimize source reconstruction. They are now combining Curry's strength with the acquisition and signal processing features of the SCAN software for a comprehensive EEG acquisition, data analysis, source localization and source imaging package.

Proper citation: CURRY (RRID:SCR_009546) Copy   

•   Source: SciCrunch Registry

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

A tool that implements a graph-based connectivity assessment method. This method uses a multi-directional graph propagation method applied to sampled orientation distribution function (ODF), which can be computed directly from the original diffusion imaging data.

Proper citation: COST (RRID:SCR_014098) Copy   

•   Source: SciCrunch Registry

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

A software package written in OpenCL (Open Computing Language) that can be used for parallel analysis of fMRI data on a large variety of hardware configurations. If BROCCOLI is running on a GPU, it can perform non-linear spatial normalization to a 1 mm brain template in 4-6 s and run a second level permutation test with 10,000 permutations.

Proper citation: BROCCOLI (RRID:SCR_014093) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/afni_3dsvm/

A command-line program and plugin for AFNI built around SVM-Light. It performs support vector machine (SVM) analysis on fMRI data and runs on Unix+X11+Motif systems, including SGI, Solaris, Linux, and Mac OS X.

Proper citation: 3dsvm (RRID:SCR_014083) Copy   

•   Source: SciCrunch Registry

http://www.softpedia.com/get/Science-CAD/BrainCSI.shtml

A tool for analysis of Magnetic Resonance Spectroscopy (MRS) data by registering it to anatomical images. BrainCSI imports LCModel results to calculate absolute metabolite concentrations using tissue water. Corrections to LCModel metabolite concentrations for partial volume of tissues are accomplished by tissue classification of the anatomical images.

Proper citation: BrainCSI (RRID:SCR_013244) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/ntu-dsi-122/

A diffusion spectrum imaging (DSI) template constructed in the standard ICBM-152 space from 122 healthy adults. The template was built through incorporating the macroscopic anatomical information using high-resolution T1-weighted images and the microscopic structural information obtained from DSI datasets, rendering it to achieve a high anatomical matching to the ICBM-152 space. This template can serve as a representative DSI dataset for a healthy adult population. It is released in its original DWI format.

Proper citation: NTU-DSI-122: a DSI template in ICBM-152 space (RRID:SCR_014155) Copy   

•   Source: SciCrunch Registry

http://www.cis.hut.fi/projects/ica/fastica/

General-purpose unsupervised data-analysis tool, most often used for brain imaging data.

Proper citation: FastICA (RRID:SCR_013110) Copy   

•   Source: SciCrunch Registry

https://github.com/NIRALUser/DTIAtlasBuilder

This tool creates an Atlas image as an average of several DTI images that will be registered. The registration will be done in two steps : - Affine Registration with BRAINSFit - Non Linear Registration with GreedyAtlas A final step will apply the transformations to the original DTI images so that the final average can be computed. The main function writes a python script that will be executed to compute the Atlas. By running DTIAtlasBuilder, you will need to fill in informations in a Graphical User Interface, and then compute the Atlas. You can also run the tool in command line without using the GUI. Using the GUI, you will be able to save or load a dataset file or a parameter file. The tool needs these other tools to work, so be sure to have these installed on your computer: - ImageMath - ResampleDTIlogEuclidean - CropDTI - dtiprocess - BRAINSFit - GreedyAtlas - dtiaverage - DTI-Reg - unu - MriWatcher If you download the package, be sure to have the glut library installed.

Proper citation: DTI Atlas Builder (RRID:SCR_013112) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/r2r_prf/

Software tool as a framework for fitting and describing connectivity patterns between regions that is a simple extension from the current population receptive field models in the visual neuroscience literature. The connectivity from each voxel in a designated seed region to a mapping region is modeled as a 3-dimensional Gaussian, providing location parameters and spread parameters. This allows the direct description of the relative mapping from one region to another.

Proper citation: Region to Region (RRID:SCR_016995) Copy   

•   Source: SciCrunch Registry

https://github.com/nipy/heudiconv

Software tool as flexible DICOM converter for organizing brain imaging data into structured directory layouts.

Proper citation: HeuDiConv: a heuristic-centric DICOM converter (RRID:SCR_017427) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/cmind_2014/

A database that contains brain imaging data collected on 3T MRI scanners from over 200 normally developing healthy children from birth to 18 years. The imaging data stored in the C-MIND database are DTI, HARDI, 3DT1W, 3DT2W, concurrent ASL-BOLD scans during two language tasks (Stories and Sentence-Picture Matching), Resting State fMRI and Baseline ASL scans.

Proper citation: C-MIND Database (RRID:SCR_014094) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/whs-sd-atlas/

Open access volumetric atlas of anatomical delineations of rat brain based on structural contrast in isotropic magnetic resonance and diffusion tensor images acquired ex vivo from 80 day old male Sprague Dawley rat at Duke Center for In Vivo Microscopy. Spatial reference is provided by Waxholm Space coordinate system. Location of bregma and lambda are identified as anchors towards stereotaxic space. Application areas include localization of signal in non structural images. Atlas, MRI and DTI volumes, and diffusion tensor data are shared in NIfTI format.

Proper citation: Waxholm Space Atlas of the Sprague Dawley Rat Brain (RRID:SCR_017124) Copy   

•   Source: SciCrunch Registry

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

Data collected from subjects scanned 3 times (V1, V2, V3), with V1 and V2 on a scanner, V3 on another scanner in another site. Resting state blood oxygenation level dependent functional MRI (BOLD fMRI), pseudo continuous arterial spin labeling (pCASL), and high resolution 3D T1 imaging were performed under eyes open (EO) and eyes closed (EC) conditions.

Proper citation: Intra- and inter-scanner reliability of RS-fMRI BOLD and ASL with eyes closed vs. eyes open (RRID:SCR_016935) Copy   

•   Source: SciCrunch Registry

https://github.com/BRAINSia/BRAINSTools

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 23,2023. A suite of tools to generate the cortical surface of the brain. The surface is generated in the middle of grey matter and can be used to measure surface features including cortical depth and curvature.

Proper citation: BRAINSCortex (RRID:SCR_001082) Copy   

•   Source: SciCrunch Registry

http://free-d.versailles.inra.fr/html/freed.html

Free-D allows the reconstruction of 3D models from image stacks (segmentation, registration, surface reconstruction, 3D rendering). It is designed in the goal of non-linear spatial normalization and averaging of collections of individual 3D models (this module is currently in alpha version only and not included in the distributed version)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Free-D (RRID:SCR_009578) Copy   

•   Source: SciCrunch Registry

http://musc.edu/cbi/dki

A software tool for post-processing diffusional kurtosis imaging (DKI) datasets. DKE consists of a suite of command-line programs along with a graphical user interface (GUI). DKE is currently supported on 32- and 64-bit Windows platforms. Given a set of diffusion-weighted images acquired following a valid DKI protocol, DKE generates a set of kurtosis (axial, mean, radial) parametric maps. DKE also generates diffusivity (axial, mean, radial) and fractional anisotropy maps using both DKI and diffusion tensor imaging signal models. DKE features include: DICOM and NIfTI format support, interactive (GUI) as well as batch mode (command-line) processing, and rigid-body motion correction. DKE implements the methods described in the following paper: Tabesh A, Jensen JH, Ardekani BA, and Helpern JA. Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging. Mag Reson Med. 2011 Mar;65(3):823-36. http://www.ncbi.nlm.nih.gov/pubmed/21337412

Proper citation: Diffusional Kurtosis Estimator (RRID:SCR_009563) 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://neurospaces.sourceforge.net/

The GEneral NEural SImulation System (GENESIS) started as a very advanced software package in the late eighties, for biologically accurate neuronal modeling. Besides being used as a neuronal simulator, it was also applied to various domains outside computational neuroscience. The Neurospaces project is a departure from the monolithic software system design of the original GENESIS system. It is a development center for software components of computational neuroscience simulators. There are many advantages of developing independent software components: - Interfacing to an individual component is obviously more simple than interfacing to a do-all monolithic system. The compartmental solver developed for the Neurospaces project can be connected to Matlab fi. - It simplifies the individual components and encourages other developers to get involved. - It allows for separate testing of the components. More than 1000 use case tests been defined for these software components, including integration tests. - Integrating different component, gives different flavours of the same simulator, and enhances the user experienced consistency when doing multilevel simulations. - A component based software system avoids vendor-lockin. Its life-cycle is more smooth than that of a monolithic system, because software components can be upgraded one at a time. The Neurospaces project embodies many software components that all have been developed in full isolation. The core of the most important components is finished. The current development focus has shifted from component integration to the support of specific use case with an emphasis on single neuron modeling. This is a list of software components that have been developed or are under construction. Together, these tools give the core for the upcoming GENESIS 3 GUI. - GShell: a simple replacement for the Genesis 2 SLI. - Heccer: a fast compartmental solver, a backend. - Dash: a second compartmental solver faster than Heccer, for simpler models. - Neurospaces Model Container: provides a solver independent internal and external storage format for models. - Discrete event system: consists of a discrete event distributor and queuer. This is used for abstract modeling of an action potential traveling inside an axon as a ''discrete event''. - SSP: a flexible scheduler written in perl, to run simulations with the Neurospaces model container and Heccer. - The Neurospaces Studio: some tools for graphical browsing and command line usage. - The Genesis Script Language Interface: a scripting component that reads Genesis 2 scripts and feeds them to the Neurospaces model container. - The Geometry Library is a general purpose geometry library, with some essential geometrical operators, not commonly found in other geometrical libraries. - Using the Geometry Library, a Reconstruct Interface has been written. This interface supports the conversion of contours exported by the Reconstruct software to the Neurospaces declarative NDF format. - The Neurospaces project browser for browsing projects and inspecting simulation results. - The Installer package contains the Neurospaces installer and developer tools that have emerged from developing Neurospaces software components. - The Configurator package contains configuration utilities for the other tools. It is not needed for the other tools to work properly. Rather, it allows to set up model database and simulation servers in a convenient way. - There is also a Neurospaces blog and a wiki at googlecode for the Neurospaces project, with information for developers.

Proper citation: GEneral NEural SImulation System: The Neurospaces Project (RRID:SCR_008035) Copy   

•   Source: SciCrunch Registry

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

A GPU-accelerated library for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail. CARLsim allows execution of networks of Izhikevich spiking neurons with realistic synaptic dynamics on both generic x86 CPUs and standard off-the-shelf GPUs. The simulator provides a PyNN-like programming interface in C/C++, which allows for details and parameters to be specified at the synapse, neuron, and network level.

Proper citation: CARLsim: a GPU-accelerated SNN Simulator (RRID:SCR_014095) Copy   

•   Source: SciCrunch Registry

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

A Matlab-based tool for computational neuroscience-based analysis and data visualization. Its features include: surface mesh visualization in PLY, PIAL, NV, STL,VTK, and GIFTI formats; conversion of NIfTI voxel images to surface meshes and saving as PLY or VTK; track (TRK files) visualization; connectome data (BrainNet Viewer .node and .edge files) visualization; intuitive GUI; that availability of all functions available in the GUI through scripting (automated scripts can be created); and exporting of rendered image as bitmap.

Proper citation: MRIcroS (RRID:SCR_014142) Copy   

•   Source: SciCrunch Registry