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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

https://hub.docker.com/r/kaczmarj/neurodocker/

Software tool to generate Dockerfiles and Singularity recipes for neuroimaging with simple command-line interface. Command line program that generates custom Dockerfiles and Singularity recipes for neuroimaging and minifies existing containers. Supports AFNI, ANTs, Convert3D, Dcm2niix, FreeSurfer, FSL, Matlab Compiler Runtime, MINC, Miniconda, MRtrix3, NeuroDebian, PETPVC, and SPM12.

Proper citation: Neurodocker (RRID:SCR_017426) Copy   

•   Source: SciCrunch Registry

http://www.psychopy.org

Open source application to allow the presentation of stimuli and collection of data for a wide range of neuroscience, psychology and psychophysics experiments. It is intended as a free, powerful alternative to Presentation or e-Prime.

Proper citation: PsychoPy (RRID:SCR_006571) 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.pymvpa.org

A Python package intended to ease statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run. Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. This Python-based, cross-platform, open-source software toolbox software toolbox for the application of classifier-based analysis techniques to fMRI datasets makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages.

Proper citation: PyMVPA (RRID:SCR_006099) Copy   

•   Source: SciCrunch Registry

http://www.ppmi-info.org/

An observational longitudinal clinical study partnership to identify and validate biomarkers of Parkinson disease (PD) progression and provide easy and open web-based access to the comprehensive set of correlated clinical data and biospecimens, information, and biosamples acquired from PD and age and gender matched healthy control subjects to the research community. The data and specimens have been collected in a standardized manner under strict protocols and includes clinical (demographic, motor and non-motor, cognitive and neurobehavioral), imaging (raw and processed MRI, SPECT and DAT), and blood chemistry and hematology subject assessments and biospecimen inventories (serum, plasma, whole blood, CSF, DNA, RNA and urine). All data are de-identified to protect patient privacy. PPMI will be carried out over five years at 21 clinical sites in the United States and Europe and requires the participation of 400 Parkinson's patients and 200 control participants. The PPMI database provides researchers with access to correlated clinical and imaging data, along with annotated biospecimens, all available within an open access system that encourages data sharing (http://www.ppmi-info.org/access-data-specimens/). The website hosts an Ongoing Analysis section to keep the scientific community apprised of analyses being completed, in hopes of stimulating collaborations between researchers who are using PPMI data and specimens.

Proper citation: Parkinson's Progression Markers Initiative (RRID:SCR_006431) Copy   

•   Source: SciCrunch Registry

http://www.megimaging.com/

A software program for source imaging Magnetoencephalographic data. Now MEG tools has added Imaged Coherence mapping, Talairach and MNI coordinates, Grainger Causality. MEG Tools also includes MR-FOCUSS, ECD, Beamformers and many other useful MEG tools. This is a Matlab-based software module that is used to image MEG data onto a patient's MRI. This software imports all MEG manufacture's data (4D-Neuroimaging/BTi, CTF and Neuromag/Elekta).

Proper citation: MEG Tools (RRID:SCR_000661) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/Debabeler

Software to manage the conversion of imaging data from one file format and convention to another. It consists of a graphical user interface to visually program the translations, and a data translation engine to read, sort and translate the input files, and write the output files to disk. The data translation engine: (1) Reads metadata from a set of image files on disk to identify the source that produced each file; (2) Groups the image files into user-defined collections using image metadata values; (3) Translates each image file collection by reading metadata and pixel data and mapping the data into the appropriate output file format through a programmable set of connected modules. The Debabeler uses the Java Image I/O Plugin Architecture to read and write a wide variety of common medical image file formats, including ANALYZE, MINC, and most variations of DICOM.

Proper citation: LONI Debabeler (RRID:SCR_001160) 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://software.incf.org/

Software repository that makes it easy for neuroscientists to find, use and share software tools. The Software Center is accessible to everyone: you can browse and download available software tools without registering. However, by creating an account, you will be able to post comments, and request to join development teams. The INCF Software Center and the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) are sharing content. Software tools hosted by NITRC also appear at the INCF Software Center. Your software tool will be available to all users of the Software Center. You will be able to upload documentation, executables and related files; track use of your software; create a wiki; and establish a development team. Registered Software Center users will be able to comment on and post reviews about your software, and can request to join your development team. INCF's vision of the Software Center is that it will become a communication enabler for software users as well as developers. Accordingly, future system features to be added include communication and collaboration functions. We also plan to include support services to allow software developers organize their software, track the use, and receive feedback for further improvement and development. Further development of the Software Center will be strongly driven by the user needs. Please let us know what features you would like to see added.

Proper citation: INCF Software Center (RRID:SCR_002347) Copy   

•   Source: SciCrunch Registry

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

Software repository of custom extensions to the GForge collaborative environment.

Proper citation: NITRC GForge Extensions (RRID:SCR_002495) Copy   

•   Source: SciCrunch Registry

http://labs.nri.ucsb.edu/reese/benjamin/SA3D.html

A user-friendly, graphical user interface (GUI) that allows statistical and visual manipulations of real and simulated three-dimensional spatial point patterns. The analyses use files containing sets of X, Y, Z coordinates. These point patterns are frequently coordinates of cells of specific cell classes within in volumes of tissue derived from microscopy analyses. The analyses are scale independent so spatial analyses of coordinates from larger and smaller scale distributions are possible. The software can also generate sample sets of X, Y, Z coordinates for program exploration and modeling purposes.

Proper citation: Spatial Analysis 3D (RRID:SCR_002563) Copy   

•   Source: SciCrunch Registry

http://www.cise.ufl.edu/~tichen/ShapeComplexAtlas.zip

A Matlab demo for constructing a neuro-anatomical shape complex atlas from 3D MRI brain structures, based on the paper Ting Chen, Anand Rangarajan, Stephan J. Eisenschenk and Baba C. Vemuri, Construction of a Neuroanatomical Shape Complex Atlas from 3D MRI Brain Structures. In NeuroImage, Volume 60, Page 1778-1787, 2012

Proper citation: ShapeComplexAtlas (RRID:SCR_002553) Copy   

•   Source: SciCrunch Registry

http://www.na-mic.org/Wiki/index.php/UNC_SPHARM-PDM_Tutorial

Software tool that computes point-based models using a parametric boundary description for the computing of Shape analysis. The point-based models computed with the SPHARM-PDM tool can be used in combination with the also UNC designed statistical tool shapeAnalysisMANCOVA to perform quantitative morphological assessment of structural changes at speci?c locations. Shape analysis has become of increasing interest to the medical community due to its potential to precisely locate morphological changes between healthy and pathological structures.

Proper citation: SPHARM-PDM Toolbox (RRID:SCR_002546) Copy   

•   Source: SciCrunch Registry

https://www.slicer.org/slicerWiki/index.php/Slicer4:VMTK

Provides series of modules which enable functions of Vascular Modeling Toolkit in 3D Slicer. Functionality includes vessel enhancement filtering, level set segmentation, centerline computation, network extraction and branch splitting.VMTK is available through the extension manager for 3D Slicer from version 4.6.2. Main difference to Slicer3 version is that now all VMTK modules come as one extension bundle. This should enhance the installation experience for users.

Proper citation: VMTK in 3D Slicer (RRID:SCR_002579) Copy   

•   Source: SciCrunch Registry

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

A stand-alone axecutable under all main Windows OS for training the working memory. The WM Trainer looks and behaves a little bit like a video-game and has been specifically conceived for children attending the primary school. However, it can be used purposefully by people of any age, including adult and elderly. This application features highest graphic quality, a powerful adaptive engine for the difficulty level, a database of users and statistical tools to evaluate the progress. Currently English, French and Italian are supported, but any language can be easily supported.

Proper citation: Working Memory Trainer (RRID:SCR_002617) Copy   

•   Source: SciCrunch Registry

http://scikit-learn.org/

scikit-learn: machine learning in Python

Proper citation: scikit-learn (RRID:SCR_002577) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/bctnet/comparison/nbs

Matlab toolbox for testing hypotheses about the human connectome. NBS has been widely used to identify connections and networks comprising the connectome that are associated with an experimental effect or a between-group difference. User provides a series of connectivity matrices from different cohorts, or from the same subject during different experimental conditions. Connectivity matrices are inferred from neuroimaging data using other packages that, for example, count the number of tractography streamlines that interconnect each pair of regions (diffusion-MRI), or measure the extent of inter-regional correlation in BOLD response (fMRI). User specifies hypothesis to be tested at every connection with the general linear model. Features include: graphical user interface; NBSview, a basic network viewer modeled on SPMresults; exchange blocks for repeated measures; options to measure network size with intensity or extent; false discovery rate (FDR) option. Developed by Zalesky, Fornito, Cocchi and Bullmore.

Proper citation: Network Based Statistic Toolbox (RRID:SCR_002454) Copy   

•   Source: SciCrunch Registry

http://nifti.nimh.nih.gov/

Coordinated and targeted service, training, and research to speed the development and enhance the utility of informatics tools related to neuroimaging. The initial focus will be on tools that are used in fMRI. If NIfTI proves useful in addressing informatics issues in the fMRI research community, it may be expanded to address similar issues in other areas of neuroimaging. Objectives of NIfTI * Enhancement of existing informatics tools used widely in neuroimaging research * Dissemination of neuroimaging informatics tools and information about them * Community-based approaches to solving common problems, such as lack of interoperability of tools and data * Unique training activities and research career development opportunities to those in the tool-user and tool-developer communities * Research and development of the next generation of neuroimaging informatics tools

Proper citation: Neuroimaging Informatics Technology Initiative (RRID:SCR_003141) Copy   

•   Source: SciCrunch Registry

http://www.pstnet.com/software.cfm?ID=94

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. NOTE: VR Worlds 2 is no longer available as a standalone software. Software application designed for the creation and execution of neurobehavioral studies. The VR Worlds 2 platform allows accurate, real-time data collection of the navigation and interactions within a simulated environment. You are free to design and perform custom or predefined experiments tailored to your personal research or clinical needs. Create complex environments with meaningful content using VR Worlds 2?s user-friendly, drag-and-drop interface. Include triggers to launch simple or intricate events, such as a conversation between characters or a customizable rating scale. VR Worlds 2 provides several realistic simulations to immerse your subjects in context appropriate environments, including: * Residential/Urban Area * Hotel Lobby * Medical Office * Grocery Store * Neighborhood for drug and alcohol cue extinction treatment (featured on GMA, motion capture process) * Casino for gambling addiction research (featured on Canadian Discovery Channel) * Driving simulation for mild cognitive impairment research * Phobia scenarios * Spatial navigation mazes

Proper citation: VR Worlds 2 (RRID:SCR_002608) Copy   

•   Source: SciCrunch Registry