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http://cibsr.stanford.edu/tools/human-brain-project/artrepair-software.html

A toolbox for SPM to improve fMRI analysis of high motion pediatric and clinical subjects. The toolbox includes special algorithms for motion adjustment, data repair, and noise filtering, and methods to find outlier subjects in group studies. Visualization tools are included for quality checking the data, including a movie format for viewing all data and all contrast estimates on every voxel of every subject. Methods are included to quantify results into percent signal change. * Operating System: OS Independent * Programming Language: MATLAB * Supported Data Format: ANALYZE, NIfTI-1 * execution requires: SPM

Proper citation: ArtRepair for robust fMRI (RRID:SCR_005990) 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   

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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   

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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   

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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   

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

A statistical analysis tool for manifold-valued data. The SPD manifold for diffusion tensor images (DTI) and the Hilbert unit sphere for square root representation of orientation distribution functions (ODF) can be used.

Proper citation: Multivariate General Linear Models (MGLM) on Riemannian Manifolds (RRID:SCR_014143) Copy   

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

Software Matlab toolbox for directed functional connectivity analysis of fMRI BOLD signal from predefined regions of interest. It recovers true structure of connections and estimates weights attributed to each connection. Obtains patterns at group and individual levels.

Proper citation: GIMME (RRID:SCR_014115) Copy   

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

A set of many useful automation scripts to facilitate the neuroimaging data analysis process. It contains BASH scripts for MRI data management, FSL automation and web application.

Proper citation: XFSL: An FSL toolbox (RRID:SCR_014181) Copy   

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

Software for efficient generation and simulation of models containing stochastic ion channels distributed across dendritic and axonal membranes. It computes the behavior of neurons taking account of the stochastic nature of ion channel gating and the detailed positions of the channels themselves. It is designed as a complement for existing tools.

Proper citation: Parallel Stochastic Ion Channel Simulator (RRID:SCR_014159) Copy   

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

Software tool to simplify creation and management of computing environments in Neuroimaging.

Proper citation: ReproMan (RRID:SCR_018468) Copy   

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http://www.chibi.ubc.ca/WhiteText/

Freely available corpus of manually annotated brain region mentions created to facilitate text mining of neuroscience literature. The corpus contains 1,377 abstracts with 18,242 brain region annotations. Interannotator agreement was evaluated for a subset of the documents, and was 90.7% and 96.7% for strict and lenient matching respectively. We observed a large vocabulary of over 6,000 unique brain region terms and 17,000 words. For automatic extraction of brain region mentions we evaluated simple dictionary methods and complex natural language processing techniques. The dictionary methods based on neuroanatomical lexicons recalled 36% of the mentions with 57% precision. The best performance was achieved using a conditional random field (CRF) with a rich feature set. Features were based on morphological, lexical, syntactic and contextual information. The CRF recalled 76% of mentions at 81% precision, by counting partial matches recall and precision increase to 86% and 92% respectively. We suspect a large amount of error is due to coordinating conjunctions, previously unseen words and brain regions of less commonly studied organisms. We found context windows, lemmatization and abbreviation expansion to be the most informative techniques. We encourage you to test new methods and applications of the dataset. Please contact us if you do, we would like to hear about and link to your work. The abstracts are from PubMed/Medline, specifically The Journal of Comparative Neurology.

Proper citation: Automated recognition of brain region mentions in neuroscience literature. (RRID:SCR_002731) Copy   

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http://www.nitrc.org/projects/cs_schizbull08/

This project hosts data for CANDI Share Schizophrenia Bulletin 2008 (reference below) as part of the CANDI Neuroimaging Access Point. This set includes preprocessed MRI images and segmentation results of all 4 diagnostic groups (Healthy Controls, N=29; Schizophrenia Spectrum, N=20; Bipolar Disorder with Psychosis, N=19; and Bipolar Disorder without Psychosis, N=35). Frazier JA, Hodge SM, Breeze JL, Giuliano AJ, Terry JE, Moore CM, Kennedy DN, Lopez-Larson MP, Caviness VS, Seidman LJ, Zablotsky B, Makris N. Diagnostic and sex effects on limbic volumes in early-onset bipolar disorder and schizophrenia. Schizophr Bull. 2008 Jan;34(1):37-46.

Proper citation: CANDI Share: Schizophrenia Bulletin 2008 (RRID:SCR_009451) Copy   

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http://www.radiologyresearch.org/HippocampusSegmentation.aspx

This dataset contains T1-weighted MR images of 50 subjects, 40 of whom are patients with temporal lobe epilepsy and 10 are nonepileptic subjects. Hippocampus labels are provided for 25 subjects for training. The users may submit their segmentation outcomes for the remaining 25 testing images to get a table of segmentation metrics.

Proper citation: MRI Dataset for Hippocampus Segmentation (RRID:SCR_009597) Copy   

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http://www.nitrc.org/projects/me-icr/

Data set of an AFNI GroupInCorr session for multi-echo independent component regression (ME-ICR) for a cohort of 52 subjects. This dataset provides a high-quality atlas of seed-based functional connectivity with strong statistical conditioning.

Proper citation: Multi-Echo Independent Component Regression Group-Level Connectivity Dataset (RRID:SCR_009508) Copy   

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http://fcon_1000.projects.nitrc.org/indi/pro/nki.html

A phenotypically rich neuroimaging sample, consisting of data obtained from individuals between the ages of 4 and 85 years-old. All individuals included in the sample undergo semi-structured diagnostic psychiatric interviews, and complete a battery of psychiatric, cognitive and behavioral assessments in order to provide comprehensive phenotypic information for the purpose of exploring brain / behavior relationships.

Proper citation: NKI/Rockland Sample (RRID:SCR_009435) Copy   

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http://www.umassmed.edu/psychiatry/candi/

A series of structural brain images, as well as their anatomic segmentations, demographic and behavioral data and a set of related morphometric resources (static and dynamic atlases) made avaialble from the Child and Adolescent NeuroDevelopment Initiative (CANDI) at UMass Medical School. Schiz Bull 2008 data is now available on NITRC-IR. Please register for access: http://www.nitrc.org/project/request.php?group_id=377

Proper citation: CANDI Neuroimaging Access Point (RRID:SCR_009542) Copy   

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

A Java tool that takes an unorganized collection of DICOM scans, sorts and categorizes them according to user-customizable rules, gathers metadata about the scans, and saves out this information to help facilitate data uploads. Batch pr

Proper citation: DICOM UploadGUI (RRID:SCR_009458) Copy   

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http://fmripower.org

An easy to use matlab-based graphical user interface that calculates power for future studies based on older analyses or pilot data.

Proper citation: FMRIpower (RRID:SCR_009576) Copy   

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http://www.nitrc.org/projects/camino-trackvis/

Software package that allows interoperability between CAMINO and TRACKVIS. CAMINO is a leading software package in DTI processing. The package is from University of College London. TRACKVIS is a tract visualizing utility with capability of visualizing up to and over a million white matter tracts seamlessly. The package is from Massachusetts General Hospital. With increasing efforts on brain connectivity analyses it becomes important to have tools that can allow increased interoperability among different tractography tools. The tools in this package allow conversion of tracts from one format to another in a very effective way with ability to handle over a million tracts.

Proper citation: CAMINO-TRACKVIS (RRID:SCR_009450) Copy   

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

A complete software package for the study of event-related brain activity with high-resolution EEG/MEG. This package has been designed to suit the high standards of neuroscience research. The software has been developed originally at the Max Planck Institute for Cognitive Neuroscience in Leipzig, Germany, and is available for other institutions through ANT Neuro B.V., The Netherlands, enhanced with the EEProbe Databrowser. ERP investigations, both in psychophysiology research and clinical applications require a multitude of processing steps. Analysis of large data sets is made efficient through advanced scripting possibilities. All different aspects of data handling are efficiently available in the EEProbe Databrowser. Alternatively, external data can be imported from a multitude of formats. Processing in EEProbe makes use of open file formats (see LIBEEP) and is designed to integrate with ASA for advanced source analysis. EEProbe is available for Linux and Mac OS X.

Proper citation: EEProbe (RRID:SCR_009570) Copy   

•   Source: SciCrunch Registry