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http://umcd.humanconnectomeproject.org

Web-based repository and analysis site for connectivity matrices that have been derived from neuroimaging data including different imaging modalities, subject groups, and studies. Users can analyze connectivity matrices that have been shared publicly and upload their own matrices to share or analyze privately.

Proper citation: USC Multimodal Connectivity Database (RRID:SCR_012809) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/meanmachine/

This software can be used to analyze EEG data either using a graphical interface (GUI) or using Matlab scripts, which make use of the functions provided by the MeanMachine. As compared to other libraries, MeanMachine can handle even very large data sets like, for example, 256 channels recorded at 2KHz.

Proper citation: Mean Machine (RRID:SCR_013103) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/liversegm/

A set of tools for the processing of liver images. These tools consist of a level set based variational approach that incorporates shape priors and appearance models. It uses ITK-SNAP 1.4 as interface. The tools are capable of automatic liver segmentation and semi-automatic injury segmentation.

Proper citation: LiverSegm (RRID:SCR_013108) Copy   

•   Source: SciCrunch Registry

http://rfmri.org/DPARSF

A MATLAB toolbox forpipeline data analysis of resting-state fMRI that is based on Statistical Parametric Mapping (SPM) and a plug-in software within DPABI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), fractional ALFF, degree centrality, voxel-mirrored homotopic connectivity (VMHC) results. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest. DPARSF basic edition is very easy to use while DPARSF advanced edition (alias: DPARSFA) is much more flexible and powerful. DPARSFA can parallel the computation for each subject, and can be used to reorient images interactively or define regions of interest interactively. Users can skip or combine the processing steps in DPARSF advanced edition freely.

Proper citation: DPARSF (RRID:SCR_002372) Copy   

•   Source: SciCrunch Registry

http://www.warwick.ac.uk/snpm

A toolbox for Statistical Parametric Mapping (SPM) that provides an extensible framework for voxel level non-parametric permutation/randomization tests of functional Neuroimaging experiments with independent observations. SnPM uses the General Linear Model to construct pseudo t-statistic images, which are then assessed for significance using a standard non-parametric multiple comparisons procedure based on randomization/permutation testing. It is most suitable for single subject PET/SPECT analyses, or designs with low degrees of freedom available for variance estimation. In these situations the freedom to use weighted locally pooled variance estimates, or variance smoothing, makes the non-parametric approach considerably more powerful than conventional parametric approaches, as are implemented in SPM. Further, the non-parametric approach is always valid, given only minimal assumptions. The SnPM toolbox provides an alternative to the Statistics section of SPM.

Proper citation: Statistical non-Parametric Mapping (RRID:SCR_002092) Copy   

•   Source: SciCrunch Registry

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

Matlab toolbox that implements the wavelet-based image fusion technique for orthogonal images, introduced in (Aganj et al, MRM 2012).

Proper citation: Wavelet-based Image Fusion (RRID:SCR_002007) Copy   

•   Source: SciCrunch Registry

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

This project is meant for planning the NITRC Grantee meetings. A website for organizing meetings for the Neuroimaging Informatics Tools and Resources Clearinghouse, to facilitate participants meeting one another, and promote discussion of common interests and collaboration.

Proper citation: Grantees Meeting for NITRC (RRID:SCR_000419) Copy   

•   Source: SciCrunch Registry

http://aimlab.cs.uoregon.edu/NEMO/web/

THIS RESOURCE IS NO LONGER IN SERVICE. NIH tombstone webpage lists Project Period : 2009 - 2013. NIH funded project to create EEG and MEG ontologies and ontology based tools. These resources will be used to support representation, classification, and meta-analysis of brain electromagnetic data. Three pillars of NEMO are: DATA, ONTOLOGY, and DATABASE. NEMO data consist of raw EEG, averaged EEG (ERPs), and ERP data analysis results. NEMO ontologies include concepts related to ERP data (including spatial and temporal features of ERP patterns), data provenance, and cognitive and linguistic paradigms that were used to collect data. NEMO database portal is large repository that stores NEMO consortium data, data analysis results, and data provenance. EEG and MEG ontologies and ontology-based tools to support representation, classification, and meta-analysis of brain electromagnetic data. Raw EEG and ERP data may be uploaded to the NEMO FTP site., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Neural ElectroMagnetic Ontologies (NEMO) Project (RRID:SCR_002001) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/iowa3/

Software for real-time parametric statistical analysis of functional MRI (fMRI) data. The system that combines a general architecture for sampling and time-stamping relevant information channels in fMRI (image acquisition, stimulation, subject responses, cardiac and respiratory monitors, etc.) and an efficient approach to manipulating these data, featuring incremental subsecond multiple linear regression. The advantages of the system are the simplification of event timing and efficient and unified data formatting. Substantial parametric analysis can be performed and displayed in real-time. Immediate (replay) and delayed off-line analysis can also be performed with the same interface. The system provides a time-accounting infrastructure that readily supports standard and innovative approaches to fMRI.

Proper citation: I/OWA (RRID:SCR_000858) Copy   

•   Source: SciCrunch Registry

http://www.imagescience.org/meijering/software/neuronj/

NeuronJ is an ImageJ plugin to facilitate the tracing and quantification of elongated structures in two-dimensional (2D) images (8-bit gray-scale and indexed color), in particular neurites in fluorescence microscopy images. Sponsors: The development of NeuronJ started while the primary developer ( Dr. Erik Meijering, PhD) was with the Biomedical Imaging Group (collaborating with people from the Laboratory of Cellular Neurobiology) of the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, and was finished while Dr. Meijering was with the Biomedical Imaging Group Rotterdam in the Netherlands.

Proper citation: NeuronJ: An ImageJ Plugin for Neurite Tracing and Quantification (RRID:SCR_002074) Copy   

•   Source: SciCrunch Registry

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

Software which aims to better estimate the neuronal activation of an individual using the results of an independent component analysis (ICA) method applied to a temporally concatenated group of functional magnetic resonance imaging (fMRI) data (i.e., Tc-GICA method). This approach employs iterative LS solutions to refine both the individual SPs and TCs with an additional a priori assumption of sparseness in the SPs (i.e., minimally overlapping SPs) based on L(1)-norm minimization.

Proper citation: Iterative dual-regression with sparse prior (RRID:SCR_014128) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/l-neuron

A program which creates anatomically realistic virtual neurons using the formalism of the Lyndenmayer systems to implement sets of neuroanatomical rules discovered by several research groups. The program algorithms read in experimental data - in the form of statistical distributions - to generate virtual structures. L-Neuron samples the values of the parameters within these statistical distributions in a stochastic (random) fashion during dendritic growth.

Proper citation: L-Neuron (RRID:SCR_014132) Copy   

•   Source: SciCrunch Registry

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

A lightweight framework for setting up dependency-driven processing pipelines. The tool is essentially a configurable shell script (sh/bash), which can be included in other scripts and primarily provides a small number of utility functions for dependency checking and NFS-safe file locking for cluster processing.

Proper citation: Lightweight Data Pipeline (RRID:SCR_014135) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/cmind_py_2014/

A python toolbox for analysis of MRI images. It relies on calls to a number of widely tested algorithms from the FMRIB software library (FSL) and the advanced normalization tools (ANTS) to provide analysis of simultaneously acquired ASL/BOLD fMRI data. It was developed for analyzing the datasets collected as part of the Cincinnati MR Imaging of NeuroDevelopment (C-MIND) project.

Proper citation: CMIND PY (RRID:SCR_014097) Copy   

•   Source: SciCrunch Registry

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

A set of ImageJ plugins for fully automated measurement of neurite outgrowth in fluorescence microscopy images of cultured neurons. The plugin analyzes fluorescence microscopy images of neurites and nuclei of dissociated cultured neurons. Given user-defined thresholds, the plugin counts neuronal nuclei, and traces and measures neurite length. NeuriteTracer accurately measures neurite outgrowth from cerebellar, DRG and hippocampal neurons.

Proper citation: NeuriteTracer (RRID:SCR_014146) Copy   

•   Source: SciCrunch Registry

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

A Matlab-based toolbox initially created for reading, writing, and processing of BrainVoyager (QX) files in Matlab.

Proper citation: NeuroElf (RRID:SCR_014147) Copy   

•   Source: SciCrunch Registry

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

An R package for descriptive (i.e., fixed-effects) multivariate analysis with singular value decomposition.

Proper citation: ExPosition Packages (RRID:SCR_014107) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE, documented December 11, 2015. A discussion group for those actively involved in research into, or applications of, biomagnetism and magnetoencephalography (MEG).

Proper citation: Biomag Discussion Group on Yahoo (RRID:SCR_014089) Copy   

•   Source: SciCrunch Registry

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

A collection of software tools developed for medical image synthesis of typically magnetic resonance (MR) brain images. The approaches have been used to create computed tomography (CT) images from MR input. The goal of image synthesis is to recover MR images with a desired optimal contrast for further processing by either registration or segmentation.

Proper citation: Image Synthesis Tools (RRID:SCR_014123) Copy   

•   Source: SciCrunch Registry

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

A collection of software tools for high dimensional brain imaging genomics. These tools are designed to perform comprehensive joint analysis of heterogeneous imaging genomics data. HDBIG-SR is an HDBIG toolkit for sparse regression while HDBIG-SCCA is an HDBIG toolkit for sparse association.

Proper citation: HDBIG (RRID:SCR_014120) Copy   

•   Source: SciCrunch Registry