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http://www.cise.ufl.edu/~abarmpou/lab/fanDTasia/

A Java applet tool for DT-MRI processing. It opens Diffusion-Weighted MRI datasets from user's computer and performs very efficient tensor field estimation using parallel threaded processing on user's browser. No installation is required. It runs on any operating system that supports Java (Windows, Mac, Linux,...). The estimated tensor field is guaranteed to be positive definite second order or higher order and is saved in user's local disc. MATLAB functions are also provided to open the tensor fields for your convenience in case you need to perform further processing. The fanDTasia Java applet provides also vector field visualization for 2nd and 4th-order tensors, as well as calculation of various anisotropic maps. Another useful feature is 3D fiber tracking (DTI-based) which is also shown using 3d graphics on the user's browser.

Proper citation: fanDTasia Java Applet: DT-MRI Processing (RRID:SCR_009624) Copy   

•   Source: SciCrunch Registry

http://www.nmr.mgh.harvard.edu/~jbm/jip/

Software toolkit for analysis of rodent and non-human primate fMRI data. The toolkit consists of binary executables, highly portable open-source c code, and image resources that enable 1) Automated registration based upon mutual information (affine, non-linear warps), with flexible control and visualization of each step; 2) visualization of 4-dimensional data using either mosaic or tri-planar display of the z/slice dimension, and integration of a general linear model for graphical display of time series analysis; 3) A simple and flexible 1st-order GLM for fMRI time series analysis, a 1st-order GLM analysis for PET data within the SRTM framework, plus a 2nd-order GLM analysis following the Worsley 2002 scheme, and 4) MRI templates to place your rodent and non-human primate data into standardized spaces.

Proper citation: JIP Analysis Toolkit (RRID:SCR_009588) Copy   

•   Source: SciCrunch Registry

http://econnectome.umn.edu/

An open-source MATLAB software package for imaging brain functional connectivity from electrophysiological signals. It provides interactive graphical interfaces for EEG/ECoG/MEG preprocessing, source estimation, connectivity analysis and visualization. Connectivity from EEG/ECoG/MEG can be mapped over sensor and source domains. This package is designed for use by researchers in neuroscience, psychology, cognitive science, clinical neurophysiology, neurology and other disciplines. The graphical interface-based platform requires little programming knowledge or experience with MATLAB. eConnectome is developed by the Biomedical Functional Imaging and Neuroengineering Laboratory at the University of Minnesota, directed by Dr. Bin He. The visualization module is jointly developed with Drs. Fabio Babiloni and Laura Astolfi at the University of Rome La Sapienza.

Proper citation: eConnectome (RRID:SCR_009618) Copy   

•   Source: SciCrunch Registry

http://pdbml.pdb.org/

Markup Language that provides a representation of PDB data in XML format. The description of this format is provided in XML schema of the PDB Exchange Data Dictionary. This schema is produced by direct translation of the mmCIF format PDB Exchange Data Dictionary Other data dictionaries used by the PDB have been electronically translated into XML/XSD schemas and these are also presented in the list below. * PDBML data files are provided in three forms: ** fully marked-up files, ** files without atom records ** files with a more space efficient encoding of atom records * Data files in PDBML format can be downloaded from the RCSB PDB website or by ftp. * Software tools for manipulating PDB data in XML format are available.

Proper citation: Protein Data Bank Markup Language (RRID:SCR_005085) Copy   

•   Source: SciCrunch Registry

http://slicer.org/

A free, open source software package for visualization and image analysis including registration, segmentation, and quantification of medical image data. Slicer provides a graphical user interface to a powerful set of tools so they can be used by end-user clinicians and researchers alike. 3D Slicer is natively designed to be available on multiple platforms, including Windows, Linux and Mac Os X. Slicer is based on VTK (http://public.kitware.com/vtk) and has a modular architecture for easy addition of new functionality. It uses an XML-based file format called MRML - Medical Reality Markup Language which can be used as an interchange format among medical imaging applications. Slicer is primarily written in C++ and Tcl.

Proper citation: 3D Slicer (RRID:SCR_005619) Copy   

•   Source: SciCrunch Registry

https://www.bci2000.org/

BCI2000 is a general-purpose system for brain-computer interface (BCI) and adaptive neurotechnology research. It can also be used for data acquisition, stimulus presentation, and brain monitoring applications. The mission of the BCI2000 project is to facilitate research and applications in the areas described. Their vision is that BCI2000 will become a widely used software tool for diverse areas of real-time biosignal processing. In order to achieve this vision, BCI2000 system is available for free for non-profit research and educational purposes. BCI2000 supports a variety of data acquisition systems, brain signals, and study/feedback paradigms. During operation, BCI2000 stores data in a common format (BCI2000 native or GDF), along with all relevant event markers and information about system configuration. BCI2000 also includes several tools for data import/conversion (e.g., a routine to load BCI2000 data files directly into Matlab) and export facilities into ASCII. BCI2000 also facilitates interactions with other software. For example, Matlab scripts can be executed in real-time from within BCI2000, or BCI2000 filters can be compiled to execute as stand-alone programs. Furthermore, a simple network-based interface allows for interactions with external programs written in any programming language. For example, a robotic arm application that is external to BCI2000 may be controlled in real time based on brain signals processed by BCI2000, or BCI2000 may use and store along with brain signals behavioral-based inputs such as eye-tracker coordinates. Because it is based on a framework whose services can support any BCI implementation, the use of BCI2000 provides maximum benefit to comprehensive research programs that operate multiple BCI2000 installations to collect data for a variety of studies. The most important benefits of the system in such situations are: - A Proven Solution - Facilitates Operation of Research Programs - Facilitates Deployment in Multiple Sites - Cross-Platform and Cross-Compiler Compatibility - Open Resource Sponsors: BCI2000 development is sponsored by NIH/NIBIB R01 and NIH/NINDS U24 grants. Keywords: General, Purpose, Systems, Brain, Computer, Interface, Research, Application, Brain, Diverse, Educational, Laboratory, Software, Network, Signals, Behavioral, Eye, Tracker,

Proper citation: Brain Computer Interface 2000 Software Package (RRID:SCR_007346) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/LONI-Inspector

A Java application for reading, displaying, searching, comparing, and exporting metadata from medical image files: AFNI, ANALYZE, DICOM, ECAT, GE, Interfile, MINC, and NIFTI.

Proper citation: LONI Inspector (RRID:SCR_004923) Copy   

•   Source: SciCrunch Registry

http://www.nsgportal.org/

Web portal that allows free access to supercomputing resources for large scale modeling and data processing. Portal facilitates access and use of National Science Foundation (NSF) High Performance Computing (HPC) resources by neuroscientists.

Proper citation: Neuroscience Gateway (RRID:SCR_008915) Copy   

•   Source: SciCrunch Registry

http://www.nmr.mgh.harvard.edu/DOT/resources/homer2/home.htm

Software matlab scripts used for analyzing fNIRS data to obtain estimates and maps of brain activation. Graphical user interface (GUI) for visualization and analysis of functional near-infrared spectroscopy (fNIRS) data.

Proper citation: Homer2 (RRID:SCR_009586) Copy   

•   Source: SciCrunch Registry

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

Decoders and encoders written in Java for the AFNI, ANALYZE, DICOM, ECAT, GE, MINC, NIFTI and other neuroimaging file formats.The plugins use Java Image I/O interfaces to read and write metadata and image data and can read and write AFNI, ANALYZE 7.5, DICOM, ECAT 7.2, GE 5.0, INTERFILE (including hrrt), MINC, NIFTI, and UCLA PACS file formats. All source code is provided and usage examples are included.

Proper citation: LONI Java Image I/O Plugins (RRID:SCR_008277) Copy   

•   Source: SciCrunch Registry

http://surfer.nmr.mgh.harvard.edu/fswiki/Tracula

Software tool developed for automatically reconstructing a set of major white matter pathways in the brain from diffusion weighted images using probabilistic tractography. This method utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual intervention with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. The trac-all script is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user''''s preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step. To explore all the options in running trac-all please refer to the trac-all wiki. In order to use this script to reconstruct tracts in Diffusion images, all the subjects in the dataset must have Freesurfer Recons.

Proper citation: TRACULA (RRID:SCR_013152) Copy   

•   Source: SciCrunch Registry

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

A software application developed to support computational anatomy and shape analysis. The capabilities of CAWorks include: interactive landmark placement to create segmentation (mask) of desired region of interest; specialized landmark placement plugins for subcortical structures such as hippocampus and amygdala; support for multiple Medical Imaging data formats, such as Nifti, Analyze, Freesurfer, DICOM and landmark data; Quadra Planar view visualization; and shape analysis plugin modules, such as Large Deformation Diffeomorphic Metric Mapping (LDDMM). Specific plugins are available for landmark placement of the hippocampus, amygdala and entorhinal cortex regions, as well as a browser plugin module for the Extensible Neuroimaging Archive Toolkit.

Proper citation: CAWorks (RRID:SCR_014185) Copy   

•   Source: SciCrunch Registry

http://becs.aalto.fi/en/research/bayes/drifter/

Model based Bayesian method for eliminating physiological noise from fMRI data. This algorithm uses image voxel analysis to isolate the cardiac and respiratory noise from the relevant data.

Proper citation: DRIFTER (RRID:SCR_014937) Copy   

•   Source: SciCrunch Registry

https://github.com/nebneuron/neural-ideal

Software package for extracting neural activity codes.

Proper citation: Neural Ideal (RRID:SCR_017448) Copy   

•   Source: SciCrunch Registry

https://github.com/Nevermore520/NeuronTools

Software tools for converting data files into persistence diagrams and distance matrices.

Proper citation: Neuron Tools (RRID:SCR_017450) Copy   

•   Source: SciCrunch Registry

http://nipy.org

Community site to make brain imaging research easier that aims to build software that is clearly written, clearly explained, a good fit for the underlying ideas, and a natural home for collaboration.

Proper citation: Neuroimaging in Python (RRID:SCR_013141) Copy   

•   Source: SciCrunch Registry

http://mrir.med.miami.edu:8000/midas

Software for processing, display, and analysis of magnetic resonance spectroscopic imaging data. MIDAS supports a "whole-brain" MRSI acquisition method that has been implemented on MRI systems from three major manufacturers., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MIDAS (RRID:SCR_015704) Copy   

•   Source: SciCrunch Registry

http://www.iu.edu/~beca/

Visualization and analysis software for interactive visual exploration and mining of fiber-tracts and brain networks with their genetic determinants and functional outcomes. BECA includes an fMRI and Diseases Analysis version as well as a Genome Explorer version.

Proper citation: BECA (RRID:SCR_015846) Copy   

•   Source: SciCrunch Registry

https://www.icpsr.umich.edu/icpsrweb/content/addep/index.html

Provides access to data including wide range of topics related to disability. ADDEP data can be used to better understand and inform the implementation of Americans with Disabilities Act and other disability policies.

Proper citation: Archive of Data on Disability to Enable Policy (ADDEP) (RRID:SCR_016315) Copy   

•   Source: SciCrunch Registry

http://www.radiology.ucsf.edu/cind

Biomedical technology research center that develops and validates new imaging methods for detecting brain abnormalities in neurodegenerative diseases, including Alzheimer's disease, vascular dementia, frontotemporal dementia, Parkinson's disease, as well as epilepsy, depression, and other conditions associated with nerve loss in the brain. As people around the globe live longer, the impact of neurodegenerative diseases is expected to increase further with dire social and economical consequences for societies if no effective treatments are developed soon. The development at CIND is aimed to improve magnetic resonance imaging (MRI). The ultimate goal of the scientific program is to identify imaging markers that improve accuracy in diagnosing neurodegenerative diseases at early stages, achieve more reliable prognoses of disease progression, and facilitate the discovery of effective treatment interventions. In addition to addressing the general needs for studying neurodegenerative diseases, another focus of CIND concerns brain diseases associated with military service and war combat, such as post traumatic stress disorder (PTSD), brain trauma, gulf war illness and the long-term effects of these conditions on the mental health of veterans. The symbiosis between CIND and the Veterans Administration Medical Center in San Francisco makes this program uniquely suited to serve military veterans.

Proper citation: Center for Imaging of Neurodegenerative Diseases (RRID:SCR_001968) Copy   

•   Source: SciCrunch Registry