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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
Open source, multi platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities. ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.
Proper citation: ParaView (RRID:SCR_002516) Copy
http://www.nitrc.org/projects/stfilter/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14, 2026. Software tools which can perform Stochastic Tractography and related analysis on DWMRI data. Stochastic Tractography applies a Bayesian approach towards the estimation of nerve fiber tracts from DWMRI images.
Proper citation: Stochastic Tractography System (RRID:SCR_002594) Copy
http://www.nitrc.org/projects/sspm/
Software package representing Spatial Statistical Parametric Mapping that includes two tools presently: MAGEE and FADTTS. MAGEE represents the Multiscale Adaptive Generalized Estimating Equation. It was developed specifically for analyzing multivariate neuroimaging data in 3-dimensional volume (or on 2-dimensional surface) from longitudinal neuroimaging studies. FADTTS represents Functional Analysis of Diffusion Tensor Tract Statistics. The aim of this tool is to implement a functional analysis pipeline, for delineating the structure of the variability of multiple diffusion properties along major white matter fiber bundles and their association with a set of covariates of interest, in various diffusion tensor imaging studies.
Proper citation: Spatial Statistical Parametric Mapping (RRID:SCR_002592) Copy
http://theobjects.com/en/products/scientific/index.php
Software with advanced visualization techniques and state-of-the-art volume rendering provide unparalleled insight into the details and properties of neurological data acquired by CT, micro-CT, MRI, PET, SPECT, microscopy and other modalities. With data fusion tools, intramodality and multimodality registration of MR/CT or PET/CT is easily accomplished, while semi-automatic VOI delineation on fused datasets can improve analysis. Standard formats, such as DICOM, RAW, JPEG, NIFTI, Analyze are supported and 3D/4D sequences can be played. Other features include MPR, oblique, CPR, volume clipping, and surface visualization of cortex, skull, and scalp models. Also standard are easy-to-use tools for voxel-based delineation of features and the measurement of properties, including areas, volumes, counts, and intensity profiles. Present your findings by creating annotated animations or high-resolution images for posters. An SDK is also available to create plug-ins that provide new workflows or functionalities.
Proper citation: ORS Visual SI (RRID:SCR_002509) Copy
http://sites.google.com/site/marcocongedo/software/nica
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13, 2026. Software program, executable under any Windows32 OS, performs Group BSS (Blind Source Separation) analysis comparing two groups of individuals and it performs NICA (Normative ICA) analysis where individuals are compared individually to a (normative) group. All analysis is performed in the frequency domain, that is, for all frequencies. The program also performs all these analysis for qEEG, that is, at the electrode level, without any BSS. The program does all computations, saves and displays results. The rationale and methods used in this program are explained in all details in the following paper: Congedo M, John ER, De Ridder D, Prichep L (2010) Group Independent Component Analysis of Resting-State EEG in Large Normative Samples International Journal of Psychophysiology 78, 89-99.
Proper citation: Normative Independent Component Analysis (RRID:SCR_002506) Copy
https://github.com/UCSFBiomagneticImagingLab/nutmeg
Software MEG/EEG analysis toolbox for reconstructing neural activation and overlaying it onto structural MR images. Toolbox runs under MATLAB in conjunction with SPM2 and can be used with Linux/UNIX, Mac OS X, and Windows platforms.
Proper citation: NUTMEG (RRID:SCR_002748) Copy
http://www.loni.usc.edu/Software/MBAT
Workflow environment bringing together heterogenous, online biological image resources, a user's image data and biological atlases in a concise, unified and intuitive workspace. The MBAT viewer displays multiple images on a single virtual canvas allowing easy side-by-side comparisons and image compositing. MBAT is written in Java so it is platform independent and is highly extensible through it's plugin architecture. MBAT integrates three distinct workspaces for online search, image alignment (registration) and image display: * Search Workspace: able to submit a query to multiple databases simultaneously and online literature searches. * Registration Workspace: performs 2D landmark based registration. * Viewer Workspace: displays & composites images and image volumes using high performance graphics hardware. * Atlas Viewer: allows navigation and interrogation of volumetric atlases. * Hierarchy Editor: create logical groupings of atlas labels.
Proper citation: Mouse BIRN Atlasing Toolkit (RRID:SCR_002814) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 23, 2013. Database for resting state functional connectivity studies. Functional connectivity has shown tremendous promise in mapping the intrinsic functional topography of the brain, evaluating neuroanatomical models, and investigating neurological and psychiatric disease. Brainscape includes a repository of public and private data and an analysis engine for exploring the correlation structure of spontaneous fluctuations in the fMRI BOLD signal. (DICOM data is the image format that can be uploaded.) With Brainscape you can upload, analyze, and share your own data. You can search for, download, and analyze studies in the repository of shared data. The analysis engine works by selecting one or more studies, typing in the coordinates of a brain region of interest, and the seed-region correlation engine computes the correlation structure across the whole brain. (T1, T2 and EPI data are the scan types Brainscape can process.) You decide who can access your data. You can keep it to yourself, share with select colleagues, or share it with everyone. The Brainscape database and analysis tools are open source and freely available.
Proper citation: Brainscape (RRID:SCR_002962) Copy
Database of the results of the ADNI study. ADNI is an initiative to develop biomarker-based methods to detect and track the progression of Alzheimer's disease (AD) that provides access to qualified scientists to their database of imaging, clinical, genomic, and biomarker data.
Proper citation: ADNI - Alzheimer's Disease Neuroimaging Initiative (RRID:SCR_003007) Copy
http://bmsr.usc.edu/software/eons/
Modeling platform to study the basic interactions between synaptic elements that allows the user to study qualitatively, and also quantitatively the relative contributions of diverse mechanisms underlying synaptic efficacy: the relevance of each and every element that comprises a synapse, the interactions between these components and their subcellular distribution, as well as the influence of synaptic geometry (presynaptic terminal, cleft and postsynaptic density). This platform consists of a graphical interface in which elements that comprise a single glutamatergic synapse (both pre- and post-synaptically), their behavior as well as the underlying synaptic geometry can be modified. For example, EONS offers the ability to study the effect of voltage-gated calcium channels density and distribution, the number and location of receptors and more. EONS is a parametric model of a generic glutamatergic synapse that takes into account pre-synaptic mechanisms, such as calcium buffering and diffusion, neurotransmitter release, diffusion and uptake in the cleft, and postsynaptic elements, such as ionotropic AMPA and NMDA receptors, their distribution and synaptic geometry, as well as metabotropic glutamate receptors. There are no complicated equations to write: all the models are predefined. This version is a great tool for first time users and students interested in learning about synapses, as well as for studying geometry and distribution hypotheses in a 2D rectangular geometry. System Requirements: EONS V1.2 is a Windows program but can be also successfully installed and run on Mac and Linux.
Proper citation: EONS (RRID:SCR_002979) Copy
Software platform designed to facilitate common management and productivity tasks for neuroimaging and associated data.
Proper citation: XNAT - The Extensible Neuroimaging Archive Toolkit (RRID:SCR_003048) Copy
https://bioimagesuiteweb.github.io/webapp/index.html
Web applications for analysis of multimodal/multispecies neuroimaging data. Image analysis software package. Has facilities for DTI and fMRI processing. Capabilities for both neuro/cardiac and abdominal image analysis and visualization. Many packages are extensible, and provide functionality for image visualization and registration, surface editing, cardiac 4D multi-slice editing, diffusion tensor image processing, mouse segmentation and registration, and much more. Can be intergrated with other biomedical image processing software, such as FSL, AFNI, and SPM.
Proper citation: BioImage Suite (RRID:SCR_002986) Copy
MOOSE is the Multiscale Object-Oriented Simulation Environment. It is the base and numerical core for large, detailed simulations including Computational Neuroscience and Systems Biology. MOOSE spans the range from single molecules to subcellular networks, from single cells to neuronal networks, and to still larger systems. it is backwards-compatible with GENESIS, and forward compatible with Python and XML-based model definition standards like SBML and MorphML. MOOSE is coordinating with the GENESIS-3 project towards the goals of developing educational resources for modeling. MOOSE is open source software, licensed under the LGPL (Lesser GNU Public License). It has absolutely no warranty. Sponsors: - National Center of Biological Sciences (NCBS) - National Institutes of Health (NIH) Collaboration - EU-India grid - Department of Atomic Energy Science Research Council (DAE/SRC) - Department of Biotechnology (DBT)
Proper citation: Multiscale Object Orientation Simulation Environment (RRID:SCR_008031) Copy
http://www.alivelearn.net/xjview8/
A viewing program for Statistical Parametric Mapping (SPM2, SPM5 and SPM8). p-value slider, displays multiple images at a time and can be used to build Region of Interest (ROI) masks. For a given region you can find the anatomical name and search the selected region in online database (wiki, Google scholar and PubMed).
Proper citation: xjView: A Viewing Program For SPM (RRID:SCR_008642) Copy
https://www.humanconnectome.org/software/connectome-workbench
Software brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. Used to map brain imaging data. Allows for visualization of outputs from HCP pipelines from single subject, or average data from group of subjects and register that data onto standard brain atlas.
Proper citation: Connectome Workbench (RRID:SCR_008750) Copy
Consortium to comprehensively map long-distance brain connections and their variability. It is acquiring data and developing analysis pipelines for several modalities of neuroimaging data plus behavioral and genetic data from healthy adults.
Proper citation: Human Connectome Coordination Facility (RRID:SCR_008749) Copy
Software package for reconstructing three-dimensional models of brain structures from 2-D delineations using a customizable and reproducible workflow. 3dBAR also works as an on-line service (http://service.3dbar.org) offering a variety of functions for the hosted datasets: * downloading reconstructions of desired brain structures in predefined quality levels in various supported formats as well as created using customizable settings, * previewing models as bitmap thumbnails and (for webGL enabled browsers) interactive manipulation (zooming, rotating, etc.) of the structures, * downloading slides from available datasets as SVG drawings. 3dBAR service can also be used by other websites or applications to enhance their functionality. * Operating System: Linux * Programming Language: Python * Supported Data Format: NIfTI-1, Other Format, VRML
Proper citation: 3DBar (RRID:SCR_008896) Copy
http://www.nitrc.org/projects/ahead/
Open-source turnkey software for automatic hippocampus segmentation. Its primary use is for delineating hippocampus in T1-weighted MRI images. AHEAD is developed by Jung W. Suh, Hongzhi Wang, Sandhitsu Das, Brian Avants, Philip Cook, John Pluta and Paul Yushkevich, and colleagues at the Penn Image Computing and Science Laboratory (PICSL) at the University of Pennsylvania.
Proper citation: AHEAD (RRID:SCR_008890) Copy
An interactive multiresolution brain atlas that is based on over 20 million megapixels of sub-micron resolution, annotated, scanned images of serial sections of both primate and non-primate brains and integrated with a high-speed database for querying and retrieving data about brain structure and function. Currently featured are complete brain atlas datasets for various species, including Macaca mulatta, Chlorocebus aethiops, Felis catus, Mus musculus, Rattus norvegicus, Tyto alba and many other vertebrates. BrainMaps is currently accepting histochemical, immunocytochemical, and tracer connectivity data, preferably whole-brain. In addition, they are interested in EM, MRI, and DTI data.
Proper citation: BrainMaps.org (RRID:SCR_006878) Copy
http://www.mlnl.cs.ucl.ac.uk/pronto/
A software toolbox based on pattern recognition techniques for the analysis of neuroimaging data. Statistical pattern recognition is a field within the area of machine learning which is concerned with automatic discovery of regularities in data through the use of computer algorithms, and with the use of these regularities to take actions such as classifying the data into different categories. In PRoNTo, brain scans are treated as spatial patterns and statistical learning models are used to identify statistical properties of the data that can be used to discriminate between experimental conditions or groups of subjects (classification models) or to predict a continuous measure (regression models).
Proper citation: PRoNTo (RRID:SCR_006908) Copy
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