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http://www.neurobs.com/

Stimulus delivery and experiment control program. Stimuli include auditory, 2D and 3D visual, and multimodal and experimental data include fMRI, ERP, MEG, psychophysics, eye movements, single neuron recording, and reaction time measures.

Proper citation: Presentation (RRID:SCR_002521) Copy   

•   Source: SciCrunch Registry

http://www.paraview.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.brainscape.org/

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   

•   Source: SciCrunch Registry

http://adni-info.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.xnat.org

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   

•   Source: SciCrunch Registry

http://www.pediatricmri.nih.gov/

Data sets of clinical / behavioral and image data are available for download by qualified researchers from a seven year, multi-site, longitudinal study using magnetic resonance technologies to study brain maturation in healthy, typically-developing infants, children, and adolescents and to correlate brain development with cognitive and behavioral development. The information obtained in this study is expected to provide essential data for understanding the course of normal brain development as a basis for understanding atypical brain development associated with a variety of developmental, neurological, and neuropsychiatric disorders affecting children and adults. This study enrolled over 500 children, ranging from infancy to young adulthood. The goal was to study each participant at least three times over the course of the project at one of six Pediatric Centers across the United States. Brain MR and clinical/behavioral data have been compiled and analyzed at a Data Coordinating Center and Clinical Coordinating Center. Additionally, MR spectroscopy and DTI data are being analyzed. The study was organized around two objectives corresponding to two age ranges at the time of enrollment, each with its own protocols. * Objective 1 enrolled children ages 4 years, 6 months through 18 years (total N = 433). This sample was recruited across the six Pediatric Study Centers using community based sampling to reflect the demographics of the United States in terms of income, race, and ethnicity. The subjects were studied with both imaging and clinical/behavioral measures at two year intervals for three time points. * Objective 2 enrolled newborns, infants, toddlers, and preschoolers from birth through 4 years, 5 months, who were studied three or more times at two Pediatric Study Centers at intervals ranging from three months for the youngest subjects to one year as the children approach the Objective 1 age range. Both imaging and clinical/behavioral measures were collected at each time point. Participant recruitment used community based sampling that included hospital venues (e.g., maternity wards and nurseries, satellite physician offices, and well-child clinics), community organizations (e.g., day-care centers, schools, and churches), and siblings of children participating in other research at the Pediatric Study Centers. At timepoint 1, of those enrolled, 114 children had T1 scans that passed quality control checks. Staged data release plan: The first data release included structural MR images and clinical/behavioral data from the first assessments, Visit 1, for Objective 1. A second data release included structural MRI and clinical/behavioral data from the second visit for Objective 1. A third data release included structural MRI data for both Objective 1 and 2 and all time points, as well as preliminary spectroscopy data. A fourth data release added cortical thickness, gyrification and cortical surface data. Yet to be released are longitudinally registered anatomic MRI data and diffusion tensor data. A collaborative effort among the participating centers and NIH resulted in age-appropriate MR protocols and clinical/behavioral batteries of instruments. A summary of this protocol is available as a Protocol release document. Details of the project, such as study design, rationale, recruitment, instrument battery, MRI acquisition details, and quality controls can be found in the study protocol. Also available are the MRI procedure manual and Clinical/Behavioral procedure manuals for Objective 1 and Objective 2.

Proper citation: NIH MRI Study of Normal Brain Development (RRID:SCR_003394) Copy   

•   Source: SciCrunch Registry

http://signalml.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023.An XML-based language designed for metadescription of formats, used for digital storage of biomedical time series. Using SignalML, information on the structure of binary data files can be simply and efficiently coded. Once written, this information can be used by any software, which - owing to this metadescription - can read data files in the original format. This eliminates the need for conversions and duplication of data. signalml.org provides the following resources for interchange of relevant information and ideas: * SignalML wiki * Newsgroup / mailing list The main current software project is Svarog - a SignalML-compliant signal viewer, annotator, analyzer and (future) recorder. Svarog is written in Java and is currently best fitted for display of EEG and MEG signals. Also open platform for implementing advanced signal processing methods in user-friendly environment, at the moment interfacs for Java code, standalone executables and Matlab code via Matlab Builder for Java.

Proper citation: signalml.org (RRID:SCR_003383) Copy   

•   Source: SciCrunch Registry

http://bio3d.colorado.edu/imod

A free, cross-platform set of image processing, modeling and display programs used for tomographic reconstruction and for 3D reconstruction of EM serial sections and optical sections. The package contains tools for assembling and aligning data within multiple types and sizes of image stacks, viewing 3-D data from any orientation, and modeling and display of the image files. IMOD 4.1.8 Is Now Available for Linux, Windows, and Mac OS X

Proper citation: IMOD (RRID:SCR_003297) Copy   

•   Source: SciCrunch Registry

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

An interactive 3D rendering and neuroanatomical analysis package developed for analyzing focal brain lesions and functional brain imaging data (Damasio and Frank, 1991; Frank, Damasio and Grabowski, 1997).

Proper citation: Brainvox (RRID:SCR_009448) Copy   

•   Source: SciCrunch Registry

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

High quality data, open and freely available to everyone to celebrate the diversity of the vertebrate brain. Do you have data that you would like to share? Do not hesitate to contact them! The Brain Catalogue is developed by Florencia Grisanti (Taxidermy Workshop of the Natural History Museum in Paris) and Roberto Toro (Neuroscience Department of the Institut Pasteur). Many of our specimens come from the Vertebrate Brain Collection of the Jardin des Plantes, curated by Marc Herbin, and are scanned at the Institut du Cerveau et de la Moelle (ICM) by Mathieu Santin and Alexandra Petiet, from the CENIR laboratory, with financial and methodological support kindly provided by Olivier Colliot, head of the Cogimage team at the ICM.

Proper citation: Brain Catalogue (RRID:SCR_009442) Copy   

•   Source: SciCrunch Registry

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

Interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. First developed on Matlab 5.3 under Linux, EEGLAB runs on Matlab v5 and higher under Linux, Unix, Windows, and Mac OS X (Matlab 7+ recommended). EEGLAB provides an interactive graphic user interface (GUI) allowing users to flexibly and interactively process their high-density EEG and other dynamic brain data using independent component analysis (ICA) and/or time/frequency analysis (TFA), as well as standard averaging methods. EEGLAB also incorporates extensive tutorial and help windows, plus a command history function that eases users'' transition from GUI-based data exploration to building and running batch or custom data analysis scripts. EEGLAB offers a wealth of methods for visualizing and modeling event-related brain dynamics, both at the level of individual EEGLAB ''datasets'' and/or across a collection of datasets brought together in an EEGLAB ''studyset.'' For experienced Matlab users, EEGLAB offers a structured programming environment for storing, accessing, measuring, manipulating and visualizing event-related EEG data. For creative research programmers and methods developers, EEGLAB offers an extensible, open-source platform through which they can share new methods with the world research community by publishing EEGLAB ''plug-in'' functions that appear automatically in the EEGLAB menu of users who download them. For example, novel EEGLAB plug-ins might be built and released to ''pick peaks'' in ERP or time/frequency results, or to perform specialized import/export, data visualization, or inverse source modeling of EEG, MEG, and/or ECOG data. EEGLAB Features * Graphic user interface * Multiformat data importing * High-density data scrolling * Defined EEG data structure * Open source plug-in facility * Interactive plotting functions * Semi-automated artifact removal * ICA & time/frequency transforms * Many advanced plug-in toolboxes * Event & channel location handling * Forward/inverse head/source modeling

Proper citation: EEGLAB (RRID:SCR_007292) Copy   

•   Source: SciCrunch Registry

http://eeg.sourceforge.net/

Software toolbox to facilitate quick and easy import, visualization and measurement for Event Related Potential (ERP) data. The toolbox can open and visualise ERP averaged data (Neuroscan, ascii formats), 2D/3D electrode coordinates and 3D cerebral tissue tesselations (meshes). All the features can be explored quickly and easily using the example data provided in the toolbox. The GUI interface is simple and intuitive.

Proper citation: Bioelectromagnetism Matlab Toolbox (RRID:SCR_006090) Copy   

•   Source: SciCrunch Registry