Tools   Select Another Resource Report Type

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

http://neurosynth.org

Platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. It''s a website wrapped around a set of open-source Python and JavaScript packages. Neurosynth lets you run crude but useful analyses of fMRI data on a very large scale. You can: * Interactively visualize the results of over 3,000 term-based meta-analyses * Select specific locations in the human brain and view associated terms * Browse through the nearly 10,000 studies in the database Their ultimate goal is to enable dynamic real-time analysis, so that you''ll be able to select foci, tables, or entire studies for analysis and run a full-blown meta-analysis without leaving your browser. You''ll also be able to do things like upload entirely new images and obtain probabilistic estimates of the cognitive states most likely to be associated with the image.

Proper citation: NeuroSynth (RRID:SCR_006798) Copy   

•   Source: SciCrunch Registry

http://www.nbtwiki.net/

An open source Matlab toolbox for the computation and integration of neurophysiological biomarkers. NBT offers a pipeline from data storage to statistics including artifact rejection, signal visualization, biomarker computation, and statistical testing. NBT allows for easy implementation of new biomarkers, and incorporates an online wiki that facilitates collaboration among NBT users including extensive help and tutorials. NBT is specialized in analyzing EEG data, however it allows the processing of any kind of signal. NBT can, e.g., be used to analyze ongoing oscillation between: * Eyes-closed rest of subject populations (e.g., healthy subjects and patients, males vs. females, young vs. old, etc.). * Two experimental condition (e.g., classical eyes-closed rest vs. meditation, or before vs. after consumption of a CNS-active substance (a drug, coffee, nicotine, alcohol, etc.)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Neurophysiological Biomarker Toolbox (RRID:SCR_009612) Copy   

•   Source: SciCrunch Registry

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

A native Java-based imaging processing environment similar to the ITK/VTK paradigm. Initially developed as an extension to MIPAV (CIT, NIH, Bethesda, MD), the JIST processing infrastructure provides automated GUI generation for application plug-ins, graphical layout tools, and command line interfaces. This repository maintains the current multi-institutional JIST development tree and is recommended for public use and extension. JIST was originally developed at IACL and MedIC (Johns Hopkins University) and is now also supported by MASI (Vanderbilt University).

Proper citation: JIST: Java Image Science Toolkit (RRID:SCR_008887) Copy   

•   Source: SciCrunch Registry

http://www.epilepsiae.eu/project_outputs/epilab_software

A Matlab-based software package developed for supporting researchers in performing studies on the prediction of epileptic seizures. It provides an intuitive and convenient graphical user interface. Fundamental concepts that are crucial for epileptic seizure prediction studies were implemented.This includes, for example, the development and statistical validation of prediction methodologies in long-term continuous recordings. Seizure prediction is usually based on electroencephalography (EEG) and electrocardiography (ECG) signals. EPILAB is able to process both EEG and ECG data stored in different formats. More than 35 time and frequency domain measures (features) can be extracted based on univariate and multivariate data analysis. These features can be post-processed and used for prediction purposes. The predictions may be conducted based on optimized thresholds or by applying classifications methods such as artificial neural networks, cellular neuronal networks, and support vector machines.

Proper citation: EPILAB (RRID:SCR_009573) Copy   

•   Source: SciCrunch Registry

http://marsbar.sourceforge.net/

A toolbox for SPM which provides routines for region of interest analysis. Features include region of interest definition, combination of regions of interest with simple algebra, extraction of data for regions with and without SPM preprocessing (scaling, filtering), and statistical analyses of ROI data using the SPM statistics machinery.

Proper citation: MarsBaR region of interest toolbox for SPM (RRID:SCR_009605) 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.imagevis3d.org/

A new volume rendering program developed by the NIH/NCRR Center for Integrative Biomedical Computing (CIBC). The main design goals of ImageVis3D are: simplicity, scalability, and interactivity. Simplicity is achieved with a new user interface that gives an unprecedented level of flexibility (as shown in the images). Scalability and interactivity for ImageVis3D mean that both on a notebook computer as well as on a high end graphics workstation, the user can interactively explore terabyte sized data sets. Finally, the open source nature as well as the strict component-by-component design allow developers not only to extend ImageVis3D itself but also reuse parts of it, such as the rendering core. This rendering core, for instance, is planned to replace the volume rendering subsystems in many applications at the SCI Institute and with their collaborators.

Proper citation: ImageVis3D (RRID:SCR_009566) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/draw3d/

Draw3D is a 3D rendering tool written entirely in VTK-TCL script. It is intended for fast command line rendering and visual inspection of datasets commonly found in medical imaging. It also allows the generation of images for reports or videos. As it is based on pure VTK, it can render whatever VTK can render, and runs wherever VTK can run. Meshinator is a simpler tool that uses VTKs isosurface functions to generate meshes from volumetric data. Please see the wiki for documentation

Proper citation: Draw3D and Meshinator (RRID:SCR_009444) 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/dti_brain_atlas/

Human DTI brain atlases have been generated at UNC-Chapel Hill for several age groups, by iterative joint deformable registration of training datasets into a single unbiased DTI average image. Atlases packages include an atlas DTI tensor image, atlas DTI property images (FA, MD, AD, RD), and single tensor tractography based fiber tracts of major tracts with related 3D planes for fiber profile information: genu, splenium, anterior and posterior limb of internal capsule, uncinate fasciculus.

Proper citation: UNC Human DTI Brain Atlas (RRID:SCR_009516) Copy   

•   Source: SciCrunch Registry

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

A nice sign of bias field correction (nonuniformity) in medical images. This tool is fast and efficient. Technical details can be found at http://zheng.vision.googlepages.com/biasCorrection_miccai09_Zheng.pdf

Proper citation: NICE-SIGN (RRID:SCR_009629) Copy   

•   Source: SciCrunch Registry

http://www.gtec.at/Products/Software/g.BSanalyze-Specs-Features

An interactive environment for multimodal biosignal data processing and analysis in the fields of clinical research and life sciences. It is the most comprehensive package to analyze non-invasive and invasive brain-, heart- and muscle-functions and dysfunctions. It includes many functions such as support vector machines, event-related ECG, support for P300 and SSVEP/SSSEP BCIs, zero class detection for BCIs, compressed spectral array, minimum energy, and more! g.BSanalyze consists of a base version for data import, visualization, transformation and pre-processing and has several dedicated toolboxes. The package comes with many sample biosignal data-sets, including P300, SSVEP, motor imagery, CSP BCIs, Tilt-Table, EPs, multi-unit activity, CFM, and ERD/ERS.

Proper citation: g.BSanalyze (RRID:SCR_009625) Copy   

•   Source: SciCrunch Registry

http://www.xinapse.com/

A medical image display package that allows easy viewing and analysis of Magnetic Resonance, x-ray CT and other types of medical image. Jim is an up-to-the-minute design with a familiar user-interface.

Proper citation: Jim (RRID:SCR_009589) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/hispeedpackets/

HI-SPEED Software Packets contain # unconstrained and constrained nonlinear least squares diffusion tensor estimation techniques, # 2-dimensional and 3-dimensional analytical (Shepp-Logan) magnetic resonance imaging phantoms in both the Fourier and image domains, # techniques for reporting the underlying signal-to-noise ratio in magnetic resonance (MR) images, # Probabilistic Identification and EStimation of NOise (PIESNO)---a technique for identifying noise-only pixels and estimating the underlying noise standard deviation in MR images, and # a signal-transformational technique for breaking the noise floor in MR images. Many more computational tools will be shared with users and developers as they become available.

Proper citation: HI-SPEED Software Packets (RRID:SCR_009585) Copy   

•   Source: SciCrunch Registry

http://www.bsl.ece.vt.edu/index.php?page=ara-dataset

Dataset of structural MR images of 70 subjects collected during 2008-2010 across a wide range of ages. The dataset also contains resting state fMRI for most subjects. The structural images are T1 weighted, T2 weighted-FLAIR, 25 direction DTI, and the T1 mapping DESPOT [1] sequence. Reconstructed T1 maps for each subject are also available. The aquisition protocol was designed to study structural differences between young and older adults including both shape and intensity changes. Anonymized DICOM image sessions and processed images for each subject are available. The data is licensed under the Creative Commons Attribution License. It may be used freely for commercial, academic, or other use, as long as the original source is properly cited. http://www.bsl.ece.vt.edu/index.php?page=ara-dataset

Proper citation: Age Related Atrophy Dataset (RRID:SCR_009528) Copy   

•   Source: SciCrunch Registry

http://amilab.org

An opensource software for image analysis, processing and visualization. It provides convenient visualization tools for 2D and 3D images and it is highly extensible through its own scripting language. At visualization level, AMILab includes a 2D/3D image viewer, a 3D polygon viewer based on OpenGL, a 2D Curve viewer to visualize 2D curves, histograms and color/opacity transfer functions, and a GPU-enabled raycasting script for Volume Rendering based on VTK. The software includes an automatic C++ wrapping system which permits fast development of new visualization tools and image processing algorithms. This wrapping system currently wraps about 200 classes from wxwidgets library and about 100 classes from VTK.

Proper citation: AMILab (RRID:SCR_009525) Copy   

•   Source: SciCrunch Registry

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

A data analysis environment for diffuse optical tomography (DOT) functional neuroimaging data. Developed to process data from steady-state time-series measurements, it allows for maximal flexibility in the number and positions of optodes. The central component is an application called NAVI. Features include: # An electronic ledger (records metadata for all data transformations). # Data conditioning (e.g., frequency-filtering, selection of data on the basis of signal-to-noise ratio.) # 2D or 3D image formation and display. # Interpretation: atlas-based mapping; automated anatomical labeling; GLM; data-driven methods (e.g., PCA, ICA); model-based (e.g., dynamic causal modeling) and data-driven (e.g., correlation) connectivity analysis. Another important component is the Brain Model Generator, which includes FEM meshes for all parts of the head accessible to DOT measurements. The user can input the numbers of optodes, and manually specify their locations or input tracking-system data.

Proper citation: fNIRS Data Analysis Environment (RRID:SCR_009522) Copy   

•   Source: SciCrunch Registry

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

3D DTI anatomical rat brain atlases have been created by the UNC- Chapel Hill Department of Psychiatry and the CAMID research collaboration. There are three age groups, postnatal day 5, postnatal day 14, and postnatal day 72. The subjects were Sprague-Dawley rats that were controls in a study on cocaine abuse and development. The P5 and P14 templates were made from scans of twenty rats each (ten female, ten male); the P72, from six females. The individual cases have been resampled to isotropic resolution, manually skull-stripped, and deformably registered via an unbiased atlas building method to create a template for each age group. Each template was then manually segmented using itk-SNAP software. Each atlas is made up of 3 files, a template image, a segmentation, and a label file.

Proper citation: 3D DTI Atlas of the Rat Brain In Postnatal Day 5 14 and Adulthood (RRID:SCR_009437) Copy   

•   Source: SciCrunch Registry