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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
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
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
http://www.softpedia.com/get/Science-CAD/BrainCSI.shtml
A tool for analysis of Magnetic Resonance Spectroscopy (MRS) data by registering it to anatomical images. BrainCSI imports LCModel results to calculate absolute metabolite concentrations using tissue water. Corrections to LCModel metabolite concentrations for partial volume of tissues are accomplished by tissue classification of the anatomical images.
Proper citation: BrainCSI (RRID:SCR_013244) Copy
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
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
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
https://compumedicsneuroscan.com/products/by-name/curry/
Processing software for multimodal neuroimaging centered on combining functional data such as EEG and MEG with imaging data from MRI and CT to optimize source reconstruction. They are now combining Curry's strength with the acquisition and signal processing features of the SCAN software for a comprehensive EEG acquisition, data analysis, source localization and source imaging package.
Proper citation: CURRY (RRID:SCR_009546) Copy
http://www.cis.hut.fi/projects/ica/fastica/
General-purpose unsupervised data-analysis tool, most often used for brain imaging data.
Proper citation: FastICA (RRID:SCR_013110) Copy
https://github.com/NIRALUser/DTIAtlasBuilder
This tool creates an Atlas image as an average of several DTI images that will be registered. The registration will be done in two steps : - Affine Registration with BRAINSFit - Non Linear Registration with GreedyAtlas A final step will apply the transformations to the original DTI images so that the final average can be computed. The main function writes a python script that will be executed to compute the Atlas. By running DTIAtlasBuilder, you will need to fill in informations in a Graphical User Interface, and then compute the Atlas. You can also run the tool in command line without using the GUI. Using the GUI, you will be able to save or load a dataset file or a parameter file. The tool needs these other tools to work, so be sure to have these installed on your computer: - ImageMath - ResampleDTIlogEuclidean - CropDTI - dtiprocess - BRAINSFit - GreedyAtlas - dtiaverage - DTI-Reg - unu - MriWatcher If you download the package, be sure to have the glut library installed.
Proper citation: DTI Atlas Builder (RRID:SCR_013112) Copy
http://www.nitrc.org/projects/cost_unc/
A tool that implements a graph-based connectivity assessment method. This method uses a multi-directional graph propagation method applied to sampled orientation distribution function (ODF), which can be computed directly from the original diffusion imaging data.
Proper citation: COST (RRID:SCR_014098) Copy
http://www.nitrc.org/projects/broccoli/
A software package written in OpenCL (Open Computing Language) that can be used for parallel analysis of fMRI data on a large variety of hardware configurations. If BROCCOLI is running on a GPU, it can perform non-linear spatial normalization to a 1 mm brain template in 4-6 s and run a second level permutation test with 10,000 permutations.
Proper citation: BROCCOLI (RRID:SCR_014093) Copy
http://www.nitrc.org/projects/afni_3dsvm/
A command-line program and plugin for AFNI built around SVM-Light. It performs support vector machine (SVM) analysis on fMRI data and runs on Unix+X11+Motif systems, including SGI, Solaris, Linux, and Mac OS X.
Proper citation: 3dsvm (RRID:SCR_014083) Copy
http://www.nitrc.org/projects/ntu-dsi-122/
A diffusion spectrum imaging (DSI) template constructed in the standard ICBM-152 space from 122 healthy adults. The template was built through incorporating the macroscopic anatomical information using high-resolution T1-weighted images and the microscopic structural information obtained from DSI datasets, rendering it to achieve a high anatomical matching to the ICBM-152 space. This template can serve as a representative DSI dataset for a healthy adult population. It is released in its original DWI format.
Proper citation: NTU-DSI-122: a DSI template in ICBM-152 space (RRID:SCR_014155) Copy
http://www.nitrc.org/projects/r2r_prf/
Software tool as a framework for fitting and describing connectivity patterns between regions that is a simple extension from the current population receptive field models in the visual neuroscience literature. The connectivity from each voxel in a designated seed region to a mapping region is modeled as a 3-dimensional Gaussian, providing location parameters and spread parameters. This allows the direct description of the relative mapping from one region to another.
Proper citation: Region to Region (RRID:SCR_016995) Copy
https://github.com/nipy/heudiconv
Software tool as flexible DICOM converter for organizing brain imaging data into structured directory layouts.
Proper citation: HeuDiConv: a heuristic-centric DICOM converter (RRID:SCR_017427) Copy
https://github.com/BRAINSia/BRAINSTools
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 23,2023. A suite of tools to generate the cortical surface of the brain. The surface is generated in the middle of grey matter and can be used to measure surface features including cortical depth and curvature.
Proper citation: BRAINSCortex (RRID:SCR_001082) Copy
http://www.montefiore.ulg.ac.be/~phillips/FASST.html
An EEG toolbox developed to help users with 3 specific types of data and problems: simulatenous EEG-fMRI recording, continuous EEG scoring (e.g. sleep) and handling (visualisation, cutting, power spectrum, etc.) multi-channel recording of spontaneous EEG. The toolbox is written in Matlab and is specifically compatible with the BrainAmp family of EEG recorders (from BrainProducts GmbH) Three other data formats are now also supported: the edf "European Data Format", exported raw-EGI data (from Electrical Geodesics, Inc.) and the BCI2000 format.The results are directly compatible with SPM8 and are saved with SPM8 EEG data format.
Proper citation: fMRI Artefact rejection and Sleep Scoring Toolbox (RRID:SCR_009620) Copy
A Python package intended to ease statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run. Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. This Python-based, cross-platform, open-source software toolbox software toolbox for the application of classifier-based analysis techniques to fMRI datasets makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages.
Proper citation: PyMVPA (RRID:SCR_006099) Copy
http://www.hitachi-medical.co.jp/english/
An instrumental supplier which provides researchers and clinicians with sophisticated All-in-One solutions in the field of neuroscience.
Proper citation: Hitachi Optical Topography System (RRID:SCR_000865) Copy
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