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https://github.com/FeeLab/seqNMF
Software tool for unsupervised discovery of sequential structure. Used to detect sequences in neural data generated by internal behaviors, such as animal thinking or sleeping. Used for unsupervised discovery of temporal sequences in high dimensional datasets in neuroscience without reference to external markers.
Proper citation: seqNMF (RRID:SCR_017068) Copy
The MiND: Metadata in NIfTI for DWI framework enables data sharing and software interoperability for diffusion-weighted MRI. This site provides specification details, tools, and examples of the MiND mechanism for representing important metadata for DWI data sets at various stages of post-processing. MiND framework provides a practical solution to the problem of interoperability between DWI analysis tools, and it effectively expands the analysis options available to end users. To assist both users and developers in working with MiND-formatted files, we provide a number of software tools for download. * MiNDHeader A utility for inspecting MiND-extended files. * I/O Libraries Programming libraries to simplify writing and parsing MiND-formatted data. * Sample Files Example files for each MiND schema. * DIRAC LONI''s Diffusion Imaging Reconstruction and Analysis Collection is a DWI processing suite which utilizes the MiND framework.
Proper citation: LONI MiND (RRID:SCR_004820) Copy
Open source, cross platform library that provides developers with extensive suite of software tools for image analysis. Developed through extreme programming methodologies, ITK builds on proven, spatially oriented architecture for processing, segmentation, and registration of scientific images in two, three, or more dimensions.
Proper citation: Insight Segmentation and Registration Toolkit (RRID:SCR_001149) Copy
http://dti-tk.sourceforge.net/pmwiki/pmwiki.php
A spatial normalization and atlas construction toolkit optimized for examining white matter morphometry using DTI data with special care taken to respect the tensorial nature of the data. It implements a state-of-the-art registration algorithm that drives the alignment of white matter (WM) tracts by matching the orientation of the underlying fiber bundle at each voxel. The algorithm has been shown to both improve WM tract alignment and to enhance the power of statistical inference in clinical settings. A 2011 study published in NeuroImage ranks DTI-TK the top-performing tool in its class. Key features include: * open standard-based file IO support: NIfTI format for scalar, vector and tensor image volumes * tool chains for manipulating tensor image volumes: resampling, smoothing, warping, registration & visualization * pipelines for WM morphometry: spatial normalization & atlas construction for population-based studies * built-in cluster-computing support: support for open source Sun Grid Engine (SGE) * Interoperability with other popular DTI tools: AFNI, Camino, FSL & DTIStudio * Interoperability with ITK-SNAP: support multi-modal visualization and segmentation
Proper citation: Diffusion Tensor Imaging ToolKit (RRID:SCR_001642) Copy
https://github.com/trendscenter/gift
Software MATLAB toolbox which implements multiple algorithms for independent component analysis and blind source separation of group (and single subject) functional magnetic resonance imaging data. GIFT works on MATLAB 6.5 and higher. Many ICA algorithms were generously contributed by Dr. Andrzej Cichocki.
Proper citation: Group ICA of fMRI Toolbox (RRID:SCR_001953) Copy
http://neuroimage.usc.edu/brainstorm/
Software as collaborative, open source application dedicated to analysis of brain recordings: MEG, EEG, fNIRS, ECoG, depth electrodes and animal invasive neurophysiology. User-Friendly Application for MEG/EEG Analysis.
Proper citation: Brainstorm (RRID:SCR_001761) Copy
http://www.nitrc.org/projects/itk-snap/
Open source interactive software application for three dimentional medical images, manual delineation of anatomical regions of interest, and performing automatic image segmentation. Used for delineating anatomical structures and regions in MRI, CT and other 3D biomedical imaging data.WebGL-based viewer for volumetric data. It is capable of displaying arbitrary (non axis-aligned) cross-sectional views of volumetric data, as well as 3-D meshes and line-segment based models (skeletons).
Proper citation: ITK-SNAP (RRID:SCR_002010) Copy
http://brainatlas.mbi.ufl.edu/Database/
Comprehensive three-dimensional digital atlas database of the C57BL/6J mouse brain based on magnetic resonance microscopy images acquired on a 17.6-T superconducting magnet. This database consists of: Individual MRI images of mouse brains; three types of atlases: individual atlases, minimum deformation atlases and probabilistic atlases; the associated quantitative structural information, such as structural volumes and surface areas. Quantitative group information, such as variations in structural volume, surface area, magnetic resonance microscopy image intensity and local geometry, have been computed and stored as an integral part of the database. The database augments ongoing efforts with other high priority strains as defined by the Mouse Phenome Database focused on providing a quantitative framework for accurate mapping of functional, genetic and protein expression patterns acquired by a myriad of technologies and imaging modalities. You must register First (Mandatory) and then you may Download Images and Data.
Proper citation: MRM NeAt (Neurological Atlas) Mouse Brain Database (RRID:SCR_007053) Copy
http://physionet.org/physiobank/
Archive of well-characterized digital recordings of physiologic signals and related data for use by the biomedical research community. PhysioBank currently includes databases of multi-parameter cardiopulmonary, neural, and other biomedical signals from healthy subjects and patients with a variety of conditions with major public health implications, including sudden cardiac death, congestive heart failure, epilepsy, gait disorders, sleep apnea, and aging. The PhysioBank Archives now contain over 700 gigabytes of data that may be freely downloaded. PhysioNet is seeking contributions of data sets that can be made freely available in PhysioBank. Contributions of digitized and anonymized (deidentified) physiologic signals and time series of all types are welcome. If you have a data set that may be suitable, please review PhysioNet''s guidelines for contributors and contact them.
Proper citation: Physiobank (RRID:SCR_006949) Copy
http://fmri.wfubmc.edu/software/PickAtlas
A software toolbox that provides a method for generating Region of Interest (ROI) masks based on the Talairach Daemon database. The atlases include Brodmann area, Lobar, Hemisphere, Anatomic Label (gyral anatomy), and Tissue type. The atlases have been extended to the vertex in MNI space, and corrected for the precentral gyrus anomaly. Additional atlases (including non-human atlases) can be added without difficulty., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: WFU PickAtlas (RRID:SCR_007378) Copy
Software Python package for simulation and analysis of neuronal networks using the NEURON simulator.Used to facilitate development, parallel simulation, analysis, and optimization of biological neuronal networks.
Proper citation: NetPyNE (RRID:SCR_014758) Copy
http://www.nitrc.org/projects/laplacebeltrami/
A filter which allows the Laplace-Beltrami operator to determine surface harmonics in terms of PointData at each vertex. It determines the requested N most significant harmonics of a surface.
Proper citation: Laplace Beltrami Filter on QuadEdge Meshes (RRID:SCR_014133) Copy
http://www.nitrc.org/projects/ap_seg_2013_nih/
A MATLAB GUI for segmenting and quantifying PET images with multi-focal and diffuse uptakes. It imports a PET image and allows the user to draw region of interests (ROIs) in 2D or 3D to roughly separate the object of interest from the background. The areas are then segmented using a PET image segmentation method based on Affinity Propagation clustering to cluster the image intensities into meaningful groups. For quantification, the Standardized Uptake Value measurements of the binary or the user defined ROI are SUVmax, SUVmean, and Volume (mm^3) and can be exported into an excel sheet.
Proper citation: NIH-CIDI Segmentation of PET Images based on Affinity Propagation Clustering (RRID:SCR_014151) Copy
Project portal dedicated to understand animal and machine intelligence and repository of data and tools. Suite of tools to analyze and graph imaging data. Image and data repository for large, publicly available neuro-specific data files and images. Contains tools for analytics, databases, cloud computing, and Web-services applied to both big neuroimages and big neurographs.
Proper citation: neurodata (RRID:SCR_014264) Copy
Software suite for processing magnetoencephalography and electroencephalography data. Open source Python software for exploring, visualizing, and analyzing human neurophysiological data including MEG, EEG, sEEG, ECoG . Implements all functionality of MNE Matlab tools in Python and extends capabilities of MNE Matlab tools to, e.g., frequency-domain and time-frequency analyses and non-parametric statistics.
Proper citation: MNE software (RRID:SCR_005972) Copy
http://users.loni.ucla.edu/~shattuck/brainsuite/
Suite of image analysis tools designed to process magnetic resonance images (MRI) of the human head. BrainSuite provides an automatic sequence to extract genus-zero cortical surface mesh models from the MRI. It also provides a set of viewing tools for exploring image and surface data. The latest release includes graphical user interface and command line versions of the tools. BrainSuite was specifically designed to guide its users through the process of cortical surface extraction. NITRC has written the software to require minimal user interaction and with the goal of completing the entire process of extracting a topologically spherical cortical surface from a raw MR volume within several minutes on a modern workstation. The individual components of BrainSuite may also be used for soft tissue, skull and scalp segmentation and for surface analysis and visualization. BrainSuite was written in Microsoft Visual C using the Microsoft Foundation Classes for its graphical user interface and the OpenGL library for rendering. BrainSuite runs under the Windows 2000 and Windows XP Professional operating systems. BrainSuite features include: * Sophisticated visualization tools, such as MRI visualization in 3 orthogonal views (either separately or in 3D view), and overlayed surface visualization of cortex, skull, and scalp * Cortical surface extraction, using a multi-stage user friendly approach. * Tools including brain surface extraction, bias field correction, voxel classification, cerebellum removal, and surface generation * Topological correction of cortical surfaces, which uses a graph-based approach to remove topological defects (handles and holes) and ensure a tessellation with spherical topology * Parameterization of generated cortical surfaces, minimizing a harmonic energy functional in the p-norm * Skull and scalp surface extraction
Proper citation: BrainSuite (RRID:SCR_006623) Copy
Software toolkit for concretely describing non-canonical polymers and complexes to facilitate global biochemical networks. Web tool for describing molecular structure of macromolecular complexes, including non canonical monomeric forms, circular topologies, and crosslinks. Describes semantic meaning of whole cell computational models.
Proper citation: BcForms (RRID:SCR_018654) Copy
Software toolkit for discovering data needed to build, calibrate, and validate mechanistic models of cells. Integrated database of molecular data for quantitatively modeling cellular behavior. Web application for identifying relevant data for modeling specific organism in specific environmental condition.
Proper citation: Datanator (RRID:SCR_018651) Copy
http://www.loni.usc.edu/Software/BrainParser
Software that uses a novel statistical-learning technique to segment brain regions of interest (ROIs) based on a training set of data and generates 3D MRI volumes. The software comes pre-trained on a provided data set but can be retrained to work with your desired regions of interest.
Proper citation: LONI Brain Parser (RRID:SCR_009572) Copy
http://www.slicer.org/slicerWiki/index.php/Slicer3:Module:Rician_Noise_Removal
Two Slicer3 modules removing rician noise in diffusion tensor MRI
Proper citation: Slicer3 Module Rician noise filter (RRID:SCR_009614) Copy
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