Tools   Select Another Resource Report Type

http://sourceforge.net/projects/polgui/

An interface between MATLAB and the Polhemus Fastrak digitizer used to digitize fiducial locations and scalp EEG electrode locations. There are 5 versions all of which work under MATLAB R14 (on both linux and windows platforms), # polgui_ver1_r14 : works with 1 receiver (stylus pen) # polgui_ver2_r14 : works with 2 receivers (including the pen) # polgui_ver3_r14 : works with 3 receivers(including the pen) # polgui_ver4_r14 : works with 4 receivers (including the pen) # polgui_ver5_r14 : Generic version which works with 1/2/3/4 receivers (WARNING: Ver 5 might be buggy; not fully tested) Requirements: MATLAB R14 (Linux/Windows)

Proper citation: POLGUI - Matlab Polhemus Interface (RRID:SCR_006752) Copy   

•   Source: SciCrunch Registry

https://itunes.apple.com/gb/app/neuropub-visualizer/id405721542?mt=8

A NIfTI visualizer for statistical brain images (fMRI, VBM, etc) the iPad. The visualizer displays these images as overlay on the MNI standard brain. You can use it to store all your statistical images from your fMRI / VBM / TBSS studies and visualise them in 2D and 3D. Use NeuroPub as a library for your statistical images. It's the perfect app to bring to meetings, conferences, etc, and show your latest results.

Proper citation: NeuroPub Visualizer (RRID:SCR_006797) Copy   

•   Source: SciCrunch Registry

http://scalablebrainatlas.incf.org/

A web-based, interactive brain atlas viewer, containing a growing number of atlas templates for various species, including mouse, macaque and human. Standard features include fast brain region lookup, point and click to select a region and view its full 3D extent, mark a stereotaxic coordinate and view all regions in a hierarchy. Built-in extensions are the CoCoMac plugin, which provides a spatial display of Macaque connectivity, and a service to transform stereotaxic coordinates to and from the INCF Waxholm space for the mouse. Three dimensional renderings of brain regions are available through a Matlab interface (local installation of Matlab required). The SBA is designed to be customizable. External users can create plugins, hosted on their own servers, to interactively attach images or data to spatial atlas locations. This fully web-based display engine for brain atlases and topologies allows client websites to show brain region related data in a 3D interactive context. Currently available atlases are: * Macaque: The Paxinos Rhesus Monkey atlas (2000) * Macaque: Various templates available through Caret, registered to F99 space: Felleman and Van Essen (1991), Lewis and Van Essen (2000), Regional Map from K��tter and Wanke (2005), Paxinos Rhesus Monkey (2000) * Macaque: The NeuroMaps Macaque atlas (2008) * Mouse: The INCF Waxholm Space for the mouse (2011). Previous versions available. * Mouse: The Allen Mouse Brain volumetric atlas (ABA07) * Human: The LPBA40 parcellation, registered to SRI24 space A variety of services are being developed around the templates contained in the Scalable Brain Atlas. For example, you can include thumbnails of brain regions in your own webpage. Other applications include: * Analyze atlas templates in Matlab * List all regions belonging to the given template * List of supported atlas templates * Find region by coordinate * Color-coded PNG (bitmap) or SVG (vector) image of a brain atlas slice * Region thumbnail in 2D (slice) or 3D (stack of slices) The Scalable Brain Atlas is created by Rembrandt Bakker and Gleb Bezgin, under supervision of Rolf K��tter in the NeuroPhysiology and -Informatics group of the Donders Institute, Radboud UMC Nijmegen.

Proper citation: Scalable Brain Atlas (RRID:SCR_006934) Copy   

•   Source: SciCrunch Registry

http://bric.unc.edu/ideagroup/free-softwares/ABSORB/

This software package implements an algorithm for effective groupwise registration. The required input is a set of 3D MR intensity images (in Analyze format with paired .hdr and .img files) with a text file (.txt) listing all header file (.hdr) names. The output is the set of registered images together with the corresponding dense deformation fields. This software has been tested on Windows XP (32-bit) and Linux (64-bit, kernel version 2.6.18-194.el5). The images should be pre-processed before applying ABSORB: * All brain MR images used as inputs to ABSORB should be in the same situation (e.g., skull-stripped or not, cerebellum removed or not, etc.). * The input images should be in Analyze format with paired header and image files. This software was developed in IDEA group in UNC-Chapel Hill.

Proper citation: ABSORB: Atlas Building by Self-Organized Registration and Bundling (RRID:SCR_007018) Copy   

•   Source: SciCrunch Registry

http://www.cns.atr.jp/dni/en/downloads/tools-for-brain-behavior-data-sharing/

This is MATLAB library to create Neuroshare data format. You can convert your own data into Neuroshare format file.

Proper citation: Matlab Neuroshare Library (RRID:SCR_006957) Copy   

•   Source: SciCrunch Registry

http://www.cognitiveatlas.org/

Knowledge base (or ontology) that characterizes the state of current thought in cognitive science that captures knowledge from users with expertise in psychology, cognitive science, and neuroscience. There are two basic kinds of knowledge in the knowledge base. Terms provide definitions and properties for individual concepts and tasks. Assertions describe relations between terms in the same way that a sentence describes relations between parts of speech. The goal is to develop a knowledge base that will support annotation of data in databases, as well as supporting improved discourse in the community. It is open to all interested researchers. A fundamental feature of the knowledge base is the desire and ability to capture not just agreement but also disagreement regarding definitions and assertions. Thus, if you see a definition or assertion that you disagree with, then you can assert and describe your disagreement. The project is led by Russell Poldrack, Professor of Psychology and Neurobiology at the University of Texas at Austin in collaboration with the UCLA Center for Computational Biology (A. Toga, PI) and UCLA Consortium for Neuropsychiatric Phenomics (R. Bilder, PI). Most tasks used in cognitive psychology research are not identical across different laboratories or even within the same laboratory over time. A major advantage of anchoring cognitive ontologies to the measurement level is that the strategy for determining changes in task properties is easier than tracking changes in concept definitions and usage. The process is easier because task parameters are usually (if not always) operationalized objectively, offering a clear basis to judge divergence in methods. The process is also easier because most tasks are based on prior tasks, and thus can more readily be considered descendants in a phylogenetic sense.

Proper citation: Cognitive Atlas (RRID:SCR_002793) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/FFT

Java library used for the execution of discrete Fourier transforms in 1-D, 2-D and 3-D through the implementation of Fast Fourier Transform (FFT) algorithms. * The FFT library has been written in Java for portability across different platforms, integrated into a single jar file for easy implementation. * The FFT library provides forward and backward fast Fourier transforms in 1-D, 2-D and 3-D with an easy-to-use manner. * The FFT requires the length equal to a number with an integer power of two. This library automatically examines the input data and detects the length to prevent improper execution.

Proper citation: FFT Library (RRID:SCR_002698) Copy   

•   Source: SciCrunch Registry

http://www.LONI.usc.edu/Software/ShapeViewer

Java-based geometry viewer that supports file formats used by Center for Computational Biology (CCB) researchers and provides necessary viewing functions. ShapeViewer uses ShapeTools library support to read and display LONI Ucf, VTX XML, FreeSurfer, Minc Obj (both binary and ascii), Open Dx, Gifti, and OFF format data files.

Proper citation: LONI ShapeViewer (RRID:SCR_002695) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/SHIVA

A Java-based visualization and analysis application that can process 2D and 3D image files and provides convenient methods for users to overlay multiple datasets. * Simultaneous visualization of multiple image volumes. * Tools for labeling and masking of structures. * Framework for the Mouse Atlas Project.

Proper citation: Synchronized Histological Image Viewing Architecture (RRID:SCR_002690) Copy   

•   Source: SciCrunch Registry

http://sumsdb.wustl.edu/sums/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 11, 2016. Repository of brain-mapping data (surfaces and volumes; structural and functional data) derived from studies including fMRI and MRI from many laboratories, providing convenient access to a growing body of neuroimaging and related data. WebCaret is an online visualization tool for viewing SumsDB datasets. SumsDB includes: * data on cerebral cortex and cerebellar cortex * individual subject data and population data mapped to atlases * data from FreeSurfer and other brainmapping software besides Caret SumsDB provides multiple levels of data access and security: * Free (public) access (e.g., for data associated with published studies) * Data access restricted to collaborators in different laboratories * Owner-only access for work in progress Data can be downloaded from SumsDB as individual files or as bundles archived for offline visualization and analysis in Caret WebCaret provides online Caret-style visualization while circumventing software and data downloads. It is a server-side application running on a linux cluster at Washington University. WebCaret "scenes" facilitate rapid visualization of complex combinations of data Bi-directional links between online publications and WebCaret/SumsDB provide: * Links from figures in online journal article to corresponding scenes in WebCaret * Links from metadata in WebCaret directly to relevant online publications and figures

Proper citation: SumsDB (RRID:SCR_002759) Copy   

•   Source: SciCrunch Registry

http://www.fmrib.ox.ac.uk/fsl/

Software library of image analysis and statistical tools for fMRI, MRI and DTI brain imaging data. Include registration, atlases, diffusion MRI tools for parameter reconstruction and probabilistic taractography, and viewer. Several brain atlases, integrated into FSLView and Featquery, allow viewing of structural and cytoarchitectonic standard space labels and probability maps for cortical and subcortical structures and white matter tracts. Includes Harvard-Oxford cortical and subcortical structural atlases, Julich histological atlas, JHU DTI-based white-matter atlases, Oxford thalamic connectivity atlas, Talairach atlas, MNI structural atlas, and Cerebellum atlas.

Proper citation: FSL (RRID:SCR_002823) Copy   

•   Source: SciCrunch Registry

http://studyforrest.org

An MRI data repository that holds a set of 7 Tesla images and behavioral metadata. Multi-faceted brain image archive with behavioral measurements. For each participant a number of different scans and auxiliary recordings have been obtained. In addition, several types of minimally preprocessed data are also provided. The full description of the data release is available in a dedicated publication. This project invites anyone to participate in a decentralized effort to explore the opportunities of open science in neuroimaging by documenting how much (scientific) value can be generated out of a single data release by publication of scientific findings derived from a dataset, algorithms and methods evaluated on this dataset, and/or extensions of this dataset by acquisition and integration of new data.

Proper citation: studyforrest.org (RRID:SCR_003112) Copy   

•   Source: SciCrunch Registry

http://brainmap.org/

A community database of published functional and structural neuroimaging experiments with both metadata descriptions of experimental design and activation locations in the form of stereotactic coordinates (x,y,z) in Talairach or MNI space. BrainMap provides not only data for meta-analyses and data mining, but also distributes software and concepts for quantitative integration of neuroimaging data. The goal of BrainMap is to develop software and tools to share neuroimaging results and enable meta-analysis of studies of human brain function and structure in healthy and diseased subjects. It is a tool to rapidly retrieve and understand studies in specific research domains, such as language, memory, attention, reasoning, emotion, and perception, and to perform meta-analyses of like studies. Brainmap contains the following software: # Sleuth: database searches and Talairach coordinate plotting (this application requires a username and password) # GingerALE: performs meta-analyses via the activation likelihood estimation (ALE) method; also converts coordinates between MNI and Talairach spaces using icbm2tal # Scribe: database entry of published functional neuroimaging papers with coordinate results

Proper citation: brainmap.org (RRID:SCR_003069) Copy   

•   Source: SciCrunch Registry

http://briansimulator.org/

Software Python package for simulating spiking neural networks. Useful for neuroscientific modelling at systems level, and for teaching computational neuroscience. Intuitive and efficient neural simulator.

Proper citation: Brian Simulator (RRID:SCR_002998) Copy   

•   Source: SciCrunch Registry

https://osf.io/

Platform to support research and enable collaboration. Used to discover projects, data, materials, and collaborators helpful to your own research.

Proper citation: Open Science Framework (RRID:SCR_003238) Copy   

•   Source: SciCrunch Registry

http://www.socr.ucla.edu/

A hierarchy of portable online interactive aids for motivating, modernizing probability and statistics applications. The tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials. The core SOCR educational and computational components include the following suite of web-based Java applets: * Distributions (interactive graphs and calculators) * Experiments (virtual computer-generated games and processes) * Analyses (collection of common web-accessible tools for statistical data analysis) * Games (interfaces and simulations to real-life processes) * Modeler (tools for distribution, polynomial and spectral model-fitting and simulation) * Graphs, Plots and Charts (comprehensive web-based tools for exploratory data analysis), * Additional Tools (other statistical tools and resources) * SOCR Java-based Statistical Computing Libraries * SOCR Wiki (collaborative Wiki resource) * Educational Materials and Hands-on Activities (varieties of SOCR educational materials), * SOCR Statistical Consulting In addition, SOCR provides a suite of tools for volume-based statistical mapping (http://wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials_AnalysesCommandLine) via command-line execution and via the LONI Pipeline workflows (http://www.nitrc.org/projects/pipeline). Course instructors and teachers will find the SOCR class notes and interactive tools useful for student motivation, concept demonstrations and for enhancing their technology based pedagogical approaches to any study of variation and uncertainty. Students and trainees may find the SOCR class notes, analyses, computational and graphing tools extremely useful in their learning/practicing pursuits. Model developers, software programmers and other engineering, biomedical and applied researchers may find the light-weight plug-in oriented SOCR computational libraries and infrastructure useful in their algorithm designs and research efforts. The three types of SOCR resources are: * Interactive Java applets: these include a number of different applets, simulations, demonstrations, virtual experiments, tools for data visualization and analysis, etc. All applets require a Java-enabled browser (if you see a blank screen, see the SOCR Feedback to find out how to configure your browser). * Instructional Resources: these include data, electronic textbooks, tutorials, etc. * Learning Activities: these include various interactive hands-on activities. * SOCR Video Tutorials (including general and tool-specific screencasts).

Proper citation: Statistics Online Computational Resource (RRID:SCR_003378) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/BIRN/Projects/Mouse/

Animal model data primarily focused on mice including high resolution MRI, light and electron microscopic data from normal and genetically modified mice. It also has atlases, and the Mouse BIRN Atlasing Toolkit (MBAT) which provides a 3D visual interface to spatially registered distributed brain data acquired across scales. The goal of the Mouse BIRN is to help scientists utilize model organism databases for analyzing experimental data. Mouse BIRN has ended. The next phase of this project is the Mouse Connectome Project (https://www.nitrc.org/projects/mcp/). The Mouse BIRN testbeds initially focused on mouse models of neurodegenerative diseases. Mouse BIRN testbed partners provide multi-modal, multi-scale reference image data of the mouse brain as well as genetic and genomic information linking genotype and brain phenotype. Researchers across six groups are pooling and analyzing multi-scale structural and functional data and integrating it with genomic and gene expression data acquired from the mouse brain. These correlated multi-scale analyses of data are providing a comprehensive basis upon which to interpret signals from the whole brain relative to the tissue and cellular alterations characteristic of the modeled disorder. BIRN's infrastructure is providing the collaborative tools to enable researchers with unique expertise and knowledge of the mouse an opportunity to work together on research relevant to pre-clinical mouse models of neurological disease. The Mouse BIRN also maintains a collaborative Web Wiki, which contains announcements, an FAQ, and much more.

Proper citation: Mouse Biomedical Informatics Research Network (RRID:SCR_003392) Copy   

•   Source: SciCrunch Registry

http://cng.gmu.edu:8080/Lm

A freely available software tool available for the Windows and Linux platform, as well as the Online version Applet, for the analysis, comparison and search of digital reconstructions of neuronal morphologies. For the quantitative characterization of neuronal morphology, LM computes a large number of neuroanatomical parameters from 3D digital reconstruction files starting from and combining a set of core metrics. After more than six years of development and use in the neuroscience community, LM enables the execution of commonly adopted analyses as well as of more advanced functions, including: (i) extraction of basic morphological parameters, (ii) computation of frequency distributions, (iii) measurements from user-specified subregions of the neuronal arbors, (iv) statistical comparison between two groups of cells and (v) filtered selections and searches from collections of neurons based on any Boolean combination of the available morphometric measures. These functionalities are easily accessed and deployed through a user-friendly graphical interface and typically execute within few minutes on a set of 20 neurons. The tool is available for either online use on any Java-enabled browser and platform or may be downloaded for local execution under Windows and Linux.

Proper citation: L-Measure (RRID:SCR_003487) Copy   

•   Source: SciCrunch Registry

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

Software containerized environments for reproducible neuroimaging. Part of ReproNim - Center for Reproducible Neuroimaging Computation. DataLad dataset with collection of popular computational tools provided within ready to use containerized environments.

Proper citation: ReproNim/containers (RRID:SCR_018467) Copy   

•   Source: SciCrunch Registry

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

Course provides training for reproducible analyses of Adolescent Brain Cognitive Development Study data. Designed to provide comprehensive background to ABCD study while delivering hands on instruction on reproducible ReproNim workflows and outcomes.

Proper citation: ABCD-ReproNim Course (RRID:SCR_018911) Copy   

•   Source: SciCrunch Registry