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http://www.iit.edu/~mri/

Atlas that contains new anatomical, DTI, HARDI templates and probabilistic gray matter labels of the adult human brain in ICBM-152 space. Artifact-free MRI data from 72 human subjects was used in the development of the atlas. All diffusion MRI data collection was conducted using Turboprop, and spatial normalization was accomplished in a population-based fashion. A description of the contents of the atlas can be found in the Downloads link. NOTE: The files of the older IIT2 DTI Brain Template are still available. However, the new DTI template of the IIT Human Brain Atlas (v.3) is of superior quality and allows more accurate registration across subjects.

Proper citation: IIT Human Brain Atlas (RRID:SCR_009587) Copy   

•   Source: SciCrunch Registry

http://hermes.ctb.upm.es/

A toolbox for the Matlab environment designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. This toolbox may be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

Proper citation: HERMES (RRID:SCR_009584) Copy   

•   Source: SciCrunch Registry

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

A semi-automated software tool for dental plaque biofilm quantification in quantitative light-induced fluorescence (QLF) images.

Proper citation: BiofilmQuant (RRID:SCR_014088) Copy   

•   Source: SciCrunch Registry

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

Data sets from the atlasing of the basal ganglia (ATAG) consortium, which provides ultra-high resolution 7Tesla (T) magnetic resonance imaging (MRI) scans from young, middle-aged, and elderly participants. They include whole-brain and reduced field-of-view MP2RAGE and T2 scans with ultra-high resolution at a sub millimeter scale. The data can be used to develop new algorithms that help building new high-resolution atlases both in the basic and clinical neurosciences. They can also be used to inform the exact positioning of deep-brain electrodes relevant in patients with Parkinsons disease and neuropsychiatric diseases.

Proper citation: 7T Structural MRI scans ATAG (RRID:SCR_014084) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/r-spit/

Group ICA (Independent Component Analysis) was used to generate spatial templates for 12 common resting-state networks in 62 typically-developing children, ages 9-15. They have made these available for those that will find them useful for masking and spatial template matching procedures. Basic demographic data on the sample is provided along with the protocol used to generate the templates.

Proper citation: resting-state pediatric imaging template (RRID:SCR_009647) Copy   

•   Source: SciCrunch Registry

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

A software application developed to support computational anatomy and shape analysis. The capabilities of CAWorks include: interactive landmark placement to create segmentation (mask) of desired region of interest; specialized landmark placement plugins for subcortical structures such as hippocampus and amygdala; support for multiple Medical Imaging data formats, such as Nifti, Analyze, Freesurfer, DICOM and landmark data; Quadra Planar view visualization; and shape analysis plugin modules, such as Large Deformation Diffeomorphic Metric Mapping (LDDMM). Specific plugins are available for landmark placement of the hippocampus, amygdala and entorhinal cortex regions, as well as a browser plugin module for the Extensible Neuroimaging Archive Toolkit.

Proper citation: CAWorks (RRID:SCR_014185) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/erppcatoolkit/

This Matlab toolkit is a general purpose tool for editing, visualizing, and analyzing EEG data (both Event Related Potential - ERP and spectral) whose most recent version has been downloaded over 1000 times. Its three chief highlights are: 1) an optimized automatic artifact correction function that includes ICA correction for eye blinks and saccades. 2) Extensive support for easily conducting PCA and ICA through all stages of the procedure, including inspection of reconstituted waveforms and batch ANOVAs. 3) Implementation of robust ANOVAs, including McCarthy-Wood vector test. It has a graphical user interface for point and click usage and comes with an extensive illustrated tutorial. A description of the toolkit was published in Dien (2010) in Journal of Neuroscience Methods. It relies on both internal functions as well as borrowed functions from both EEGlab and FieldTrip.

Proper citation: ERP PCA Toolkit (RRID:SCR_013105) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/gsa-snp/

A tool for the gene-set (or pathway) analysis of a genome-wide association study result. It accepts a genome-wide list of SNPs and their association P-values. It summarizes the SNP P-values into nearby genes. The gene-by-gene summary results are then further summarized by gene-sets such as Gene Ontology, KEGG pathways, or user-created gene-sets. Various standardization and statistical tests can be performed and the resulting gene-sets that pass a significance level after multiple-testing correction are reported. The tool is written in Java and is available as a standalone version.

Proper citation: GSA-SNP (RRID:SCR_013109) Copy   

•   Source: SciCrunch Registry

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

Software that allows users to dynamically interact with multiple surfaces simultaneously. It is very useful for visualisation and comparison of 3D surfaces by also displaying their scalars or vectors attributes stored in the points, and allowing the user to simply modify the colormap. ShapePopulationViewer is available as an extension of 3D Slicer.

Proper citation: ShapePopulationViewer (RRID:SCR_014167) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/search/?type_of_search=group&q=wisconsin&sa.x=0&sa.y=0&sa=Search

Atlases enable alignment of individual scans to improve localization and statistical power of results, and allow comparison of results between studies and institutions. Set of multi subject atlas templates is constructed specifically for functional and structural imaging studies of rhesus macaque.

Proper citation: Rhesus Macaque Brain Atlases (RRID:SCR_017533) Copy   

•   Source: SciCrunch Registry

http://brainliner.jp

Portal and tools for sharing and editing neurophysiological and behavioral data for brain-machine interface research. Users can search for existing data or login with their Google, Facebook, or Twitter account and upload new data. Their main focus is on supporting brain-machine interface research, so we encourage users to not just provide recordings of brain activity data, but also information about stimuli, etc., so that statistical relationships can be found between stimuli and/or subject behavior and brain activity. The Matlab tools are for writing, reading, and converting Neuroshare files, the common file format. A free, open source desktop tool for editing neurophysiological data for brain-machine interface research is also available: https://github.com/ATR-DNI/BrainLiner Since data formats aren''''t standardized between programs and researchers, data and analysis programs for data cannot be easily shared. Neuroshare was selected as the common file format. Neuroshare can contain several types of neurophysiological data because of its high flexibility, including analog time-series data and neuronal spike timing. Some applications have plug-ins or libraries available that can read Neuroshare format files, thus making Neuroshare somewhat readily usable. Neuroshare can contain several types of neurophysiological data, but there were no easy tools to convert data into the Neuroshare format, so they made and are providing a Neuroshare Converter Library and Simple Converter using the library. In future work they will make and provide many more useful tools for data sharing. Shared experiments include: EMG signal, Takemiya Exp, Reconstruct (Visual image reconstruction from human brain activity using a combination of multi-scale local image decoders), SPIKE data, Speech Imagery Dataset (Single-trial classification of vowel speech imagery using common spatial patterns), Functional Multineuron Calcium Imaging (fMCI), Rock-paper-scissors (The data was obtained from subject while he make finger-form of rock/paper/scissors). They also have a page at https://www.facebook.com/brainliner where you can contact us

Proper citation: BrainLiner (RRID:SCR_004951) Copy   

•   Source: SciCrunch Registry

http://openneuro.org

Open platform for analyzing and sharing neuroimaging data from human brain imaging research studies. Brain Imaging Data Structure ( BIDS) compliant database. Formerly known as OpenfMRI. Data archives to hold magnetic resonance imaging data. Platform for sharing MRI, MEG, EEG, iEEG, and ECoG data.

Proper citation: OpenNeuro (RRID:SCR_005031) Copy   

•   Source: SciCrunch Registry

http://neurolex.org/wiki/Main_Page

A freely editable semantic wiki for community-based curation of the terms used in Neuroscience. Entries are curated and eventually incorporated into the formal NIFSTD ontology. NeuroLex also includes a Resource branch for community members to freely add neuroscience relevant resources that do not become part of NIFSTD ontology but rather make up the NIF Registry. As part of the NIF, we provide a simple search interface to many different sources of neuroscience information and data. To make this search more effective, we are constructing ontologies to help organize neuroscience concepts into category hierarchies, e.g., neuron is a cell. These categories provide the means to perform more effective searches and also to organize and understand the information that is returned. But an important adjunct to this activity is to clearly define all of the terms that we use to describe our data, e.g., anatomical terms, techniques, organism names. Because wikis provide an easy interface for communities to contribute their knowledge, we started the NeuroLex.

Proper citation: NeuroLex (RRID:SCR_005402) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/

Collection of resting state fMRI (R-fMRI) datasets from sites around world. It demonstrates open sharing of R-fMRI data and aims to emphasize aggregation and sharing of well-phenotyped datasets.

Proper citation: 1000 Functional Connectomes Project (RRID:SCR_005361) Copy   

•   Source: SciCrunch Registry

http://www.biological-networks.org/pubs/suppl/sinomo/

Analysis-tool which identifies singular node motifs in a network. Network nodes can be described by node-motifs. It is an improvement to the method described in Costa et al. (2009).

Proper citation: SINOMO (RRID:SCR_005286) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/adhd200/index.html#

A grassroots initiative dedicated to accelerating the scientific community''''s understanding of the neural basis of ADHD through the implementation of open data-sharing and discovery-based science. They believe that a community-wide effort focused on advancing functional and structural imaging examinations of the developing brain will accelerate the rate at which neuroscience can inform clinical practice. The ADHD-200 Global Competition invited participants to develop diagnostic classification tools for ADHD diagnosis based on functional and structural magnetic resonance imaging (MRI) of the brain. Applying their tools, participants provided diagnostic labels for previously unlabeled datasets. The competition assessed diagnostic accuracy of each submission and invited research papers describing novel, neuroscientific ideas related to ADHD diagnosis. Twenty-one international teams, from a mix of disciplines, including statistics, mathematics, and computer science, submitted diagnostic labels, with some trying their hand at imaging analysis and psychiatric diagnosis for the first time. The data for the competition was provided by the ADHD-200 Consortium. Consortium members from institutions around the world provided de-identified, HIPAA compliant imaging datasets from almost 800 children with and without ADHD. A phenotypic file including all of the test set subjects and their diagnostic codes can be downloaded. Winner is presented. The ADHD-200 consortium included: * Brown University, Providence, RI, USA (Brown) * The Kennedy Krieger Institute, Baltimore, MD, USA (KKI) * The Donders Institute, Nijmegen, The Netherlands (NeuroImage) * New York University Medical Center, New York, NY, USA (NYU) * Oregon Health and Science University, Portland, OR, USA (OHSU) * Peking University, Beijing, P.R.China (Peking 1-3) * The University of Pittsburgh, Pittsburgh, PA, USA (Pittsburgh) * Washington University in St. Louis, St. Louis, MO, USA (WashU)

Proper citation: ADHD-200 Sample (RRID:SCR_005358) Copy   

•   Source: SciCrunch Registry

http://cbrain.mcgill.ca/

A flexible software platform for distributed processing, analysis, exchange and visualization of brain imaging data. The expected result is a middleware platform that will render the processing environment (hardware, operating systems, storage servers, etc...) transparent to a remote user. Interaction with a standard web browser allows application of complex algorithm pipelines to large datasets stored at remote locations using a mixture of network available resources such as small clusters, neuroimaging tools and databases as well as Compute Canada's High Performance Computing Centers (HPC). Though the focus of CBRAIN is providing tools for use by brain imaging researchers, the platform is generalizable to other imaging domains, such as radiology, surgical planning and heart imaging, with profound consequences for Canadian medical research. CBRAIN expanded its concept to include international partners in the US, Germany and Korea. As of December 2010, GBRAIN has made significant progress with the original three partners and has developed new partners in Singapore, China, India, and Latin America. CBRAIN is currently deployed on 6 Compute Canada HPC clusters, one German HPC cluster and 3 clusters local to McGill University Campus, totaling more than 80,000 potential CPU cores.

Proper citation: CBRAIN (RRID:SCR_005513) Copy   

•   Source: SciCrunch Registry

http://www.cma.mgh.harvard.edu/iatr/

A centrally available listing of all image analysis tools that are available to the neuroscience community in order to facilitate the development, identification, and sharing of tools. It is hoped that this helps the tool developers to get their tools to a larger user community and to reduce redundancy (or at least utilize tool redundancy to facilitate optimal tool design) in tool development. This also helps tool users in identification of the existing tools for specific problems as they arise. The registry is designed to be self-moderated. This means that all tool entries are owned by some responsible party who enters the tool information, and keeps it up to date via the Web.

Proper citation: Internet Analysis Tools Registry (RRID:SCR_005638) Copy   

•   Source: SciCrunch Registry

http://slicer.org/

A free, open source software package for visualization and image analysis including registration, segmentation, and quantification of medical image data. Slicer provides a graphical user interface to a powerful set of tools so they can be used by end-user clinicians and researchers alike. 3D Slicer is natively designed to be available on multiple platforms, including Windows, Linux and Mac Os X. Slicer is based on VTK (http://public.kitware.com/vtk) and has a modular architecture for easy addition of new functionality. It uses an XML-based file format called MRML - Medical Reality Markup Language which can be used as an interchange format among medical imaging applications. Slicer is primarily written in C++ and Tcl.

Proper citation: 3D Slicer (RRID:SCR_005619) Copy   

•   Source: SciCrunch Registry

http://www.birncommunity.org/tools-catalog/human-imaging-database-hid/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented October 5, 2017.

Database management system developed to handle the increasingly large and diverse datasets collected as part of the MBIRN and FBIRN collaboratories and throughout clinical imaging communities at large. The HID can be extended to contain relevant information concerning experimental subjects, assessments of subjects, the experimental data collected, the experimental protocols, and other metadata normally included with experiments.

Proper citation: Human Imaging Database (RRID:SCR_006126) Copy   

•   Source: SciCrunch Registry