Tools   Select Another Resource Report Type

http://www.brain-connectivity-toolbox.net

A large selection of complex network measures in Matlab that are increasingly used to characterize structural and functional brain connectivity datasets. Several people have contributed to the toolbox, and if you wish to contribute with a new function or set of functions, please contact Olaf Sporns. All efforts have been made to avoid errors, but users are strongly urged to independently verify the accuracy and suitability of toolbox functions for the chosen application. Please report bugs or substantial improvements.

Proper citation: Brain Connectivity Toolbox (RRID:SCR_004841) Copy   

•   Source: SciCrunch Registry

http://www.biological-networks.org/p/outliers/

Software that performs a morphology-based approach for the automatic identification of outlier neurons based on neuronal tree structures. This tool was used by Zawadzki et al. (2012), who reported on and its application to the NeuroMorpho database. For the analysis, each neuron is represented by a feature vector composed of 20 measurements, which are projected into lower dimensional space with PCA. Bivariate kernel density estimation is then used to obtain a probability distribution for cells. Cells with high probabilities are understood as archetypes, while those with the small probabilities are classified as outliers. Further details about the method and its application in other domains can be found in Costa et al. (2009) and Echtermeyer et al. (2011). This version requires Matlab (Mathworks Inc, Natick, USA) and allows the user to apply the workflow using a graphical user interface.

Proper citation: DONE: Detection of Outlier NEurons (RRID:SCR_005299) Copy   

•   Source: SciCrunch Registry

http://ccr.coriell.org/Sections/Collections/NINDS/?SsId=10

Open resource of biological samples (DNA, cell lines, and other biospecimens) and corresponding phenotypic data to promote neurological research. Samples from more than 34,000 unique individuals with cerebrovascular disease, dystonia, epilepsy, Huntington's Disease, motor neuron disease, Parkinsonism, and Tourette Syndrome, as well as controls (population control and unaffected relatives) have been collected. The mission of the NINDS Repository is to provide 1) genetics support for scientists investigating pathogenesis in the central and peripheral nervous systems through submissions and distribution; 2) information support for patients, families, and advocates concerned with the living-side of neurological disease and stroke.

Proper citation: NINDS Repository (RRID:SCR_004520) Copy   

•   Source: SciCrunch Registry

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

Software toolbox to simplify and streamline mechanism of pre and post processing 2D brain image data. Neuroscience image processing and analysis utilities. Stand alone application that runs on all operating systems.

Proper citation: Nutil - Neuroimaging utilities (RRID:SCR_017183) Copy   

•   Source: SciCrunch Registry

http://www.mricro.com

Software tool as a cross-platform NIfTI format image viewer. Used for viewing and exporting of brain images. MRIcroGL is a variant of MRIcron.

Proper citation: MRIcron (RRID:SCR_002403) Copy   

•   Source: SciCrunch Registry

http://openneu.ro/metasearch

Web application search tool intended to help users find MRI data shared publicly on the Web, particularly from projects organized under the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data-sharing Initiative (INDI). Users can perform queries visually to select a cohort of participants with brain imaging data based on their demographics and phenotypic information and then link out to imaging measures.

Proper citation: MetaSearch (RRID:SCR_014751) Copy   

•   Source: SciCrunch Registry

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

An effort to provide a set of quasi-probabilistic atlases for established functional ROIs in the human neuroimaging literature. Many atlases exist for various anatomical parcellation schemes, such as the Brodmann areas, the structural atlases, tissue segmentation atlases, etc. To date, however, there is no atlas for so-called functional ROIs. Such fROIs are typically associated with an anatomical label of some kind (e.g. the _fusiform_ face area), but these labels are only approximate and can be misleading inasmuch as fROIs are not constrained by anatomical landmarks, whether cytoarchitectonic or based on sulcal and gyral landmarks. The goal of this project is to provide quasi-probabilistic atlases for fROIs that are based on published coordinates in the neuroimaging literature. This is an open-ended enterprise and the atlas can grow as needed. Members of the neuroscience and neuroimaging community interested in contributing to the project are encouraged to do so.

Proper citation: Functional ROI Atlas (RRID:SCR_009481) Copy   

•   Source: SciCrunch Registry

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

This atlas takes advantage of ultra-high resolution 7T MRI to provide unprecedented levels of detail on structures of the basal ganglia in-vivo. The atlas includes probability maps of the Subthalamic Nucleus (STh) using T2*-imaging. For now it has been created on 13 young healthy participants with a mean age of 24.38 (range: 22-28, SD: 2.36). We recently also created atlas STh probability maps from 8 middle-aged participants with a mean age of 50.67 (range: 40-59, SD: 6.63), and 9 elderly participants with a mean age of 72.33 (range: 67-77, SD: 2.87). You can find more details about the creation of these maps in the following papers: Young: http://www.ncbi.nlm.nih.gov/pubmed/22227131 Middle-aged & Elderly: http://www.ncbi.nlm.nih.gov/pubmed/23486960 Participating institutions are the Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, and the Cognitive Science Center Amsterdam, University of Amsterdam, the Netherlands.

Proper citation: Atlasing of the basal ganglia (RRID:SCR_009431) Copy   

•   Source: SciCrunch Registry

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

An atlas intended to provide accurate data in terms of specific uptake location to make the BP quantitation. The VOIs were manually drawn with software Analyze 9.0 (Mayo Clinic) in 18F-DOPA brain image after spatial normalization with a 18F-DOPA Template. Each striatum was divided into 6 sub-regions: ventral caudate, anterior dorsal caudate, posterior dorsal caudate, ventral putamen, anterior dorsal putamen and posterior dorsal putamen.

Proper citation: Striatal Subregional VOImap (RRID:SCR_014173) Copy   

•   Source: SciCrunch Registry

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

The Brain Coactivation Map describes all the coactivation networks in the human brain based on the meta-analysis of more than 5,400 neuroimaging articles (from NeuroSynth) containing more than 16,000 individual experiments. The map can be browsed interactively (CoactivationMap.app on GitHub) or queried from a shell using a command line tool (cmtool on GitHub).

Proper citation: Brain Coactivation Map (RRID:SCR_014172) Copy   

•   Source: SciCrunch Registry

http://www.dian-info.org/default.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. An international research partnership of leading scientists determined to understand a rare form of Alzheimers disease that is caused by a gene mutation and to establish a research database and tissue repository to support research on Alzheimers disease by other investigators around the world. One goal of DIAN is to study possible brain changes that occur before Alzheimers disease is expressed in people who carry an Alzheimers disease mutation. Other family members without a mutation will serve as a comparison group. People in families in which a mutation has been identified will be tracked in order to detect physical or mental changes that might distinguish people who inherited the mutation from those who did not. DIAN currently involves eleven outstanding research institutions in the United States, United Kingdom, and Australia. John C. Morris, M.D., Friedman Distinguished Professor of Neurology at Washington University School of Medicine in St. Louis, is the principal investigator of the project., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: DIAN - Dominantly Inherited Alzheimer Network (RRID:SCR_000812) Copy   

•   Source: SciCrunch Registry

http://mindboggle.info/data.html

Complete set of free, publicly accessible, downloadable atlases, templates, and individual manually labeled brain image data, the largest collection of publicly available, manually labeled human brains in the world! http://journal.frontiersin.org/article/10.3389/fnins.2012.00171/full

Proper citation: Mindboggle-101 atlases (RRID:SCR_002439) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/colin3t7t

High-field extension of the Colin27 single-subject atlas with additional high-resolution, quantitative, averaged scans at both 3T and 7T.

Proper citation: Colin 3T/7T High-resolution Atlas (RRID:SCR_000160) Copy   

•   Source: SciCrunch Registry

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

Symmetric atlas of the primate brain created using 18 cases of rhesus macaques aged 16-34 months. It includes the T1-weighted image (with and without skull), and also tissue segmentation probability maps (white matter, gray matter, CSF, rest), subcortical structures segmentation (amygdala, caudate, hippocampus, pallidus, putamen), and a lobar parcellation map. You can find more details about the creation of this atlas in the following paper : M. Styner, R. Knickmeyer, S. Joshi, C. Coe, S. J. Short, and J. Gilmore. Automatic brain segmentation in rhesus monkeys. In Proc SPIE Vol 6512, Medical Imaging, 2007, pp. 65122 L1-8

Proper citation: UNC Primate Brain Atlas (RRID:SCR_002570) Copy   

•   Source: SciCrunch Registry

http://www.med.unc.edu/bric/ideagroup/free-softwares/unc-infant-0-1-2-atlases

3 atlases dedicated for neonates, 1-year-olds, and 2-year-olds. Each atlas comprises a set of 3D images made up of the intensity model, tissue probability maps, and anatomical parcellation map. These atlases are constructed with the help of state-of-the-art infant MR segmentation and groupwise registration methods, on a set of longitudinal images acquired from 95 normal infants (56 males and 39 females) at neonate, 1-year-old, and 2-year-old.

Proper citation: UNC Infant 0-1-2 Atlases (RRID:SCR_002569) Copy   

•   Source: SciCrunch Registry

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

A 3D stereoscopic (anaglyph method) full brain functional connectivity atlas created using a parcellation atlas published by Craddock et al. (2012). Using 3D Slicer 3.6.3 and the two hundred Region of Interest (ROI) version of the Craddock atlas, 200 grayscale surface models were created using a z-stat threshold > 2.3, and each surface model was processed with a surface decimation algorithm, smoothed with the Taubin algorithm and without surface normals. For improved visualization of the functional connectivity networks and their relative anatomical position, the surface model of five subcortical anatomical structures (corpus callosum, bilateral caudate, pallidum, putamen, thalamus, amygdala and hippocampus) were included in SAIBN. These surfaces were created with 3D Slicer using the segmentation computed with Freesurfer v. 5.1. The viewer should use red-cyan glasses to see the 3D stereoscopic effect using 3D Slicer (version 3.6.3, http://www.slicer.org/pages/Special:SlicerDownloads).

Proper citation: Stereoscopic Atlas of Intrinsic Brain Networks (RRID:SCR_002568) Copy   

•   Source: SciCrunch Registry

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

A set of tools for deriving region of interest (ROI) atlases by whole brain clustering of task or resting state data. This resource also contains several atlases derived by parcellating publicly available resting state fMRI datasets. The initial release will include python scripts and ROI atlases developed to perform the analyses described in Craddock et. al., A whole brain fMRI atlas generated via spatially constrained spectral clustering, which is currently in revision in Human Brain Mapping. The scripts provide all of the tools necessary to derive an ROI atlases using spatially constrained Ncut spectral clustering. The scripts require python, numpy and scipy to run. Source code and parcellations now available! Go to http://ccraddock.github.io/cluster_roi/ for more information.

Proper citation: Spatially Constrained Parcellation (RRID:SCR_002198) Copy   

•   Source: SciCrunch Registry

http://datacite.labs.orcid-eu.org

Service (Beta) that allows users to search the DataCite Metadata Store, and add their research outputs including datasets, software, and others to their ORCID profile. This should increase the visibility of these research data, and will make it easier to use these data citations in applications that connect to the ORCID Registry. In addition, the service is also providing formatted citations in several popular citation styles, supports COinS, links to related resources, and displays the attached Creative Commons license where this information is available. The DataCite Metadata Store of course also contains many text documents from academic publishers and services such as figshare or PeerJ Preprints, and these works can also be claimed. This tool is a collaborative effort by ORCID, CrossRef and DataCite.

Proper citation: ODIN (RRID:SCR_001386) Copy   

•   Source: SciCrunch Registry

http://www.mouseconnectome.org/

Three-dimensional digital connectome atlas of the C57Black/6J mouse brain and catalog of neural tracer injection cases, which will eventually cover the entire brain. Serial sections of each case are available to view at 10x magnification in the interactive iConnectome viewer. The Image Gallery provides a glimpse into some of the highlights of their data set. Representative images of multi-fluorescent tracer labeling can be viewed, while more in depth examination of these and all other cases can be performed in the iConnectome viewer. Phase 1 of this project involves generating a physical map of the basic global wiring diagram by applying proven, state of the art experimental circuit tracing methods systematically, uniformly, and comprehensively to the structural organization of all major neuronal pathways in the mouse brain. Connectivity imaging data for the whole mouse brain at cellular resolution will be presented within a standard 3D anatomic frame available through the website and accompanied by a comprehensive searchable online database. A Phase 2 goal for the future will allow users to view, search, and generate driving direction-like roadmaps of neuronal pathways linking any and all structures in the nervous system. This could be looked on as a pilot project for more ambitious projects in species with larger brains, such as human, and for providing a reliable framework for more detailed local circuitry mapping projects in the mouse.

Proper citation: Mouse Connectome Project (RRID:SCR_004096) 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