Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://www.nitrc.org/projects/mriwatcher/
This simple visualization tool allows to load several images at the same time. The cursor across all windows are coupled and you can move/zoom on all the images at the same time. Very useful for quality control, image comparison.
Proper citation: MriWatcher (RRID:SCR_002318) Copy
http://www.nitrc.org/projects/neuroscope/
An advanced viewer for electrophysiological and behavioral data: it can display local field potentials (EEG), neuronal spikes, behavioral events, as well as the position of the animal in the environment. It also features limited editing capabilities.
Proper citation: NeuroScope (RRID:SCR_002455) Copy
http://www.bic.mni.mcgill.ca/software/N3/
The perl script nu_correct implements a novel approach to correcting for intensity non-uniformity in MR data that achieves high performance without requiring supervision. By making relatively few assumptions about the data, the method can be applied at an early stage in an automated data analysis, before a tissue intensity or geometric model is available. Described as Non-parametric Non-uniform intensity Normalization (N3), the method is independent of pulse sequence and insensitive to pathological data that might otherwise violate model assumptions. To eliminate the dependence of the field estimate on anatomy, an iterative approach is employed to estimate both the multiplicative bias field and the distribution of the true tissue intensities. Preprocessing of MR data using N3 has been shown to substantially improve the accuracy of anatomical analysis techniques such as tissue classification and cortical surface extraction.
Proper citation: MNI N3 (RRID:SCR_002484) Copy
http://www.kcl.ac.uk/iop/depts/neuroimaging/research/imaginganalysis/Software/rBET.aspx
A modified version of the Brain Extraction Tool (BET) that can process rodent brains.
Proper citation: Rodent Brain Extraction Tool (RRID:SCR_002538) Copy
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
http://www.tractor-mri.org.uk/
Software application that includes R packages for reading, writing and visualising magnetic resonance images stored in Analyze, NIfTI and DICOM file formats (DICOM support is read only). It also contains functions specifically designed for working with diffusion MRI and tractography, including a standard implementation of the neighbourhood tractography approach to white matter tract segmentation. A shell script is also provided to run experiments with TractoR without interacting with R.
Proper citation: TractoR: Tractography with R (RRID:SCR_002602) Copy
http://www.nitrc.org/projects/phycaa_plus/
Software algorithm that automatically estimates and removes physiological noise in BOLD fMRI data, including the effects of heartbeat and respiration. This algorithm (1) masks out high-variance CSF and vascular tracts that may otherwise confound analyses, and (2) regresses out noise timeseries in grey matter tissue, using an adaptive multivariate component decomposition (Canonical Autocorrelations Analysis). PHYCAA+ is an efficient, automated procedure that does NOT require external measures of physiology, nor does it require the user to manually identify noise components. Based on the peer-reviewed article: Churchill & Strother (2013). PHYCAA+: An Optimized, Adaptive Procedure for Measuring and Controlling Physiological Noise in BOLD fMRI. NeuroImage 82: 306-325
Proper citation: PHYCAA+: adaptive physiological noise correction for BOLD fMRI (RRID:SCR_002514) Copy
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
http://www.nitrc.org/projects/meshmetric3d/
Software visualization tool based on the VTK library. Its main feature is to measure and display surface-to-surface distance between two triangle meshes using user-specified uniform sampling. Offers all the basic tools to visualize meshes such as color, opacity, smoothing, down sampling or type of representation.
Proper citation: 3DMeshMetric (RRID:SCR_000043) Copy
http://www.nitrc.org/projects/cabn/
Construct and analyse brain network is a brain network visualization tool, which can help researchers to visualize construct and analyse resting state functional brain networks from different levels in a quick, easy and flexible way. Entrance parameter of construct and analyse brain network is export parameters of dparsf software.It would be greatly appreciated if you have any suggestions about the package or manual.
Proper citation: BrainNetworkConstructionAnalysisPlatform (RRID:SCR_000854) Copy
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
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
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
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
http://www.nitrc.org/projects/bnv/
Aa brain network visualization tool, which can help researchers to visualize structural and functional connectivity patterns from different levels in a quick, easy, and flexible way.
Proper citation: BrainNet Viewer (RRID:SCR_009446) Copy
Mindboggle (http://mindboggle.info) is open source software for analyzing the shapes of brain structures from human MRI data. The following publication in PLoS Computational Biology documents and evaluates the software: Klein A, Ghosh SS, Bao FS, Giard J, Hame Y, Stavsky E, Lee N, Rossa B, Reuter M, Neto EC, Keshavan A. (2017) Mindboggling morphometry of human brains. PLoS Computational Biology 13(3): e1005350. doi:10.1371/journal.pcbi.1005350
Proper citation: Mindboggle (RRID:SCR_002438) Copy
http://www.nitrc.org/projects/surfacestat/
Software tool for performing a per vertex statistical analysis across a population. The underlying statistical framework uses the R language.
Proper citation: BRAINSSurfaceStats (RRID:SCR_002582) Copy
http://www.loni.usc.edu/Software/LONI-Inspector
A Java application for reading, displaying, searching, comparing, and exporting metadata from medical image files: AFNI, ANALYZE, DICOM, ECAT, GE, Interfile, MINC, and NIFTI.
Proper citation: LONI Inspector (RRID:SCR_004923) Copy
http://www.ebire.org/hcnlab/software/cleave.html
A UNIX-style command-line program which quickly computes multifactorial ANOVAs for very large data sets with minimal memory use (without loading all of the data into memory). It has been used for fMRI analysis, e.g. CLEAVE adds the following to the standard ANOVA analyses: # Unlimited numbers of factors can be analyzed. # Factor Correlation and Unequal Variance Corrections # Treatment Magnitudes: omega^2, partial eta^2, and R^2 # A convenient Ranking of Factors based upon treatment magnitudes and significance levels. # Post-Hoc Significance Tests # Post-Hoc Power Table to gauge how many subjects will be needed to achieve significance. # Allows the use of Random Factors. # A Configuration File to make the program more tunable # A Histogram and Cell Line Diagrams: which help the user to detect outliers. # Associated MATLAB functions: port CLEAVE-style data sets in or out of MATLAB.
Proper citation: CLEAVE (RRID:SCR_007113) Copy
BCI2000 is a general-purpose system for brain-computer interface (BCI) and adaptive neurotechnology research. It can also be used for data acquisition, stimulus presentation, and brain monitoring applications. The mission of the BCI2000 project is to facilitate research and applications in the areas described. Their vision is that BCI2000 will become a widely used software tool for diverse areas of real-time biosignal processing. In order to achieve this vision, BCI2000 system is available for free for non-profit research and educational purposes. BCI2000 supports a variety of data acquisition systems, brain signals, and study/feedback paradigms. During operation, BCI2000 stores data in a common format (BCI2000 native or GDF), along with all relevant event markers and information about system configuration. BCI2000 also includes several tools for data import/conversion (e.g., a routine to load BCI2000 data files directly into Matlab) and export facilities into ASCII. BCI2000 also facilitates interactions with other software. For example, Matlab scripts can be executed in real-time from within BCI2000, or BCI2000 filters can be compiled to execute as stand-alone programs. Furthermore, a simple network-based interface allows for interactions with external programs written in any programming language. For example, a robotic arm application that is external to BCI2000 may be controlled in real time based on brain signals processed by BCI2000, or BCI2000 may use and store along with brain signals behavioral-based inputs such as eye-tracker coordinates. Because it is based on a framework whose services can support any BCI implementation, the use of BCI2000 provides maximum benefit to comprehensive research programs that operate multiple BCI2000 installations to collect data for a variety of studies. The most important benefits of the system in such situations are: - A Proven Solution - Facilitates Operation of Research Programs - Facilitates Deployment in Multiple Sites - Cross-Platform and Cross-Compiler Compatibility - Open Resource Sponsors: BCI2000 development is sponsored by NIH/NIBIB R01 and NIH/NINDS U24 grants. Keywords: General, Purpose, Systems, Brain, Computer, Interface, Research, Application, Brain, Diverse, Educational, Laboratory, Software, Network, Signals, Behavioral, Eye, Tracker,
Proper citation: Brain Computer Interface 2000 Software Package (RRID:SCR_007346) Copy
Can't find your Tool?
We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.
Welcome to the RRID Resources search. From here you can search through a compilation of resources used by RRID and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that RRID has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on RRID then you can log in from here to get additional features in RRID such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into RRID you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the sources that were queried against in your search that you can investigate further.
Here are the categories present within RRID that you can filter your data on
Here are the subcategories present within this category that you can filter your data on
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.