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.
Open source application to allow the presentation of stimuli and collection of data for a wide range of neuroscience, psychology and psychophysics experiments. It is intended as a free, powerful alternative to Presentation or e-Prime.
Proper citation: PsychoPy (RRID:SCR_006571) Copy
http://www.uzh.ch/keyinst/loreta
Software package for functional imaging of human brain. Used to compute three dimensional distribution of electric neuronal activity from non-invasive measurements of scalp electric potential differences with high time resolution in millisecond range. Non-invasive intracranial time series are used for studying functional dynamic connectivity.. Current software version includes two new, improved variants of the original method: standardized (sLORETA) and exact (eLORETA). The new methods are characterized by exact localization when tested with point sources. Due to the fact that these methods are multivariate tomographies that are solutions to the inverse EEG problem, and that they are linear in nature, they will produce a low spatial resolution image for any distribution of activity. This property is not shared by naive one-at-a-time single dipole techniques.
Proper citation: Low Resolution Electromagnetic Tomography (RRID:SCR_007077) Copy
A Python package intended to ease statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run. Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. This Python-based, cross-platform, open-source software toolbox software toolbox for the application of classifier-based analysis techniques to fMRI datasets makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages.
Proper citation: PyMVPA (RRID:SCR_006099) Copy
An observational longitudinal clinical study partnership to identify and validate biomarkers of Parkinson disease (PD) progression and provide easy and open web-based access to the comprehensive set of correlated clinical data and biospecimens, information, and biosamples acquired from PD and age and gender matched healthy control subjects to the research community. The data and specimens have been collected in a standardized manner under strict protocols and includes clinical (demographic, motor and non-motor, cognitive and neurobehavioral), imaging (raw and processed MRI, SPECT and DAT), and blood chemistry and hematology subject assessments and biospecimen inventories (serum, plasma, whole blood, CSF, DNA, RNA and urine). All data are de-identified to protect patient privacy. PPMI will be carried out over five years at 21 clinical sites in the United States and Europe and requires the participation of 400 Parkinson's patients and 200 control participants. The PPMI database provides researchers with access to correlated clinical and imaging data, along with annotated biospecimens, all available within an open access system that encourages data sharing (http://www.ppmi-info.org/access-data-specimens/). The website hosts an Ongoing Analysis section to keep the scientific community apprised of analyses being completed, in hopes of stimulating collaborations between researchers who are using PPMI data and specimens.
Proper citation: Parkinson's Progression Markers Initiative (RRID:SCR_006431) Copy
http://www.nitrc.org/projects/cmind_2014/
A database that contains brain imaging data collected on 3T MRI scanners from over 200 normally developing healthy children from birth to 18 years. The imaging data stored in the C-MIND database are DTI, HARDI, 3DT1W, 3DT2W, concurrent ASL-BOLD scans during two language tasks (Stories and Sentence-Picture Matching), Resting State fMRI and Baseline ASL scans.
Proper citation: C-MIND Database (RRID:SCR_014094) Copy
http://www.nitrc.org/projects/imeka_tracto
A diffusion MRI service that handles the processing of diffusion data from raw data to structural connectivity. They provide high angular resolution (HARDI) reconstruction from DTI data with at least 20 gradient directions acquisitions.
Proper citation: Imeka Tractography Service (RRID:SCR_014124) Copy
http://www.nitrc.org/projects/jhucis_pedatlas/
Anatomical atlases constructed by Computational Anatomy of Johns Hopkins University for analysis of shape vectors. The atlases were generated from segmented hippocampal and amygdala structures in acquired populations of children, adolescents and young adults in neuroimaging studies of major depression disorder (MDD) at Washington University at St Louis.
Proper citation: Atlases of amygdala and hippocampus for pediatric populations (RRID:SCR_014085) Copy
http://www.nitrc.org/projects/crl_fetal_atlas
An atlas of of the fetal brain from MRI of normal fetuses scanned prenatally generated using a mathematical framework. The atlas shows the inter-subject anatomic variability of the fetal brain over the fetal brain growth period and is currently available between 27 weeks gestational age to 35 weeks. It has been constructed following an unbiased minimum distance template estimation approach which utilizes symmetric diffeomorphic deformation and the cross-correlation (CC) similarity metric integrated with kernel regression in age.
Proper citation: CRL Unbiased and Deformable Spatiotemporal Atlas of the Fetal Brain (RRID:SCR_014176) Copy
http://www.nitrc.org/projects/brainarteries/
Stereotactic atlases with probabilistic values describing the location of the main cerebral arteries. The data collected are from the COBRA study as described in "COBRA: A prospective multimodal imaging study of dopamine, brain structure and function, and cognition" by Nevalainen et al.
Proper citation: Umea Brain Arteries (RRID:SCR_014752) Copy
http://www.nitrc.org/projects/whs-sd-atlas/
Open access volumetric atlas of anatomical delineations of rat brain based on structural contrast in isotropic magnetic resonance and diffusion tensor images acquired ex vivo from 80 day old male Sprague Dawley rat at Duke Center for In Vivo Microscopy. Spatial reference is provided by Waxholm Space coordinate system. Location of bregma and lambda are identified as anchors towards stereotaxic space. Application areas include localization of signal in non structural images. Atlas, MRI and DTI volumes, and diffusion tensor data are shared in NIfTI format.
Proper citation: Waxholm Space Atlas of the Sprague Dawley Rat Brain (RRID:SCR_017124) Copy
http://www.nitrc.org/projects/reliability/
Data collected from subjects scanned 3 times (V1, V2, V3), with V1 and V2 on a scanner, V3 on another scanner in another site. Resting state blood oxygenation level dependent functional MRI (BOLD fMRI), pseudo continuous arterial spin labeling (pCASL), and high resolution 3D T1 imaging were performed under eyes open (EO) and eyes closed (EC) conditions.
Proper citation: Intra- and inter-scanner reliability of RS-fMRI BOLD and ASL with eyes closed vs. eyes open (RRID:SCR_016935) Copy
http://www.nitrc.org/projects/miitra/
Atlas for studies of older adult brain. Includes T1-weighted template of older adult brain and tissue probability maps. Exhibits high image sharpness, provides higher inter-subject spatial normalization accuracy compared to other standardized templates and similar normalization accuracy to well-constructed study-specific templates.
Proper citation: MIITRA atlas (RRID:SCR_017566) Copy
http://www.nitrc.org/projects/onprc18_atlas/
Atlas includes co-registered templates constructed from MR images frequently used to characterize macroscopic brain structure T2/SPACE and T1/MP-RAGE, and diffusion tensor imaging template.
Proper citation: ONPRC18 Multimodal MRI Atlas (RRID:SCR_019073) Copy
A software program for source imaging Magnetoencephalographic data. Now MEG tools has added Imaged Coherence mapping, Talairach and MNI coordinates, Grainger Causality. MEG Tools also includes MR-FOCUSS, ECD, Beamformers and many other useful MEG tools. This is a Matlab-based software module that is used to image MEG data onto a patient's MRI. This software imports all MEG manufacture's data (4D-Neuroimaging/BTi, CTF and Neuromag/Elekta).
Proper citation: MEG Tools (RRID:SCR_000661) Copy
http://www.loni.usc.edu/Software/Debabeler
Software to manage the conversion of imaging data from one file format and convention to another. It consists of a graphical user interface to visually program the translations, and a data translation engine to read, sort and translate the input files, and write the output files to disk. The data translation engine: (1) Reads metadata from a set of image files on disk to identify the source that produced each file; (2) Groups the image files into user-defined collections using image metadata values; (3) Translates each image file collection by reading metadata and pixel data and mapping the data into the appropriate output file format through a programmable set of connected modules. The Debabeler uses the Java Image I/O Plugin Architecture to read and write a wide variety of common medical image file formats, including ANALYZE, MINC, and most variations of DICOM.
Proper citation: LONI Debabeler (RRID:SCR_001160) Copy
https://github.com/BRAINSia/BRAINSTools
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 23,2023. A suite of tools to generate the cortical surface of the brain. The surface is generated in the middle of grey matter and can be used to measure surface features including cortical depth and curvature.
Proper citation: BRAINSCortex (RRID:SCR_001082) Copy
Software repository that makes it easy for neuroscientists to find, use and share software tools. The Software Center is accessible to everyone: you can browse and download available software tools without registering. However, by creating an account, you will be able to post comments, and request to join development teams. The INCF Software Center and the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) are sharing content. Software tools hosted by NITRC also appear at the INCF Software Center. Your software tool will be available to all users of the Software Center. You will be able to upload documentation, executables and related files; track use of your software; create a wiki; and establish a development team. Registered Software Center users will be able to comment on and post reviews about your software, and can request to join your development team. INCF's vision of the Software Center is that it will become a communication enabler for software users as well as developers. Accordingly, future system features to be added include communication and collaboration functions. We also plan to include support services to allow software developers organize their software, track the use, and receive feedback for further improvement and development. Further development of the Software Center will be strongly driven by the user needs. Please let us know what features you would like to see added.
Proper citation: INCF Software Center (RRID:SCR_002347) Copy
http://www.nitrc.org/projects/nitrcext/
Software repository of custom extensions to the GForge collaborative environment.
Proper citation: NITRC GForge Extensions (RRID:SCR_002495) Copy
http://labs.nri.ucsb.edu/reese/benjamin/SA3D.html
A user-friendly, graphical user interface (GUI) that allows statistical and visual manipulations of real and simulated three-dimensional spatial point patterns. The analyses use files containing sets of X, Y, Z coordinates. These point patterns are frequently coordinates of cells of specific cell classes within in volumes of tissue derived from microscopy analyses. The analyses are scale independent so spatial analyses of coordinates from larger and smaller scale distributions are possible. The software can also generate sample sets of X, Y, Z coordinates for program exploration and modeling purposes.
Proper citation: Spatial Analysis 3D (RRID:SCR_002563) Copy
http://www.nitrc.org/projects/ohbm_hack
A multi-day event hosted by the Organization for Human Brain Mapping which features collaborative and open neuroscience projects in data analysis and methods development. Locations change annually.
Proper citation: HBM Hackathon (RRID:SCR_014119) 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.