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http://www.harvard.edu/

Institution of higher education in the United States. Private Ivy League research university in Cambridge, Massachusetts.

Proper citation: Harvard University; Cambridge; United States (RRID:SCR_011273) Copy   

•   Source: SciCrunch Registry

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

Based on JIST and MIPAV, this pipeline combines structural magnetic resonance data with diffusion tensor imaging to estimate a connectome, which is a comprehensive description of the wiring diagram of the brain.

Proper citation: MR Connectome Automated Pipeline (RRID:SCR_002252) Copy   

•   Source: SciCrunch Registry

http://www.incf.org/

Independent international facilitator catalyzing and coordinating global development of neuroinformatics aiming to advance data reuse and reproducibility in global brain research. Integrates and analyzes diverse data across scales, techniques, and species to understand brain function and positively impact the health and well being of society.

Proper citation: International Neuroinformatics Coordinating Facility (RRID:SCR_002282) Copy   

•   Source: SciCrunch Registry

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

An EEGLAB plugin which adaptively estimates and removes sinusoidal artifacts from independent component analysis (ICA) components or scalp channels using a frequency-domain (multi-taper) regression technique with a Thompson F-statistic for identifying significant sinusoidal artifacts. This approach has been advocated by Partha Mitra and Hemant Bokil (Observed Brain Dynamics, Chapter 7.3.4., 2007) and CleanLine utilizes modified routines from the Mitra Lab's Chronux Toolbox (www.chronux.org). Sinusoidal noise can be a prominent artifact in recorded electrophysiological data. This can stem from AC power line fluctuations (e.g. 50/60 Hz line noise + harmonics), power suppliers (e.g. in medical equipment), fluorescent lights, etc. Notch filtering is generally undesirable due to creation of band-holes, and significant distortion of frequencies around the notch frequency (as well as phase distortion at other frequencies and Gibbs rippling in the time-domain).

Proper citation: CleanLine (RRID:SCR_002233) Copy   

•   Source: SciCrunch Registry

http://www.pstnet.com/hardware.cfm?ID=92

MRI Simulator that provides a realistic approximation of an actual MRI scanner to allow habituation and training of participants in an environment less daunting than a real scanner. Special populations such as children, the elderly, and psychiatric patients, are often prone to claustrophobia and anxiety in the bore of a magnet, and consequently have a much higher rate of terminating the experiment or scan session before its completion. Some centers that have dealt with these populations estimate a 50%-80% failure rate. With the use of the MRI Simulator this failure rate can often be reduced below 5%, improving cost effectiveness.

Proper citation: PSTNet: MRI Simulator (RRID:SCR_002460) Copy   

•   Source: SciCrunch Registry

http://www.brain.org.au/software/

A collection of tools that generate numerical fiber structures with the complexity of human white matter and simulate Diffusion-Weighted MR images that would arise from them. Its primary use is to enable the testing of tracking algorithms

Proper citation: Numerical Fibre Generator (RRID:SCR_002457) Copy   

•   Source: SciCrunch Registry

http://www.pstnet.com/hardware.cfm?ID=90

MRI Digital Projection System that uses Digital Light Processing (DLP) technology providing microsecond pixel rise times, outstanding contrast with all-digital fiber optic control that allows you to project crystal clear, sharp images. Includes: * High resolution (1024x768) DLP Projector with RF filtered enclosure, custom lens assembly, digital video (DVI) over fiber, high flow fans, internal thermal sensor * Control room device to perform DVI to Fiber conversion, remotely power down the projector, and allow use of projector remote control from control room * 30 meter fiber optic cable that runs between the projector and projector control station * Heavy duty, magnet compatible, projector stand (assembly required) * Heavy duty, magnet compatible mirror stand with mirror (assembly required) * High resolution, lenticular pitch rear projection screen for high quality image reproduction * Optional VGA to DVI converter (native DVI video cards on Windows or Macintosh recommended)

Proper citation: MRI Digital Projection System (RRID:SCR_002486) Copy   

•   Source: SciCrunch Registry

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

This resouce will centralize development of tools for interaction with medical imaging data in immersive virtual environments (based on the Vizard platform).

Proper citation: Medical Image Processing and Visualization in Virtual Environments (RRID:SCR_001751) Copy   

•   Source: SciCrunch Registry

http://niftilib.sourceforge.net/pynifti/

PyNIfTI is no longer actively developed. At has been superseded by NiBabel -- a pure-Python package that provides everything that PyNIfTI could do, and a lot more. The PyNIfTI module is a Python interface to the NIfTI I/O libraries. Using PyNIfTI, one can easily read and write NIfTI and ANALYZE images from within Python. The NiftiImage class provides pythonic access to the full header information and for a maximum of interoperability the image data is made available via NumPy arrays.

Proper citation: PyNIfTI (RRID:SCR_000693) Copy   

•   Source: SciCrunch Registry

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

A cross platform, open source gesture tracking program. You launch it from the web, and use it to streamline the way you communicate with the computer. It allows for a more natural method of issuing commands than with keyboard shortcuts or GUI buttons. GesTr supports simple XML files to customize recognized gestures and their corresponding actions. GesTr also has experimental support for the Wii Remote used with an infrared pen as an alternative input device.

Proper citation: GesTr (RRID:SCR_000857) Copy   

•   Source: SciCrunch Registry

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

A loose collection of programs and configuration options that intend to make working with data more transparent to formats. Currently available is a basic specification for NIfTI-1 for the UNIX file command and proof of concept code for the concept of treating data as an abstract concept and instantiating physical instances on demand.

Proper citation: Data Format Tools (RRID:SCR_000856) Copy   

•   Source: SciCrunch Registry

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

Software tool for MRI intensity standardization by aligning histograms of higher dimensions. The methods defined in http://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2006/Jaeger06-ANM.pdf are implemented as and ITK filter.

Proper citation: VectorValuedHistogramNormalizer (RRID:SCR_000082) Copy   

•   Source: SciCrunch Registry

http://mousetracker.jbfreeman.net

A free, user-friendly software package that allows researchers to record and analyze hand movements traveling toward potential responses on the screen (via the x, y coordinates of the computer mouse). By looking at the dynamics of how participants' hand movements settle into a response alternative--and how they may be partially pulled toward other alternatives--researchers glean valuable information about real-time cognitive processing. It's like opening up a single reaction time into a continuous stream of rich cognitive output. MouseTracker has impressive temporal resolution, comparable to eye-tracking and event-related brain potential (ERP) measures. Experiments can incorporate images, letter strings, sounds, and videos. Once recorded, mouse trajectories can be visualized, averaged, and explored, and measures of attraction/curvature, complexity, velocity, and acceleration can be computed. Precise characterizations of mouse trajectories' temporal and spatial dynamics are available, and these can shed light on a variety of important empirical questions across psychology, cognitive science, and beyond.

Proper citation: MouseTracker (RRID:SCR_005979) Copy   

•   Source: SciCrunch Registry

http://nifti.nimh.nih.gov/

Coordinated and targeted service, training, and research to speed the development and enhance the utility of informatics tools related to neuroimaging. The initial focus will be on tools that are used in fMRI. If NIfTI proves useful in addressing informatics issues in the fMRI research community, it may be expanded to address similar issues in other areas of neuroimaging. Objectives of NIfTI * Enhancement of existing informatics tools used widely in neuroimaging research * Dissemination of neuroimaging informatics tools and information about them * Community-based approaches to solving common problems, such as lack of interoperability of tools and data * Unique training activities and research career development opportunities to those in the tool-user and tool-developer communities * Research and development of the next generation of neuroimaging informatics tools

Proper citation: Neuroimaging Informatics Technology Initiative (RRID:SCR_003141) Copy   

•   Source: SciCrunch Registry

http://www.ppmi-info.org/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://www.slicer.org/slicerWiki/index.php/Slicer4:VMTK

Provides series of modules which enable functions of Vascular Modeling Toolkit in 3D Slicer. Functionality includes vessel enhancement filtering, level set segmentation, centerline computation, network extraction and branch splitting.VMTK is available through the extension manager for 3D Slicer from version 4.6.2. Main difference to Slicer3 version is that now all VMTK modules come as one extension bundle. This should enhance the installation experience for users.

Proper citation: VMTK in 3D Slicer (RRID:SCR_002579) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/bctnet/comparison/nbs

Matlab toolbox for testing hypotheses about the human connectome. NBS has been widely used to identify connections and networks comprising the connectome that are associated with an experimental effect or a between-group difference. User provides a series of connectivity matrices from different cohorts, or from the same subject during different experimental conditions. Connectivity matrices are inferred from neuroimaging data using other packages that, for example, count the number of tractography streamlines that interconnect each pair of regions (diffusion-MRI), or measure the extent of inter-regional correlation in BOLD response (fMRI). User specifies hypothesis to be tested at every connection with the general linear model. Features include: graphical user interface; NBSview, a basic network viewer modeled on SPMresults; exchange blocks for repeated measures; options to measure network size with intensity or extent; false discovery rate (FDR) option. Developed by Zalesky, Fornito, Cocchi and Bullmore.

Proper citation: Network Based Statistic Toolbox (RRID:SCR_002454) Copy   

•   Source: SciCrunch Registry

http://software.incf.org/

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   

•   Source: SciCrunch Registry

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

This package is a set of three slicer modules which together are able to compute a DWI Atlas given a set of DWI''s. The modules included are: # A Groupwise Registration module -> compute''s a deformation field for each DWI, using, for example, FA maps as input # Warp DWI module -> used to warp each DWI using the deformation from (1) # DWI Averager -> used to average the set of warped DWI''s producing the final DWI Atlas

Proper citation: Create DWI Atlas (RRID:SCR_009455) Copy   

•   Source: SciCrunch Registry