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

Pipeline developed for delineating the association between multiple diffusion properties along major white matter fiber bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these white matter tract properties in various diffusion tensor imaging studies. FADTTS can be used to facilitate understanding of normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles. The advantages of FADTTS compared with the other existing approaches are that they are capable of modelling the structured inter-subject variability, testing the joint effects, and constructing their simultaneous confidence bands.

Proper citation: Functional Analysis of Diffusion Tensor (RRID:SCR_008888) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://www.bci2000.org/

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   

•   Source: SciCrunch Registry

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

A novel C++ based application developped at UNC-Chapel Hill that performs automatic brain tissue classification and structural segmentation. AutoSeg is designed for use with human and non-human primate pediatric, adolescent and adult data. AutoSeg uses a BatchMake pipeline script that includes the main steps of the framework entailing N4 bias field correction, rigid registration to a common coordinate image, tissue segmentation, skull-stripping, intensity rescaling, atlas-based registration, subcortical segmentation and lobar parcellation, regional cortical thickness and intensity statistics. AutoSeg allows efficient batch processing and grid computing to process large datasets and provides quality control visualizations via Slicer3 MRML scenes.

Proper citation: AutoSeg (RRID:SCR_009438) Copy   

•   Source: SciCrunch Registry

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

A collection of data processing and image analysis tools for data in BXH or XCEDE format. This includes data format encapsulation/conversion, event-related analysis, QA tools, and more. These tools form the basis of the fBIRN QA procedures and are also distributed as part of the fBIRN Data Upload Scripts.

Proper citation: BXH/XCEDE Tools (RRID:SCR_009439) Copy   

•   Source: SciCrunch Registry

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

A set of deformable modeling algorithms for shape analysis and structure-specific normalization. Applications of cm-reps include structure-specific fMRI analysis, DTI analysis, and structural brain mor

Proper citation: cmrep (RRID:SCR_009434) Copy   

•   Source: SciCrunch Registry

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

Resting state functional magnetic resonance imaging (R-fMRI) datasets from 539 individuals with autism spectrum disorder (ASD) and 573 typical controls. This initiative involved 16 international sites, sharing 20 samples yielding 1112 datasets composed of both MRI data and an extensive array of phenotypic information common across nearly all sites. This effort is expected to facilitate discovery science and comparisons across samples. All datasets are anonymous, with no protected health information included.

Proper citation: ABIDE (RRID:SCR_003612) Copy   

•   Source: SciCrunch Registry

http://sccn.ucsd.edu/wiki/BCILAB

Open Source MATLAB toolbox and EEGLAB plugin for the design, prototyping, testing, experimentation with, and evaluation of Brain-Computer Interfaces (BCIs), and other systems in the same computational framework. It facilitates the design and development of new methods for cognitive state estimation and their use in both offline data analysis and real-time applications. BCILAB includes an easily extensible collection of currently over 100 methods from the literature (covering signal processing, machine learning and BCI-specific methods). Aside from supporting advanced BCI research, a special aim of BCILAB is to facilitate the adoption of machine learning and advanced statistical modeling for functional neuroimaging purposes in tandem with the EEGLAB platform. The toolbox offers multiple different interfaces which link to the same backend functionality, including a GUI, scripting support (MATLAB-based), APIs for real-time processing, and a variety of extension component interfaces. MATLAB programming is not strictly necessary, as most BCILAB features can be accessed from the GUI, although it is required for batch scripting and custom extensions. The strength of MATLAB-based software lies in its resources for leading-edge scientific computing, as well as in the good support for rapid prototyping, but BCI systems developed in it can be used for real-time out-of-lab experimentation, and can in principle be deployed without the need for a MATLAB license. However, due to the complexity and overhead of the MATLAB environment, the system is best used as a research platform, and not as a product development environment -- end-user software is ideally re-implemented in a compiled language, after a suitable approach has been identified and extensively tested. The process of identifying and testing an approach involves more than just computation, but also data exploration and investigation - an area which is helped by the deep integration with the EEGLAB platform. In the future, this integration will be further strengthened, bringing rich statistical learning and signal processing into routine EEG analysis workflows. The toolbox has been developed by C. Kothe at the Swartz Center, inspired by the preceding PhyPA BCI toolbox created by C. Kothe and T. Zander at the Chair for Human-Machine Systems, Berlin Institute of Technology.

Proper citation: BCILAB (RRID:SCR_007013) Copy   

•   Source: SciCrunch Registry

http://www.remedyinformatics.com/

Software to harmonize the data that you have in different Excel files, databases, repositories, biospecimen applications, etc. and maps it to one common registry. Remedy Informatics' platform aggregates data from multiple sources, harmonizes the data via Ontology, and provides data visualization and pattern recognition and querying tools.

Proper citation: Registry Builder Data Harmonization and Aggregation Tool (RRID:SCR_006559) Copy   

•   Source: SciCrunch Registry

http://www.sr-research.com

THIS RESOURCE IS NO LONGER AVAILABLE,documented on February 1st, 2022. Instrument supplier providing eye tracking capabilities for behavioral labs as well as for MRI, MEG, and EEG research environments.

Proper citation: SR Research EyeLink Eye Trackers (RRID:SCR_009602) Copy   

•   Source: SciCrunch Registry

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

A free collection of MRI brain images for testing segmentation algorithms. It is available for download to assess the accuracy, reproducibility and sensitivity of MRI segmentation software. It includes data from infants and adults as well as patients with Alzheimer's disease.

Proper citation: Brain Segmentation Testing Protocol (RRID:SCR_009445) Copy   

•   Source: SciCrunch Registry

https://github.com/BRAINSia/BRAINSTools/tree/master/TestData

About 1.2GB of anonymized imaging data of many different file formats used by the BRAINS suite of tools (BRAINSFit, GTRACT, BRAINS, BRAINSTracer... and others) as a common set of anonymized data for nightly regression testing.

Proper citation: BRAINSTestData (RRID:SCR_009517) Copy   

•   Source: SciCrunch Registry

http://www.fnirdevices.com

fNIR Imager 1100 is a new generation portable functional near-infrared (fNIR) imaging research tool capable of monitoring brain?s hemodynamics and thereby the cognitive state of the subject in natural environments. Neuroimaging Solution for Natural Environments: * fNIR is the only stand-alone and field-deployable technology able to determine localized brain activity. * fNIR can be readily integrated with other physiological and neurobehavioral measures that assess human brain activity, including eye tracking, pupil reflex, respiration and electrodermal activity. fNIR can also complement other techniques. * Studies have shown a positive correlation between a participant's performance and fNIR responses as a function of task load. * It has also been shown that fNIR can effectively monitor attention and working memory in real-life situations.

Proper citation: fNIR Devices (RRID:SCR_009623) Copy   

•   Source: SciCrunch Registry

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

A collection of 32-channel data from 14 subjects (7 males, 7 females) acquired using the Neuroscan software. Subjects are performing a go-nogo categorization task and a go-no recognition task on natural photographs presented very briefly (20 ms). Each subject responded to a total of 2500 trials. Data is CZ referenced and is sampled at 1000 Hz (total data size is 4Gb; more details are given later).

Proper citation: EEG human categorization data (RRID:SCR_009468) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/diffusion-data

An open-data initiative for the distributation of common datasets for the evaluation and validation of diffusion MRI processing methods. http://www.dkfz.de/en/medphysrad/projectgroups/dwi/DTI_projects.html#inhalt3

Proper citation: Diffusion MRI - In-vivo and Phantom Data (RRID:SCR_009464) Copy   

•   Source: SciCrunch Registry

https://vpixx.com/products/viewpixx-3d/

VIEWPixx /3D (VPixx Technologies) is a 1920x1080 resolution, 120 Hz, calibrated research-grade LCD monitor. It is designed for stereoscopic (3D) stimulus presentation and other high-dynamic vision-science paradigms where deterministic timing and synchronized I/O are critical. It pairs fast-response industrial TN LCD glass with a custom VPixx panel/video controller and a scanning direct-RGB LED backlight engineered to reduce motion artifacts/ghosting/crosstalk, and to improve spatial uniformity, while bypassing consumer “enhancement” processing for predictable experimental output. For stereoscopic workflows, VIEWPixx /3D supports 120 Hz frame-sequential 3D (60 Hz/eye) when used with 3DPixx active shutter glasses (RF emitter + glasses kit), and it can provide a dual-link DVI console output to mirror the participant's view without adding GPU load. The system is also a synchronized display + acquisition toolbox: integrated button-box interface, 24-channel TTL triggers, stereo audio I/O, and a full analog I/O subsystem are implemented on the same board as video control to enable microsecond-precision synchronization to video refresh—useful for EEG triggers, reaction-time tasks, and other timing-sensitive paradigms.In terms of bit depth, the VIEWPixx /3D is native 8 bits per colour, with support fot 10-bit resolution per RGB channel via custom video modes.

Proper citation: VPixx: VIEWPixx /3D (RRID:SCR_009646) Copy   

•   Source: SciCrunch Registry

http://www.pstnet.com/eprime.cfm

A suite of applications to fulfill all of your computerized experiment needs. Used by more than 15,000 professionals in the research community, E-Prime provides a truly easy-to-use environment for computerized experiment design, data collection, and analysis. E-Prime provides millisecond precision timing to ensure the accuracy of your data. E-Prime's flexibility to create simple to complex experiments is ideal for both novice and advanced users. The E-Prime suite of applications includes: * E-Studio ? Drag and drop graphical interface for experiment design * E-Basic ? Underlying scripting language of E-Prime * E-Run ? Once the experiment is generated with a single click, E-Run affords you the millisecond precision of stimulus presentation, synchronizations, and data collection. * E-Merge ? Merges your single session data files for group analysis * E-DataAid ? Data management utility * E-Recovery ? Recovers data files

Proper citation: E-Prime (RRID:SCR_009567) Copy   

•   Source: SciCrunch Registry

https://github.com/hjmjohnson/DTIPrep

DTIPrep performs a Study-specific Protocol based automatic pipeline for DWI/DTI quality control and preparation. This is both a GUI and command line tool. The configurable pipeline includes image/diffusion information check, padding/Cropping of data, slice-wise, interlace-wise and gradient-wise intensity and motion check, head motion and Eddy current artifact correction, and DTI computing.

Proper citation: DWI/DTI Quality Control Tool: DTIPrep (RRID:SCR_009562) Copy   

•   Source: SciCrunch Registry

http://www.paradigmexperiments.com

Software application for millisecond accurate experimental control for cognitive neuroscience, psychology and linguistics research. Presents text, images, sounds, movies, self-paced reading trials and rating scales. An integrated Python scripting API is available. Joystick and microphone response are available. Supports button boxes from PST, Cedrus, fORP and custom built response boxes. Paradigm can detect fMRI triggers through serial and parallel ports. Includes sample experiments that implement many of the most popular experiment designs., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Paradigm (RRID:SCR_009634) Copy   

•   Source: SciCrunch Registry

http://genome.sph.umich.edu/wiki/Mach2dat:_Association_with_MACH_output

Software that performs logistic regression, using imputed SNP dosage data and adjusting for covariates.

Proper citation: Mach2dat (RRID:SCR_009599) Copy   

•   Source: SciCrunch Registry