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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.loni.usc.edu/Software/IO_Plugins

Decoders and encoders written in Java for the AFNI, ANALYZE, DICOM, ECAT, GE, MINC, NIFTI and other neuroimaging file formats.The plugins use Java Image I/O interfaces to read and write metadata and image data and can read and write AFNI, ANALYZE 7.5, DICOM, ECAT 7.2, GE 5.0, INTERFILE (including hrrt), MINC, NIFTI, and UCLA PACS file formats. All source code is provided and usage examples are included.

Proper citation: LONI Java Image I/O Plugins (RRID:SCR_008277) Copy   

•   Source: SciCrunch Registry

https://github.com/scidash/neuronunit

Software toolkit for data-driven validation of neuron and ion channel models using SciUnit. NeuronUnit implements an interface to several simulators and model description languages, handles test calculations according to domain standards, and enables automated construction of tests based on data from several major public data repositories.

Proper citation: NeuronUnit (RRID:SCR_015634) Copy   

•   Source: SciCrunch Registry

http://mialab.mrn.org/data/index.html

An MRI data set that demonstrates the utility of a mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12-71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described, provide a useful baseline for future investigations of brain networks in health and disease.

Proper citation: MIALAB - Resting State Data (RRID:SCR_008914) Copy   

•   Source: SciCrunch Registry

http://www.nmr.mgh.harvard.edu/DOT/resources/homer2/home.htm

Software matlab scripts used for analyzing fNIRS data to obtain estimates and maps of brain activation. Graphical user interface (GUI) for visualization and analysis of functional near-infrared spectroscopy (fNIRS) data.

Proper citation: Homer2 (RRID:SCR_009586) Copy   

•   Source: SciCrunch Registry

http://surfer.nmr.mgh.harvard.edu/fswiki/Tracula

Software tool developed for automatically reconstructing a set of major white matter pathways in the brain from diffusion weighted images using probabilistic tractography. This method utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual intervention with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. The trac-all script is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user''''s preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step. To explore all the options in running trac-all please refer to the trac-all wiki. In order to use this script to reconstruct tracts in Diffusion images, all the subjects in the dataset must have Freesurfer Recons.

Proper citation: TRACULA (RRID:SCR_013152) Copy   

•   Source: SciCrunch Registry

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

A software application developed to support computational anatomy and shape analysis. The capabilities of CAWorks include: interactive landmark placement to create segmentation (mask) of desired region of interest; specialized landmark placement plugins for subcortical structures such as hippocampus and amygdala; support for multiple Medical Imaging data formats, such as Nifti, Analyze, Freesurfer, DICOM and landmark data; Quadra Planar view visualization; and shape analysis plugin modules, such as Large Deformation Diffeomorphic Metric Mapping (LDDMM). Specific plugins are available for landmark placement of the hippocampus, amygdala and entorhinal cortex regions, as well as a browser plugin module for the Extensible Neuroimaging Archive Toolkit.

Proper citation: CAWorks (RRID:SCR_014185) Copy   

•   Source: SciCrunch Registry

http://becs.aalto.fi/en/research/bayes/drifter/

Model based Bayesian method for eliminating physiological noise from fMRI data. This algorithm uses image voxel analysis to isolate the cardiac and respiratory noise from the relevant data.

Proper citation: DRIFTER (RRID:SCR_014937) Copy   

•   Source: SciCrunch Registry

https://github.com/nebneuron/neural-ideal

Software package for extracting neural activity codes.

Proper citation: Neural Ideal (RRID:SCR_017448) Copy   

•   Source: SciCrunch Registry

https://github.com/Nevermore520/NeuronTools

Software tools for converting data files into persistence diagrams and distance matrices.

Proper citation: Neuron Tools (RRID:SCR_017450) Copy   

•   Source: SciCrunch Registry

http://web.mit.edu/spectroscopy/facilities/lbrc.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Biomedical technology research center that develops basic scientific understanding and new techniques required for advancing clinical applications of lasers and spectroscopy. LBRC merges optical spectroscopy, imaging, scattering, and interferometry techniques to study biophysics and biochemistry of healthy and diseased biological structures from subcellular to entire-organ scale.

Proper citation: Laser Biomedical Research Center (RRID:SCR_000106) Copy   

•   Source: SciCrunch Registry

http://www.raraf.org/

Biomedical technology research center dedicated for radiobiological research with available ionizing radiations such as protons, alpha particles, and neutrons. RARAF is well-established and highly user-friendly. The focus of RARAF is the development of high-throughput single-cell/single-particle microbeams, which can deliver defined amounts of ionizing radiation into individual cells with a spatial resolution of a few microns or better. The ability of a microbeam to put double strand break damage at any specific known location in a given cell has allowed new approaches to the study of damage signaling.

Proper citation: Radiological Research Accelerator Facility (RRID:SCR_001425) Copy   

•   Source: SciCrunch Registry

http://www.cmrr.umn.edu/

Biomedical technology research center that focuses on development of unique magnetic resonance (MR) imaging and spectroscopy methodologies and instrumentation for the acquisition of structural, functional, and biochemical information non-invasively in humans, and utilizing this capability to investigate organ function in health and disease. The distinctive feature of this resource is the emphasis on ultrahigh magnetic fields (7 Tesla and above), which was pioneered by this BTRC. This emphasis is based on the premise that there exists significant advantages to extracting biomedical information using ultrahigh magnetic fields, provided difficulties encountered by working at high frequencies corresponding to such high field strengths can be overcome by methodological and engineering solutions. This BTRC is home to some of the most advanced MR instrumentation in the world, complemented by human resources that provide unique expertise in imaging physics, engineering, and signal processing. No single group of scientists can successfully carry out all aspects of this type of interdisciplinary biomedical research; by bringing together these multi-disciplinary capabilities in a synergistic fashion, facilitating these interdisciplinary interactions, and providing adequate and centralized support for them under a central umbrella, this BTRC amplifies the contributions of each of these groups of scientists to basic and clinical biomedical research. Collectively, the approaches and instrumentation developed in this BTRC constitute some of the most important tools used today to study system level organ function and physiology in humans for basic and translational research, and are increasingly applied world-wide. CMRR Faculty conducts research in a variety of areas including: * High field functional brain mapping in humans; methodological developments, mechanistic studies, and neuroscience applications * Metabolism, bioenergetics, and perfusion studies of human pathological states (tumors, obesity, diabetes, hepatic encephalopathy, cystic fibrosis, and psychiatric disorders) * Cardiac bioenergetics under normal and pathological conditions * Automated magnetic field shimming methods that are critical for spectroscopy and ultrafast imaging at high magnetic fields * Development of high field magnetic resonance imaging and spectroscopy techniques for anatomic, physiologic, metabolic, and functional studies in humans and animal models * Radiofrequency (RF) pulse design based on adiabatic principles * Development of magnetic resonance hardware for high fields (e.g. RF coils, pre-amplifiers, digital receivers, phased arrays, etc.) * Development of software for data analysis and display for functional brain mapping.

Proper citation: Center for Magnetic Resonance Research (RRID:SCR_003148) Copy   

•   Source: SciCrunch Registry

https://github.com/ccipd/MRQy

Software quality assurance and checking tool for quantitative assessment of magnetic resonance imaging and computed tomography data. Used for quality control of MR imaging data.

Proper citation: MRQy (RRID:SCR_025779) Copy   

•   Source: SciCrunch Registry

https://github.com/Washington-University/HCPpipelines

Software package as set of tools, primarily shell scripts, for processing multi-modal, high-quality MRI images for the Human Connectome Project. Minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space.

Proper citation: HCP Pipelines (RRID:SCR_026575) Copy   

•   Source: SciCrunch Registry

https://github.com/ReproBrainChart

Open data resource for mapping brain development and its associations with mental health. Integrates data from 5 large studies of brain development in youth from three continents (N = 6,346). Bifactor models were used to create harmonized psychiatric phenotypes, capturing major dimensions of psychopathology. Neuroimaging data were carefully curated and processed using consistent pipelines in a reproducible manner.

Proper citation: Reproducible Brain Charts (RRID:SCR_027837) Copy   

•   Source: SciCrunch Registry

http://www.imagwiki.nibib.nih.gov/

Special interest group that brings together program officers who have a shared interest in applying modeling and analysis methods to biomedical systems. The meetings are formatted to facilitate an open discussion of what is currently being supported, and for planning future directions in these areas. At each meeting, time is allotted to hear focused presentations from one or two participants to discuss issues relating to modeling and analysis across the government agencies. Discussions also occur online, and participants are informed of talks, conferences and other activities of interest to the group. IMAG recognized that the modeling community is on the forefront of thinking across the biological continuum, rather than just focusing at one scale or level of resolution. In addition IMAG identified a strong desire among modelers to form multi-disciplinary partnerships across varied research communities. Overall Intent of IMAG through the MSM Consortium is: * To develop new methodologies that span across biological scales * To develop multiscale methodologies applicable to biomedical, biological and behavioral research * To develop methodologies within the local multidisciplinary team and within the larger Framework environment * To further promote multiscale modeling through model sharing This wiki contains information relevant to the IMAG (Interagency Modeling and Analysis Group) and the MSM (Multi-scale Modeling Consortium).

Proper citation: Interagency Modeling and Analysis Group and Multi-scale Modeling Consortium Wiki (RRID:SCR_008046) Copy   

•   Source: SciCrunch Registry

http://www.fz-juelich.de/ime/spm_anatomy_toolbox

A MATLAB toolbox which uses three dimensional probabilistic cytoarchitechtonic maps to correlate microscopic, anatomic and functional data of the cerebral cortex. Correlating the activation foci identified in functional imaging studies of the human brain with structural (e.g., cytoarchitectonic) information on the activated areas is a major methodological challenge for neuroscience research. We here present a new approach to make use of three-dimensional probabilistic cytoarchitectonic maps, as obtained from the analysis of human post-mortem brains, for correlating microscopical, anatomical and functional imaging data of the cerebral cortex. We introduce a new, MATLAB based toolbox for the SPM2 software package which enables the integration of probabilistic cytoarchitectonic maps and results of functional imaging studies. The toolbox includes the functionality for the construction of summary maps combining probability of several cortical areas by finding the most probable assignment of each voxel to one of these areas. Its main feature is to provide several measures defining the degree of correspondence between architectonic areas and functional foci. The software, together with the presently available probability maps, is available as open source software to the neuroimaging community. This new toolbox provides an easy-to-use tool for the integrated analysis of functional and anatomical data in a common reference space.

Proper citation: SPM Anatomy Toolbox (RRID:SCR_013273) Copy   

•   Source: SciCrunch Registry

https://www.nature.com/articles/s41467-018-03367-w

Nanodroplet processing platform for deep and quantitative proteome profiling of 10 to 100 mammalian cells. It enhances efficiency and recovery of sample processing by downscaling processing volumes.

Proper citation: nanoPOTS (RRID:SCR_017129) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/flowBin.html

A software package to combine flow cytometry data that has been multiplexed into multiple tubes with common markers between them. It establishes common bins across tubes in terms of the common markers, then determines expression within each tube for each bin in terms of the tube-specific markers.

Proper citation: flowBin (RRID:SCR_000051) Copy   

•   Source: SciCrunch Registry