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http://www.nitrc.org/projects/ruby-nifti/

A library for handling NIfTI data in the Ruby programming language. Ruby NIfTI supports basic read and write access to NIfTI files, including basic and extended header information and image information. It doesn't attempt to touch the image data but it does provide access to qform and sform orientation matrices. It also provides a nice interface to get at NIfTI info from within Ruby.

Proper citation: Ruby NIfTI (RRID:SCR_014164) Copy   

•   Source: SciCrunch Registry

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

A collection of methods for comparing the performance of different image algorithms. These methods generate quantitative scores that measure divergences to a standard.

Proper citation: SCORE (RRID:SCR_014165) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/pca-scalar-mesh

An implementation of standard PCA algorithms for use on scalar or vector data sets. Kernel PCA is implemented in this class, where the data sets are scalar or vector valued functions assigned at each of the points in a PointSet. A Gaussian Distance Kernel class is provided with the PCA class.

Proper citation: Principal Components Analysis of Scalar, Vector, and Mesh Vertex Data (RRID:SCR_014163) Copy   

•   Source: SciCrunch Registry

http://ibvd.virtualbrain.org/

A database of brain neuroanatomic volumetric observations spanning various species, diagnoses, and structures for both individual and group results. A major thrust effort is to enable electronic access to the results that exist in the published literature. Currently, there is quite limited electronic or searchable methods for the data observations that are contained in publications. This effort will facilitate the dissemination of volumetric observations by making a more complete corpus of volumetric observations findable to the neuroscience researcher. This also enhances the ability to perform comparative and integrative studies, as well as metaanalysis. Extensions that permit pre-published, non-published and other representation are planned, again to facilitate comparative analyses. Design strategy: The principle organizing data structure is the "publication". Publications report on "groups" of subjects. These groups have "demographic" information as well as "volume" information for the group as a whole. Groups are comprised of "individuals", which also have demographic and volume information for each of the individuals. The finest-grained data structure is the "individual volume record" which contains a volume observation, the units for the observation, and a pointer to the demographic record for individual upon which the observation is derived. A collection of individual volumes can be grouped into a "group volume" observation; the group can be demographically characterized by the distribution of individual demographic observations for the members of the group.

Proper citation: Internet Brain Volume Database (RRID:SCR_002060) Copy   

•   Source: SciCrunch Registry

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

A set of tools for deriving region of interest (ROI) atlases by whole brain clustering of task or resting state data. This resource also contains several atlases derived by parcellating publicly available resting state fMRI datasets. The initial release will include python scripts and ROI atlases developed to perform the analyses described in Craddock et. al., A whole brain fMRI atlas generated via spatially constrained spectral clustering, which is currently in revision in Human Brain Mapping. The scripts provide all of the tools necessary to derive an ROI atlases using spatially constrained Ncut spectral clustering. The scripts require python, numpy and scipy to run. Source code and parcellations now available! Go to http://ccraddock.github.io/cluster_roi/ for more information.

Proper citation: Spatially Constrained Parcellation (RRID:SCR_002198) Copy   

•   Source: SciCrunch Registry

http://mindboggle.info/data.html

Complete set of free, publicly accessible, downloadable atlases, templates, and individual manually labeled brain image data, the largest collection of publicly available, manually labeled human brains in the world! http://journal.frontiersin.org/article/10.3389/fnins.2012.00171/full

Proper citation: Mindboggle-101 atlases (RRID:SCR_002439) Copy   

•   Source: SciCrunch Registry

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

Symmetric atlas of the primate brain created using 18 cases of rhesus macaques aged 16-34 months. It includes the T1-weighted image (with and without skull), and also tissue segmentation probability maps (white matter, gray matter, CSF, rest), subcortical structures segmentation (amygdala, caudate, hippocampus, pallidus, putamen), and a lobar parcellation map. You can find more details about the creation of this atlas in the following paper : M. Styner, R. Knickmeyer, S. Joshi, C. Coe, S. J. Short, and J. Gilmore. Automatic brain segmentation in rhesus monkeys. In Proc SPIE Vol 6512, Medical Imaging, 2007, pp. 65122 L1-8

Proper citation: UNC Primate Brain Atlas (RRID:SCR_002570) Copy   

•   Source: SciCrunch Registry

http://www.med.unc.edu/bric/ideagroup/free-softwares/unc-infant-0-1-2-atlases

3 atlases dedicated for neonates, 1-year-olds, and 2-year-olds. Each atlas comprises a set of 3D images made up of the intensity model, tissue probability maps, and anatomical parcellation map. These atlases are constructed with the help of state-of-the-art infant MR segmentation and groupwise registration methods, on a set of longitudinal images acquired from 95 normal infants (56 males and 39 females) at neonate, 1-year-old, and 2-year-old.

Proper citation: UNC Infant 0-1-2 Atlases (RRID:SCR_002569) Copy   

•   Source: SciCrunch Registry

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

A 3D stereoscopic (anaglyph method) full brain functional connectivity atlas created using a parcellation atlas published by Craddock et al. (2012). Using 3D Slicer 3.6.3 and the two hundred Region of Interest (ROI) version of the Craddock atlas, 200 grayscale surface models were created using a z-stat threshold > 2.3, and each surface model was processed with a surface decimation algorithm, smoothed with the Taubin algorithm and without surface normals. For improved visualization of the functional connectivity networks and their relative anatomical position, the surface model of five subcortical anatomical structures (corpus callosum, bilateral caudate, pallidum, putamen, thalamus, amygdala and hippocampus) were included in SAIBN. These surfaces were created with 3D Slicer using the segmentation computed with Freesurfer v. 5.1. The viewer should use red-cyan glasses to see the 3D stereoscopic effect using 3D Slicer (version 3.6.3, http://www.slicer.org/pages/Special:SlicerDownloads).

Proper citation: Stereoscopic Atlas of Intrinsic Brain Networks (RRID:SCR_002568) Copy   

•   Source: SciCrunch Registry

http://epilepsy.uni-freiburg.de/database

A comprehensive database for human surface and intracranial EEG data that is suitable for a broad range of applications e.g. of time series analyses of brain activity. Currently, the EU database contains annotated EEG datasets from more than 200 patients with epilepsy, 50 of them with intracranial recordings with up to 122 channels. Each dataset provides EEG data for a continuous recording time of at least 96 hours (4 days) at a sample rate of up to 2500 Hz. Clinical patient information and MR imaging data supplement the EEG data. The total duration of EEG recordings included execeeds 30000 hours. The database is composed of different modalities: Binary files with EEG recording / MR imaging data and Relational database for supplementary meta data.

Proper citation: EPILEPSIE database (RRID:SCR_003179) Copy   

•   Source: SciCrunch Registry

http://www.mouseconnectome.org/

Three-dimensional digital connectome atlas of the C57Black/6J mouse brain and catalog of neural tracer injection cases, which will eventually cover the entire brain. Serial sections of each case are available to view at 10x magnification in the interactive iConnectome viewer. The Image Gallery provides a glimpse into some of the highlights of their data set. Representative images of multi-fluorescent tracer labeling can be viewed, while more in depth examination of these and all other cases can be performed in the iConnectome viewer. Phase 1 of this project involves generating a physical map of the basic global wiring diagram by applying proven, state of the art experimental circuit tracing methods systematically, uniformly, and comprehensively to the structural organization of all major neuronal pathways in the mouse brain. Connectivity imaging data for the whole mouse brain at cellular resolution will be presented within a standard 3D anatomic frame available through the website and accompanied by a comprehensive searchable online database. A Phase 2 goal for the future will allow users to view, search, and generate driving direction-like roadmaps of neuronal pathways linking any and all structures in the nervous system. This could be looked on as a pilot project for more ambitious projects in species with larger brains, such as human, and for providing a reliable framework for more detailed local circuitry mapping projects in the mouse.

Proper citation: Mouse Connectome Project (RRID:SCR_004096) 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: VIEWPixx /3D (RRID:SCR_009646) Copy   

•   Source: SciCrunch Registry

http://www.birncommunity.org/current-users/morphometry-birn/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 4th,2023. Calibration data set of spoiled gradient-recalled echo magnetic resonance imaging data from five healthy volunteers (four males and one female) scanned twice at four sites having 1.5T systems from different vendors (Siemens, GE, Marconi Medical Systems) pooled by the Morphometry Testbed's (MBIRN). Some subjects were also scanned a single time at another site. One subject was only scanned twice at three sites (subject 73213384) and once at another site. For each subject, four Fast Low-Angle Shot (FLASH) scans with flip angles of 3, 5, 20, and 30 degrees were obtained in a single scan session, from which tissue proton density and T1 maps can be derived. These data were acquired to investigate various metrics of within-site and across-site reproducibility. The images have been defaced so that no facial features can be reconstructed from these data. The Morphometry Testbed (MBIRN) of the Biomedical Informatics Research Network (BIRN) focused on pooling and analyzing of neuroimaging data acquired at multiple sites. Specific applications include potential relationships between anatomical differences and specific memory dysfunctions, such as Alzheimer's disease. With the completion of the initial BIRN testbed phase, each of the original BIRN testbeds have now been retired in order to focus on new users in other biomedical domains.

Proper citation: Morphometry BIRN (RRID:SCR_000155) Copy   

•   Source: SciCrunch Registry

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

A reference MINC set of files that currently includes human head images only of standard modalities. The goal is to build a well curated collection of files that demonstrate the capabilities of MINC

Proper citation: MINC Example files (RRID:SCR_000859) Copy   

•   Source: SciCrunch Registry