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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.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

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.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

https://osf.io/

Platform to support research and enable collaboration. Used to discover projects, data, materials, and collaborators helpful to your own research.

Proper citation: Open Science Framework (RRID:SCR_003238) 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://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://cocomac.g-node.org/main/index.php?

Online access (html or xml) to structural connectivity ("wiring") data on the Macaque brain. The database has become by far the largest of its kind, with data extracted from more than four hundred published tracing studies. The main database, contains data from tracing studies on anatomical connectivity in the macaque cerebral cortex. Also available are a variety of tools including a graphical simulation workbench, map displays and the CoCoMac-Paxinos-3D viewer. Submissions are welcome. To overcome the problem of divergent brain maps ORT (Objective Relational Transformation) was developed, an algorithmic method to convert data in a coordinate- independent way based on logical relations between areas in different brain maps. CoCoMac data is used to analyze the organization of the cerebral cortex, and to establish its structure- function relationships. This includes multi-variate statistics and computer simulation of models that take into account the real anatomy of the primate cerebral cortex. This site * Provides full, scriptable open access to the data in CoCoMac (you must adhere to the citation policy) * Powers the graphical interface to CoCoMac provided by the Scalable Brain Atlas * Sports an extensive search/browse wizard, which automatically constructs complex search queries and lets you further explore the database from the results page. * Allows you to get your hands dirty, by using the custom SQL query service. * Displays connectivity data in tabular form, through the axonal projections service. CoCoMac 2 was initiated at the Donders Institute for Brain, Cognition and Behaviour, and is currently supported by the German neuroinformatics node and the Computational and Systems Neuroscience group at the Juelich research institute.

Proper citation: CoCoMac (RRID:SCR_007277) Copy   

•   Source: SciCrunch Registry

http://www.oasis-brains.org/

Project aimed at making neuroimaging data sets of brain freely available to scientific community. By compiling and freely distributing neuroimaging data sets, future discoveries in basic and clinical neuroscience are facilitated.

Proper citation: Open Access Series of Imaging Studies (RRID:SCR_007385) Copy   

•   Source: SciCrunch Registry

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

A set of ImageJ plugins for fully automated measurement of neurite outgrowth in fluorescence microscopy images of cultured neurons. The plugin analyzes fluorescence microscopy images of neurites and nuclei of dissociated cultured neurons. Given user-defined thresholds, the plugin counts neuronal nuclei, and traces and measures neurite length. NeuriteTracer accurately measures neurite outgrowth from cerebellar, DRG and hippocampal neurons.

Proper citation: NeuriteTracer (RRID:SCR_014146) Copy   

•   Source: SciCrunch Registry

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

A large scale functional connectivity data mining software package which enables large-scale seed-based analysis and brain-behavior analysis. It can examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables.

Proper citation: Advanced Connectivity Analysis (ACA) (RRID:SCR_014195) Copy   

•   Source: SciCrunch Registry

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

Behavioral and imaging data from about 120 participants aged 18-89. Data were collected as part of a grant to use high-resolution imaging and advanced behavioral tasks to understand how aging affects the hippocampus and how this is related to age-related cognitive decline. The full dataset includes traditional neuropsycholgical measures, hippocampal-specific behavioral measures, whole-brain DTI, high-resolution DTI of the medial temporal lobes, and structural MRI including segmentation of grey/white/CSF, of cortical regions and of hippocampal subfields.

Proper citation: Stark Cross-Sectional Aging (RRID:SCR_014171) Copy   

•   Source: SciCrunch Registry

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

A dataset which contains diffusion tensor images of 93 healthy, young male subjects.

Proper citation: YMDTI: Diffusion Tensor Images of Healthy Young Males (RRID:SCR_014183) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/hfh_t1_hp_seg1/

Shared dataset which consists of skull-stripped T1 MRI images and segmented hippocampi of 163 Temporal Lobe Epilepsy (TLE) patients. The T1 and hippocampal segmentation data of TLE patients are uploaded in three separate datasets which can be accessed from the main site.

Proper citation: Epilepsy T1 and Hippocampal Segmentation Datasets (RRID:SCR_014926) Copy   

•   Source: SciCrunch Registry

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

Data set of manually-guided expert segmentation results along with magnetic resonance brain image data. Its purpose is to encourage the development and evaluation of segmentation methods by providing raw test and image data, human expert segmentation results, and methods for comparing segmentation results. Please see the MediaWiki for more information. This repository is meant to contain standard test image data sets which will permit a standardized mechanism for evaluation of the sensitivity of a given analysis method to signal to noise ratio, contrast to noise ratio, shape complexity, degree of partial volume effect, etc. This capability is felt to be essential to further development in the field since many published algorithms tend to only operate successfully under a narrow range of conditions which may not extend to those experienced under the typical clinical imaging setting. This repository is also meant to describe and discuss methods for the comparison of results.

Proper citation: Internet Brain Segmentation Repository (RRID:SCR_001994) Copy   

•   Source: SciCrunch Registry

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

Public datasets that have been transcoded into multiple formats. This library of valid file format conversions (DICOM->NIFTI, DICOM->PAR/REC, etc.) will provide a reference for tool developers seeking to support multiple sources of data.

Proper citation: Rosetta Bit (RRID:SCR_001906) Copy   

•   Source: SciCrunch Registry

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

Expertly collected, well-curated data sets consisting of comprehensive clinical characterization and raw structural, functional and diffusion-weighted DICOM images in schizophrenia patients and gender and age-matched controls are now accessible to the scientific community through an on-line data repository (coins.mrn.org). This data repository will be useful to 1) educators in the fields of neuroimaging, medical image analysis and medical imaging informatics who need exemplar data sets for courses and workshops; 2) computer scientists and software algorithm developers for testing and validating novel registration, segmentation, and other analysis software; and 3) scientists who can study schizophrenia by further analysis of this cohort and/or by pooling with other data.

Proper citation: MCIC (RRID:SCR_002310) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/projects/nitrc_es

An on-demand, cloud based computational virtual machine pre-installed with popular NITRC neuroimaging tools built using NeuroDebian. For a listing of current NITRC-CE packages visit: http://www.nitrc.org/ce-packages. You can also use the "public Amazon Machine Interface (AMI)" to conduct your analyses on the Amazon EC2 platform.

Proper citation: NITRC Computational Environment (RRID:SCR_002171) 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

http://www.temporal-lobe.com/

Interactive diagram containing existing knowledge of hippocampal-parahippocampal connections in which any connection can be turned on or off at the level of cortical layers. It includes references for each connection.

Proper citation: Temporal-Lobe: Hippocampal - Parahippocampal Neuroanatomy of the Rat (RRID:SCR_002816) Copy   

•   Source: SciCrunch Registry