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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://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

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://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://fcon_1000.projects.nitrc.org/indi/retro/cobre.html

Data set of raw anatomical and functional MR data from 72 patients with Schizophrenia and 75 healthy controls (ages ranging from 18 to 65 in each group). All subjects were screened and excluded if they had: history of neurological disorder, history of mental retardation, history of severe head trauma with more than 5 minutes loss of consciousness, history of substance abuse or dependence within the last 12 months. Diagnostic information was collected using the Structured Clinical Interview used for DSM Disorders (SCID). A multi-echo MPRAGE (MEMPR) sequence was used with the following parameters: TR/TE/TI = 2530/(1.64, 3.5, 5.36, 7.22, 9.08)/900 ms, flip angle = 7��, FOV = 256x256 mm, Slab thickness = 176 mm, Matrix = 256x256x176, Voxel size =1x1x1 mm, Number of echos = 5, Pixel bandwidth =650 Hz, Total scan time = 6 min. With 5 echoes, the TR, TI and time to encode partitions for the MEMPR are similar to that of a conventional MPRAGE, resulting in similar GM/WM/CSF contrast. Rest data was collected with single-shot full k-space echo-planar imaging (EPI) with ramp sampling correction using the intercomissural line (AC-PC) as a reference (TR: 2 s, TE: 29 ms, matrix size: 64x64, 32 slices, voxel size: 3x3x4 mm3). Slice Acquisition Order: Rest scan - collected in the Axial plane - series ascending - multi slice mode - interleaved MPRAGE - collected in the Sag plane - series interleaved - multi slice mode - single shot The following data are released for every participant: * Resting fMRI * Anatomical MRI * Phenotypic data for every participant including: gender, age, handedness and diagnostic information.

Proper citation: COBRE (RRID:SCR_010482) 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

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://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.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

http://pingstudy.ucsd.edu/

A large multi-site pediatric MRI and genetics data resource to facilitate studies of the genomic landscape of the developing human brain. It includes information about the developing mental and emotional functions of the children to understand the genetic basis of individual differences in brain structure and connectivity, cognition, and personality. Investigators on the project are studying 1400 children between the ages of 3 and 20 years so that links between genetic variation and developing patterns of brain connectivity can be examined. Investigators interested in the effects of a particular gene will be able to search the database for any brain areas or connections between areas that differ as a function of variation in a particular gene, and also to determine if the genes appear to affect the course of brain development at some point during childhood. A data exploration tool has been created for mapping and analyzing MRI data sets collected for PING and related developmental studies. Approved investigators will be able to view raw image sets and derived 3D brain maps of MRI and DTI data, conduct hypothesis testing, and graph brain area measures as they change across the time course of development. PING Cores * Coordinating Core: Functions include project management, screening of participants and maintaining the database * Neuroimaging Core: applying a standardized high-resolution structural MRI protocol involving 3-D T1-weighted scans, a T2-weighted volume, and a set of diffusion-weighted scans with multiple b values and diffusion directions, scans to estimate MRI relaxation rates, and gradient echo EPI scans for resting state fMRI. Importantly, adaptive motion compensation, using ����??PROMO����??, a novel real-time motion correction algorithm will be used. Specific PING protocols for each scanner manufacturer: ** PING MRI Protocol - GE ** PING MRI Protocol - Philips ** PING MRI Protocol - Siemens * Assessment Core: Cognitive assessments for the PING project are conducted using the NIH Toolbox for Cognition. * Genomics Core: functions as a central repository for receipt of saliva samples collected for each study participant. Once received, samples are catalogued, maintained, and DNA is extracted using state-of-the-field laboratory techniques. Ultimately, genome-wide genotyping is performed on the extracted DNA using the Illumina Human660W-Quad BeadChip. PING involves 10 sites throughout the country including UCSD, University of Hawaii, Scripps Genomics, UCLA, UC Davis, Kennedy Krieger Institute/Johns Hopkins, Sacker Institute/Cornell University, University of Massachusetts, Massachusetts General Hospital/Harvard, and Yale. Families who may want to participate in the study, or others who want to know more about it, may email questions to ping (at) ucsd.edu.

Proper citation: Pediatric Imaging Neurocognition and Genetics (RRID:SCR_008953) Copy   

•   Source: SciCrunch Registry

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

A project which systematically preprocess the data from the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data-sharing Initiative (INDI) and openly share the results. Data is currently hosted in an Amazon Web Services Public S3 Bucket and at NITRC.

Proper citation: Preprocessed Connectomes Project (RRID:SCR_014162) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/pd3/

THIS RESOURCE IS NO LONGER IN SERVICE, documented Jan. 5, 2016. Tools will be available for biomedical data mining and visualization as well as linkages to Google Maps and other online resources.

Proper citation: Parkinsons Disease Discovery Database (RRID:SCR_014160) Copy   

•   Source: SciCrunch Registry

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

Database as an open science framework with a scientific data extracted from scientific literature about various altered states of consciousness assessed with questionnaires. Used to compare what experiences are elicited by different drugs and non-pharmacological methods that induce altered states to help to understand human consciousness functions. Is listed by Neuroimaging Informatics Tools.

Proper citation: Altered States Database (RRID:SCR_016350) Copy   

•   Source: SciCrunch Registry

http://neuromorphometrics.com/?page_id=23

Collection of neuroanatomically labeled MRI brain scans, created by neuroanatomical experts. Regions of interest include the sub-cortical structures (thalamus, caudate, putamen, hippocampus, etc), along with ventricles, brain stem, cerebellum, and gray and white matter and sub-divided cortex into parcellation units that are defined by gyral and sulcal landmarks.

Proper citation: Manually Labeled MRI Brain Scan Database (RRID:SCR_009604) Copy   

•   Source: SciCrunch Registry

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

Structure from motion algorithms repository. Common interface for various sfm algorithms.

Proper citation: SFMProject (RRID:SCR_014166) Copy   

•   Source: SciCrunch Registry