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http://sleep.alleninstitute.org

Collection of gene expression data in mouse brain for five different conditions of sleep and wakefulness to understand sleep deprivation and dynamic changes underlying sleep and wake cycles. Platform to generate cellular resolution expression data.

Proper citation: Allen Institute for Brain Science Sleep Study (RRID:SCR_002983) Copy   

•   Source: SciCrunch Registry

http://www.virtualflybrain.org

An interactive tool for neurobiologists to explore the detailed neuroanatomy, neuron connectivity and gene expression of the adult Drosophila melanogaster brain.

Proper citation: Virtual Fly Brain (RRID:SCR_004229) Copy   

•   Source: SciCrunch Registry

http://aimlab.cs.uoregon.edu/NEMO/web/

THIS RESOURCE IS NO LONGER IN SERVICE. NIH tombstone webpage lists Project Period : 2009 - 2013. NIH funded project to create EEG and MEG ontologies and ontology based tools. These resources will be used to support representation, classification, and meta-analysis of brain electromagnetic data. Three pillars of NEMO are: DATA, ONTOLOGY, and DATABASE. NEMO data consist of raw EEG, averaged EEG (ERPs), and ERP data analysis results. NEMO ontologies include concepts related to ERP data (including spatial and temporal features of ERP patterns), data provenance, and cognitive and linguistic paradigms that were used to collect data. NEMO database portal is large repository that stores NEMO consortium data, data analysis results, and data provenance. EEG and MEG ontologies and ontology-based tools to support representation, classification, and meta-analysis of brain electromagnetic data. Raw EEG and ERP data may be uploaded to the NEMO FTP site., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Neural ElectroMagnetic Ontologies (NEMO) Project (RRID:SCR_002001) Copy   

•   Source: SciCrunch Registry

http://cvr.yorku.ca/home/

The Centre for Vision Research focuses on interdisciplinary research into human and machine vision and visual processes, into vision's interactions with other senses and with motor and cognitive processes, and in applications such as visually-guided robotics or clinical diagnosis and treatment. The Centre for Vision Research includes the following major research themes: - Human Visual Performance - Visual Human-Computer Interaction, Graphics and Virtual Reality - Visual Psychophysics - Eye Movements and Hand-Eye Coordination - Computational Modeling and Computer Vision - Electrophysiology - Clinical and Developmental Studies - Brain Imaging

Proper citation: Centre for Vision Research (RRID:SCR_002879) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu

The SenseLab Project is a long-term effort to build integrated, multidisciplinary models of neurons and neural systems. It was founded in 1993 as part of the original Human Brain Project, which began the development of neuroinformatics tools in support of neuroscience research. It is now part of the Neuroscience Information Framework (NIF) and the International Neuroinformatics Coordinating Facility (INCF). The SenseLab project involves novel informatics approaches to constructing databases and database tools for collecting and analyzing neuroscience information, using the olfactory system as a model, with extension to other brain systems. SenseLab contains seven related databases that support experimental and theoretical research on the membrane properties: CellPropDB, NeuronDB, ModelDB, ORDB, OdorDB, OdorMapDB, BrainPharmA pilot Web portal that successfully integrates multidisciplinary neurocience data.

Proper citation: SenseLab (RRID:SCR_007276) Copy   

•   Source: SciCrunch Registry

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

This resource was created to host descriptions of protocols, definitions and rules for the reliable identification and localization of human brain anatomy and discussions of best practices in brain labeling. Project for manual anatomical labeling of human brain MRI data, and the visual presentation of labeled brain images.

Proper citation: BrainColor: Collaborative Open Labeling Online Resource (RRID:SCR_006377) Copy   

•   Source: SciCrunch Registry

https://www.msu.edu/~brains/brains/human/index.html

A labeled three-dimensional atlas of the human brain created from MRI images. In conjunction are presented anatomically labeled stained sections that correspond to the three-dimensional MRI images. The stained sections are from a different brain than the one which was scanned for the MRI images. Also available the major anatomical features of the human hypothalamus, axial sections stained for cell bodies or for nerve fibers, at six rostro-caudal levels of the human brain stem; images and Quicktime movies. The MRI subject was a 22-year-old adult male. Differing techniques used to study the anatomy of the human brain all have their advantages and disadvantages. Magnetic resonance imaging (MRI) allows for the three-dimensional viewing of the brain and structures, precise spatial relationships and some differentiation between types of tissue, however, the image resolution is somewhat limited. Stained sections, on the other hand, offer excellent resolution and the ability to see individual nuclei (cell stain) or fiber tracts (myelin stain), however, there are often spatial distortions inherent in the staining process. The nomenclature used is from Paxinos G, and Watson C. 1998. The Rat Brain in Stereotaxic Coordinates, 4th ed. Academic Press. San Diego, CA. 256 pp

Proper citation: Human Brain Atlas (RRID:SCR_006131) Copy   

•   Source: SciCrunch Registry

http://www.nih.gov/science/brain/

Project aimed at revolutionizing understanding of human brain, to show how individual cells and complex neural circuits interact, enable rapid progress in development of new technologies and data analysis tools to treat and prevent brain disorders. BRAIN Initiative encourages collaborations between neurobiologists and scientists from disciplines such as statistics, physics, mathematics, engineering, and computer and information sciences. Institutes and centers contributing to NIH BRAIN Initiative support those research efforts.

Proper citation: BRAIN Initiative (RRID:SCR_006770) Copy   

•   Source: SciCrunch Registry

http://www.neuroethics.ubc.ca/

It is an interdisciplinary research group dedicated to tackling the ethical, legal, policy and social implications of frontier technological developments in the neurosciences. Our objective is to align innovations in the brain sciences with societal, cultural and individual human values through high impact research, education and outreach. The Core''s major research projects are focused on high impact, high visibility areas including the use of drugs and devices for neuroenhancement, ethics in neurodegenerative disease and regenerative medicine research, international and cross-cultural challenges in brain research, neuroimaging in the private sector, and the ethics of personalized medicine, among others. Members of the Core also lead initiatives aside from their research projects. Sponsors: This Core is supported by the University of Brititsh Columbia.

Proper citation: UBC National Core for Neuroethics (RRID:SCR_008063) 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://hermes.ctb.upm.es/

A toolbox for the Matlab environment designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. This toolbox may be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

Proper citation: HERMES (RRID:SCR_009584) Copy   

•   Source: SciCrunch Registry

http://rfmri.org/dpabi

Software toolbox for data processing and analysis of brain imaging, evolved from DPARSF (Data Processing Assistant for Resting-State fMRI).

Proper citation: DPABI (RRID:SCR_010501) Copy   

•   Source: SciCrunch Registry

https://singlecell.broadinstitute.org/single_cell

Portal specializes in visualizing and disseminating single cell data. Allows you to use natural language and faceted search to discover other scientists’ research and share your own findings. Each study includes information on cell types, singular or multiple gene expression, and spatial transcriptomics. Interactive visualizations allow to explore cell clusters and search for related genes.

Proper citation: Single Cell Portal (RRID:SCR_014816) 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/atag_mri_scans/

Data sets from the atlasing of the basal ganglia (ATAG) consortium, which provides ultra-high resolution 7Tesla (T) magnetic resonance imaging (MRI) scans from young, middle-aged, and elderly participants. They include whole-brain and reduced field-of-view MP2RAGE and T2 scans with ultra-high resolution at a sub millimeter scale. The data can be used to develop new algorithms that help building new high-resolution atlases both in the basic and clinical neurosciences. They can also be used to inform the exact positioning of deep-brain electrodes relevant in patients with Parkinsons disease and neuropsychiatric diseases.

Proper citation: 7T Structural MRI scans ATAG (RRID:SCR_014084) Copy   

•   Source: SciCrunch Registry

https://www.synapse.org/#!Synapse:syn4921369/wiki/235539

Portal of PsychENCODE Consortium to study role of rare genetic variants involved in several psychiatric disorders. Database of regulatory elements, epigenetic modifications, RNA and protein in brain.

Proper citation: PsychENCODE Knowledge Portal (RRID:SCR_017500) Copy   

•   Source: SciCrunch Registry

https://github.com/mitragithub/Registration

Software package to align brain slice images in atlas free manner.

Proper citation: Registration Software Mitra Lab (RRID:SCR_018353) Copy   

•   Source: SciCrunch Registry

http://braintechsci.blogspot.com/index.html

Blog about brain technology and science news that covers topics such as high-resolution brain imaging, brain maps API and whole-brain atlases.

Proper citation: BrainTechSci. (RRID:SCR_000113) Copy   

•   Source: SciCrunch Registry

https://bams1.org/connectomes/standard_rat.php, https://bams1.org/connectomes/custom_rat.php

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 9,2022. Database of information about brain region circuitry, it collates data from the literature on tract tracing studies and provides tools for analysis and visualization of connectivity between brain regions., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BAMS Connectivity (RRID:SCR_000561) Copy   

•   Source: SciCrunch Registry

http://research.mssm.edu/cnic/

Center to advance research and training in mathematical, computational and modern imaging approaches to understanding the brain and its functions. Software tools and associated reconstruction data produced in the center are available. Researchers study the relationships between neural function and structure at levels ranging from the molecular and cellular, through network organization of the brain. This involves the development of new computational and analytic tools for imaging and visualization of 3-D neural morphology, from the gross topologic characteristics of the dendritic arbor to the fine structure of spines and their synapses. Numerical simulations of neural mechanisms based on these structural data are compared with in-vivo and in-vitro electrophysiological recordings. The group also develops new theoretical and analytic approaches to exploring the function of neural models of working memory. The goal of this analytic work is to combine biophysically realistic models and simulations with reduced mathematical models that capture essential dynamical behaviors while reproducing the functionally important features of experimental data. Research areas include: Imaging Studies, Volume Integration, Visualization Techniques, Medial Axis Extraction, Spine Detection and Classification, Applications of Rayburst, Analysis of Spatially Complex Structures, Computational Modeling, Mathematical and Analytic Studies

Proper citation: Computational Neurobiology and Imaging Center (RRID:SCR_013317) Copy   

•   Source: SciCrunch Registry