List of neuroscience databases

Last updated

A number of online neuroscience databases are available which provide information regarding gene expression, neurons, macroscopic brain structure, and neurological or psychiatric disorders. Some databases contain descriptive and numerical data, some to brain function, others offer access to 'raw' imaging data, such as postmortem brain sections or 3D MRI and fMRI images. Some focus on the human brain, others on non-human.

Contents

As the number of databases that seek to disseminate information about the structure, development and function of the brain has grown, so has the need to collate these resources themselves. As a result, there now exist databases of neuroscience databases, some of which reach over 3000 entries. [1]

Neuroscience databases


NameDescriptionOrganismLevel (gene, neuron, macroscopic)Data (MRI, fMRI, images, descriptive, numerical)DisorderRegister to view data?Ref.
A Virtual Library for Behavioral Performance in Standard Conditions – Rodent Spontaneous Activity in an Open Field during Repeated Testing and after Treatment with Drugs or Brain LesionsResearch using an animal model of obsessive-compulsive disorder employed a standardized paradigm where the behavior of rats in a large open field was video recorded for 55 min on each test.RatMacroscopicVideoObsessive-compulsive disorderNo [2]
Allen Brain Atlas Atlas, stained sections from brains showing development and gene expressionMouse, HumanMacroscopic, GeneImagesHealthyNo [3]
Alzheimer's Disease Neuroimaging Initiative (ADNI)Structural MRI imagesHumanMacroscopicMRI datasetsHealthy and Alzheimer's disease Yes [4]
Big Brain3D reconstruction of complete brain from cell-body stained histology sections at 20 micron isotropic resolutionHumanMicroscopicImagesHealthyNo [5]
BIRN fMRI and MRI datafMRI, MRI scans and atlases for human and mouse brainsMouse, HumanMultilevel: brain regions, connections, neurons, gene expression patternsMRI datasets, fMRI datasetsHealthy, Elderly No
Bipolar Disorder Neuroimaging DatabaseMeta-analysis and database of MRI studiesHumanMacroscopicDescriptive, numerical Bipolar Disorder No [6]
Brain Architecture Management SystemOnline resource for information about neural circuitryRat, mouse, humanMultilevel: brain regions, connections, neurons, gene expression patternsDescriptive, numericalHealthyNo
Brain CloudGene expression in the human prefrontal cortexHumanGene expression patternsDescriptive, numericalHealthyNo
Brain-CODE A multi-modal, cross-disorder platform for integrated neuroscience research and data by the Ontario Brain Institute.Human, AnimalMultimodal datasets (clinical, imaging, molecular, etc.)Descriptive, numerical, imaging, molecular, geneticsNeurodevelopmental, Cerebral Palsy, Epilepsy, Depression, Neurodegeneration, ConcussionYes [7]
Brain-Development.orgStructural MRI images and AtlasesHumanMacroscopicMRI datasetsFetuses, healthy and prematurely born neonatesYes [8]
Braingraph.orgBraingraphs computed from the Human Connectome Project dataHumanMacroscopic, up to 1015 nodesdirected and undirected graphs in anatomically annotated GraphML formatHealthyNo [9]
BraininfoAtlas, schematic atlas of Macaca fascicularis Macaque MacroscopicSchematic imagesHealthyYes
Brain Machine Interface PlatformDifferent types of data related to brain machine interfaceHuman, MonkeyMacroscopic, NeuronImages, NumericalHealthyNo
BrainMap.orgfMRI coordinate databaseHumanMacroscopicDescriptiveHealthyYes [10]
BrainMaps Atlas, high resolution stained sections from brainsHuman, primate and non-primate (14 species in all)Neuron and MacroscopicImagesHealthyNo [11]
Brain/MINDS Dataportal Atlas, in-vivo and ex-vivo MRI scans, ECoG recordingsCommon Marmoset, HumanMacroscopicImagesHealthyNo [12]
Brede DatabasefMRI and PET coordinate databaseHumanMacroscopicDescriptiveHealthyNo [13]
Brainmuseum.org / MSU Brain Biodiversity BankAtlas, stained sections from brains and MRI imagesHuman and 62 other speciesMacroscopicImagesHealthyNo
Brainomics/LocalizerfMRI and MRI scans, behavioral dataHumanMacroscopicImages, NumericalHealthyNo [14]
BuzLabDB: The Buzsaki Lab Databank Electrophysiological recordings performed in freely moving rats and mice collected by investigators in the Buzsaki LabMice and ratsMultiscaleSpike trains, LFP, Raw ephys dataHealthyNo [15] [16]
Caltech Subcortical AtlasMRI scansHumanMacroscopicMRIHealthyNo [17]
Cambridge Centre for Ageing and Neuroscience (Cam-CAN)MRI, fMRI, MEG data for ~700 population-derived healthy adults aged 18–88HumanMacroscopicImages, Descriptive, NumericalHealthyNo [18]
The Cancer Imaging ArchiveMRI, CT, and PET imaging of cancer patients with supporting clinical data (in many cases)HumanMacroscopicImages, Descriptive, NumericalCancerNo [19]
Cerebellar Development Transcriptome DatabaseAtlas, stained sections from mouse brains showing cerebellar development and gene expressionMouseMacroscopic, GeneImagesHealthyNo [20]
Collaborative Research in Computational Neuroscience (CRCNS.org)Many kinds of neuroscience results that are relevant for modelingHuman and several other speciesMultiscaleSpike trains, LFP, MUA, MRIHealthyYes
DANDI: Distributed Archives for Neurophysiology Data Integration cellular neurophysiology data including electrophysiology, optophysiology, and behavioral time-series, and images from immunostaining experimentsHuman and several other speciesMultiscaleSpike trains, LFP, MUA, MRIHealthy
Database for Reaching Experiments And Models (DREAM)Reaching data (behavioral, generalization, adaptation, learning, spike, fMRI, uncertainty)Human and monkeyMacroscopicKinematic, Spike, fMRIHealthyYes
The fMRI Data Center fMRI datasets from published studiesHumanMacroscopicfMRI datasetsHealthyYes [21]
GLIMPS Project (GLucose IMaging in Parkinsonian Syndromes)International FDG-PET scan neurodegenerative disease databaseHumanMacroscopic FDG-PET images Parkinson's disease (PD), Alzheimer's disease (AD), multiple system atrophy (MSA), progressive supranuclear palsy (PSP), etc.Yes
Hippocampome PortalCircuitry, neural types, electrophysiologyAdult humanNeuronCell morphology, electrophysiology, region makeup, connectivityHealthyYes [22] [23]
IBA: Infant Brain Atlas Infant brain atlases from 2 weeks to 2 years of ageHuman infantsMacroscopic, microscopic, brain regionsMRIHealthyNo [24]
International Epilepsy Electrophysiology Database (IEEG.org)EEG, metadata, imaging, annotations on dataHumans and animal models of epilepsyEEG, local fields, micro-ECoGElectrophysiologyNon-healthy, several healthyYes
International Neuroimaging Data-sharing Initiative (INDI)Functional connectivity data from many different groupsInvertebrates (47 species in all)MacroscopicFunctional connectivityHealthy, non-healthyYes
Invertebrate Brain PlatformPhotos of dissections of invertebrates nervous systemsInvertebrates (47 species in all)MacroscopicPhotosHealthyNo
In vivo human phantomUltrahigh resolution MRI data of a single participant including 150 μm ToF angiography, 250 μm T1-weighted MPRAGE, 330 μm QSM, 450 μm T2-weighted TSE, 800 μm DTI, one hour continuous 1.8 mm rs-fMRI and structural data acquired over more than a decadeHumanMesoscopicStructural MRI with various contrasts, microstructure MRI and functional MRIHealthyNo [25]
JuBrain atlasProbabilistic cytoarchitectonic 3D maps of the human brainHumanMesoscopicStructuralHealthyNo [26] [27]
Kymata AtlasFunctional atlas of the human cortexHumanMacroscopicFunctionalHealthyNo [28]
Major Depressive Disorder Neuroimaging DatabaseMeta-analysis and database of MRI studiesHumanMacroscopicDescriptive, numerical Major Depressive Disorder No [29]
Marmoset Gene Atlas Gene expression in the common marmoset whole brainCommon MarmosetMacroscopic, GeneImagesHealthyNo [30]
Mouse Brain LibraryAtlas, stained sections from mouse brainsMouseMacroscopicImagesHealthyNo [31]
MouseLight Complete, whole-brain reconstructionsMouseNeuronCell morphology, projectome connectivityHealthyNo [32]
NeuroData Volumetric datasets, atlases, and connectomics researchMultipleMultiscaleImages (3D, 4D)VariousNo
Neuroelectro.orgElectrophysiology of neuronsHuman, othersNeuronElectrophysiological properties and dataHealthyNo [33]
Neuromorpho.org3D models of real neuronsHuman, rat, mouse, monkey, othersNeuronImages and 3D dataHealthyNo [34]
Neuromorphometrics.com Manually labeled MRI Brain ScansHumanMacroscopicT1-weighted MRI, labeled volumesHealthyNo
NeuronDBDatabase of Neuron properties and classificationHumanNeuronDescriptiveHealthyNo [35]
Neuroimaging Tools and Resources Collaboratory (NITRC) Award-winning free collaboratory with over 1000 neuroinformatics software tools, imaging datasets, and community resources including forums and events.Human, mouse, rat, otherMicroscopic, macroscopicDatasetsHealthy and diseased No
Open Access Series of Imaging Studies (OASIS)Structural MRI imagesHumanMacroscopicMRI datasetsHealthy and Alzheimer's disease Yes [36]
Open Connectome ProjectDatabase of different circuitry frameworks and neuroimaging datasets, including volumetric datasets, atlases, and connectomics researchHuman, mouse, bat, zebrafish, insect, otherMultilevel: brain regions, connections, neurons, gene expression patternsImages and 3D dataHealthyNo [37]
openfnirs a meta-database specific to fNIRS data. The “Openfnirs meta-database” (https://openfnirs.org/data/) is a part of the openfnirs initiative whose mission is to foster the development of an fNIRS ecosystem and to promote the open dissemination of fNIRS hardware and software, as well as provide access to resources, documentation and training opportunities for fNIRS users.HumanMacroscopicfNIRS (Functional_near-infrared_spectroscopy)Healthy and eventually various diseasesNo [38]
OpenNeuro Large and diverse collection of raw data from various research studies distributed under permissive licenses (CC0 and CC BY). All datasets are formatted according to the same format (Brain Imaging Data Structure) and can be accessed via Amazon S3.HumanMacroscopicFunctional, structural, diffusion MRI, and Magnetoencephalography datasetsHealthy and various diseasesNo [39]
Open MEG Archive (OMEGA) Magnetoencephalography, structural MRI datasets, and demographicsHumanMacroscopicMEG, T1 MRI datasets, demographic dataHealthy, ADHD, Traumatic brain injury Yes [40]
The PAIN RepositoryStructural, Diffusion and Functional MRI datasetsHumanHuman MacroscopicMRI datasets and MetadataHealthy and Pain ConditionsYes [41]
Pig Brain AtlasPig Brain Atlas is a three-dimensional MRI-based averaged brain and atlas of the neonatal piglet (Sus scrofa).Pig (Sus scrofa)MacroscopicStructural MRIHealthyYes [42]
Primate Cell Type Database PrimateDatabase.com, a publicly available web-accessible archive of intracellular patch clamp recordings and highly detailed three-dimensional digital reconstructions of neuronal morphology.Non-human primate and humanNeuronElectrophysiology, Morphology and 3-d ReconstructionsHealthyNo
SchizConnectSchizConnect is an open, public search-and-download virtual database for schizophrenia neuroimaging (MRI) images and related data.HumanMacroscopicStructural, Diffusion and Functional MRI datasets, cognitive and clinical assessmentsSchizophrenia (+ siblings), Bipolar Disorder, Controls (+ siblings)Yes [43]
Temple EEG DatabaseOver 30,000 clinical EEGs and accompanying neurologist reportsHumanMacroscopicEEGHealthy and various diseasesYes [44]
Ultrahigh resolution T1-weighted whole brain MR datasetT1-weighted MR data acquired using prospective motion correction at an ultrahigh isotropic resolution of 250 µm.HumanMesoscopicStructural MRI dataset including scanner's raw to processed dataHealthyNo [45]
UNC-Wisconsin Neurodevelopment Rhesus MRI DatabaseStructural and Diffusion Weighted MRI images in Native and Atlas Space Macaque MacroscopicMRI datasetsHealthyNo
Whole Brain AtlasAtlas, Structural MRI images and PET imagesHumanMacroscopicImagesHealthy and various diseasesNo
NeuroVault Unthresholded statistical maps from MRI and PET studies.HumanMacroscopicImagesHealthy and various diseasesNo [46]

Databases of neuroscience databases

NameDescriptionOrganismLevel (gene, neuron, macroscopic)Data (MRI, fMRI, images, descriptive, numerical)DisorderRegister to view data?Ref.
Neuroscience Information Framework A meta database of neuroscience-relevant data incorporating over 100 databases.Human, mouse, rat, wormMicroscopic, macroscopicDatasetsHealthy and diseased No [47]

Neuroscience article aggregators

Neuroscience feed at RightRelevance. [48]

See also

Related Research Articles

Brain mapping is a set of neuroscience techniques predicated on the mapping of (biological) quantities or properties onto spatial representations of the brain resulting in maps.

<span class="mw-page-title-main">FreeSurfer</span> Brain imaging software package

FreeSurfer is a brain imaging software package originally developed by Bruce Fischl, Anders Dale, Martin Sereno, and Doug Greve. Development and maintenance of FreeSurfer is now the primary responsibility of the Laboratory for Computational Neuroimaging at the Athinoula A. Martinos Center for Biomedical Imaging. FreeSurfer contains a set of programs with a common focus of analyzing magnetic resonance imaging (MRI) scans of brain tissue. It is an important tool in functional brain mapping and contains tools to conduct both volume based and surface based analysis. FreeSurfer includes tools for the reconstruction of topologically correct and geometrically accurate models of both the gray/white and pial surfaces, for measuring cortical thickness, surface area and folding, and for computing inter-subject registration based on the pattern of cortical folds.

<span class="mw-page-title-main">International Neuroinformatics Coordinating Facility</span>

The International Neuroinformatics Coordinating Facility is an international non-profit organization with the mission to develop, evaluate, and endorse standards and best practices that embrace the principles of Open, FAIR, and Citable neuroscience. INCF also provides training on how standards and best practices facilitate reproducibility and enables the publishing of the entirety of research output, including data and code. INCF was established in 2005 by recommendations of the Global Science Forum working group of the OECD. The INCF is hosted by the Karolinska Institutet in Stockholm, Sweden. The INCF network comprises institutions, organizations, companies, and individuals active in neuroinformatics, neuroscience, data science, technology, and science policy and publishing. The Network is organized in governing bodies and working groups which coordinate various categories of global neuroinformatics activities that guide and oversee the development and endorsement of standards and best practices, as well as provide training on how standards and best practices facilitate reproducibility and enables the publishing of the entirety of research output, including data and code. The current Directors are Mathew Abrams and Helena Ledmyr, and the Governing Board Chair is Maryann Martone

<span class="mw-page-title-main">Connectome</span> Comprehensive map of neural connections in the brain

A connectome is a comprehensive map of neural connections in the brain, and may be thought of as its "wiring diagram". An organism's nervous system is made up of neurons which communicate through synapses. A connectome is constructed by tracing the neuron in a nervous system and mapping where neurons are connected through synapses.

Connectomics is the production and study of connectomes: comprehensive maps of connections within an organism's nervous system. More generally, it can be thought of as the study of neuronal wiring diagrams with a focus on how structural connectivity, individual synapses, cellular morphology, and cellular ultrastructure contribute to the make up of a network. The nervous system is a network made of billions of connections and these connections are responsible for our thoughts, emotions, actions, memories, function and dysfunction. Therefore, the study of connectomics aims to advance our understanding of mental health and cognition by understanding how cells in the nervous system are connected and communicate. Because these structures are extremely complex, methods within this field use a high-throughput application of functional and structural neural imaging, most commonly magnetic resonance imaging (MRI), electron microscopy, and histological techniques in order to increase the speed, efficiency, and resolution of these nervous system maps. To date, tens of large scale datasets have been collected spanning the nervous system including the various areas of cortex, cerebellum, the retina, the peripheral nervous system and neuromuscular junctions.

<span class="mw-page-title-main">Default mode network</span> Large-scale brain network active when not focusing on an external task

In neuroscience, the default mode network (DMN), also known as the default network, default state network, or anatomically the medial frontoparietal network (M-FPN), is a large-scale brain network primarily composed of the dorsal medial prefrontal cortex, posterior cingulate cortex, precuneus and angular gyrus. It is best known for being active when a person is not focused on the outside world and the brain is at wakeful rest, such as during daydreaming and mind-wandering. It can also be active during detailed thoughts related to external task performance. Other times that the DMN is active include when the individual is thinking about others, thinking about themselves, remembering the past, and planning for the future.

The Human Connectome Project (HCP) is a five-year project sponsored by sixteen components of the National Institutes of Health, split between two consortia of research institutions. The project was launched in July 2009 as the first of three Grand Challenges of the NIH's Blueprint for Neuroscience Research. On September 15, 2010, the NIH announced that it would award two grants: $30 million over five years to a consortium led by Washington University in St. Louis and the University of Minnesota, with strong contributions from University of Oxford (FMRIB) and $8.5 million over three years to a consortium led by Harvard University, Massachusetts General Hospital and the University of California Los Angeles.

Anders Martin Dale is a prominent neuroscientist and professor of radiology, neurosciences, psychiatry, and cognitive science at the University of California, San Diego (UCSD), and is one of the world's leading developers of sophisticated computational neuroimaging techniques. He is the founding Director of the Center for Multimodal Imaging Genetics (CMIG) at UCSD.

<span class="mw-page-title-main">Resting state fMRI</span> Type of functional magnetic resonance imaging

Resting state fMRI is a method of functional magnetic resonance imaging (fMRI) that is used in brain mapping to evaluate regional interactions that occur in a resting or task-negative state, when an explicit task is not being performed. A number of resting-state brain networks have been identified, one of which is the default mode network. These brain networks are observed through changes in blood flow in the brain which creates what is referred to as a blood-oxygen-level dependent (BOLD) signal that can be measured using fMRI.

Connectograms are graphical representations of connectomics, the field of study dedicated to mapping and interpreting all of the white matter fiber connections in the human brain. These circular graphs based on diffusion MRI data utilize graph theory to demonstrate the white matter connections and cortical characteristics for single structures, single subjects, or populations.

Dynamic functional connectivity (DFC) refers to the observed phenomenon that functional connectivity changes over a short time. Dynamic functional connectivity is a recent expansion on traditional functional connectivity analysis which typically assumes that functional networks are static in time. DFC is related to a variety of different neurological disorders, and has been suggested to be a more accurate representation of functional brain networks. The primary tool for analyzing DFC is fMRI, but DFC has also been observed with several other mediums. DFC is a recent development within the field of functional neuroimaging whose discovery was motivated by the observation of temporal variability in the rising field of steady state connectivity research.

<span class="mw-page-title-main">Russell Poldrack</span>

Russell "Russ" Alan Poldrack is an American psychologist and neuroscientist. He is a professor of psychology at Stanford University, associate director of Stanford Data Science, member of the Stanford Neuroscience Institute and director of the Stanford Center for Reproducible Neuroscience and the SDS Center for Open and Reproducible Science.

<span class="mw-page-title-main">OpenNeuro</span>

OpenNeuro is an open-science neuroinformatics database storing datasets from human brain imaging research studies.

Viktor K. Jirsa is a German physicist and neuroscientist, director of research at the Centre national de la recherche scientifique (CNRS), director of the Institut de Neuroscience des Systèmes and co-director of the Fédération Hospitalo-Universitaire (FHU) EPINEXT "Epilepsy and Disorders of Neuronal Excitability" in Marseille, France. He is workpackage leader in the Epinov project funded in the context of the RHU3 call and coordinated by Fabrice Bartolomei.

<span class="mw-page-title-main">John-Dylan Haynes</span> British-German brain researcher (born 1971)

John-Dylan Haynes is a British-German brain researcher.

Social cognitive neuroscience is the scientific study of the biological processes underpinning social cognition. Specifically, it uses the tools of neuroscience to study "the mental mechanisms that create, frame, regulate, and respond to our experience of the social world". Social cognitive neuroscience uses the epistemological foundations of cognitive neuroscience, and is closely related to social neuroscience. Social cognitive neuroscience employs human neuroimaging, typically using functional magnetic resonance imaging (fMRI). Human brain stimulation techniques such as transcranial magnetic stimulation and transcranial direct-current stimulation are also used. In nonhuman animals, direct electrophysiological recordings and electrical stimulation of single cells and neuronal populations are utilized for investigating lower-level social cognitive processes.

<span class="mw-page-title-main">NeuroVault</span>

NeuroVault is an open-science neuroinformatics online repository of brain statistical maps atlases and parcellations.

Network neuroscience is an approach to understanding the structure and function of the human brain through an approach of network science, through the paradigm of graph theory. A network is a connection of many brain regions that interact with each other to give rise to a particular function. Network Neuroscience is a broad field that studies the brain in an integrative way by recording, analyzing, and mapping the brain in various ways. The field studies the brain at multiple scales of analysis to ultimately explain brain systems, behavior, and dysfunction of behavior in psychiatric and neurological diseases. Network neuroscience provides an important theoretical base for understanding neurobiological systems at multiple scales of analysis.

<span class="mw-page-title-main">Dimitri Van De Ville</span> Swiss-Belgian computer scientist and neuroscientist specialized in brain activity networks

Dimitri Van De Ville is a Swiss and Belgian computer scientist and neuroscientist specialized in dynamical and network aspects of brain activity. He is a professor of bioengineering at EPFL and the head of the Medical Image Processing Laboratory at EPFL's School of Engineering.

References

  1. "Number of entries using search query 'database'". neuinfo.org. NIF. Retrieved 25 Jan 2015.
  2. Szechtman H, Dvorkin-Gheva A, Gomez-Marin A (September 21, 2022). "Supporting data for "A Virtual Library for Behavioral Performance in Standard Conditions – Rodent Spontaneous Activity in an Open Field during Repeated Testing and after Treatment with Drugs or Brain Lesions"". GigaScience Database. doi:10.5524/102261.{{cite journal}}: Cite journal requires |journal= (help)CS1 maint: multiple names: authors list (link)
  3. Lein ES, Hawrylycz MJ, Ao N, Ayres M, Bensinger A, Bernard A, et al. (January 2007). "Genome-wide atlas of gene expression in the adult mouse brain". Nature. 445 (7124): 168–76. Bibcode:2007Natur.445..168L. doi:10.1038/nature05453. PMID   17151600. S2CID   4421492.
  4. Jack CR, Bernstein MA, Fox NC, Thompson P, Alexander G, Harvey D, et al. (April 2008). "The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods". Journal of Magnetic Resonance Imaging. 27 (4): 685–91. doi:10.1002/jmri.21049. PMC   2544629 . PMID   18302232.
  5. Amunts K, Lepage C, Borgeat L, Mohlberg H, Dickscheid T, Rousseau MÉ, et al. (June 2013). "BigBrain: an ultrahigh-resolution 3D human brain model". Science. 340 (6139): 1472–5. Bibcode:2013Sci...340.1472A. doi:10.1126/science.1235381. PMID   23788795. S2CID   14122170.
  6. Kempton MJ, Geddes JR, Ettinger U, Williams SC, Grasby PM (September 2008). "Meta-analysis, database, and meta-regression of 98 structural imaging studies in bipolar disorder". Archives of General Psychiatry. 65 (9): 1017–32. doi: 10.1001/archpsyc.65.9.1017 . PMID   18762588.
  7. Vaccarino AL, Dharsee M, Strother S, Aldridge D, Arnott SR, Behan B, Dafnas C, Dong F, Edgecombe K, El-Badrawi R, El-Emam K, Gee T, Evans SG, Javadi M, Jeanson F, Lefaivre S, Lutz K, MacPhee FC, Mikkelsen J, Mikkelsen T, Mirotchnick N, Schmah T, Studzinski CM, Stuss DT, Theriault E, Evans KR (2018). "Brain-CODE: A Secure Neuroinformatics Platform for Management, Federation, Sharing and Analysis of Multi-Dimensional Neuroscience Data". Frontiers in Neuroinformatics. 12: 28. doi: 10.3389/fninf.2018.00028 . ISSN   1662-5196. PMC   5974337 . PMID   29875648.
  8. Serag A, Aljabar P, Ball G, Counsell SJ, Boardman JP, Rutherford MA, et al. (February 2012). "Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression". NeuroImage. 59 (3): 2255–65. doi:10.1016/j.neuroimage.2011.09.062. PMID   21985910. S2CID   9747334.
  9. Szalkai B, Kerepesi C, Varga B, Grolmusz V (February 2017). "Parameterizable consensus connectomes from the Human Connectome Project: the Budapest Reference Connectome Server v3.0". Cognitive Neurodynamics. 11 (1): 113–116. arXiv: 1602.04776 . doi:10.1007/s11571-016-9407-z. PMC   5264751 . PMID   28174617.
  10. Laird AR, Lancaster JL, Fox PT (2005). "BrainMap: the social evolution of a human brain mapping database" (PDF). Neuroinformatics. 3 (1): 65–78. doi:10.1385/ni:3:1:065. PMID   15897617.
  11. Mikula S, Trotts I, Stone JM, Jones EG (March 2007). "Internet-enabled high-resolution brain mapping and virtual microscopy". NeuroImage. 35 (1): 9–15. doi:10.1016/j.neuroimage.2006.11.053. PMC   1890021 . PMID   17229579.
  12. Okano H, Sasaki E, Yamamori T, Iriki A, Shimogori T, Yamaguchi Y, Kasai K, Miyawaki A (November 2016). "Brain/MINDS: A Japanese National Brain Project for Marmoset Neuroscience". Neuron. 92 (3): 582–590. doi: 10.1016/j.neuron.2016.10.018 . PMID   27809998.
  13. Nielsen, F.A. (2003). The Brede database: a small database for functional neuroimaging NeuroImage 19(2), Presented at the 9th International Conference on Functional Mapping of the Human Brain, June 19--22, 2003, New York.
  14. Papadopoulos Orfanos D, Michel V, Schwartz Y, Pinel P, Moreno A, Le Bihan D, Frouin V (January 2017). "The Brainomics/Localizer database". NeuroImage. 144 (Pt B): 309–314. doi:10.1016/j.neuroimage.2015.09.052. PMID   26455807. S2CID   13004274.
  15. Petersen, Peter Christian; Hernandez, Michelle; Buzsáki, György (2020). "The Buzsaki Lab Databank – Public electrophysiological datasets from awake animals". doi:10.5281/zenodo.4307883.{{cite journal}}: Cite journal requires |journal= (help)
  16. "The Buzsaki Lab databank".
  17. Tyszka JM, Pauli WM (November 2016). "In vivo delineation of subdivisions of the human amygdaloid complex in a high-resolution group template". Human Brain Mapping. 37 (11): 3979–3998. doi:10.1002/hbm.23289. PMC   5087325 . PMID   27354150.
  18. Shafto MA, Tyler LK, Dixon M, Taylor JR, Rowe JB, Cusack R, et al. (October 2014). "The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) study protocol: a cross-sectional, lifespan, multidisciplinary examination of healthy cognitive ageing". BMC Neurology. 14 (6): 204. doi: 10.1186/s12883-014-0204-1 . PMC   4219118 . PMID   25412575.
  19. Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, et al. (December 2013). "The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository". Journal of Digital Imaging. 26 (6): 1045–57. doi:10.1007/s10278-013-9622-7. PMC   3824915 . PMID   23884657.
  20. Sato A, Sekine Y, Saruta C, Nishibe H, Morita N, Sato Y, Sadakata T, Shinoda Y, Kojima T, Furuichi T (October 2008). "Cerebellar development transcriptome database (CDT-DB): profiling of spatio-temporal gene expression during the postnatal development of mouse cerebellum". Neural Networks. 21 (8): 1056–69. doi:10.1016/j.neunet.2008.05.004. PMID   18603407.
  21. Van Horn JD, Grethe JS, Kostelec P, Woodward JB, Aslam JA, Rus D, Rockmore D, Gazzaniga MS (2001) The Functional Magnetic Resonance Imaging Data Center (fMRIDC): the challenges and rewards of large-scale databasing of neuroimaging studies Philos Trans R Soc Lond B Biol Sci Aug 29;356(1412):1323-39
  22. "Hippocampome". hippocampome.org. Retrieved 10 August 2016.
  23. Wheeler DW, White CM, Rees CL, Komendantov AO, Hamilton DJ, Ascoli GA (September 2015). "Hippocampome.org: a knowledge base of neuron types in the rodent hippocampus". eLife. 4: e09960. doi: 10.7554/eLife.09960 . PMC   4629441 . PMID   26402459.
  24. Ahmad S, Wu W, Wu Z, Thung KH, Liu S, Lin W, Li G, Wang L, Yap PT (2023). "Multifaceted atlases of the human brain in its infancy". Nature Methods. 20 (1): 55–64. doi:10.1038/s41592-022-01703-z. PMC   9834057 . PMID   36585454. S2CID   247600108.
  25. Lüsebrink F, Mattern H, Yakupov R, Acosta-Cabronero J, Ashtarayeh M, Oeltze-Jafra S, Speck O (May 2021). "Comprehensive ultrahigh resolution whole brain in vivo MRI dataset as a human phantom". Scientific Data. 8 (1): 138. Bibcode:2021NatSD...8..138L. doi: 10.1038/s41597-021-00923-w . PMC   8149725 . PMID   34035308.
  26. Amunts K, Zilles K (December 2015). "Architectonic Mapping of the Human Brain beyond Brodmann". Neuron. 88 (6): 1086–1107. doi: 10.1016/j.neuron.2015.12.001 . PMID   26687219.
  27. Zilles K, Amunts K (February 2010). "Centenary of Brodmann's map--conception and fate". Nature Reviews. Neuroscience. 11 (2): 139–45. doi:10.1038/nrn2776. PMID   20046193. S2CID   5278040.
  28. "The Kymata Atlas Homepage". The Kymata Atlas. University of Cambridge. Retrieved 11 December 2015.
  29. Kempton MJ, Salvador Z, Munafò MR, Geddes JR, Simmons A, Frangou S, et al. (July 2011). "Structural neuroimaging studies in major depressive disorder. Meta-analysis and comparison with bipolar disorder". Archives of General Psychiatry. 68 (7): 675–90. doi: 10.1001/archgenpsychiatry.2011.60 . PMID   21727252. see also MRI database at www.depressiondatabase.org
  30. Shimogori T, Abe A, Go Y, Hashikawa T, Kishi N, Kikuchi SS, Kita Y, Niimi K, Nishibe H, Okuno M, Saga K, Sakurai M, Sato M, Serizawa T, Suzuki S, Takahashi E, Tanaka M, Tatsumoto S, Toki M, U M, Wang Y, Windak KJ, Yamagishi H, Yamashita K, Yoda T, Yoshida AC, Yoshida C, Yoshimoto T, Okano H (March 2018). "Digital gene atlas of neonate common marmoset brain". Neurosci Res. 128: 1–13. doi:10.1016/j.neures.2017.10.009. PMID   29111135. S2CID   3735944.
  31. Rosen GD, Williams AG, Capra JA, Connolly MT, Cruz B, Lu L, Airey DC, Kulkarni K, Williams RW (2000) The Mouse Brain Library @ www.mbl.org. Int Mouse Genome Conference 14: 166. www.mbl.org.
  32. Winnubst, Johan; Bas, Erhan; Ferreira, Tiago A.; Wu, Zhuhao; Economo, Michael N.; Edson, Patrick; Arthur, Ben J.; Bruns, Christopher; Rokicki, Konrad; Schauder, David; Olbris, Donald J.; Murphy, Sean D.; Ackerman, David G.; Arshadi, Cameron; Baldwin, Perry (2019-09-19). "Reconstruction of 1,000 Projection Neurons Reveals New Cell Types and Organization of Long-Range Connectivity in the Mouse Brain". Cell. 179 (1): 268–281.e13. doi:10.1016/j.cell.2019.07.042. ISSN   1097-4172. PMC   6754285 . PMID   31495573.
  33. Tripathy, Shreejoy; Gerkin, Richard. "NeuroElectro". www.neuroelectro.org. Retrieved 10 August 2016.
  34. Ascoli GA, Donohue DE, Halavi M (August 2007). "NeuroMorpho.Org: a central resource for neuronal morphologies". The Journal of Neuroscience. 27 (35): 9247–51. doi:10.1523/JNEUROSCI.2055-07.2007. PMC   6673130 . PMID   17728438.
  35. Mirsky JS, Nadkarni PM, Healy MD, Miller PL, Shepherd GM (July 1998). "Database tools for integrating and searching membrane property data correlated with neuronal morphology". Journal of Neuroscience Methods. 82 (1): 105–21. doi: 10.1016/S0165-0270(98)00049-1 . PMID   10223520. S2CID   12871618.
  36. Marcus DS, Wang TH, Parker J, Csernansky JG, Morris JC, Buckner RL (September 2007). "Open Access Series of Imaging Studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults". Journal of Cognitive Neuroscience. 19 (9): 1498–507. doi:10.1162/jocn.2007.19.9.1498. PMID   17714011. S2CID   10840552.
  37. Vogelstein, Joshua T (2011-11-18). "Q&A: What is the Open Connectome Project?". Neural Systems & Circuits. 1 (1): 16. doi: 10.1186/2042-1001-1-16 . ISSN   2042-1001. PMC   3278382 . PMID   22329952.
  38. Yücel, M. A., Tucker, S., Choi, J., Boas, D. A. (2020), Data – openfnirs , retrieved 18 April 2024
  39. Poldrack RA, Barch DM, Mitchell JP, Wager TD, Wagner AD, Devlin JT, Cumba C, Koyejo O, Milham MP (Jul 2013). "Toward open sharing of task-based fMRI data: the OpenfMRI project". Frontiers in Neuroinformatics. 7 (12): 12. doi: 10.3389/fninf.2013.00012 . PMC   3703526 . PMID   23847528.
  40. Niso G, Rogers C, Moreau JT, Chen LY, Madjar C, Das S, et al. (January 2016). "OMEGA: The Open MEG Archive". NeuroImage. 124 (Pt B): 1182–7. doi:10.1016/j.neuroimage.2015.04.028. PMID   25896932. S2CID   29021506.
  41. Labus JS, Naliboff B, Kilpatrick L, Liu C, Ashe-McNalley C, dos Santos IR, et al. (January 2016). "Pain and Interoception Imaging Network (PAIN): A multimodal, multisite, brain-imaging repository for chronic somatic and visceral pain disorders". NeuroImage. 124 (Pt B): 1232–7. doi:10.1016/j.neuroimage.2015.04.018. PMC   4627849 . PMID   25902408.
  42. Conrad MS, Sutton BP, Dilger RN, Johnson RW (September 2014). "An In Vivo Three-Dimensional Magnetic Resonance Imaging-Based Averaged Brain Collection of the Neonatal Piglet (Sus scrofa)". PLOS ONE. 9 (9): e107650. Bibcode:2014PLoSO...9j7650C. doi: 10.1371/journal.pone.0107650 . PMC   4177841 . PMID   25254955.
  43. Wang L, Alpert KI, Calhoun VD, Cobia DJ, Keator DB, King MD, et al. (January 2016). "SchizConnect: Mediating neuroimaging databases on schizophrenia and related disorders for large-scale integration". NeuroImage. 124 (Pt B): 1155–67. doi:10.1016/j.neuroimage.2015.06.065. PMC   4651768 . PMID   26142271.
  44. Obeid I, Picone J (2016-05-13). "The Temple University Hospital EEG Data Corpus". Frontiers in Neuroscience. 10: 196. doi: 10.3389/fnins.2016.00196 . PMC   4865520 . PMID   27242402.
  45. Lüsebrink F, Sciarra A, Mattern H, Yakupov R, Speck O (March 2017). "1-weighted in vivo human whole brain MRI dataset with an ultrahigh isotropic resolution of 250 μm". Scientific Data. 4 (170032): 170032. Bibcode:2017NatSD...470032L. doi:10.1038/sdata.2017.32. PMC   5349250 . PMID   28291265.
  46. Gorgolewski KJ, Varoquaux G, Rivera G, Schwartz Y, Ghosh SS, Maumet M, Nichols TE, Poldrack RA, Poline JB, Yarkoni T, Margulies DS (Oct 2014). "NeuroVault.org: A web-based repository for collecting and sharing unthresholded statistical maps of the human brain". bioRxiv   10.1101/010348 .
  47. Gardner D, Akil H, Ascoli GA, Bowden DM, Bug W, Donohue DE, et al. (September 2008). "The neuroscience information framework: a data and knowledge environment for neuroscience". Neuroinformatics. 6 (3): 149–60. doi:10.1007/s12021-008-9024-z. PMC   2661130 . PMID   18946742.
  48. "Right Relevance : Neuroscience". www.rightrelevance.com. Right Relevance. Retrieved 10 August 2016.