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http://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1

An unbiased standard magnetic resonance imaging template brain volume for pediatric data from the 4.5 to 18.5y age range. These volumes were created using data from 324 children enrolled in the NIH-funded MRI study of normal brain development (Almli et al., 2007, Evans and Group 2006). Tools for using these atlases can be found in the Software section. To view the atlases online, click on the appropriate JIV2 link in the Download section. You can download templates constructed for different age ranges. For each age range you will get an average T1w, T2w, PDw maps normalized between 0 and 100 and tissue probability maps, with values between 0 and 1. Also each age range includes a binary brain mask.

Proper citation: NIHPD Objective 1 atlases (4.5 - 18.5y) (RRID:SCR_008794) 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.cs.tau.ac.il/~shlomito/tissue-net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Network visualizations in which the expression and predicted flux data are projected over the global human network. These network visualizations are accessible through the supplemental website using the publicly available Cytoscape software (Cline, Smoot et al. 2007). Since many high degree nodes exist in the network, special layouts are required to produce network visualizations that are readily interpretable. To this end we produced network visualizations in which hub nodes are repeated multiple times and hence layouts with a small number of edge crossings can be generated. Contains entries for brain compartments and brain pathways.

Proper citation: Network-based Prediction of Human Tissue-specific Metabolism (RRID:SCR_007392) Copy   

•   Source: SciCrunch Registry

http://nac.spl.harvard.edu/

Biomedical Technology Resource Center that develops image processing and analysis techniques for basic and clinical neurosciences. The NAC research approach emphasizes both specific core technologies and collaborative application projects. The core activity of the center is the development of algorithms and techniques for postprocessing of imaging data. New segmentation techniques aid identification of brain structures and disease. Registration methods are used for relating image data to specific patient anatomy or one set of images to another. Visualization tools allow the display of complex anatomical and quantitative information. High-performance computing hardware and associated software techniques further accelerate algorithms and methods. Digital anatomy atlases are developed for the support of both interactive and algorithmic computational tools. Although the emphasis of the NAC is on the dissemination of concepts and techniques, specific elements of the core software technologies have been made available to outside researchers or the community at large. The NAC's core technologies serve the following major collaborative projects: Alzheimer's disease and the aging brain, morphometric measures in schizophrenia and schizotypal disorder, quantitative analysis of multiple sclerosis, and interactive image-based planning and guidance in neurosurgery. One or more NAC researchers have been designated as responsible for each of the core technologies and the collaborative projects.

Proper citation: Neuroimage Analysis Center (RRID:SCR_008998) Copy   

•   Source: SciCrunch Registry

https://confluence.crbs.ucsd.edu/display/NIF/StemCellInfo

Data tables providing an overview of information about stem cells that have been derived from mice and humans. The tables summarize published research that characterizes cells that are capable of developing into cells of multiple germ layers (i.e., multipotent or pluripotent) or that can generate the differentiated cell types of another tissue (i.e., plasticity) such as a bone marrow cell becoming a neuronal cell. The tables do not include information about cells considered progenitor or precursor cells or those that can proliferate without the demonstrated ability to generate cell types of other tissues. The tables list the tissue from which the cells were derived, the types of cells that developed, the conditions under which differentiation occurred, the methods by which the cells were characterized, and the primary references for the information.

Proper citation: National Institutes of Health Stem Cell Tables (RRID:SCR_008359) 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

http://www.cma.mgh.harvard.edu/

A center dedicated to developing and applying morphometric methods to biomedical imaging data such as high-resolution MRI. The lab uses automated and semi-automated software such that MRI brain images are segmented into anatomical regions of interest. Projects in both basic and applied brain research include research on strokes and tumors; medical image processing research includes shape analysis of anatomical brain regions and measurement and analysis of brain volumes.

Proper citation: MGH Center for Morphometric Analysis (RRID:SCR_000885) Copy   

•   Source: SciCrunch Registry

http://blog.wholebraincatalog.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 6,2023. The blog of the Whole Brain Catalog.

Proper citation: Whole Brain Catalog Blog (RRID:SCR_000582) Copy   

•   Source: SciCrunch Registry

https://www.upf.edu/web/ntsa/downloads/-/asset_publisher/xvT6E4pczrBw/content/2001-indications-of-nonlinear-deterministic-and-finite-dimensional-structures-in-time-series-of-brain-electrical-activity-dependence-on-recording-regi?p_r_p_assetEntryId=229569389&_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_type=content&_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_urlTitle=2001-indications-of-nonlinear-deterministic-and-finite-dimensional-structures-in-time-series-of-brain-electrical-activity-dependence-on-recording-regi&_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_redirect=https%3A%2F%2Fwww.upf.edu%3A443%2Fweb%2Fntsa%2Fdownloads%3Fp_p_id%3Dcom_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw%26p_p_lifecycle%3D0%26p_p_state%3Dnormal%26p_p_mode%3Dview%26p_r_p_assetEntryId%3D229569389%26_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_xvT6E4pczrBw_cur%3D0%26p_r_p_resetCur%3Dfalse#229569389

Five data sets containing quasi-stationary, artifact-free EEG signals both in normal subjects and epileptic patients were put in the web by Ralph Andrzejak from the Epilepsy center in Bonn, Germany. Each data set contains 100 single channel EEG segments of 23.6 sec duration.

Proper citation: EEG time series Data Sets (RRID:SCR_001579) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/

Biomedical technology resource center specializing in novel approaches and tools for neuroimaging. It develops novel strategies to investigate brain structure and function in their full multidimensional complexity. There is a rapidly growing need for brain models comprehensive enough to represent brain structure and function as they change across time in large populations, in different disease states, across imaging modalities, across age and sex, and even across species. International networks of collaborators are provided with a diverse array of tools to create, analyze, visualize, and interact with models of the brain. A major focus of these collaborations is to develop four-dimensional brain models that track and analyze complex patterns of dynamically changing brain structure in development and disease, expanding investigations of brain structure-function relations to four dimensions.

Proper citation: Laboratory of Neuro Imaging (RRID:SCR_001922) Copy   

•   Source: SciCrunch Registry

http://www.fmri.org

THIS RESOURCE IS NO LONGER IN SERVICE, documented on 7/28/13. Core facility of Columbia Neuroscience with the goal of establishing a collaborative and multi-investigator neuroimaging environment that is focused on the investigation of the neurocircuitry of the brain that underlies cognition, perception and action, and also the development of clinical applications that enhance the goals of personalized medicine. Within this environment the specific current research interests of the Hirsch group include several related directions of investigation. The first is conscious and subconscious neural processes that mediate emotion and cognition in healthy individuals and in patients with psychiatric disorders. This direction also includes neurocircuitry that is characteristic of disorders of consciousness such as minimally conscious or vegetative states, self and visual awareness, and attention. Neurocircuitry of other complex cognitive processes such as decisions, inductive and deductive reasoning, language, truthfulness and top-down influences of expectation, reward, and regulation on early visual and mid-level perceptual and emotional systems. On-going projects targeted for clinical applications include benefits for neurosurgery such as the development of task batteries to map the cortical locations of essential functions such as language, motor, sensation, memory, emotion and sensory functions including visions, audition and the chemical senses. Computational innovations for labeling correspondence between brain structure and specific functional regions are under development to achieve the highest interpretive precision. Current projects include integration of EEG and fMRI techniques to localize seizuregenic cortex in relation to eloquent and functioning cortex for neurosurgical planning; integration of TMS and fMRI to discriminate essential and associative language-sensitive cortical areas; and integration of VEP, EEG and fMRI to inform assessments of visual disease secondary to stroke or neural degeneration. Projects intended to refine and enhance diagnosis of psychiatric disorders such as anxiety, depression, and eating disorders include development of specialized paradigms to target dysfunctional neurocircuitry such as emotional systems (amygdala and basal ganglia) and control and regulatory systems (cingulate and pre-frontal cortex). Comparison of before-treatment images with after-treatment images to inform models of both treatment and disease and investigation of the hypothesis that individual genetic and functional differences have predictive value for treatment options and outcome are currently underway. The lab has pioneered techniques for functional mapping of single patients, and operates an active clinical service for mapping individuals for neurosurgical planning, assessments of the neurocircuitry that underlie acquired or inherited disabilities and the mechanisms of neuroplasticity that restore lost functions are actively investigated using both groups and single subject studies. :

Proper citation: fMRI Research Center at Columbia (RRID:SCR_002658) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/pro/BeijingShortTR.html

Dataset of resting state fMRI scans obtained using two different TR's in healthy college-aged volunteers. Specifically, for each participant, data is being obtained with a short TR (0.4 seconds) and a long TR (2.0 seconds). In addition this dataset contains a 64-direction DTI scan for every participant. The following data are released for every participant: * 8-minute resting-state fMRI scan (TR = 2 seconds, # repetitions = 240) * 8-minute resting-state fMRI scans (TR = 0.4 seconds, # repetitions = 1200) * MPRAGE anatomical scan, defaced to protect patient confidentiality * 64-direction diffusion tensor imaging scan (2mm isotropic) * Demographic information

Proper citation: Beijing: Short TR Study (RRID:SCR_003502) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/pro/Quiron-Valencia.html

Resting state datasets, including an anatomical as well as a resting state fMRI scan, collected from a community sample in Valencia, Spain. The first release includes data for 45 participants. Participants were instructed to keep their eyes open during the resting state scan, no visual stimulus was presented. The following data are released for every participant: * Scanner Type: Philips Achieva 3T-TX * One high-resolution T1-weighted mprage, defaced to protect patient confidentiality * At least one 6-minute resting state fMRI scan (R-fMRI), eyes open, no visual stimulus presented * Demographic Information

Proper citation: Quiron-Valencia Sample (RRID:SCR_003538) Copy   

•   Source: SciCrunch Registry

http://www.linked-neuron-data.org/

Neuroscience data and knowledge from multiple scales and multiple data sources that has been extracted, linked, and organized to support comprehensive understanding of the brain. The core is the CAS Brain Knowledge base, a very large scale brain knowledge base based on automatic knowledge extraction and integration from various data and knowledge sources. The LND platform provides services for neuron data and knowledge extraction, representation, integration, visualization, semantic search and reasoning over the linked neuron data. Currently, LND extracts and integrates semantic data and knowledge from the following resources: PubMed, INCF-CUMBO, Allen Reference Atlas, NIF, NeuroLex, MeSH, DBPedia/Wikipedia, etc.

Proper citation: Linked Neuron Data (RRID:SCR_003658) Copy   

•   Source: SciCrunch Registry

https://voxelmorph.net

Software tool for joint surface based registration and atlas construction of brain geometry and function.Cortical registration framework that jointly models mismatch between geometry and function while simultaneously learning unbiased population specific atlas.

Proper citation: JOSA (RRID:SCR_024756) Copy   

•   Source: SciCrunch Registry

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FLIRT

Sotware automated robust and accurate tool for linear (affine) intra- and inter-modal brain image registration.

Proper citation: FMRIB's Linear Image Registration Tool (RRID:SCR_024922) Copy   

•   Source: SciCrunch Registry

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/XTRACT

Software command line tool for automated tractography. Standardised protocols for automated tractography in human and macaque brain.

Proper citation: XTRACT (RRID:SCR_024933) Copy   

•   Source: SciCrunch Registry

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/verbena

Software tool for quantification of perfusion and other haemodynamic parameters from Dynamic Susceptibility Contrast perfusion MRI of the brain.

Proper citation: VERBENA (RRID:SCR_024919) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/pro/nyu.html

Datasets including a collection of scans from 49 psychiatrically evaluated neurotypical adults, ranging in age from 6 to 55 years old, with age, gender and intelligence quotient (IQ) information provided. Future releases will include more comprehensive phenotypic information, and child and adolescent datasets, as well as individuals from clinical populations. The following data are released for every participant: * At least one 6-minute resting state fMRI scan (R-fMRI) * * One high-resolution T1-weighted mprage, defaced to protect patient confidentiality * Two 64-direction diffusion tensor imaging scans * Demographic information (age, gender) and IQ-measures (Verbal, Performance, and Composite; Weschler Abbreviated Scale of Intelligence - WASI) * Most participants have 2 R-fMRI scans, collected less than 1 hour apart in the same scanning session. Rest_1 is always collected first.

Proper citation: NYU Institute for Pediatric Neuroscience Sample (RRID:SCR_010458) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/pro/VirginiaTech.html

Dataset including a T1 weighted anatomical image as well as two 10-minute resting state scans acquired during the same session from 25 psychiatrically screened healthy adults (community sample) ranging in age from 18 to 65 years old, with age, sex, education level, and ethnicity provided. Some subjects also returned several weeks after the first scan for a second scanning session. The number of days between scan sessions, for subjects that had two sessions, is indicated in the demographics spreadsheet. The study scanning protocol included: # 13 sec localizer # 4 minute 38 second T1 weighted anatomical # Subject given instructions for resting state scan #1 # 10 minute 4 second resting state scan #1 # Subject given instructions for resting state scan #2 # 10 minute 4 second resting state scan #2 Scanning was performed on one of three different 3T Siemens TIM TRIOs at the Human Neuroimaging Lab at Baylor College of Medicine in Houston, Texas. All scans were acquired using the standard Siemen''s TIM 12-channel head matrix. The resting state scans were acquired with a custom sequence that is a slight modification to the standard Siemen''s EPI sequence that supports real-time fMRI. Images were acquired slightly oblique to minimize dephasing in the orbito-frontal cortex. Detailed scanning parameters are included in separate .pdf files.

Proper citation: Virginia Tech Carilion Research Institute Sample (RRID:SCR_010459) Copy   

•   Source: SciCrunch Registry