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http://healthybrain.umn.edu/

Research forum portal to address brain status by acquiring comprehensive, multimodal data from healthy humans across the lifespan to characterize brain status, assess its change over time, and associate composite descriptors of brain status. Specifically, the measurements are acquired noninvasively by existing neuroimaging technologies (structural MRI, functional MRI, magnetic resonance spectroscopy, diffusion MRI, and magnetoencephalography); in addition, genetic, cognitive, language, and lifestyle data are acquired. Goals: * Derive the Brain Health Index- An integrative assessment of brain status derived from multimodal measurements of brain structure, function, and chemistry. * Continue acquiring data to construct the first-ever databank on brain, cognitive, language and genetic measurements for healthy people across the lifespan. * Provide a novel and unique dataset by which to: characterize brain status, assess its change over time, and associate it with genetic makeup, cognitive function, and language abilities. * Forecast future brain health and disease based on current measurements and guide physicians towards new interventions and evaluate interventions as they develop. * Extend to siblings and other family members to further assess the genetic influences and inheritability.

Proper citation: HBP: Healthy Brain Project (RRID:SCR_013137) Copy   

•   Source: SciCrunch Registry

https://github.com/NOCIONS/letswave6/wiki/Download-and-setup

Open source electroencephalogram (EEG) signal processing toolbox to process and visualise EEG/MEG data and other neurophysiological signals.

Proper citation: Letswave (RRID:SCR_016414) Copy   

•   Source: SciCrunch Registry

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

Software toolbox to simplify and streamline mechanism of pre and post processing 2D brain image data. Neuroscience image processing and analysis utilities. Stand alone application that runs on all operating systems. Nutil is part of the QUINT workflow.

Proper citation: Nutil - Neuroimaging utilities (RRID:SCR_017183) Copy   

•   Source: SciCrunch Registry

http://hpc-bioinformatics.cineca.it/stress_mice/

Sapienza University of Rome and Cineca consortium portal. Used for analyzing published RNAseq transcriptomes obtained from brain of mice exposed to different kinds of stress protocols, to generate database of stress related differentially expressed genes and to identify factors contributing to vulnerability or resistance to stress. Allows to query database of RNAseq data.

Proper citation: Stress Mice Portal (RRID:SCR_017572) Copy   

•   Source: SciCrunch Registry

http://coins.mrn.org/

A web-based neuroimaging and neuropsychology software suite that offers versatile, automatable data upload/import/entry options, rapid and secure sharing of data among PIs, querying and export all data, real-time reporting, and HIPAA and IRB compliant study-management tools suitable to large institutions as well as smaller scale neuroscience and neuropsychology researchers. COINS manages over over 400 studies, more than 265,000 clinical neuropsychological assessments, and 26,000 MRI, EEG, and MEG scan sessions collected from 18,000 participants at over ten institutions on topics related to the brain and behavior. As neuroimaging research continues to grow, dynamic neuroinformatics systems are necessary to store, retrieve, mine and share the massive amounts of data. The Collaborative Informatics and Neuroimaging Suite (COINS) has been created to facilitate communication and cultivate a data community. This tool suite offers versatile data upload/import/entry options, rapid and secure sharing of data among PIs, querying of data types and assessments, real-time reporting, and study-management tools suitable to large institutions as well as smaller scale researchers. It manages studies and their data at the Mind Research Network, the Nathan Kline Institute, University of Colorado Boulder, the Olin Neuropsychiatry Research Center (at) Hartford Hospital, and others. COINS is dynamic and evolves as the neuroimaging field grows. COINS consists of the following collaboration-centric tools: * Subject and Study Management: MICIS (Medical Imaging Computer Information System) is a centralized PostgreSQL-based web application that implements best practices for participant enrollment and management. Research site administrators can easily create and manage studies, as well as generate reports useful for reporting to funding agencies. * Scan Data Collection: An automated DICOM receiver collects, archives, and imports imaging data into the file system and COINS, requiring no user intervention. The database also offers scan annotation and behavioral data management, radiology review event reports, and scan time billing. * Assessment Data Collection: Clinical data gathered from interviews, questionnaires, and neuropsychological tests are entered into COINS through the web application called Assessment Manager (ASMT). ASMT's intuitive design allows users to start data collection with little or no training. ASMT offers several options for data collection/entry: dual data entry, for paper assessments, the Participant Portal, an online tool that allows subjects to fill out questionnaires, and Tablet entry, an offline data entry tool. * Data Sharing: De-identified neuroimaging datasets with associated clinical-data, cognitive-data, and associated meta-data are available through the COINS Data Exchange tool. The Data Exchange is an interface that allows investigators to request and share data. It also tracks data requests and keeps an inventory of data that has already been shared between users. Once requests for data have been approved, investigators can download the data directly from COINS.

Proper citation: Mind Research Network - COINS (RRID:SCR_000805) Copy   

•   Source: SciCrunch Registry

http://www.loni.ucla.edu/~thompson/thompson.html

The UCLA laboratory of neuroimaging is working in several areas to enhance knowledge of anatomy, including brain mapping in large human populations, HIV, Schizophrenia, methamphetamine, tumor growth and 4d brain mapping, genetics and detection of abnormalities.

Proper citation: University of California at Los Angeles, School of Medicine: Neuro Imaging Lab of Thompson (RRID:SCR_001924) Copy   

•   Source: SciCrunch Registry

http://humanconnectome.org/connectome/connectomeDB.html

Data management platform that houses all data generated by the Human Connectome Project - image data, clinical evaluations, behavioral data and more. ConnectomeDB stores raw image data, as well as results of analysis and processing pipelines. Using the ConnectomeDB infrastructure, research centers will be also able to manage Connectome-like projects, including data upload and entry, quality control, processing pipelines, and data distribution. ConnectomeDB is designed to be a data-mining tool, that allows users to generate and test hypotheses based on groups of subjects. Using the ConnectomeDB interface, users can easily search, browse and filter large amounts of subject data, and download necessary files for many kinds of analysis. ConnectomeDB is designed to work seamlessly with Connectome Workbench, an interactive, multidimensional visualization platform designed specifically for handling connectivity data. De-identified data within ConnectomeDB is publicly accessible. Access to additional data may be available to qualified research investigators. ConnectomeDB is being hosted on a BlueArc storage platform housed at Washington University through the year 2020. This data platform is based on XNAT, an open-source image informatics software toolkit developed by the NRG at Washington University. ConnectomeDB itself is fully open source.

Proper citation: ConnectomeDB (RRID:SCR_004830) Copy   

•   Source: SciCrunch Registry

http://www.neuro.uni-jena.de/cat/

Software toolbox as extension to SPM12 to provide computational anatomy. This covers diverse morphometric methods such as voxel based morphometry, surface based morphometry, deformation based morphometry, and region or label based morphometry.

Proper citation: Computational Anatomy Toolbox for SPM (RRID:SCR_019184) 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.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

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

https://molbio.princeton.edu/core-facilities/confocal-microscopy

Core provides researchers with ability to visualize samples, from monolayers and small organisms, such as developing fly and fish embryos, to very thick sections from brain and other organ tissues by using instruments including laser point (LSCM) and field scanning confocal (CSU), Total Internal Reflectance Fluorescence (TIRF), Multi Photon (MP), and Widefield (WF). Services in imaging in mammalian cells, yeast cells, Drosophila and Zebrafish embryos and ovaries, bacteria, sections of brain and other tissues, in both fixed and live specimens, Quantitative imaging methods such as FRAP, FLIP, and FRET, software packages for image processing, analysis, and 3D image reconstruction.

Proper citation: Princeton University Confocal Microscopy Core Facility (RRID:SCR_017812) Copy   

•   Source: SciCrunch Registry

http://case.edu/medicine/ccir/imaging-research-core/

Core provides preclinical and clinical imaging instrumentation and techniques.Preclinical services include Bioluminescence,Fluorescence,In situ cryoimaging,Magnetic Resonance Imaging (MRI),Positron Emission Tomography (PET),Radiochemistry Synthesis, Scintigraphy,Ultrasound,X-ray / Computed Tomography (CT) / micro CT,Image Processing / Quantification clinical research imaging systems. Clinical services include Comprehensive MR imaging research services, Dedicated Siemens Skyra 3T MRI scanner, Large animal preclinical studies, or clinical human research may be conducted,Structural and functional brain scanning can be performed with Avotec LCD Projection System, Coodination of access to PET and CT scanners for additional preclinical and human imaging studies. Core includes PET radiopharmaceutical core facility. Core staff provide radiochemistry synthesis.

Proper citation: Case Western Reserve University Imaging Research Core Facility (RRID:SCR_017917) 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