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http://www.brainbank.nl

A biomaterial supply resource which collects, stores, and disseminates diseased and healthy brain tissue. The Netherlands Brain Bank currently contains more than 3600 samples, and each sample includes a neuropathological report and donor medical history. The samples can additionally be matched with ante-mortem parameters and post-mortem parameters upon request. Sample types include cortex, spinal cord, cerebrospinal fluid, plasma, and DNA, among others. Database mining is available with a financial contribution.

Proper citation: Netherlands Brain Bank (RRID:SCR_013841) Copy   

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http://www.ncl.ac.uk/ion/about/facilities/nbtr/

A biomaterial supply resource which archives and disseminates brain tissue for the study of normal brain aging and brain disorders. Researchers must create an account in order to browse the database of available tissue. Samples are distributed to researchers in such a way that the identity and personal information of donors is protected.

Proper citation: Newcastle Brain Tissue Resource (RRID:SCR_013843) Copy   

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https://support.inscopix.com/search/site/Mosaic

Mosaic software features apps designed to help you derive deeper insights from videos of large scale circuit dynamics by Inscopix Inc.

Proper citation: Mosaic (RRID:SCR_017408) Copy   

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http://autopatcher.org/

Software tool for neuronal recording in intact brain.

Proper citation: Autopatcher (RRID:SCR_017464) Copy   

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https://github.com/dorianps/LESYMAP

Software R package to conduct lesion-to-symptom mapping from human MRI data.Takes lesion maps and cognitive performance scores from patients with stroke, and maps brain areas responsible for cognitive deficit.

Proper citation: LESYMAP (RRID:SCR_017967) Copy   

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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   

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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   

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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://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   

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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   

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http://sig.biostr.washington.edu/projects/MindSeer/index.html

A cross-platform application for 3D brain visualization for multi-modality neuroimaging data written in Java/Java3D, that runs in both standalone and client-server mode. It supports basic data management capabilities, visualization of 3D surfaces (SPM's output or OFF files), volumes (Analyze, NIFTI or Minc) and label sets. MindSeer has 2 different modes: # Client/Server is designed to allow users to visualize data that is stored centrally and enhance collaboration. # Standalone mode is available to view local data and is built for more performance than Client/Server Both modes have the same interface and support the same features. It has a modular architecture and is designed to be extensible. Requirements: # Java 5.0 or above. # Java Web Start. # Java3D (installed automatically by Web Start).

Proper citation: MindSeer (RRID:SCR_003019) Copy   

•   Source: SciCrunch Registry

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

Simulation software that generates pathological ground truth from a healthy ground truth. The software requires an input directory that describes a healthy anatomy (anatomical probabilities, mesh, diffusion tensor image, etc) and then outputs simulation images.

Proper citation: TumorSim (RRID:SCR_002604) Copy   

•   Source: SciCrunch Registry

Issue

https://github.com/spm

Software package for analysis of brain imaging data sequences. Sequences can be a series of images from different cohorts, or time-series from same subject. Current release is designed for analysis of fMRI, PET, SPECT, EEG and MEG.

Proper citation: SPM (RRID:SCR_007037) 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://braincanada.ca/

Brain Canada is a national non-profit organization that develops and supports collaborative, multidisciplinary, multi-institutional research across the neurosciences. Through partnering with the public, private and voluntary sectors, Brain Canada connects the knowledge and resources available in this area to accelerate neuroscience research and funding and maximize the output of Canada''s world-class scientists and researchers. Brain Canada was created to address the twin challenges of increasing the scale of brain research funding in Canada and widening its scope to encourage interdisciplinary collaboration to produce insights for treating multiple disorders. Brain Canada is built on the successes and model of NeuroScience Canada (NSC). Established in 1999, NSC raised more than $11.5 million, leveraged over $20 million with partnered funding, and funded 100 individual and teams of researchers in Canada. Brain Canada is the new vision for Canadian brain researchthe voice for the brain and the grouping of brain disorders, raising awareness about their prevalence and impact on individuals, families, the economy and society. But most important, through the research we are funding, we are giving hope to the millions of Canadians who are directly or indirectly touched by diseases, disorders, and injuries of the brain, spinal cord and nervous system.

Proper citation: Brain Canada (RRID:SCR_005053) Copy   

•   Source: SciCrunch Registry

https://neuroscienceblueprint.nih.gov/Resources-Tools/Blueprint-Resources-Tools-Library

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 22, 2023. National initiative to advance biomedical research through data sharing and online collaboration that provides data sharing infrastructure, software tools, strategies and advisory services. Groups may choose whether to share data internally or with external audiences. Hardware and data remain under control of individual user groups.

Proper citation: Biomedical Informatics Research Network (RRID:SCR_005163) Copy   

•   Source: SciCrunch Registry

http://hdbase.org/cgi-bin/welcome.cgi

A community website for Huntington''s Disease (HD) research that currently contains Y2H and Mass spectrometry protein-protein interaction data centered around the HD protein (huntingtin) and information on therapeutic studies in mouse. Also available are raw Human and Mouse Affymetrix Microarray data. The protein interaction data is from several sources, including interactions curated from the literature by ISB staff, experimentally determined interactions produced by Bob Hughes and colleagues at Prolexys (currently password protected), and interactions reported in a recent publication by Goehler et al from Eric Wanker''s lab. Content areas that may be covered by the site include the following: * Therapeutic studies in mouse, primarily drug screens. * HD mouse models with a focus on timelines of disease progression. * Antibodies used in HD research. * Microarray gene expression studies. * Genes and proteins relevant to HD research. This includes HD itself, the growing list of proteins thought to interact directly or indirectly with huntingtin (Htt), and other genes and proteins implicated in the disease process. * Molecular pathways thought to be involved in the disease process. * Timelines of disease for Mouse models

Proper citation: HDBase (RRID:SCR_007132) Copy   

•   Source: SciCrunch Registry

http://www.uky.edu/coa/ADC

Alzheimer's Disease Center that serves as the focal point for all Alzheimer's disease-related activities at the University of Kentucky and the Commonwealth of Kentucky providing an environment and core resources that catalyze innovative research, outreach, education, and clinical programs. Their ADC plans to build on its historic strengths and capitalize on emerging opportunities to provide an infrastructure that supports research designed to translate knowledge into therapeutic strategies for AD. They focus on two interrelated themes: Transitions and Translation. Their overall emphasis is to more effectively bridge the gap between basic research and clinical studies by facilitating translational efforts. They also carefully characterize transitions across the spectrum of cognitive impairment (normal/ preclinical AD/ MCI/ dementia), with focus on definition of early disease, and continue to support neuropathology as the bedrock of our center. The Alzheimer Disease Center's 2006-2011 grant award from the National Institute on Aging consists of five cores: * Administrative Core * Clinical Core * Biostatistics and Data Management Core * Neuropathology Core * Education & Information Transfer Core

Proper citation: University of Kentucky Alzheimer's Disease Center (RRID:SCR_008767) 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

https://www.aplysia.earth.miami.edu/

Center where Aplysia californica are cultured and raised for research purposes. Aplysia from the facility serve in research on genomics, human brain function, toxicology for developmental studies, natural products, chemistry for isolation of novel anti-tumor and antibacterial compounds, in the study of transport by digestive tissues and have potential for use in studies of substance addiction and nerve senescence and regeneration.

Proper citation: National Resource for Aplysia (RRID:SCR_008361) Copy   

•   Source: SciCrunch Registry