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http://brainandsociety.org/the-brain-observatory
Formerly a topical portal studying the brain which collected and imaged 1000 human brains, the Brain Observatory has partnered with the Institute for Brain and Society to build virtual laboratories that will feed directly into the database of images and knowledge created in the context of the Human Brain Library. The Brain Observatory will also host exhibits, conferences, and events aimed at promoting a heightened awareness of brain research and how its results can benefit personal brain fitness and mental health.
Proper citation: Brain Observatory (RRID:SCR_010641) Copy
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
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
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
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
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
http://neurobureau.projects.nitrc.org/BrainArt/Competition.html
An annual Brain-Art Competition to recognize the beauty and creativity of artistic renderings emerging from the neuroimaging community. Submission deadline: June 1st, 2012. Awards will be announced on June 11th during the OHBM conference in Beijing. (You need not be present to win) Countless hours are devoted to creation of informative visualizations for communicating neuroscientific findings. This competition once again aims to recognize the artistic creativity of our community that often goes underappreciated in the publication process. We are inviting researchers to submit their favorite unpublished works for entry. Both team and single-person entries are welcomed. The competition will have five award categories: # Best Representation of the Human Connectome # Best Abstract Brain Illustration # Best Educational Brain Illustration # Best Humorous Brain Illustration # Best Video Illustration of the Brain Submissions will be evaluated based on their aesthetic merit
Proper citation: Brain-Art Competition (RRID:SCR_005360) Copy
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
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
Visualization and analysis software for interactive visual exploration and mining of fiber-tracts and brain networks with their genetic determinants and functional outcomes. BECA includes an fMRI and Diseases Analysis version as well as a Genome Explorer version.
Proper citation: BECA (RRID:SCR_015846) Copy
Consortium for the cell census in the brain. Integrated network of data generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate brains.
Proper citation: BICCN (RRID:SCR_015820) Copy
Consortium studying the regulation and alternative splicing of gene expression in multiple tissues from human brains. The UKBEC dataset comprises of brains from individuals free of neurodegenerative disorders.
Proper citation: UK Brain Expression Consortium (RRID:SCR_015889) Copy
https://github.com/ABCD-STUDY/ABCDreport
Software application as a simple system to review study progress. Used in ABCD study.
Proper citation: ABCDreport (RRID:SCR_016030) Copy
Research project examining how biological, psychological, and environmental factors during adolescence may influence brain development and mental health. Using brain imaging and genetics, the project will help develop prevention strategies and improved therapies for mental health disorders in the future., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: IMAGEN (RRID:SCR_016045) Copy
https://www.nitrc.org/projects/normalizefov
FSoftware for field-of-view normalization to minimize mismatch in different subjects' images. It aids that streamline analysis of large-scale brain MRI datasets.
Proper citation: NeuroImage Field-of-View Normalization Tool (RRID:SCR_015957) Copy
Portal enabling web based visualization and analysis of multi omic data describing cell types in developing and adult brain, powered by gEAR and EpiViz. Release 1 on April 2019 includes single cell and bulk tissue RNAseq, ATACseq, and ChIPseq from fetal human prefrontal cortex, as well as from stem cell models of neural induction. Portal will expand to include multiple regions of developing and adult brain and additional analytical tools.
Proper citation: NeMO Analytics (RRID:SCR_018164) Copy
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
Software designed to automatically realign brain images for easier cross patient examination regardless of age, disease or head position. It positions and aligns anatomy-related sagittal, coronal and axial slices using anatomical landmarks.
Proper citation: AutoAlign Head (RRID:SCR_014245) Copy
https://cfn.upenn.edu/~zewang/BENtbx.php
A toolkit for mapping brain entropy using fMRI. It uses several functions from ASLtbx. At its core, the toolkit is a collection of batch scripts that implement a pipeline for processing fMRI data in order to get Sample entropy for each voxel.
Proper citation: Brain Entropy Mapping Toolbox (RRID:SCR_014470) Copy
http://www.brainsimagebank.ac.uk
A searchable collection of anonymised images and associated clinical data. It includes normal individuals at all ages (from prenatal to old age). The image bank contains integrated data sets already collected as part of research studies which include control subjects. New data is added as they become available.
Proper citation: BRAINS Imagebank (RRID:SCR_014576) Copy
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