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http://www.opensourcebrain.org

A resource for sharing and collaboratively developing computational models of neural systems. While models can be submitted and developed in any format, the use of open standards such as NeuroML and PyNN is encouraged, to ensure transparency, modularity, accessibility and cross simulator portability. OSB will provide advanced facilities to analyze, visualize and transform models in these formats, and to connect researchers interested in models of specific neurons, brain regions and disease states. Research themes include: Basal ganglia modelling, Cerebellar Granule cell modelling, Cerebellar modelling, Hippocampal modelling, Neocortical modelling, Whole brain models. Additional themes are welcome.

Proper citation: Open Source Brain (RRID:SCR_001393) Copy   

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http://www.theopensourcescienceproject.com/

Platform where academic researchers from around the world collaborate to propose and conduct basic research projects with the support of funding provided by the broader online community. The OSSP hopes to transform how academic research is funded and increase the accessibility of academic research. * Researchers pay a monthly subscription to create and maintain public profiles * Researchers alone (or in teams) submit proposed research studies - each study is peer reviewed, and (if approved) is then posted online * Investors browse through posted studies, and invest in them via small grants (microinvestments). The OSSP doesn''t charge any transaction fees or commissions * Researchers whose studies are funded conduct their research and publish their results It is in the best interest of each researcher to make their case to as many citizens as possible to ensure that they are aware of the work the researcher is engaged in - and of its importance. It is to help academic researchers make this case, and invite the broader non-research community to play a more active role in the academic research process, that The OSSP has developed this unique platform. Through the tools and resources offered by The OSSP, academic researchers may: * Create publicly-accessible profiles * Interact and exchange ideas with peers and colleagues * Manage scholarly publications/bibliographies * Secure research funding (in the form of microgrants provided by the broader non-research community) Simultaneously non-researchers, by registering as ''investors'', may: * Read through cutting-edge (peer-reviewed) research proposals * Interact and exchange ideas with academic researchers * Fund academic research projects

Proper citation: Open Source Science Project (RRID:SCR_006395) Copy   

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http://ompc.juricap.com

OMPC aims to enable reuse of the huge open and free code base of MATLAB on a free and faster growing Python platform. Running Python and MATLAB in a single interpreter avoids issues with running two separate applications. Python adds general purpose programming libraries to the convenient syntax of the language of technical computing. OMPC is not an interpreter, it lets Python to do the work. This means that if Python gets faster OMPC gets faster too. OMPC translates the m-files preserving the structure of the original programs as much as possible. Although OMPC comes with a library that emulates the features of numerical array of MATLAB there is nothing that will stop you from running the translated code the way you like it. This means that you could run the OMPC generated code on IronPython, Jython, PyPy or whatever else if you write your own numerical class. Sponsors: This resource is supported by RIKEN Brain Science Institute.

Proper citation: An Open-Source MATLAB-to-Python Compiler (RRID:SCR_008409) Copy   

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https://doi.org/10.17605/OSF.IO/WDR78

Open source resource of manually curated and expert reviewed infant brain segmentations hosted on OpenNeuro.org. and OSF.io. Anatomical MRI data was segmented from 71 infant imaging visits across 51 participants, using both T1w and T2w images per visit. Images showed dramatic differences in myelination and intensities across 1–9 months, emphasizing the need for densely sampled gold-standard segmentations across early life. This dataset provides a benchmark for evaluating and improving pipelines dependent upon segmentations in the youngest populations. As such, this dataset provides a vitally needed foundation for early-life large-scale studies such as HBCD.

Proper citation: Baby Open Brains (RRID:SCR_027836) Copy   

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http://www.ant-neuro.com/products/asa

A highly flexible EEG/ERP and MEG analysis package with a variety of source reconstruction, signal analysis and MRI processing features. ASA combines functional brain imaging with the visualization and incorporation of morphological information obtained from MRI or CT. ASA is a highly interactive and flexible software tool that can be applied to neuro-physiological and clinical brain research. ASA gives a realistic impression of your experimental configuration together with topographical mapping of EEG and MEG and the results of your analysis. ASA is developed for and by people dedicated to brain research. The concept of flexibility and openness covers even most complex analysis demands. The ASA environment is particularly attractive for those that wish to develop their own methods in third party packages like Matlab and use ASA for pre-processing and visualization purposes.

Proper citation: ASA - Advanced Source Analysis (RRID:SCR_012867) Copy   

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http://openconnectomeproject.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. Connectomes repository to facilitate the analysis of connectome data by providing a unified front for connectomics research. With a focus on Electron Microscopy (EM) data and various forms of Magnetic Resonance (MR) data, the project aims to make state-of-the-art neuroscience open to anybody with computer access, regardless of knowledge, training, background, etc. Open science means open to view, play, analyze, contribute, anything. Access to high resolution neuroanatomical images that can be used to explore connectomes and programmatic access to this data for human and machine annotation are provided, with a long-term goal of reconstructing the neural circuits comprising an entire brain. This project aims to bring the most state-of-the-art scientific data in the world to the hands of anybody with internet access, so collectively, we can begin to unravel connectomes. Services: * Data Hosting - Their Bruster (brain-cluster) is large enough to store nearly any modern connectome data set. Contact them to make your data available to others for any purpose, including gaining access to state-of-the-art analysis and machine vision pipelines. * Web Viewing - Collaborative Annotation Toolkit for Massive Amounts of Image Data (CATMAID) is designed to navigate, share and collaboratively annotate massive image data sets of biological specimens. The interface is inspired by Google Maps, enhanced to allow the exploration of 3D image data. View the fork of the code or go directly to view the data. * Volume Cutout Service - RESTful API that enables you to select any arbitrary volume of the 3d database (3ddb), and receive a link to download an HDF5 file (for matlab, C, C++, or C#) or a NumPy pickle (for python). Use some other programming language? Just let them know. * Annotation Database - Spatially co-registered volumetric annotations are compactly stored for efficient queries such as: find all synapses, or which neurons synapse onto this one. Create your own annotations or browse others. *Sample Downloads - In addition to being able to select arbitrary downloads from the datasets, they have also collected a few choice volumes of interest. * Volume Viewer - A web and GPU enabled stand-alone app for viewing volumes at arbitrary cutting planes and zoom levels. The code and program can be downloaded. * Machine Vision Pipeline - They are building a machine vision pipeline that pulls volumes from the 3ddb and outputs neural circuits. - a work in progress. As soon as we have a stable version, it will be released. * Mr. Cap - The Magnetic Resonance Connectome Automated Pipeline (Mr. Cap) is built on JIST/MIPAV for high-throughput estimation of connectomes from diffusion and structural imaging data. * Graph Invariant Computation - Upload your graphs or streamlines, and download some invariants. * iPad App - WholeSlide is an iPad app that accesses utilizes our open data and API to serve images on the go.

Proper citation: Open Connectome Project (RRID:SCR_004232) Copy   

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http://www.opencolleges.edu.au/

A resource for online accredited courses in a wide variety of areas, including accounting, animal care, beauty, building and construction, business, education, design and writing. This resource is based in Australia.

Proper citation: Open Colleges (RRID:SCR_000418) Copy   

•   Source: SciCrunch Registry
  

http://conp.ca/

Web interface that facilitates open science for neuroscience community by simplifying global access to and sharing of datasets and tools. Portal internalizes typical data cycle of research project, beginning with data acquisition, followed by data processing with published tools, and ultimately publication of results with link to original dataset. Platform to form interactive network of collaborations in brain research, interdisciplinary student training, international partnerships, clinical translation and open publishing. Provides unified interface to Canadian neuroscience research community. Open neuroscience research with sharing of both data and methods, to create large-scale databases, development of standards for sharing, facilitation of advanced analytic strategies, open dissemination to global community of neuroscience data and methods, and establishment of training programs for next generation of computational neuroscience researchers.

Proper citation: Canadian Open Neuroscience Platform (RRID:SCR_016433) Copy   

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https://edspace.american.edu/openbehavior/project/open-ephys/

Organization mission is to advance understanding of brain by promoting community ownership of neuroscience tools.Collaborative effort to develop, document, and distribute open source tools for systems neuroscience.Project aims to distribute reliable open source software as well as tools for extracellular recording and stimulation.

Proper citation: Open Ephys (RRID:SCR_021624) Copy   

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https://www.mcgill.ca/bic/resources/omega

Open data repository fully dedicated to MEG data in raw and processed form. The archive also contains anatomical MRI volumes and demographic and questionnaire information. Organized and stored as the Brain Imaging Data Structure (BIDS) with the integration of multimodal electrophysiology data. Directly readable by data-analysis software with Brainstorm. OMEGA will continue to expand, with contributions from the scientific community.

Proper citation: Open MEG Archive (RRID:SCR_014930) Copy   

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

High quality data, open and freely available to everyone to celebrate the diversity of the vertebrate brain. Do you have data that you would like to share? Do not hesitate to contact them! The Brain Catalogue is developed by Florencia Grisanti (Taxidermy Workshop of the Natural History Museum in Paris) and Roberto Toro (Neuroscience Department of the Institut Pasteur). Many of our specimens come from the Vertebrate Brain Collection of the Jardin des Plantes, curated by Marc Herbin, and are scanned at the Institut du Cerveau et de la Moelle (ICM) by Mathieu Santin and Alexandra Petiet, from the CENIR laboratory, with financial and methodological support kindly provided by Olivier Colliot, head of the Cogimage team at the ICM.

Proper citation: Brain Catalogue (RRID:SCR_009442) Copy   

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http://brainnetworks.sourceforge.net

Brain Networks: Code to perform network analysis on brain imaging data.

Proper citation: Brain Networks (RRID:SCR_005841) Copy   

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https://brainiak.org

Open source software package of Python modules for neuroscience, primarily focused on functional Magnetic Resonance Imaging (fMRI) analysis. Used for analyzing neuroimaging data.

Proper citation: Brain Imaging Analysis Kit (RRID:SCR_014824) Copy   

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http://sig.biostr.washington.edu/projects/brain/

The UW Integrated Brain Project is one project within the national Human Brain Project, a national multi-agency effort to develop informatics tools for managing the exploding amount of information that is accumulating about the human brain. The objective of the UW Integrated Brain Project effort is to organize and integrate distributed functional information about the brain around the structural information framework that is the long term goal of our work. This application therefore extends the utility of the Digital Anatomist Project by using it to organize non-structural information. The initial driving neuroscience problem that is being addressed is the management, visualization and analysis of cortical language mapping data. In recent years, advances in imaging technology such as PET and functional MRI have allowed researchers to observe areas of the cortex that are activated when the subject performs language tasks. These advances have greatly accelerated the amount of data available about human language, but have also emphasized the need to organize and integrate the sometimes contradictory sources of data, in order to develop theories about language organization. The hypothesis is that neuroanatomy is the common substrate on which the diverse kinds of data can be integrated. A result of the work done by this project is a set of software tools for generating a 3-D reconstruction of the patient''s own brain from MRI, for mapping functional data to this reconstruction, for normalizing individual anatomy by warping to a canonical brain atlas and by annotating data with terms from an anatomy ontology, for managing individual lab data in local laboratory information systems, for integrating and querying data across separate data management systems, and for visualizing the integrated results. Sponsors: This Human Brain Project research is funded jointly by the National Institute on Deafness and Other Communication Disorders, the National Institute of Mental Health, and the National Institute on Aging.

Proper citation: University of Washington Integrated Brain Project (RRID:SCR_008075) Copy   

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https://github.com/srkesler/bnets

Software repository containing code for measuring brain networks from structural and functional MRI data. Several programs require MATLAB to run.

Proper citation: Brain Networks Toolbox (RRID:SCR_014788) Copy   

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http://www.wholebraincatalog.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016. An open source, downloadable, 3d atlas of the mouse brain and its cellular constituents that allows multi-scale data to be visualized in a seamless way, similar to Google earth. Data within the Catalog is marked up with annotations and can link out to additional data sources via a semantic framework. This next generation open environment has been developed to connect members of the neuroscience community to facilitate solutions for today's intractable challenges in brain research through cooperation and crowd sourcing. The client-server platform provides rich 3-D views for researchers to zoom in, out, and around structures deep in a multi-scale spatial framework of the mouse brain. An open-source, 3-D graphics engine used in graphics-intensive computer gaming generates high-resolution visualizations that bring data to life through biological simulations and animations. Within the Catalog, researchers can view and contribute a wide range of data including: * 3D meshes of subcellular scenes or brain region territories * Large 2D image datasets from both electron and light level microscopy * NeuroML and Neurolucida neuronal reconstructions * Protein Database molecular structures Users of the Whole Brain Catalog can: * Fit data of any scale into the international standard atlas coordinate system for spatial brain mapping, the Waxholm Space. * View brain slices, neurons and their animation, neuropil reconstructions, and molecules in appropriate locations * View data up close and at a high resolution * View their own data in the Whole Brain Catalog environment * View data within a semantic environment supported by vocabularies from the Neuroscience Information Framework (NIF) at http://www.neuinfo.org. * Contribute code and connect personal tools to the environment * Make new connections with related research and researchers 5 Easy Ways to Explore: * Explore the datasets across multiple scales. * View data closely at high resolution. * Observe accurately simulated neurons. * Readily search for content. * Contribute your own research.

Proper citation: Whole Brain Catalog (RRID:SCR_007011) Copy   

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http://www.mprc.umaryland.edu/mbc.asp

The Maryland Brain Collection (MBC), a resource of the Maryland Psychiatric Research Center (MPRC), is dedicated to promoting research with brain tissue obtained post-mortem from individuals with schizophrenia or related disorders. The primary goal of the MBC is to provide high-quality tissue, along with comprehensive clinical information, for hypothesis-driven research. The MBC is not conceptualized as a Brain Bank with open access but is maintained and funded through collaborative research. The Maryland Brain Collection is managed by researchers at the Maryland Psychiatric Research Center (MPRC). MPRC scientists are dedicated to understanding the causes and improving the treatment of mental illness. The Maryland Brain Collection is associated with the Office of the Chief Medical Examiner for the State of Maryland and other donor sources. MPRC scientists collaborate with scientists from around the world to understand how abnormalities in brain tissue relate to mental illness. The purpose of the MBC is to study the following: Schizophrenia, Bipolar Disorder, Depression, Suicide/Teen suicide, Substance Abuse.

Proper citation: Maryland Brain Collection (RRID:SCR_004384) Copy   

•   Source: SciCrunch Registry
  

http://fruitflybrain.org

Open source software platform for studying fruit fly brain function, and for investigating fruit fly brain disease models that are highly relevant to mechanisms of human neurological and psychiatric disorders. Collaborative ecosystem for accelerating discovery of functional logic of fruit fly brain. Includes FlyBrainLab and BrainMapsViz. Stores and integrates fruit fly brain research data. Repository of tools and methods to build, emulate and compare fruit fly brain models in health and disease. Open framework for fruit fly brain data processing and model execution.

Proper citation: Fruit Fly Brain Observatory (RRID:SCR_019244) Copy   

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https://github.com/Whitlock-Group/HERBS

Open source, extendable, intuitive and interactive software platform for image visualisation and image registration. Python based GUI for histological E-data registration in brain space.

Proper citation: Histological E data Registration in rodent Brain Spaces (RRID:SCR_022776) Copy   

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http://www.thebrainproject.org/

The Mission of the Sarah Jane Brain Project is to create a model system of care for children and young adults suffering from all Pediatric Acquired Brain Injuries in order to advance our knowledge of the brain fifty years over the next five years! As a father of a child suffering from a Pediatric Acquired Brain Injury (PABI), I have spent countless hours searching the internet and speaking with Sarah Jane's development team (doctors, therapists and other professionals) trying to improve the development of my daughter. What I found was that while there are a countless number of wonderful and informative prevention sites for Shaken Baby Syndrome and advocacy sites for brain injuries, there is no one centralized resource for research and rehabilitation for PABI. Furthermore, many of the issues families and children face are the same whether the brain injury was caused by a car crash, a sports-related concussion, an assault or by a tumor. No one person or organization has all the answers to the questions that parents of children suffering from PABI face. Yet through my own experience, I learned that the coordination and dissemination of Sarah Jane's medical and therapy records and data in an orderly manner greatly helps her development team better help her. These wonderful individuals are constantly looking for additional ways to improve Sarah Jane's progress by speaking with their colleagues, reading literature on brain injury, and collaborating with other parents. But they all admit there is a considerable amount that still needs to be learned about the human brain, particularly the developing brain. The field of neuroscience today is similar to the computer science field of the 1950s and 1960s: you have a diverse group of very smart people working independently of one another throughout the United States and the world, yet few know what the others are doing behind closed doors. Fast- forward 50 years and many of the breakthroughs in the computer industry have been made utilizing the principles of open source a research method that promotes free and open access to the design and production of goods and knowledge. Its use was made well-known through the creation of the Linux computer operating system, in which professionals share knowledge to make corrections and fix problems. Open source is commonly used by millions of people today through the Wikipedia online free encyclopedia, a collection of public entries on established subjects that allows anyone to make additions or corrections. The National Institute of Mental Health launched The Human Brain Project in 1993 to develop and support the new science of neuro-informatics. From this initiative, it became obvious what needed to be done. That's why we created the Sarah Jane Brain Virtual Center of Excellence an ecosystem for professionals and families dealing with PABI around the world and a vehicle to help implement the PABI Plan by establishing a model system for PABI.

Proper citation: Sarah Jane Brain Project (RRID:SCR_000620) Copy   

•   Source: SciCrunch Registry