The fast and parallel Virtual Brain

A fast implementation of The Virtual Brain brain network simulator is

  • written in C using a host of optimizations that make brain simulation faster
  • parallelized (multithreading)
  • containerized (can be conveniently run e.g. through Docker, Shifter or Singularity, without the need to install dependencies or set up environment)
  • uses the Deco-Wang (aka "ReducedWongWang") neural mass model to simulate local brain region activity as described in Deco et al., 2014, Journal of Neuroscience or Schirner et al., 2018, eLife

An overview over TVB-on-EBRAINS services is provided in the preprint https://arxiv.org/abs/2102.05888

Launch online
Contributors
MS PR

Other Tools

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siibra-explorer

siibra-explorer is built around an interactive 3D view of the brain displaying a unique selection of detailed templates and parcellation maps for the human, macaque, rat or mouse brain, including BigBrain as a microscopic resolution human brain model at its full resolution of 20 micrometres.

Collaboratory

The EBRAINS Collaboratory offers researchers and developers a secure environment to work with others. You control the level of collaboration by sharing your projects with specific users, teams or all of the Internet. Many researchers are sharing their work already; several services, tools, datasets and other resources are publicly available, and many more are available for registered users.

MeshView

MeshView is a web application for real-time 3D display of surface mesh data representing structural parcellations from volumetric atlases, such as the Waxholm Space Atlas of the Sprague Dawley Rat Brain. MeshView is available as an EBRAINS community app, accessible via a collab (further info: https://wiki.ebrains.eu/bin/view/Collabs/image-registration-and-analysis-demo/) Key features: orbiting view with toggleable opaque/transparent/hidden parcellation meshes rendering user defined cut surface as if meshes were solid objects rendering point-clouds (simple type-in, or loaded from a JSON format) coordinate system is compatible with QuickNII (https://www.nitrc.org/projects/quicknii)

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