The Virtual Brain: a simulator of primate brain network dynamics

• Main Authors: Paula eSanz Leon, Stuart A. Knock, M. Marmaduke Woodman, Lia eDomide, Jochen eMersmann, Anthony R. McIntosh, Viktor eJirsa
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2013-06-01
• Series: Frontiers in Neuroinformatics
• Subjects: connectivity; connectome; python; neural field; virtual brain; neural mass
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fninf.2013.00010/full

We present TheVirtualBrain (TVB), a neuroinformatics platform for full brainnetwork simulations using biologically realistic connectivity. This simulationenvironment enables the model-based inference of neurophysiological mechanismsacross different brain scales that underlie the generation of macroscopicneuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchersfrom different backgrounds can benefit from an integrative software platformincluding a supporting framework for data management (generation,organization, storage, integration and sharing) and a simulation core writtenin Python. TVB allows the reproduction and evaluation of personalizedconfigurations of the brain by using individual subject data. Thispersonalization facilitates an exploration of the consequences of pathologicalchanges in the system, permitting to investigate potential ways to counteractsuch unfavorable processes. The architecture of TVB supports interaction withMATLAB packages, for example, the well known Brain Connectivity Toolbox. TVBcan be used in a client-server configuration, such that it can be remotelyaccessed through the Internet thanks to its web-basedHTML5, JS and WebGL graphical user interface. TVB is alsoaccessible as a standalone cross-platform Python library and application, andusers can interact with the scientific core through the scripting interfaceIDLE, enabling easy modeling, development and debugging of the scientifickernel. This second interface makes TVB extensible by combining it with otherlibraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to thedevelopment of TVB, the architecture and features of its major softwarecomponents as well as potential neuroscience applications.