Will talk about: The Virtual Brain: a simulator of large-scale brain network dynamics
Viktor Jirsa is Director of Research at the Centre National de la Recherche Scientifique (CNRS) in Marseille, France. He is Co-Director of the Inserm Institut de Neurosciences des Systèmes at Aix-Marseille-Université. Dr.Jirsa received his PhD in 1996 in Theoretical Physics from the University of Stuttgart and has since thencontributed to the field of Theoretical Neuroscience, in particular through the development of large-scale brainnetwork models based on realistic connectivity, linking network dynamics to brain function and imaging. Hiswork has contributed to a better understanding of the resting state, epilepsy and motor coordination.
We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference ofneurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVBextensible by combining it with other libraries and modules developed by the Python scientific community. Here we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications.