Tutorials & E-Library

This tutorial on how to simulate using TVB is part of the TVB Node 10 series, a 4 day workshop dedicated to learning about The Virtual Brain, brain imaging, brain simulation, personalised brain models, TVB use cases, etc. TVB is a full brain simulation platform.

This tutorial presents the basic anatomy of a region simulation using The Virtual Brain's (TVB's) scripting interface.

This extends the basic region simulation, covered in the region simulation tutorial, to include the folded cortical surface to the anatomical structure on which the simulation is based.

This tutorial discusses using the phase_plane_interactive plotting tool to explore the dynamics of a Model object and, at the same time, set its parameters.

This works best for the simpler, 2d, Models, as their trajectories and nullclines lie within a single plane and are thus easily visualised. And so, for the demo here we'll stick with a Model of that type. However, although it requires a little more effort, it can still be used to get a basic handle on the dynamics of higher dimensional models.

It is also important to note that this is only for the local dynamic model, that is, it only represents the dynamic behaviour of a disconnected node.

Evoked Responses in the Visual Cortex

Fluctuations in brain activity in non-task conditions are now a well-established phenomena in the literature. These fluctuations are not random but shown to exhibit spatial patterns, referred to as resting state networks. Despite being readily identifiable during rest, these networks are related to specific functions and on the other hand abnormalities in such RSNs have been associated with pathology.

The main goal of this tutorial is to provide a clear understanding of how we can reproduce clinically relevant senarios such as the propagation of an epileptic seizure in the human brain, electrical stimulation of a brain region that can trigger a seizure, or surgical resection of brain regions.

TVB allows for a systematic exploration and manipulation of every underlying component of a large-scale brain network model, such as the neural mass model governing the local dynamics or the structural connectivity constraining the space-time structure of the network coupling

First things first. We are going to use tvb-data which is present within the distribution (at TVB_Distribution/tvb_data/Lib/site-packages/tvb-data).

A current topic in system neuroscience literature is the presence of brain activity in the absence of a task condition. These task-negative, spontaneous fluctuations occur in the so-called rest state, and a recurring theme of these fluctuations is that they have a network structure. Because TVB uses the structural connectivity of the brain as the backbone for simulating spontaneous activity, resting state activity and its network structure is a prime candidate for modeling in TVB.

TVB can be used to model large-scale epileptic seizure dynamics. Using relevant neural mass models, TVB allows to ask multiple questions such as the localisation of the epileptogenic zone or the validity of different neuroimaging modalities to assess the epileptogenicity of a brain structure. Here we will present an example of such a modelisation.

These tutorials show how to use the CellBuilder, a powerful and convenient tool for constructing and managing models of individual neurons. The CellBuilder is a "graphical form for specifying the properties of a model cell." It breaks the job of model specification into a sequence of tasks :

Setting up model topology (branching pattern).
Grouping sections with shared properties into subsets.
Assigning geometric properties (length, diameter) to subsets or individual sections, and specifying a discretization strategy (i.e. how to set nseg).
Assigning biophysical properties (Ra, cm, ion channels, buffers, pumps, etc.) to subsets or individual sections.

These are the same things we would have to do, and pretty much the same sequence we'd follow, in order to define a model by writing hoc code. However, the CellBuilder helps us keep it all nice and organized, and eliminates a lot of error-prone typging.