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Resting State Networks


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.


This tutorial will demonstrate a brain network model approach to the human resting state and its network structure, with the goals of understanding how to parametrize a neural mass model, place it in a network context, identify and explore the relevant parameter space, perform extended simulations in the realistic region of parameter space and finally analyze the resulting simulated fMRI BOLD signals to reproduce experimental results published in the resting state literature.

This tutorial is a work in progress and will be continuously expanded over the next several months. For a tutorial on the same topic which uses the scripting interface, with TVB as a Python library, please see the resting state network scripting tutorial.

Parameterizing the local neural mass model

work in progress

Placing the mass model in a network context

work in progress

Identify a parameter space

work in progress

Perform extended simulation

work in progress

Analyze fMRI BOLD time series

work in progress

Power spectra

work in progress

Seed-region correlation

work in progress

More Documentation

For more information on modeling resting state networks with TVB, see Ghosh_et_al_, Knock_et_al_, Spiegler_et_al_.


The official TVB website is All the documentation and tutorials are hosted on You will find our public repository at For questions and bug reports we have a users group!forum/tvb-users