Computational modelling of brain dynamical networks
Computational modelling of brain dynamical networks

The estimation, quantification and comparison of brain dynamics is one of the central challenges of modern neuroscience.
The brain network model has emerged over the past few years as an important representation for describing such brain dynamics.

The objective of Cronos is to develop models, algorithms and software to estimate, understand and quantify the dynamics of the whole brain.
It will be achieved by modeling the macroscopic architecture and connectivity of the brain at 3 different levels of complexity:

  • The sensor level which is low dimensional and contains most of the necessary information (but often in an obsfucated fashion).
  • The source level which is closer to anatomy, so more meaningful, but often lies in a high dimensional space (so information is often redundant).
  • The group level which aims at extracting statistical characteristics of signals related to specific tasks so as to provide constrains to both sensor and source levels and ease the extraction of information at these levels.

These three levels will be studied through the unifying representation of dynamic networks, integrating the dynamic and the partial information from various non-invasive brain observation modalities (fMRI, dMRI, EEG, MEG, ...) in a global and consistent model.

Target applications for these tools range from basic neuroscience, cognitive and clinical studies to brain-computer interfaces.
We expect to expand our impact in these areas by providing open source software implementing our models and algorithms in ways that are accessible to non-technical users. .

Centre(s) inria
Inria Centre at Université Côte d'Azur


Team leader

Claire Senica

Team assistant