Keller Colloquium in Computing and Mathematical Sciences

An important area of brain research is focused on brain dynamics in the so-called resting state, rather than during the execution of explicit tasks. In an idling condition, the brain is thought to prepare itself for future demands by generating coordinated dynamics that largely overlap with patterns of previous activity. These coordinates dynamics can be studied by using functional connectivity methods. Recently, I reported - for the first time - the successful brain network imaging using high-density EEG (hdEEG). Here, I will present some methodological approaches that are needed to improve the spatial resolution of hdEEG, and to permit brain network imaging using this technique. In particular, we have developed tools for signal preprocessing, head modelling, brain activity reconstruction and connectivity analysis. As for the hdEEG connectivity tools, we have implemented both data-driven and hypothesis-driven analysis strategies, as those used in fMRI and MEG connectivity studies. The developed techniques were extensively validated, and the potential advantages brought by the use of hdEEG connectivity as compared to fMRI connectivity was demonstrated. I hope that our methodological work will contribute to rise of hdEEG as a powerful tool for brain research.