Professor Francesco Andriulli :
Department of Electronics and Telecommunications
Politecnico di Torin, Turin, Italy
IAS Distinguished Lecturer, 2021-2022
Abstract
Electroencephalography (EEG) is one of the most used non-invasive acquisition methods to reconstruct the brain electrical activity from scalp potential recordings. As a clinical diagnostic tool, EEG source imaging plays a crucial role in epilepsy evaluation. This particularly applies to patients suffering from focal epilepsy, when source characterization and localization are two decisive stages of a pre-surgical epilepsy evaluation which prepares for the ablation of the patient’s brain area where the seizure originates. Moreover, EEG source imaging also extends to the development of Mind-Machine Interfaces (MMIs or BCIs): non-muscular communication channels leveraging brain signals for the control of external devices.
Modern high-resolution EEGs are computationally intensive devices where a large part of the imaging process is underpinned by advanced tools in the physical modeling of brain electric propagation. For this reason, several cross-disciplinary research efforts are focused on developing advanced tools for brain-related computational electromagnetics. Unfortunately, however, these tools often turn out to be computationally intensive, limiting the resolution of the physical model that can be achieved.
This talk will focus on recent advances in electromagnetic modeling and computational strategies for high resolution EEGs. Theoretical, algorithmic, and experimental advances will be presented together with their promising applications in next-generation high-resolution electroencephalographies, epilepsy diagnostics, computationally enhanced brain-computer interfaces, and real-time neurofeedback. In addition to the theoretical frameworks, this talk will present recent discoveries and achievements together with open Grand Challenges, including current research efforts about diagnostic, BCIs and immersive neurofeedback in the framework of the projects ERC “321” and EIC pathfinder “CEREBRO”, both at the theoretical and experimental level.
