FE

The project is divided in five points, involving the IGG for the clinical and data collection phase, and DIBRIS and DIMA for the development of software that supports the non-invasive localization of the EZ. To this end, for each patient referred to IGG, (S1) neurophysiologists will record the neurological signal through high density EEG (HDEEG), totally non-invasive. Based on the information collected in the clinical analysis phase, patients will be divided into homogeneous groups.


When required by clinical needs, the patient will be sent to Niguarda Hospital (Milan) for the implantation of SEEG electrodes. The recordings with HDEEG will first be used to identify functionally connected brain regions (S2). Connectivity information can in fact be used as a constraint in the definition of a neural model and in the study of signal propagation; in this way, they constitute a tool to improve the detection of epileptic patterns in the signal, which will be done through the use of innovative methods of signal analysis and machine learning techniques (S3).Identifying and isolating epileptic patterns in the HDEEG trace is in turn essential to be able to localize with good accuracy the neural source that generated them; for this purpose Bayesian inversion techniques will be used (S4). The reliability of EZ localization will be tested against SEEG data.


Finally, the project will transfer the developed tools to the clinical routine (S5), following a thorough validation on the data collected during the whole project. The validation will be performed using retrospective data provided by Niguarda, and prospectively through the analysis of data acquired by IGG during the project.