Activités de recherche

Our research focuses on the development and application of advanced signal processing methods for the analysis of human electrophysiological recordings, whether invasive (iEEG) or non-invasive (EEG and MEG), specifically in the context of epilepsy.

Brain Connectivity: Epilepsy is a brain network disease and brain connectivity appears to be an idea tool to characterise epileptic brains. Non-invasively derived brain connectivity metrics need to be validated with a gold standard. Our aim is to take advantage of the rare simultaneous hd-EEG-iEEG recordings to validate them.

Postsurgical Outcome Prediction: By combining connectivity/network analysis and clinical data, we aim to develop a machine learning algorithm, coupled to a clinical report, to predict which patients might benefit from resective surgery.

Contact

Département de Neurosciences cliniques
HUG
Email: nicolas.roehri@unige.ch