Nicolas Roehri
Function: Maître-Assistant
Nom du groupe: Electrophysiological Signal Processing for Epilepsy Research
Group type: Affiliated
Affiliations: Department of Clinical Neurosciences
Domaines: Development and Plasticity
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.
Dernières publications
Asymmetry of sleep electrophysiological markers in patients with focal epilepsy.
Cortico-cortical and thalamo-cortical connectivity during non-REM and REM sleep: Insights from intracranial recordings in humans.
Aberrant Developmental Patterns of Gamma-Band Response and Long-Range Communication Disruption in Youths With 22q11.2 Deletion Syndrome.
Phase-Amplitude Coupling and Phase Synchronization Between Medial Temporal, Frontal and Posterior Brain Regions Support Episodic Autobiographical Memory Recall.
Contact
Département de Neurosciences cliniques
HUG
Email: nicolas.roehri@unige.ch