3 papers
q-bio.NC2026
Low-dimensional representation of brain networks for seizure risk forecasting
Steven Rico-Aparicio, Martin Guillemaud, Alice Longhena +3
Identifying preictal states -- periods during which seizures are more likely to occur -- remains a central challenge in clinical computational neuroscience. In this study, we intro…
q-bio.NC2025
Geometric representations of brain networks can predict the surgery outcome in temporal lobe epilepsy
Martin Guillemaud, Alice Longhena, Louis Cousyn +4
Epilepsy surgery, particularly for temporal lobe epilepsy (TLE), remains a vital treatment option for patients with drug-resistant seizures. However, accurately predicting surgical…
q-bio.NC2025
Hyperbolic embedding of brain networks as a tool for epileptic seizures forecasting
Martin Guillemaud, Louis Cousyn, Vincent Navarro +1
The evidence indicates that intracranial EEG connectivity, as estimated from daily resting state recordings from epileptic patients, may be capable of identifying preictal states.…