2 citations · 3 across the 2 of their papers we have counts for
3 papers
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…
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…
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.…