7 papers
Graph-based analysis of inflammatory profiles in New Onset Refractory Status Epilepticus (NORSE)
Linon Denis, Martin Guillemaud, Vincent Navarro +2
Background and Objectives: Cryptogenic new-onset refractory status epilepticus (cNORSE) represents one of the most severe forms of status epilepticus, occurring in patients without…
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…
Hyperbolic embedding of multilayer networks
Martin Guillemaud, Vera Dinkelacker, Mario Chavez
Multilayer networks offer a powerful framework for modeling complex systems across diverse domains, effectively capturing multiple types of connections and interdependent subsystem…
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.…
Hyperbolic embedding of brain networks detects regions disrupted by neurodegeneration in Alzheimer's disease
Alice Longhena, Martin Guillemaud, Fabrizio De Vico Fallani +2
Graph theoretical methods have proven valuable for investigating alterations in both anatomical and functional brain connectivity networks during Alzheimer's disease (AD). Recent s…