Epilepsy is well-recognized as a disorder of brain networks. There is a growing body of
research to identify critical nodes within dynamic epileptic networks with the aim to target …

Individuals with drug-resistant focal epilepsy are candidates for surgical treatment as a
curative option. Before surgery can take place, the patient must have a presurgical …

Precise estimates of epileptogenic zone networks (EZNs) are crucial for planning
intervention strategies to treat drug-resistant focal epilepsy. Here, we present the virtual …

Over the past 10 years, the drive to improve outcomes from epilepsy surgery has stimulated
widespread interest in methods to quantitatively guide epilepsy surgery from intracranial …

Objective The virtual epileptic patient (VEP) is a large‐scale brain modeling method based
on virtual brain technology, using stereoelectroencephalography (SEEG), anatomical data …

A fundamental problem in many sciences is the learning of causal structure underlying a
system, typically through observation and experimentation. Commonly, one even collects …

Brain–computer interfaces (BCIs) have garnered significant attention in recent years due to
their potential applications in medical, assistive, and communication technologies. Building …

The close coupling of artificial intelligence (AI) and electroencephalography (EEG) has
substantially advanced human-computer interaction (HCI) technologies in the AI era …

During human seizures, organized waves of voltage activity rapidly sweep across the cortex.
Two contradictory theories describe the source of these fast traveling waves: either a slowly …

In this work, we investigate epilepsy seizure detection using machine learning. In the
literature, a machine learning model is usually trained to help automate the epileptic …