CNS*2025 Florence

Epilepsy remains a complex neurological condition, necessitating innovative approaches to understanding
and mitigating seizure activity. This workshop is designed to bring together computational neuroscientists
and researchers with experimental and clinical background to explore cutting-edge strategies in epilepsy
modeling and seizure control. For the general content structure, we plan to start from a modeler's
perspective and then progressively move towards more data-driven approaches.

The first session will explore seizure mechanisms through biophysical and neural mass models at different
temporal and spatial scales, investigating, among others, ionic dynamics and network plasticity. It aims to
understand seizure initiation, progression, and duration.

The second session will focus on the application of computational models to EEG data recorded in epileptic
patients. First, it will discuss advanced parameter inference methods to tailor models to individual data
samples to provide mechanistic insight. It then moves on to issues of seizure monitoring using wearable
devices and long-term EEG recordings, and in particular the use of data features inspired by concepts
derived from mathematical modeling in epilepsy.

The third session will examine stimulation-based strategies to terminate or prevent seizures. There will
be a focus on recent advancements in closed-loop and low-frequency electrical stimulation to control
seizures. On top of model-based approaches, this session will also include the clinical perspective on
stimulation treatment and data-driven studies.