Description

• Mapping the spatio-temporal extent of epileptic networks in the human brain. Characterization of the transition from normal to pre-ictal activity from human intracranial recordings and understanding how this transition is caused by the epileptogenic regions of drug-resistant epileptic patients. Developing practical algorithms to be used in a clinical setting that help identify epileptogenic regions and prevent seizures. Methods: Signal processing, information theory and statistical models, statistical learning, network science, biophysical modelling.

• Modelling and inference of neural communication in the brain. Formulating a biophysical plausible communication model that is compatible with information-theoretic principles and developing statistical methods to infer communication pathways from electrophysiological recordings during cognitive tasks and pathological conditions. Methods: Signal processing, information theory and statistical models, statistical learning, stochastic model simulations, biophysical modelling.