Analysis of intracranial EEG recordings from epilepsy patients

The research of the nonlinear time series analysis group is positioned at the interface between physics, applied mathematics, neuroscience, and engineering. One of our main targets is the development of innovative nonlinear time series analysis techniques. These techniques aim to characterize dynamical systems for which nonlinearities cause a complicated temporal evolution. A further main target of our work is the application of nonlinear time series techniques to electrophysiological recordings from the brain of epilepsy patients. In patients with a certain type of epilepsy an optimal diagnostics requires to carry out electroencephalographic recordings directly from inside the patients’ skull (intracranial EEG) or from between the skull and scalp (subcutaneous EEG). These EEG recordings allow us to study a variety important questions, such as the localization of areas in the patients’ brain in which epileptic seizures start, the timely detection of epileptic seizures, the characterization of cyclic variations in the seizure likelihood, among many others. The general project aim is to apply nonlinear time series analysis techniques to EEG recordings. The specific topic can be tailored to the interests of the student.

For more details see our recent publications at https://www.upf.edu/web/ntsa/publications-featured. Please note that we publish on different topics. You will be able to conclude from titles which projects are related to the study of EEG recordings.

In a first phase the student will familiarize himself/herself with the signal analysis techniques studying signals from mathematical model systems. In the second step, the student will learn about EEG recordings. The final phase will consist of the application of the signal analysis techniques to the EEG recordings.

As a starting point, the student should have a good knowledge in basics of dynamical systems theory as well as in linear signal techniques such as spectral and correlation analysis. Knowledge on nonlinear signals techniques is not a prerequisite. The student should certainly know how to program in Matlab or some other higher programming language. Basic knowledge in electrophysiology and epileptology is a plus but not a prerequisite.

Both the study of mathematical model systems as well as the analysis of the EEG is purely numerical. This thesis involves no laboratory, experimental or clinical work. The student will not be in contact with the patients. Previous experience in the study of dynamical systems is a plus. The candidate will work in our nonlinear time series analysis group, an international team that puts a strong emphasis on well-organized supervision of its junior members and regular research activities such as journal clubs, project meetings, etc.