Dynamic brain network analysis

The brain is considered to be a complex network of interacting elements. When the nodes and the wiring work well, this organization enables fast and efficient information processing. However, when some elements of this network fail, serious neurological conditions, such as epilepsy, may occur. Therefore, understanding brain function is one of the greatest scientific challenges of our times. Multidisciplinary efforts, combining advances in neuroimaging, electronic sensor technologies and signal processing are necessary to unravel the processing pathways within the brain. In turn, these findings can inspire novel, neuromorphic computing architectures and paradigms, as well as better diagnostic tools and treatment for brain disorders.

Assignment

There are various signal processing techniques to unravel and characterise the fluctuating activity of brain networks, such as independent component analysis, hidden markov models, or time-varying graphs. Each technique relies on different mathematical assumptions, which are translated to different physiological assumptions regarding the network properties. As such, they all provide a complementary view on brain networks. Therefore, the thesis project starts with a literature review to study different functional brain imaging (EEG, fMRI, functional ultrasound) and signal processing techniques. A few of the selected techniques should be implemented, tested and compared on signals recorded in epilepsy patients. The goal of the thesis is twofold: (1) to select an appropriate combination of imaging and signal processing technique, including preprocessing and appropriate model parameters (2) to compare brain network fluctuations during, before and after an epileptic seizure in order to reveal the dynamic changes in the networks leading to an epileptic seizure.

Requirements

We are looking for a student from electrical engineering or biomedical engineering with a strong signal processing background. Good programming skills (in Matlab, or Python, …) are also required. Previous experience with biomedical signals and genuine interest in neuroimaging is appreciated.

Contact

dr. Borbála Hunyadi

Signal Processing Systems Group

Department of Microelectronics

Last modified: 2019-04-04