Research

My research focuses on the indirect relationship between the encoding of neural networks and their function. In particular, I am interested in how structural and self-organizing mechanisms affect the network topology and how this in turn contributes to the function of a network.

I mostly use computational models of neural networks for my research. But I am also looking for description languages that allow the Artificial Development of neural networks in order to generate scalable and evolvable structures.

The hippocampus is a good region to work along these lines of research as the anatomy of the network is unique and well conserved across species. Its context-dependent functional role in spatial navigation and memory formation however points to an underlying universal function of high evolutionary importance. Identifying this function will not only let us understand how the hippocampus does what it does. We can also learn how the function of neuronal networks in general emerge from structural encodings, self-organizing mechanisms and external input. In this regard, I would call the field I am working in “evolutionary computational neuroscience”.

Background

I completed my diploma in computer science with an emphasis on artificial intelligence and linguistics at the University of Münster. During my PhD and my first PostDoc, I investigated the influence of cognitive tasks on the Default Mode Network in subsequent rest. In my current position, I use computational methods to investigate the neural mechanisms underlying hippocampal functions.

Expertise

I programmed in Delphi, Java, C/C#, Matlab, Python and some other languages. I use programming languages in my professional and private life for all purposes. After many years of experience, I don’t really care anymore about the language itself I have to use. But if I can choose, I would currently prefer Matlab and Python.

Furthermore, I have experience in generating 2d and 3d graphics, mostly using open source tools.