I am studying biology at the University of Würzburg and joined the Ache lab for my Bachelor’s thesis project. The dream of my childhood was becoming a writer because I love books. The most fascinating thing for me always has been, and still is, the imagination. More precisely, the ability to create quite complex situations, entire worlds and stories, which exist only in someone’s brain.

At the same time, I always was interested in complex systems and wanted to understand their governing mechanisms. The brain might very well be the most complex system known to humans. During my studies, I got to learn about many things I couldn’t even imagine previously. Especially, neurobiology was enthralling to me. After I studied a lot of neurobiology in my free time and during an internship in Korea at the Laboratory of Social Decision Neuroscience (Korea University), I decided to join the Ache lab for my Bachelor’s thesis.

In the fruit fly Drosophila, we have the techniques to understand neuronal circuits in more and more detail. With more detail and improved measuring devices, that enable large-scale data capturing approaches, comes the need – as in all research fields – to use computational analysis to handle great amounts of data. Moreover, computational models can help us to understand complex systems that are not graspable by simply looking at large amounts of data. Thus, the function of specific neuronal populations, which are individually studied, can be integrated.

In my thesis project, I perform computational analysis and modeling, focusing on the neuronal control of adaptive locomotion. For this purpose, I am using Matlab to process and visualize data from behavioral experiments in which my colleagues, in particular Fathima Iqbal, activated different individual neurons in the fly’s brain which can change parameters of locomotion. Thus, I quantify the behavioral effects of identified interneurons, which play a decisive role in locomotion, and controlfor example walking initiation and termination, speed and direction of walking. My main goal is to incorporate these findings into a model of an artificial fly that’s freely walking around, in which we can recapitulate the most important neuronal effects on walking parameters and thus understand fundamental basics of the neuronal control of adaptive walking.