How do groups of nerve cells process information? What is the role of signals that are timed on the precise millisecond? And how can a network of nerve cells learn to produce a specific rhythm of signals? „I am interested in the temporal characteristics of electrical signals, which neurons in biological neural networks use to communicate with each other,“ Memmesheimer says. The physicist’s tools are theoretical models. On their basis he wants to reconstruct and understand the complex dynamics of medium-sized nerve cell networks. His research takes place in close relation to experimental science: „We incorporate biological data in our network models,“ he describes, „and our theoretical models make concrete predictions, which are then investigated in real neural populations by experimental neuroscientists.“
In his previous work, Memmesheimer for instance assessed the situation when several signals that arrive at a nerve cell at the same time can lead to a strong signal enhancement. The impact of this effect on the dynamics of a network is difficult to examine in living systems. Using his models, the neuroscientist revealed that the effect leads to characteristic rhythmic oscillations in the network. Subsequently, he learned: these rhythms actually exist in the hippocampus, the „memory center“ of the brain.
With the investigation of neural networks — comprising some hundreds to thousands of neurons —Memmesheimer wants to contribute to closing the knowledge gap between the relatively well examined level of individual nerve cells and whole brain areas. On the one hand, this will help to understand the link between individual neurons and the entire brain’s activity. On the other hand, Memmesheimer’s findings facilitate artificial intelligence research. In the long term, he wants to develop highly biologically inspired algorithms that can recognize and predict temporal patterns. „This could be used to design even more sophisticated robots,“ says the brain scientist. He plans to pursue the questions of the brain’s temporal network dynamics at Göttingen University, where he wants to collaborate with scientists at the Bernstein Center and the Bernstein Focus Neurotechnology.
Raoul-Martin Memmesheimer studied theoretical physics at the universities of Kaiserslautern, Munich and Jena. Starting in 2004, he devoted himself to research, first as a graduate student and later as a postdoctoral fellow in the group of Marc Timme in the department of Theo Geisel at the Max Planck Institute for Dynamics and Self-Organization in Göttingen. He received his doctorate in 2007 and was honored with the Otto Hahn Medal of the Max Planck Society for his doctoral thesis. From 2008 to 2010 he worked as an independent Swartz Fellow at Harvard University (USA), where he collaborated with Haim Sompolinsky. Since April 2010 he is Assistant Professor in the Department for Neuroinformatics at the Donders Institute, Radboud University Nijmegen.
The Bernstein Award has been conferred for the ninth time this year and is part of the National Bernstein Network for Computational Neuroscience, a funding initiative launched by the Federal Ministry of Education and Research (BMBF) in 2004. The initiative’s aim was to sustainably establish the new and promising research discipline of Computational Neuroscience in Germany. With this support, the network meanwhile has developed into one of the largest research networks in the field of computational neuroscience worldwide. The network is named after the German physiologist Julius Bernstein (1835-1917).
Weitere Informationen erteilt Ihnen gerne:
Dr. Raoul-Martin Memmesheimer, Assistenzprofessor
Department for Neuroinformatics
Donders Institute for Brain, Cognition and Behavior
Radboud University Nijmegen
Tel: +31 (0)24 365 2166