Biological communication and information systems have evolved over millions of years. Although they have been optimized under different design criteria than recent man-made technical communication systems, both are subject to the same information theoretic principles.
We want to design channel models to describe the information flow and information processing by neural networks. Massive parallelism, quantization, and information fusion are principles which have to be included in such models, as inspired by the biological ideal.
Our research has two main objectives:
- Provide models to numerically simulate certain aspects of neuronal communication to assist biological research.
- Isolate useful features of biological communication systems to analyze their applicability for technical scenarios.
Related research topics and publications
- A Bio-Inspired Approach to Condensing Information
- Cooperative Detection over Multiple Parallel Channels: a Principle Inspired by Nature
- ITOLF - An Information Theoretic Approach to Stimulus Processing in the Olfactory System. This project aims at applying the above mentioned methodology specifically to model the olfactory system of mice. We are working on this project in collaboration with Prof. Dr. Marc Spehr from the Department of Chemosensation.
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