Our overarching aim is to form a better understanding of how small and fast fluctuations in relative concentrations of odor mixtures are used by animals to reliably identify odor sources will help us identify common principles of how animals’ brains represent and process their environment.
To this end, we will use behavioral experiments in honey bees to identify naturally evolved strategies of odor-background segregation. At the same time, physiological recordings will inform us about neuronal processing and the receptor neurons’ and the brain’s different roles.
Furthermore, we will use computational models to formulate mechanistic explanations of the process of odor-background segregation and generate predictions to test in experiments.
Finally, to overcome the limitations of in silico simulations, we will finally transfer successful models to the embodied context of odor tracking robots.