Animals as diverse as mammals, birds and insects use odors to find mates, hosts and food sources. This is a difficult task because natural odors occur in complex turbulent air plumes and the relevant target odors intermingle with plumes of multiple background odors stemming from a variety of natural and anthropogenic sources (vegetation, exhaust fumes, etc.).
It is essential for animals to be able to separate target from background odors. We hypothesize that animals may use temporal information from natural odor fluctuations to achieve odor-background segregation, as odorants from the same source fluctuate together in synchrony, while odorants from different sources do not.
Behavioral studies have shown that insects can indeed use fast temporal stimulus cues but it is not yet known how the brain accomplishes the difficult task of odor-background segregation. In this project we will investigate the neural mechanisms of odor-background segregation using the honey bee as model organism.
Honey bees visit many different flower species for nectar and pollen. However, over a series of trips an individual forager bee only visits a single flower species on which it has found nectar previously, a phenomenon called floral constancy. To localizes the target flowers in a natural environment bees use several cues, including odors. As the bee is challenged by multiple background odors in every flower patch, bees must be equipped with efficient mechanisms of odor-background segregation.
Department of Neurobiology, Universität Konstanz, Germany.
The principal investigator and Project Coodinator will be Dr Paul Szyszkapaul.firstname.lastname@example.org
The team will focus on the insect physiology aspects of the project.
Research Center for Advanced Science and Technology, University of Tokyo, Japan
The principal investigator will be Professor Ryohei Kanzaki. email@example.com
The team will focus on odor plume dynamics and robotics aspects of the project.
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.