Cue integration by bumblebees during navigation in uncertain environments with multiplegoal options: Behavioural analysis in virtual reality and computational modelling

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Many animals can accurately navigate between their home and behaviourally relevant locations, such as food sources, in uncertain and cluttered environments. Our project will analyse by behavioural and computational approaches the mechanisms underlying these remarkable abilities. More specifically, we will investigate the mechanisms involved in goal finding and decision making in bumblebees as they need to identify rewarding food sources among the many other objects in their environment. We will conduct behavioural experiments on walking bumblebees using visual and olfactory stimuli in a custom-designed virtual reality (VR) embedded trackball setup in close combination with computational modelling of the underlying control mechanisms. Bumblebees are an established model system for this type of behavioural research and parts of their navigation system. Our project aims to investigate several aspects of goal-finding behaviour, including: how initially inexperienced bees discover a rewarding goal among many other objects for the first time, how bees gain experience and improve their goal finding strategies by learning different environmental cues that aid in locating and recognizing profitable food sources, how bees make decisions in cluttered environments with multiple goal options of different reward value, how bees learn to distinguish reliable environmental features from those that can change. Our project's findings will provide new insights into the mechanisms involved in goal-directed behaviour and decision-making in animals. By implementing a modular simulated agent that receives the sensory input provided to the animals in the behavioural experiments in the VR setup and generates bee-like behaviour in response, we will test if the formalized computational model is sufficient to qualitatively reproduce the observed behaviour of the bumblebees. This intricate interaction of experimental analysis using VR technology and computational modelling will help us gain a more comprehensive understanding of the complex and multi-faceted processes of goal finding in insects.