Roving robots gain from an orientation algorithm of fruit flies and predict a fly decision-making algorithm

Abstract

Simple organisms like bacteria are directly influenced by momentary changes in concentration or strength of sensory signals. In noisy sensory gradients frequent zigzagging reduces the performance of the cell or organism. Drosophila melanogaster flies significantly deviate from a direct response to sensory input when orienting in gradients. A dynamical model has been derived which reproduces fly behaviour. Here we report on an emergent property of the model. Implemented in a robot, the algorithm is sustaining decisions between visual targets. The behaviour was consequently found in wild-type flies, which stay with a once-chosen visual target for considerable longer times than mutant flies with a specific brain defect. This allowed the localisation of the integrator. Flies were tested in a virtual-reality arena with two alternatingly visible target objects under different visibility regimes. The finding exemplifies how basic research and technical application can mutually benefit from close collaboration. © 2014 Springer International Publishing.