Computational modeling and experimental validation of odor detection behaviors of classically conditioned parasitic...

A prototype chemical sensor named Wasp hound® that utilizes five classically conditioned parasitoid wasps, Microplitis croceipes (Cresson) (Hymenoptera: Braconidae), to detect volatile odors was successfully implemented in a previous study. To improve the odor-detecting ability of Wasp Hound®, searching behaviors of an individual wasp in a confined area are studied and modeled through stochastic differential equations in this paper. The wasps are conditioned to 20 mg of coffee when associated with food and subsequently, tested to 5, 10, 20, and 40 mg of coffee. A stochastic model is developed and validated based on three positive behavioral responses (walking, rotation around odor source, and self-rotation) from conditioned wasps at four different test dosages. The model is capable to reproducing the behaviors of conditioned wasps, and can be used to improve the ability of Wasp Hound® to assess changes in odor concentration. The model simulation results show the behaviors of conditioned wasps are significantly different when tested at different coffee dosages. We conjecture that the searching behaviors of conditioned wasps are based on the temporal and spatial neuron activity of olfactory receptor neurons and glomeruli, which are strongly correlated to the training dosages. The overall results demonstrate the utility of mathematical models for interpreting experimental observations, gaining novel insights into the dynamic behavior of classically conditioned wasps, as well as broadening the practical uses of Wasp Hound.