Navigation of Drosophila Larvae in Taste Gradients

Drosophila larva is a powerful model organism that allows us to understand how patterns of neural activity encode behaviors. To navigate its environments, larvae undergo biased random walks, by interspersing forward runs with reorienting turns. The navigational strategies have already been identified in gradients of odors, light, wind, CO2, but little is known how animals navigate gradients of different tastants, where prior experience may modify the perception of and behavior to novel presentations of tastants. We’ve adopted an experimental procedure in which we incorporate a tastant and use a wedge technique that allows the tastant to diffuse through another layer of agarose to create a gradient on the surface. By generating gradients of simple sugars we quantify navigational behaviors in these taste gradients through machine vision. By pre-exposing larvae to a different tastant prior to releasing them onto an established gradient, we quantify how their experience can modulate navigational strategies.