An optimal population code for global motion estimation in local direction-selective cells

Abstract

AbstractNervous systems allocate computational resources to match stimulus statistics. However, the physical information that needs to be processed depends on the animal’s own behavior. For example, visual motion patterns induced by self-motion provide essential information for navigation. How behavioral constraints affect neural processing is not known. Here we show that, at the population level, local direction-selective T4/T5 neurons in Drosophila represent optic flow fields generated by self-motion, reminiscent to a population code in retinal ganglion cells in vertebrates. Whereas in vertebrates four different cell types encode different optic flow fields, the four uniformly tuned T4/T5 subtypes described previously represent a local snapshot. As a population, six T4/T5 subtypes encode different axes of self-motion. This representation might serve to efficiently encode more complex flow fields generated during flight. Thus, a population code for optic flow appears to be a general coding principle of visual systems, but matching the animal’s individual ethological constraints.