Ramirez, L.; Gjorgjieva, J.; Silies, M.

As animals move through the world, their visual input can change gradually or shift rapidly, spanning a broad range of temporal frequencies. Visual circuits therefore face the challenge of encoding inputs with an inherently multiscale temporal structure. From insects to vertebrates, peripheral visual neurons exhibit striking temporal diversity, yet the principles underlying this organization remain unclear. Here, we show that temporal diversity in the fly visual system supports efficient coding of natural motion by distributing encoding across complementary timescales. Using well-characterized fly motion-detection pathways as a model, we show that temporal filters within and across visual hierarchies occupy a low-dimensional feature space defined by filter polarity and characteristic timescale. Within an efficient-coding framework constrained by natural motion statistics, circuits that combine temporally distinct filters encode naturalistic inputs more efficiently than circuits composed of more similar filters, an advantage that largely disappears when changing the stimulus statistics. Measured filters of fly visual cell types closely match the optimal solutions predicted for natural motion, and these optima map onto both circuit architecture and function. Finally, extending beyond the motion pathway, we identify distinct correlation structures in circuits within and outside the motion pathway. Together, we identify temporal diversity in response filters as a circuit-level strategy for encoding natural motion, shaped by the multiscale statistics of the environment.