Functional temporal diversity in the fly reflects natural motion statistics
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. Significance statementNeuronal diversity is ubiquitous across sensory systems, yet its functional role remains poorly understood. We investigate a prominent form of diversity: the wide temporal response profile of visual neurons, from transient detectors to slow integrators. Using the fly visual system, we uncover a coding function of temporal diversity. Neurons with complementary temporal properties span the multiscale structure of natural motion, achieving coding efficiency that no single neuron type can implement alone. Predictions from an efficient coding framework grounded in natural motion statistics closely match fly visual circuit organization, from cell-type response properties to anatomical wiring. Because similar temporal diversity exists in the vertebrate retina, we suggest this distributed temporal coding is a conserved design principle shaped by natural scene statistics.