Flexible filtering by neural inputs supports motion computation across states and stimuli

Sensory systems flexibly adapt their processing properties across a wide range of environmental and behavioral conditions. Such variable processing complicates attempts to extract a mechanistic understanding of sensory computations. This is evident in the highly constrained, canonical Drosophila motion detection circuit, where the core computation underlying direction selectivity is still debated despite extensive studies. Here we measured the filtering properties of neural inputs to the OFF motion-detecting T5 cell in Drosophila. We report state- and stimulus-dependent changes in the shape of these signals, which become more biphasic under specific conditions. Summing these inputs within the framework of a connectomic-constrained model of the circuit demonstrates that these shapes are sufficient to explain T5 responses to various motion stimuli. Thus, our stimulus- and state-dependent measurements reconcile motion computation with the anatomy of the circuit. These findings provide a clear example of how a basic circuit supports flexible sensory computation. [Display omitted] •Neural inputs to Drosophila motion detector T5 are state and stimulus dependent•Their temporal responses are more biphasic in certain conditions•T5 responses can be explained by linear summation of state/stimulus-dependent input•A biologically constrained model predicts T5 motion responses across conditions Kohn, Portes et al. measure state and stimulus dependent high temporal resolution responses of neural inputs to the Drosophila T5 motion detector. They show that simple linear summation of excitatory adaptive neural input signals is sufficient to explain direction selective responses across conditions.