Interestingly, a second pairwise correlation is also generated in the opposite direction, corresponding to a reverse-phi signal. The check details reverse-phi signal is specific to the type of edge, with light edges associated with dark-bright reverse phi and dark edges associated

with bright-dark reverse phi. Intriguingly, animals bearing only a single functional L1 or L2 neuron type retained only the reverse-phi signal appropriate to the edge type for which they are behaviorally selective. We therefore considered whether these reverse-phi correlations could be important for edge selectivity. To do this, we created a weighted quadrant model. We simulated an array of HRCs with response properties to phi and reverse-phi stimuli that were appropriate to either the L1 or L2 pathway and examined their edge selectivity. In particular, we constructed our model by using the measured weightings buy Anti-diabetic Compound Library of the unit computations of the HRC (Figure 7). That is, the only difference between the two pathways in our model was the differential weightings of the four unit multiplications of the filtered intensity input. In constructing the model, we also incorporated the following assumptions. First, as L1 and L2 pathways are thought to be completely sufficient for motion detection (Rister et al., 2007), our model included only these inputs. Second, we used both our measured delay filter and the behavioral

filter taken from measurements of wild-type flies (Figure 2, see Supplemental Experimental Procedures). Third, while the kinetics of genetically encoded calcium indicators are too slow to allow us to directly measure a physiological filter for L1 and L2, electrical recordings in LMC cell bodies made in blowfly at similar intensities to our experiments have shown that LMCs act as high-pass or band-pass filters, emphasizing changes old in

contrast and suppressing absolute contrast on timescales longer than ∼50–100 ms (Juusola et al., 1995 and Laughlin et al., 1987). The high-pass filter incorporated into our model was therefore made to be consistent with these measurements. We validated our model by showing that it responded to the sequential bar stimuli in the same proportions as the corresponding silenced flies; this result is by construction (Figure S7A). A version of the model including both pathways and representing a wild-type fly subjected to random Gaussian contrast bar pairs (Figure 2A) yielded filters that closely resembled those measured in Figure 2 (Figures S7B and S7C). By using this model, we then calculated the predicted responses of L1 and L2 pathways to light and dark edges and compared the edge selectivity in those responses to the actual edge selectivity observed in each pathway. We defined edge selectivity as the integrated light edge response minus the integrated dark edge response, divided by their sum.