Axonal gap junctions in the fly visual system enable fast prediction for evasive flight maneuvers

The visual system must make predictions to compensate for inherent delays in its processing, yet little is unknown, mechanistically, about how prediction aids natural behaviors. Here we show that despite a 30ms intrinsic processing delay, the vertical motion sensitive (VS) network of the blowfly can achieve maximally efficient prediction. This prediction enables fine discrimination of input motion direction during evasive flight maneuvers, which last just 40ms. Combining a rich database of behavioral recordings with detailed compartmental modeling of the VS network, we further show that the VS network implements this optimal prediction with a specific wiring architecture; axonal gap junctions between the VS cells are crucial for optimal prediction during the short timespan of the evasive maneuver. Furthermore, a subpopulation output of the VS network can selectively convey predictive information about the future visual input to the downstream neck motor center. Our work links prediction to behavior, via its neural implementation.