Neuron
Volume 70, Issue 6, 23 June 2011, Pages 1165-1177
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Article
Defining the Computational Structure of the Motion Detector in Drosophila

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Summary

Many animals rely on visual motion detection for survival. Motion information is extracted from spatiotemporal intensity patterns on the retina, a paradigmatic neural computation. A phenomenological model, the Hassenstein-Reichardt correlator (HRC), relates visual inputs to neural activity and behavioral responses to motion, but the circuits that implement this computation remain unknown. By using cell-type specific genetic silencing, minimal motion stimuli, and in vivo calcium imaging, we examine two critical HRC inputs. These two pathways respond preferentially to light and dark moving edges. We demonstrate that these pathways perform overlapping but complementary subsets of the computations underlying the HRC. A numerical model implementing differential weighting of these operations displays the observed edge preferences. Intriguingly, these pathways are distinguished by their sensitivities to a stimulus correlation that corresponds to an illusory percept, “reverse phi,” that affects many species. Thus, this computational architecture may be widely used to achieve edge selectivity in motion detection.

Highlights

► Visual motion is detected as correlated changes in light over time and space ► This visual circuitry can be modeled with the Hassenstein-Reichardt correlator (HRC) ► We identify a mechanism that tunes the HRC to detect moving bright and dark edges ► This information is transmitted separately in laminar L1 and L2 pathways

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