Direct Measurement of Correlation Responses in Drosophila Elementary Motion Detectors Reveals Fast Timescale Tuning

• Published in: Neuron (Cambridge, Mass.) Mass.), 2016-10, Vol.92 (1), p.227-239
• Main Authors: Salazar-Gatzimas, Emilio, Chen, Juyue, Creamer, Matthew S., Mano, Omer, Mandel, Holly B., Matulis, Catherine A., Pottackal, Joseph, Clark, Damon A.
• Format: Article
• Language: English
• Subjects: Acoustic Stimulation; Animals; Behavior; Drosophila - physiology; Insects; Light; Models, Neurological; Motion Perception - physiology; Motor Activity - physiology; Neurons; Neurons - physiology; Photic Stimulation; Photoreceptors; Rotation; Studies; Time Factors
• ISSN: 0896-6273; 1097-4199
• DOI: 10.1016/j.neuron.2016.09.017

Animals estimate visual motion by integrating light intensity information over time and space. The integration requires nonlinear processing, which makes motion estimation circuitry sensitive to specific spatiotemporal correlations that signify visual motion. Classical models of motion estimation weight these correlations to produce direction-selective signals. However, the correlational algorithms they describe have not been directly measured in elementary motion-detecting neurons (EMDs). Here, we employed stimuli to directly measure responses to pairwise correlations in Drosophila’s EMD neurons, T4 and T5. Activity in these neurons was required for behavioral responses to pairwise correlations and was predictive of those responses. The pattern of neural responses in the EMDs was inconsistent with one classical model of motion detection, and the timescale and selectivity of correlation responses constrained the temporal filtering properties in potential models. These results reveal how neural responses to pairwise correlations drive visual behavior in this canonical motion-detecting circuit. •Neural and behavioral responses to visual correlations were measured directly•Both neural and behavioral responses are precisely tuned to fast correlations•Neural signals predict behavioral responses to “reverse-phi” illusory motion•Responses to correlations constrain circuit models of motion detection Salazar-Gatzimas et al. investigated the tuning properties of elementary motion detectors by measuring behavioral and neural responses to specific spatiotemporal correlations. They found neural tuning to fast correlation timescales, which constrained models of motion detection and predicted features of behavior.