Data from: Asymmetric ON-OFF processing of visual motion cancels variability induced by the structure of natural scenes
Chen, Juyue, Yale University
Mandel, Holly B.
Fitzgerald, James E.
Clark, Damon A.
Published Nov 08, 2019 on Dryad.
Cite this dataset
Chen, Juyue; Mandel, Holly B.; Fitzgerald, James E.; Clark, Damon A. (2019). Data from: Asymmetric ON-OFF processing of visual motion cancels variability induced by the structure of natural scenes [Dataset]. Dryad. https://doi.org/10.5061/dryad.7jm87bt
Animals detect motion using a variety of visual cues that reflect regularities in the natural world. Experiments in animals across phyla have shown that motion percepts incorporate both pairwise and triplet spatiotemporal correlations that could theoretically benefit motion computation. However, it remains unclear how visual systems assemble these cues to build accurate motion estimates. Here we use comprehensive measurements of fruit fly motion perception to show how flies combine local pairwise and triplet correlations to reduce variability in motion estimates across natural scenes. By generating synthetic images with statistics controlled by maximum entropy distributions, we showed that the observed improvement occurs only when light-dark asymmetries mimic natural ones. Thus, fly behavior suggests that asymmetric ON-OFF processing is tuned to the particular statistics of natural scenes. Since all animals encounter the world’s light-dark asymmetries, many visual systems are likely to use asymmetric ON-OFF processing to improve motion estimation.
This dataset contains the data needed to regenerate the figures. The code repository can be found in https://github.com/ClarkLabCode/ThirdOrderKernelCode.