2019
DOI: 10.1038/s41593-019-0443-y
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Dynamic nonlinearities enable direction opponency in Drosophila elementary motion detectors

Abstract: Direction-selective neurons respond to visual motion in a preferred direction. They are directionopponent if they are also inhibited by motion in the opposite direction. In flies and vertebrates, direction opponency has been observed in second-order direction-selective neurons, which achieve this opponency by subtracting signals from first-order direction-selective cells with opposite directional tunings. Here, we report direction opponency in Drosophila that emerges in first-order direction-selective neurons,… Show more

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Cited by 29 publications
(90 citation statements)
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“…We sought to maximally constrain our choices of model parameters by published physiological measurements and to show that the model is relatively robust to the specific values of remaining unconstrained parameters. The set of input parameters used here is equal to that used in a model developed to explain direction-opponency in T4 cells (Badwan et al, 2019). To approximately match the spatial acceptance functions of photoreceptors in the fly eye (Stavenga, 2003), we set the full width at half maximum of the input spatial filters to 5.7 degrees.…”
Section: Selecting Model Parametersmentioning
confidence: 99%
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“…We sought to maximally constrain our choices of model parameters by published physiological measurements and to show that the model is relatively robust to the specific values of remaining unconstrained parameters. The set of input parameters used here is equal to that used in a model developed to explain direction-opponency in T4 cells (Badwan et al, 2019). To approximately match the spatial acceptance functions of photoreceptors in the fly eye (Stavenga, 2003), we set the full width at half maximum of the input spatial filters to 5.7 degrees.…”
Section: Selecting Model Parametersmentioning
confidence: 99%
“…Broadening the input spatial receptive fields or decreasing the input spacing would increase the correlation between the input conductances in this model. We would expect that to affect the spatiotemporal correlations to which the model is sensitive (Badwan et al, 2019;Fitzgerald & Clark, 2015). Previous functional studies of the inputs to T4 cells have suggested that their spatial receptive fields may be somewhat wider than that of one photoreceptor (Arenz et al, 2017;Behnia et al, 2014;Gruntman et al, 2018), but we use this simplified spatial processing because our goal is to construct a minimal model.…”
Section: Selecting Model Parametersmentioning
confidence: 99%
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