| Literature DB >> 32442466 |
Ryosuke Tanaka1, Damon A Clark2.
Abstract
Visual systems are often equipped with neurons that detect small moving objects, which may represent prey, predators, or conspecifics. Although the processing properties of those neurons have been studied in diverse organisms, links between the proposed algorithms and animal behaviors or circuit mechanisms remain elusive. Here, we have investigated behavioral function, computational algorithm, and neurochemical mechanisms of an object-selective neuron, LC11, in Drosophila. With genetic silencing and optogenetic activation, we show that LC11 is necessary for a visual object-induced stopping behavior in walking flies, a form of short-term freezing, and its activity can promote stopping. We propose a new quantitative model for small object selectivity based on the physiology and anatomy of LC11 and its inputs. The model accurately reproduces LC11 responses by pooling fast-adapting, tightly size-tuned inputs. Direct visualization of neurotransmitter inputs to LC11 confirmed the model conjectures about upstream processing. Our results demonstrate how adaptation can enhance selectivity for behaviorally relevant, dynamic visual features.Entities:
Keywords: Drosophila; connectomics; neurotransmitter imaging; object detection; psychophysics; quantitative modeling; vision; visual feature detection; voltage imaging
Mesh:
Year: 2020 PMID: 32442466 PMCID: PMC8716191 DOI: 10.1016/j.cub.2020.04.068
Source DB: PubMed Journal: Curr Biol ISSN: 0960-9822 Impact factor: 10.834