Hypercomplex properties of Drosophila object detecting neurons
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چکیده
Many animals rely on vision to detect objects such as conspecifics, predators, and prey. Hypercomplex cells of the feline cortex and small target motion detectors of the dragonfly and hoverfly optic lobe demonstrate robust tuning for small objects with weak or no response to elongated edges or movement of the visual panorama [1–4]. However, the relationship between anatomical, molecular, and functional properties of object detection circuitry is not understood. Here, we characterize a previously identified lobula columnar neuron (LC11) in Drosophila [5]. By imaging calcium dynamics with two-photon excitation microscopy we show that LC11 responds to the non-directional motion of a small object darker than the background, with little or no responses to static flicker, elongated bars, or panoramic gratings. LC11 dendrites reside at the boundary between GABA-ergic and cholinergic layers of the lobula, each dendrite spans enough columns to sample 75-degrees of visual space, yet the functional receptive field is only 20-degrees wide, and shows robust responses to an object spanning less than one 5-degree facet of the compound eye. The dendrites of neighboring LC11s encode object motion retinotopically, but the axon terminals fuse into a glomerular structure in the central brain where retinotopy is lost. Blocking inhibitory ionic currents abolishes small object sensitivity and facilitates responses to elongated bars and gratings. Our results reveal high acuity small object motion detection in the Drosophila optic lobe.
منابع مشابه
Object-Detecting Neurons in Drosophila
Many animals rely on vision to detect objects such as conspecifics, predators, and prey. Hypercomplex cells found in feline cortex and small target motion detectors found in dragonfly and hoverfly optic lobes demonstrate robust tuning for small objects, with weak or no response to larger objects or movement of the visual panorama [1-3]. However, the relationship among anatomical, molecular, and...
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تاریخ انتشار 2016