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Song, Z.; Juusola, M.I.
Publisher: Wiley
Journal: The Journal of Physiology
Languages: English
Types: Article
Subjects: fly photoreceptor, light adaptation, quantum sampling, stochastic adaptive sampling, Special section reviews: Shining new light into the workings of photoreceptors and visual interneurons, Symposium Review, gain control, large dynamic range, phototransduction
Light intensities (photons/s/um2) in a natural scene vary over several orders of magnitude\ud from shady woods to direct sunlight. A major challenge facing the visual system is how to map such a\ud large dynamic input range to its limited output range, so that signal is neither buried into noise in\ud darkness and nor saturated in brightness. A fly photoreceptor has achieved such a large dynamic\ud range; it can encode intensity changes from single photons to billions more, outperforming man-made\ud light sensors. This performance requires powerful light-adaptation, the neural implementation of\ud which has only become clearer recently. A computational fly photoreceptor model, which mimics the\ud real phototransduction processes, has elucidated how light adaptation happens dynamically through\ud stochastic adaptive quantal information sampling. A Drosophila R1-R6 photoreceptor’s light-sensor, the\ud rhabdomere, has 30,000 microvilli, each of which stochastically samples incoming photons. Each\ud microvillus employs a full G-protein-coupled-receptor (GPCR) signalling pathway to adaptively\ud transduce photons into quantum bumps (QBs, or samples). QBs then sum up the macroscopic\ud photoreceptor responses, governed by four quantal sampling factors (limitations): (1) the number of\ud photon sampling units in the cell structure (microvilli); (2) sample size (QB waveform); (3) latency\ud distribution (time delay between photon arrival to emergence of a QB), and (4) refractory period\ud distribution (time for a microvillus to recover after a QB). Here, we review how these factors jointly\ud orchestrate light adaptation over a large dynamic range.

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