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Many diurnal photoreceptors encode vast real-world light changes effectively, but how this performance originates from photon sampling is unclear. A 4-module biophysically-realistic fly photoreceptor model, in which information capture is limited by the number of its sampling units (microvilli) and their photon-hit recovery time (refractoriness), can accurately simulate real recordings and their information content. However, sublinear summation in quantum bump production ( quantum-gain-nonlinearity ) may also cause adaptation by reducing the bump/photon gain when multiple photons hit the same microvillus simultaneously. Here, we use a  Random Photon Absorption Model  ( RandPAM ), which is the 1st module of the 4-module fly photoreceptor model, to quantify the contribution of  quantum-gain-nonlinearity  in light adaptation. We show how  quantum-gain-nonlinearity  already results from photon sampling alone. In the extreme case, when two or more simultaneous photon-hits reduce to a single sublinear value,  quantum-gain-nonlinearity  is preset before the phototransduction reactions adapt the quantum bump waveform. However, the contribution of  quantum-gain-nonlinearity  in light adaptation depends upon the likelihood of multi-photon-hits, which is strictly determined by the number of microvilli and light intensity. Specifically, its contribution to light-adaptation is marginal (≤ 1%) in fly photoreceptors with many thousands of microvilli, because the probability of simultaneous multi-photon-hits on any one microvillus is low even during daylight conditions. However, in cells with fewer sampling units, the impact of  quantum-gain-nonlinearity  increases with brightening light.

Random Photon Absorption Model Elucidates How Early Gain Control in Fly Photoreceptors Arises from Quantal Sampling