Dynamical adaptation in photoreceptors with gain control

The retina hosts all processes needed to convert external visual stimuli into a neural code. Light phototransduction and its conversion into an electrical signal involve biochemical cascades, ionic regulations, and different kinds of coupling, among other relevant processes. These create a nonlinear processing scheme and light-dependent adaptive responses. The dynamical adaptation model formulated in recent years is an excellent phenomenological candidate to resume all these phenomena into a single feedforward processing scheme. In this work, we analyze this description in highly nonlinear conditions and find that responses do not match those resulting from a very detailed microscopic model, developed to reproduce electrophysiological recordings on horizontal cells. When a delayed light-dependent gain factor incorporates into the description, responses are in excellent agreement, even when spanning several orders of magnitude in light intensity, contrast, and duration, for simple and complex stimuli. This extended model may be instrumental for studies of the retinal function, enabling the linking of the microscopic domain to the understanding of signal processing properties, and further incorporated in spatially extended retinal networks.