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SUMMARY Neuromodulators regulate circuits throughout the nervous system, and revealing the cell types and stimulus conditions controlling their release is vital to understanding their function. The effects of the neuromodulator nitric oxide (NO) have been studied in many circuits, including in the vertebrate retina, where it regulates synaptic release, gap junction coupling, and blood vessel dilation, but little is known about the cells that release NO. We show that a single type of amacrine cell (AC) controls NO release in the inner retina, and we report its light responses, electrical properties, and calcium dynamics. We discover that this AC forms a dense gap junction network and that the strength of electrical coupling in the network is regulated by NO. A model of the network offers insights into the biophysical specializations leading to auto-regulation of NO release within the network.

The retina transforms patterns of light into visual feature representations supporting behaviour. These representations are distributed across various types of retinal ganglion cells (RGCs), whose spatial and temporal tuning properties have been extensively studied in many model organisms, including the mouse. However, it has been difficult to link the potentially nonlinear retinal transformations of natural visual inputs to specific ethological purposes. Here, we discover a novel selectivity to chromatic contrast in an RGC type that allows the detection of transitions of the horizon across a retinal region. We trained a convolutional neural network (CNN) model on large-scale functional recordings of RGC responses to natural mouse movies, and then used this model to search in silico for stimuli that maximally excite distinct types of RGCs. This procedure predicted centre colour-opponency in transient Suppressed-by-Contrast RGCs (tSbC), a cell type whose function is being debated. We confirmed experimentally that these cells indeed responded very selectively to Green-OFF, UV-ON contrasts, which we found to be characteristic of transitions from ground to sky in the visual scene, as might be elicited by head- or eye-movements across the horizon. Because tSbCs reliably detected these transitions, we suggest a role for this RGC type in providing contextual information (i.e. sky or ground) necessary for the selection of appropriate behavioural responses to other stimuli, such as looming objects. Our work showcases how a combination of experiments with natural stimuli and computational modelling allows discovering novel types of stimulus selectivity and identifying their potential ethological relevance.

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