The retina uses two photoreceptor types to encode the wide range of light intensities in the natural environment. Rods mediate vision in dim light, whereas cones mediate vision in bright light. Mouse photoreceptors include only 3% cones, and the majority of these co-express two opsins (S, M), with peak sensitivity to either ultraviolet (360 nm) or green light (508 nm). The M:S opsin ratio varies across the retina but has not been characterized functionally, preventing quantitative study of cone-mediated vision. Furthermore, physiological and behavioral measurements suggested that mouse retina supports relatively slow temporal processing (peak sensitivity, ~2–5 Hz), compared to primates; however, past studies used visible wavelengths that are inefficient at stimulating mouse S opsin. Here, we measured the M:S opsin expression ratio across the mouse retina, as reflected by ganglion cell responses, in vitro, and probed cone-mediated ganglion cell temporal properties using ultraviolet light stimulation and linear systems analysis. From recordings in mice lacking rod function (Gnat1−/−, Rho−/−), we estimate ~70% M-opsin expression in far dorsal retina, dropping to <5% M-opsin expression throughout ventral retina. In mice lacking cone function (Gnat2cpfl3), light-adapted rod-mediated responses peaked at ~5–7 Hz. In wild-type mice, cone-mediated responses peaked at ~10 Hz, with substantial responsiveness up to ~30 Hz. Therefore, despite the small percentage of cones, cone-mediated responses in mouse ganglion cells are fast and robust, similar to those in primates. These measurements enable quantitative analysis of cone-mediated responses at all levels of the visual system.

In zebrafish, Müller glia (MG) are a source of retinal stem cells that can replenish damaged retinal neurons and restore vision. In mammals, however, MG do not spontaneously re-enter the cell cycle to generate a population of stem or progenitor cells that differentiate into retinal neurons. Nevertheless, the regenerative machinery may exist in the mammalian retina, as retinal injury can stimulate MG proliferation followed by limited neurogenesis. Therefore, there is still a fundamental question regarding whether MG-derived regeneration can be exploited to restore vision in mammalian retinas. Gene transfer of β-catenin stimulates MG proliferation in the absence of injury in mouse retinas. Here we report that following gene transfer of β-catenin, cell-cycle-reactivated MG can be reprogrammed to generate rod photoreceptors by subsequent gene transfer of transcription factors essential for rod cell fate specification and determination. MG-derived rods restored visual responses in Gnat1Gnat2 double mutant mice, a model of congenital blindness, throughout the visual pathway from the retina to the primary visual cortex. Together, our results provide evidence of vision restoration after de novo MG-derived genesis of rod photoreceptors in mammalian retinas.

SUMMARY Rod photoreceptors contribute to vision over a ~6 log-unit range of light intensities. The wide dynamic range of rod vision is thought to depend upon light intensity-dependent switching between two parallel pathways linking rods to ganglion cells: a rod→rod bipolar (RB) cell pathway that operates at dim backgrounds and a rod→cone→cone bipolar cell pathway that operates at brighter backgrounds. We evaluated this conventional model of rod vision by recording rod-mediated light responses from ganglion and AII amacrine cells and by recording RB-mediated synaptic currents from AII amacrine cells in mouse retina. Contrary to the conventional model, we found that the RB pathway functioned at backgrounds sufficient to activate the rod→cone pathway. As background light intensity increased, the RB’s role changed from encoding the absorption of single photons to encoding contrast modulations around mean luminance. This transition is explained by the intrinsic dynamics of transmission from RB synapses.

Visual processing depends on specific computations implemented by complex neural circuits. Here, we present a circuit-inspired model of retinal ganglion cell computation, targeted to explain their temporal dynamics and adaptation to contrast. To localize the sources of such processing, we used recordings at the levels of synaptic input and spiking output in the in vitro mouse retina. We found that an ON-Alpha ganglion cell's excitatory synaptic inputs were described by a divisive interaction between excitation and delayed suppression, which explained nonlinear processing that was already present in ganglion cell inputs. Ganglion cell output was further shaped by spike generation mechanisms. The full model accurately predicted spike responses with unprecedented millisecond precision, and accurately described contrast adaptation of the spike train. These results demonstrate how circuit and cell-intrinsic mechanisms interact for ganglion cell function and, more generally, illustrate the power of circuit-inspired modeling of sensory processing.

Visual processing depends on specific computations implemented by complex neural circuits. Here, we present a circuit-inspired model of retinal ganglion cell computation, targeted to explain their temporal dynamics and adaptation to contrast. To localize the sources of such processing, we used recordings at the levels of synaptic input and spiking output in the in vitro mouse retina. We found that an ON-Alpha ganglion cell's excitatory synaptic inputs were described by a divisive interaction between excitation and delayed suppression, which explained nonlinear processing that was already present in ganglion cell inputs. Ganglion cell output was further shaped by spike generation mechanisms. The full model accurately predicted spike responses with unprecedented millisecond precision, and accurately described contrast adaptation of the spike train. These results demonstrate how circuit and cell-intrinsic mechanisms interact for ganglion cell function and, more generally, illustrate the power of circuit-inspired modeling of sensory processing.DOI: http://dx.doi.org/10.7554/eLife.19460.001

Visual processing depends on specific computations implemented by complex neural circuits. Here, we present a circuit-inspired model of retinal ganglion cell computation, targeted to explain their temporal dynamics and adaptation to contrast. To localize the sources of such processing, we used recordings at the levels of synaptic input and spiking output in the in vitro mouse retina. We found that an ON-Alpha ganglion cell's excitatory synaptic inputs were described by a divisive interaction between excitation and delayed suppression, which explained nonlinear processing that was already present in ganglion cell inputs. Ganglion cell output was further shaped by spike generation mechanisms. The full model accurately predicted spike responses with unprecedented millisecond precision, and accurately described contrast adaptation of the spike train. These results demonstrate how circuit and cell-intrinsic mechanisms interact for ganglion cell function and, more generally, illustrate the power of circuit-inspired modeling of sensory processing.

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