Gregory W. Schwartz

The spatial structure of a nonlinear receptive field

Understanding a sensory system implies the ability to predict responses to a variety of inputs from a common model. In the retina, this includes predicting how the integration of signals across visual space shapes the outputs of retinal ganglion cells. Existing models of this process generalize poorly to predict responses to new stimuli. This failure arises in part from properties of the ganglion cell response that are not well captured by standard receptive-field mapping techniques: nonlinear spatial integration and fine-scale heterogeneities in spatial sampling. Here we characterize a ganglion cells spatial receptive field using a mechanistic model based on measurements of the physiological properties and connectivity of only the primary excitatory circuitry of the retina. The resulting simplified circuit model successfully predicts ganglion-cell responses to a variety of spatial patterns and thus provides a direct correspondence between circuit connectivity and retinal output.

Visual Space Is Represented by Nonmatching Topographies of Distinct Mouse Retinal Ganglion Cell Types

The distributions of neurons in sensory circuits display ordered spatial patterns arranged to enhance or encode specific regions or features of the external environment. Indeed, visual space is not sampled uniformly across the vertebrate retina. Retinal ganglion cell (RGC) density increases and dendritic arbor size decreases toward retinal locations with higher sampling frequency, such as the fovea in primates and area centralis in carnivores [1]. In these locations, higher acuity at the level of individual cells is obtained because the receptive field center of a RGC corresponds approximately to the spatial extent of its dendritic arbor [2, 3]. For most species, structurally and functionally distinct RGC types appear to have similar topographies, collectively scaling their cell densities and arbor sizes toward the same retinal location [4]. Thus, visual space is represented across the retina in parallel by multiple distinct circuits [5]. In contrast, we find a population of mouse RGCs, known as alpha or alpha-like [6], that displays a nasal-to-temporal gradient in cell density, size, and receptive fields, which facilitates enhanced visual sampling in frontal visual fields. The distribution of alpha-like RGCs contrasts with other known mouse RGC types and suggests that, unlike most mammals, RGC topographies in mice are arranged to sample space differentially.

The Synaptic and Circuit Mechanisms Underlying a Change in Spatial Encoding in the Retina

Components of neural circuits are often repurposed so that the same biological hardware can be used for distinct computations. This flexibility in circuit operation is required to account for the changes in sensory computations that accompany changes in input signals. Yet we know little about how such changes in circuit operation are implemented. Here we show that a single retinal ganglion cell performs a different computation in dim light--averaging contrast within its receptive field--than in brighter light, when the cell becomes sensitive to fine spatial detail. This computational change depends on interactions between two parallel circuits that control the ganglion cells excitatory synaptic inputs. Specifically, steady-state interactions through dendro-axonal gap junctions control rectification of the synapses providing excitatory input to the ganglion cell. These findings provide a clear example of how a simple synaptic mechanism can repurpose a neural circuit to perform diverse computations.

Interplay of Cell-Autonomous and Nonautonomous Mechanisms Tailors Synaptic Connectivity of Converging Axons In Vivo

Neurons receive input from diverse afferents but form stereotypic connections with each axon type to execute their precise functions. Developmental mechanisms that specify the connectivity of individual axons across populations of converging afferents are not well-understood. Here, we untangled the contributions of activity-dependent and independent interactions that regulate the connectivity of afferents providing major and minor input onto a neuron. Individual transmission-deficient retinal bipolar cells (BCs) reduced synapses with retinal ganglion cells (RGCs), but active BCs of the same type sharing the dendrite surprisingly did not compensate for this loss. Genetic ablation of some BC neighbors resulted in increased synaptogenesis by the remaining axons in a transmission-independent manner. Presence, but not transmission, of the major BC input also dissuades wiring with the minor input and with synaptically compatible but functionally mismatched afferents. Cell-autonomous, activity-dependent and nonautonomous, activity-independent mechanisms thus together tailor connectivity of individual axons among converging inner retinal afferents.

Cardinal Orientation Selectivity Is Represented by Two Distinct Ganglion Cell Types in Mouse Retina

Orientation selectivity (OS) is a prominent and well studied feature of early visual processing in mammals, but recent work has highlighted the possibility that parallel OS circuits might exist in multiple brain locations. Although both classic and modern work has identified an OS mechanism in selective wiring from lateral geniculate nucleus (LGN) to primary visual cortex, OS responses have now been found upstream of cortex in mouse LGN and superior colliculus, suggesting a possible origin in the retina. Indeed, retinal OS responses have been reported for decades in rabbit and more recently in mouse. However, we still know very little about the properties and mechanisms of retinal OS in the mouse, including whether there is a distinct OS ganglion cell type, which orientations are represented, and what are the synaptic mechanisms of retinal OS. We have identified two novel types of OS ganglion cells in the mouse retina that are highly selective for horizontal and vertical cardinal orientations. Reconstructions of the dendritic trees of these OS ganglion cells and measurements of their synaptic conductances offer insights into the mechanism of the OS computation at the earliest stage of the visual system. SIGNIFICANCE STATEMENT Orientation selectivity (OS) is one of the most well studied computations in the brain and has become a prominent model system in various areas of sensory neuroscience. Although the cortical mechanism of OS suggested by Hubel and Wiesel (1962) has been investigated intensely, other OS cells exist upstream of cortex as early as the retina and the mechanisms of OS in subcortical regions are much less well understood. We identified two ON retinal ganglion cells (RGCs) in mouse that compute OS along the horizontal (nasal–temporal) and vertical (dorsoventral) axes of visual space. We show the relationship between dendritic morphology and OS for each RGC type and reveal new synaptic mechanisms of OS computation in the retina.

Fine Spatial Information Represented in a Population of Retinal Ganglion Cells

Detailed measurement of ganglion cell receptive fields often reveals significant deviations from a smooth, Gaussian profile. We studied the effect of these irregularities on the representation of fine spatial information in the retina. We recorded from nearby clusters of ganglion cells, testing their ability to determine the location of small flashed spots, and we compared the results to the prediction of a Gaussian receptive field model derived from reverse correlation. Despite considerable receptive field overlap, almost all ganglion cell pairs signaled nearly independently. For groups of five cells with highly overlapping receptive fields, the measured light-evoked currents encoded ∼33% more information than predicted by the Gaussian receptive field model. Including measured local irregularities in the receptive field model increased performance to the level observed experimentally. These results suggest that instead of being an unavoidable defect, irregularities may be a positive design feature of population neural codes.

An amacrine cell circuit for signaling steady illumination in the retina

Decades of research have focused on the circuit connectivity between retinal neurons, but only a handful of amacrine cells have been described functionally and placed in the context of a specific retinal circuit. Here, we identify a circuit where inhibition from a specific amacrine cell plays a vital role in shaping the feature selectivity of a postsynaptic ganglion cell. We record from transgenically labeled CRH-1 amacrine cells and identify a postsynaptic target for CRH-1 amacrine cell inhibition in an atypical retinal ganglion cell (RGC) in mouse retina, the Suppressed-by-Contrast (SbC) RGC. Unlike other RGC types, SbC RGCs spike tonically in steady illumination and are suppressed by both increases and decreases in illumination. Inhibition from GABAergic CRH-1 amacrine cells shapes this unique contrast response profile to positive contrast. We show the existence and impact of this circuit, with both paired recordings and cell-type-specific ablation.

Circuit Mechanisms of a Retinal Ganglion Cell with Stimulus-Dependent Response Latency and Activation Beyond Its Dendrites

Center-surround antagonism has been used as the canonical model to describe receptive fields of retinal ganglion cells (RGCs) for decades. We describe a newly identified RGC type in the mouse, called the ON delayed (OND) RGC, with receptive field properties that deviate from center-surround organization. Responding with an unusually long latency to light stimulation, OND RGCs respond earlier as the visual stimulus increases in size. Furthermore, OND RGCs are excited by light falling far beyond their dendrites. We unravel details of the circuit mechanisms behind these phenomena, revealing new roles for inhibition in controlling both temporal and spatial receptive field properties. The non-canonical receptive field properties of the OND RGC-integration of long temporal and large spatial scales-suggest that unlike typical RGCs, it may encode a slowly varying, global property of the visual scene.

Electrical synapses convey orientation selectivity in the mouse retina

Sensory neurons downstream of primary receptors are selective for specific stimulus features, and they derive their selectivity both from excitatory and inhibitory synaptic inputs from other neurons and from their own intrinsic properties. Electrical synapses, formed by gap junctions, modulate sensory circuits. Retinal ganglion cells (RGCs) are diverse feature detectors carrying visual information to the brain, and receive excitatory input from bipolar cells and inhibitory input from amacrine cells (ACs). Here we describe a RGC that relies on gap junctions, rather than chemical synapses, to convey its selectivity for the orientation of a visual stimulus. This represents both a new functional role of electrical synapses as the primary drivers of feature selectivity and a new circuit mechanism for orientation selectivity in the retina.Visual input received by photoreceptors is relayed to retinal ganglion cells (RGCs), which have selectivity for inputs of certain orientations. Here, the authors show that gap junction-mediated input onto one type of RGC contributes to its orientation selectivity.

Controlling gain one photon at a time

Adaptation is a salient property of sensory processing. All adaptational or gain control mechanisms face the challenge of obtaining a reliable estimate of the property of the input to be adapted to and obtaining this estimate sufficiently rapidly to be useful. Here, we explore how the primate retina balances the need to change gain rapidly and reliably when photons arrive rarely at individual rod photoreceptors. We find that the weakest backgrounds that decrease the gain of the retinal output signals are similar to those that increase human behavioral threshold, and identify a novel site of gain control in the retinal circuitry. Thus, surprisingly, the gain of retinal signals begins to decrease essentially as soon as background lights are detectable; under these conditions, gain control does not rely on a highly averaged estimate of the photon count, but instead signals from individual photon absorptions trigger changes in gain. DOI: http://dx.doi.org/10.7554/eLife.00467.001