Cellular and Circuit Mechanisms Shaping the Perceptual Properties of the Primate Fovea.

The fovea is a specialized region of the retina that dominates the visual perception of primates by providing high chromatic and spatial acuity. While the foveal and peripheral retina share a similar core circuit architecture, they exhibit profound functional differences whose mechanisms are unknown. Using intracellular recordings and structure-function analyses, we examined the cellular and synaptic underpinnings of the primate fovea. Compared to peripheral vision, the fovea displays decreased sensitivity to rapid variations in light inputs; this difference is reflected in the responses of ganglion cells, the output cells of the retina. Surprisingly, and unlike in the periphery, synaptic inhibition minimally shaped the responses of foveal midget ganglion cells. This difference in inhibition cannot however, explain the differences in the temporal sensitivity of foveal and peripheral midget ganglion cells. Instead, foveal cone photoreceptors themselves exhibited slower light responses than peripheral cones, unexpectedly linking cone signals to perceptual sensitivity.

The Geometry of Information Coding in Correlated Neural Populations.

Neurons in the brain represent information in their collective activity. The fidelity of this neural population code depends on whether and how variability in the response of one neuron is shared with other neurons. Two decades of studies have investigated the influence of these noise correlations on the properties of neural coding. We provide an overview of the theoretical developments on the topic. Using simple, qualitative, and general arguments, we discuss, categorize, and relate the various published results. We emphasize the relevance of the fine structure of noise correlation, and we present a new approach to the issue. Throughout this review, we emphasize a geometrical picture of how noise correlations impact the neural code.

Systematic reduction of the dimensionality of natural scenes allows accurate predictions of retinal ganglion cell spike outputs.

The mammalian retina engages a broad array of linear and nonlinear circuit mechanisms to convert natural scenes into retinal ganglion cell (RGC) spike outputs. Although many individual integration mechanisms are well understood, we know less about how multiple mechanisms interact to encode the complex spatial features present in natural inputs. Here, we identified key spatial features in natural scenes that shape encoding by primate parasol RGCs. Our approach identified simplifications in the spatial structure of natural scenes that minimally altered RGC spike responses. We observed that reducing natural movies into 16 linearly integrated regions described ∼80% of the structure of parasol RGC spike responses; this performance depended on the number of regions but not their precise spatial locations. We used simplified stimuli to design high-dimensional metamers that recapitulated responses to naturalistic movies. Finally, we modeled the retinal computations that convert flashed natural images into one-dimensional spike counts.

Light Adaptation of Retinal Rod Bipolar Cells.

The sensitivity of retinal cells is altered in background light to optimize the detection of contrast. For scotopic (rod) vision, substantial adaptation occurs in the first two cells, the rods and rod bipolar cells (RBCs), through sensitivity adjustments in rods and postsynaptic modulation of the transduction cascade in RBCs. To study the mechanisms mediating these components of adaptation, we made whole-cell, voltage-clamp recordings from retinal slices of mice from both sexes. Adaptation was assessed by fitting the Hill equation to response-intensity relationships with the parameters of half-maximal response (I1/2 ), Hill coefficient (n), and maximum response amplitude (Rmax ). We show that rod sensitivity decreases in backgrounds according to the Weber-Fechner relation with an I1/2 of ∼50 R* s-1 The sensitivity of RBCs follows a near-identical function, indicating that changes in RBC sensitivity in backgrounds bright enough to adapt the rods are mostly derived from the rods themselves. Backgrounds too dim to adapt the rods can however alter n, relieving a synaptic nonlinearity likely through entry of Ca2+ into the RBCs. There is also a surprising decrease of Rmax , indicating that a step in RBC synaptic transduction is desensitized or that the transduction channels became reluctant to open. This effect is greatly reduced after dialysis of BAPTA at a membrane potential of +50 mV to impede Ca2+ entry. Thus the effects of background illumination in RBCs are in part the result of processes intrinsic to the photoreceptors and in part derive from additional Ca2+-dependent processes at the first synapse of vision.SIGNIFICANCE STATEMENT Light adaptation adjusts the sensitivity of vision as ambient illumination changes. Adaptation for scotopic (rod) vision is known to occur partly in the rods and partly in the rest of the retina from presynaptic and postsynaptic mechanisms. We recorded light responses of rods and rod bipolar cells to identify different components of adaptation and study their mechanisms. We show that bipolar-cell sensitivity largely follows adaptation of the rods but that light too dim to adapt the rods produces a linearization of the bipolar-cell response and a surprising decrease in maximum response amplitude, both mediated by a change in intracellular Ca2+ These findings provide a new understanding of how the retina responds to changing illumination.

Nonlinear convergence boosts information coding in circuits with parallel outputs.

Neural circuits are structured with layers of converging and diverging connectivity and selectivity-inducing nonlinearities at neurons and synapses. These components have the potential to hamper an accurate encoding of the circuit inputs. Past computational studies have optimized the nonlinearities of single neurons, or connection weights in networks, to maximize encoded information, but have not grappled with the simultaneous impact of convergent circuit structure and nonlinear response functions for efficient coding. Our approach is to compare model circuits with different combinations of convergence, divergence, and nonlinear neurons to discover how interactions between these components affect coding efficiency. We find that a convergent circuit with divergent parallel pathways can encode more information with nonlinear subunits than with linear subunits, despite the compressive loss induced by the convergence and the nonlinearities when considered separately.

Predicting and Manipulating Cone Responses to Naturalistic Inputs.

Primates explore their visual environment by making frequent saccades, discrete and ballistic eye movements that direct the fovea to specific regions of interest. Saccades produce large and rapid changes in input. The magnitude of these changes and the limited signaling range of visual neurons mean that effective encoding requires rapid adaptation. Here, we explore how macaque cone photoreceptors maintain sensitivity under these conditions. Adaptation makes cone responses to naturalistic stimuli highly nonlinear and dependent on stimulus history. Such responses cannot be explained by linear or linear-nonlinear models but are well explained by a biophysical model of phototransduction based on well-established biochemical interactions. The resulting model can predict cone responses to a broad range of stimuli and enables the design of stimuli that elicit specific (e.g., linear) cone photocurrents. These advances will provide a foundation for investigating the contributions of cone phototransduction and post-transduction processing to visual function.SIGNIFICANCE STATEMENT We know a great deal about adaptational mechanisms that adjust sensitivity to slow changes in visual inputs such as the rising or setting sun. We know much less about the rapid adaptational mechanisms that are essential for maintaining sensitivity as gaze shifts around a single visual scene. We characterize how phototransduction in cone photoreceptors adapts to rapid changes in input similar to those encountered during natural vision. We incorporate these measurements into a quantitative model that can predict cone responses across a broad range of stimuli. This model not only shows how cone phototransduction aids the encoding of natural inputs but also provides a tool to identify the role of the cone responses in shaping those of downstream visual neurons.

Stimulation of functional neuronal regeneration from Müller glia in adult mice.

Many retinal diseases lead to the loss of retinal neurons and cause visual impairment. The adult mammalian retina has little capacity for regeneration. By contrast, teleost fish functionally regenerate their retina following injury, and Müller glia (MG) are the source of regenerated neurons. The proneural transcription factor Ascl1 is upregulated in MG after retinal damage in zebrafish and is necessary for regeneration. Although Ascl1 is not expressed in mammalian MG after injury, forced expression of Ascl1 in mouse MG induces a neurogenic state in vitro and in vivo after NMDA (N-methyl-d-aspartate) damage in young mice. However, by postnatal day 16, mouse MG lose neurogenic capacity, despite Ascl1 overexpression. Loss of neurogenic capacity in mature MG is accompanied by reduced chromatin accessibility, suggesting that epigenetic factors limit regeneration. Here we show that MG-specific overexpression of Ascl1, together with a histone deacetylase inhibitor, enables adult mice to generate neurons from MG after retinal injury. The MG-derived neurons express markers of inner retinal neurons, synapse with host retinal neurons, and respond to light. Using an assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq), we show that the histone deacetylase inhibitor promotes accessibility at key gene loci in the MG, and allows more effective reprogramming. Our results thus provide a new approach for the treatment of blinding retinal diseases.

A high-density narrow-field inhibitory retinal interneuron with direct coupling to Müller glia.

Amacrine cells are interneurons composing the most diverse cell class in the mammalian retina. They help encode visual features such as edges or directed motion by mediating excitatory and inhibitory interactions between input (i.e. bipolar) and output (i.e. ganglion) neurons in the inner plexiform layer (IPL). Like other brain regions, the retina also contains glial cells that contribute to neurotransmitter uptake, metabolic regulation and neurovascular control. Here, we report that in mouse retina (of either sex), an abundant, though previously unstudied inhibitory amacrine cell is coupled directly to Müller glia. Electron microscopic reconstructions of this amacrine type revealed chemical synapses with known retinal cell types and extensive associations with Müller glia, the processes of which often completely ensheathe the neurites of this amacrine cell. Microinjecting small tracer molecules into the somas of these amacrine cells led to selective labelling of nearby Müller glia, leading us to suggest the name "Müller glia-coupled amacrine cell," or MAC. Our data also indicate that MACs release glycine at conventional chemical synapses, and viral retrograde transsynaptic tracing from the dorsal lateral geniculate nucleus (dLGN) showed selective connections between MACs and a subpopulation of RGC types. Visually-evoked responses revealed a strong preference for light increments; these "ON" responses were primarily mediated by excitatory chemical synaptic input and direct electrical coupling with other cells. This initial characterization of the MAC provides the first evidence for neuron-glia coupling in the mammalian retina and identifies the MAC as a potential link between inhibitory processing and glial function.Significance Statement:Gap junctions between pairs of neurons or glial cells are commonly found throughout the nervous system and play multiple roles, including electrical coupling and metabolic exchange. In contrast, gap junctions between neurons and glia cells have rarely been reported and are poorly understood. Here we report the first evidence for neuron-glia coupling in the mammalian retina, specifically between an abundant (but previously unstudied) inhibitory interneuron and Müller glia. Moreover, viral tracing, optogenetics and serial electron microscopy provide new information about the neuron's synaptic partners and physiological responses.

GABA release selectively regulates synapse development at distinct inputs on direction-selective retinal ganglion cells.

Synaptic inhibition controls a neuron's output via functionally distinct inputs at two subcellular compartments, the cell body and the dendrites. It is unclear whether the assembly of these distinct inhibitory inputs can be regulated independently by neurotransmission. In the mammalian retina, γ-aminobutyric acid (GABA) release from starburst amacrine cells (SACs) onto the dendrites of on-off direction-selective ganglion cells (ooDSGCs) is essential for directionally selective responses. We found that ooDSGCs also receive GABAergic input on their somata from other amacrine cells (ACs), including ACs containing the vasoactive intestinal peptide (VIP). When net GABAergic transmission is reduced, somatic, but not dendritic, GABAA receptor clusters on the ooDSGC increased in number and size. Correlative fluorescence imaging and serial electron microscopy revealed that these enlarged somatic receptor clusters are localized to synapses. By contrast, selectively blocking vesicular GABA release from either SACs or VIP ACs did not alter dendritic or somatic receptor distributions on the ooDSGCs, showing that neither SAC nor VIP AC GABA release alone is required for the development of inhibitory synapses in ooDSGCs. Furthermore, a reduction in net GABAergic transmission, but not a selective reduction from SACs, increased excitatory drive onto ooDSGCs. This increased excitation may drive a homeostatic increase in ooDSGC somatic GABAA receptors. Differential regulation of GABAA receptors on the ooDSGC's soma and dendrites could facilitate homeostatic control of the ooDSGC's output while enabling the assembly of the GABAergic connectivity underlying direction selectivity to be indifferent to altered transmission.

A computational observer model of spatial contrast sensitivity: Effects of photocurrent encoding, fixational eye movements, and inference engine.

We have recently shown that the relative spatial contrast sensitivity function (CSF) of a computational observer operating on the cone mosaic photopigment excitations of a stationary retina has the same shape as human subjects. Absolute human sensitivity, however, is 5- to 10-fold lower than the computational observer. Here we model how additional known features of early vision affect the CSF: fixational eye movements and the conversion of cone photopigment excitations to cone photocurrents (phototransduction). For a computational observer that uses a linear classifier applied to the responses of a stimulus-matched linear filter, fixational eye movements substantially change the shape of the CSF by reducing sensitivity above 10 c/deg. For a translation-invariant computational observer that operates on the squared response of a quadrature-pair of linear filters, the CSF shape is little changed by eye movements, but there is a two fold reduction in sensitivity. Phototransduction dynamics introduce an additional two fold sensitivity decrease. Hence, the combined effects of fixational eye movements and phototransduction bring the absolute CSF of the translation-invariant computational observer to within a factor of 1 to 2 of the human CSF. We note that the human CSF depends on processing of the retinal representation by many thalamo-cortical neurons, which are individually quite noisy. Our modeling suggests that the net effect of post-retinal noise on contrast-detection performance, when considered at the neural population and behavioral level, is quite small: The inference mechanisms that determine the CSF, presumably in cortex, make efficient use of the information carried by the cone photocurrents of the fixating eye.

Temporal resolution of single-photon responses in primate rod photoreceptors and limits imposed by cellular noise.

Sensory receptor noise corrupts sensory signals, contributing to imperfect perception and dictating central processing strategies. For example, noise in rod phototransduction limits our ability to detect light, and minimizing the impact of this noise requires precisely tuned nonlinear processing by the retina. But detection sensitivity is only one aspect of night vision: prompt and accurate behavior also requires that rods reliably encode the timing of photon arrivals. We show here that the temporal resolution of responses of primate rods is much finer than the duration of the light response and identify the key limiting sources of transduction noise. We also find that the thermal activation rate of rhodopsin is lower than previous estimates, implying that other noise sources are more important than previously appreciated. A model of rod single-photon responses reveals that the limiting noise relevant for behavior depends critically on how rod signals are pooled by downstream neurons. NEW & NOTEWORTHY Many studies have focused on the visual system's ability to detect photons, but not on its ability to encode the relative timing of detected photons. Timing is essential for computations such as determining the velocity of moving objects. Here we examine the timing precision of primate rod photoreceptor responses and show that it is more precise than previously appreciated. This motivates an evaluation of whether scotopic vision approaches limits imposed by rod temporal resolution.

Predicting how and when hidden neurons skew measured synaptic interactions.

A major obstacle to understanding neural coding and computation is the fact that experimental recordings typically sample only a small fraction of the neurons in a circuit. Measured neural properties are skewed by interactions between recorded neurons and the "hidden" portion of the network. To properly interpret neural data and determine how biological structure gives rise to neural circuit function, we thus need a better understanding of the relationships between measured effective neural properties and the true underlying physiological properties. Here, we focus on how the effective spatiotemporal dynamics of the synaptic interactions between neurons are reshaped by coupling to unobserved neurons. We find that the effective interactions from a pre-synaptic neuron r' to a post-synaptic neuron r can be decomposed into a sum of the true interaction from r' to r plus corrections from every directed path from r' to r through unobserved neurons. Importantly, the resulting formula reveals when the hidden units have-or do not have-major effects on reshaping the interactions among observed neurons. As a particular example of interest, we derive a formula for the impact of hidden units in random networks with "strong" coupling-connection weights that scale with [Formula: see text], where N is the network size, precisely the scaling observed in recent experiments. With this quantitative relationship between measured and true interactions, we can study how network properties shape effective interactions, which properties are relevant for neural computations, and how to manipulate effective interactions.

Contrast-dependent red-green hue shift.

On bright surrounds, red-green-balanced yellow targets become greenish brown with decreased target luminance, and red-green-balanced brown targets become reddish yellow with increased target luminance. These effects imply luminance- and/or contrast-dependent weighting of M- and L-cone signals in post-receptoral pathways. We show psychophysically that luminance contrast between the surround and the target is the primary determinant of the magnitude of red-green hue shift, requiring surround luminance at least twice the target luminance and increasing with further increases of surround/target contrast. There is a much smaller effect of absolute stimulus luminance, with dimmer stimuli showing slightly larger hue shifts. To evaluate a possible retinal origin of the changes in cone-signal weightings underlying the hue shift, we recorded spike responses from both ON- and OFF-center midget ganglion cells in peripheral primate retina. We found no evidence that the relative strength of L- and M-cone post-receptoral responses changed systematically with change of surround irradiance. Nor was there any systematic difference between ON- and OFF-subtypes. This suggests that the change in cone signal weighting occurs later in the visual system.

Neurotransmission plays contrasting roles in the maturation of inhibitory synapses on axons and dendrites of retinal bipolar cells.

Neuronal output is modulated by inhibition onto both dendrites and axons. It is unknown whether inhibitory synapses at these two cellular compartments of an individual neuron are regulated coordinately or separately during in vivo development. Because neurotransmission influences synapse maturation and circuit development, we determined how loss of inhibition affects the expression of diverse types of inhibitory receptors on the axon and dendrites of mouse retinal bipolar cells. We found that axonal GABA but not glycine receptor expression depends on neurotransmission. Importantly, axonal and dendritic GABAA receptors comprise distinct subunit compositions that are regulated differentially by GABA release: Axonal GABAA receptors are down-regulated but dendritic receptors are up-regulated in the absence of inhibition. The homeostatic increase in GABAA receptors on bipolar cell dendrites is pathway-specific: Cone but not rod bipolar cell dendrites maintain an up-regulation of receptors in the transmission deficient mutants. Furthermore, the bipolar cell GABAA receptor alterations are a consequence of impaired vesicular GABA release from amacrine but not horizontal interneurons. Thus, inhibitory neurotransmission regulates in vivo postsynaptic maturation of inhibitory synapses with contrasting modes of action specific to synapse type and location.

How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?

Neural circuits reliably encode and transmit signals despite the presence of noise at multiple stages of processing. The efficient coding hypothesis, a guiding principle in computational neuroscience, suggests that a neuron or population of neurons allocates its limited range of responses as efficiently as possible to best encode inputs while mitigating the effects of noise. Previous work on this question relies on specific assumptions about where noise enters a circuit, limiting the generality of the resulting conclusions. Here we systematically investigate how noise introduced at different stages of neural processing impacts optimal coding strategies. Using simulations and a flexible analytical approach, we show how these strategies depend on the strength of each noise source, revealing under what conditions the different noise sources have competing or complementary effects. We draw two primary conclusions: (1) differences in encoding strategies between sensory systems-or even adaptational changes in encoding properties within a given system-may be produced by changes in the structure or location of neural noise, and (2) characterization of both circuit nonlinearities as well as noise are necessary to evaluate whether a circuit is performing efficiently.

Broad thorny ganglion cells: a candidate for visual pursuit error signaling in the primate retina.

Functional analyses exist only for a few of the morphologically described primate ganglion cell types, and their correlates in other mammalian species remain elusive. Here, we recorded light responses of broad thorny cells in the whole-mounted macaque retina. They showed ON-OFF-center light responses that were strongly suppressed by stimulation of the receptive field surround. Spike responses were delayed compared with parasol ganglion cells and other ON-OFF cells, including recursive bistratified ganglion cells and A1 amacrine cells. The receptive field structure was shaped by direct excitatory synaptic input and strong presynaptic and postsynaptic inhibition in both ON and OFF pathways. The cells responded strongly to dark or bright stimuli moving either in or out of the receptive field, independent of the direction of motion. However, they did not show a maintained spike response either to a uniform background or to a drifting plaid pattern. These properties could be ideally suited for guiding movements involved in visual pursuit. The functional characteristics reported here permit the first direct cross-species comparison of putative homologous ganglion cell types. Based on morphological similarities, broad thorny ganglion cells have been proposed to be homologs of rabbit local edge detector ganglion cells, but we now show that the two cells have quite distinct physiological properties. Thus, our data argue against broad thorny cells as the homologs of local edge detector cells.

Noise correlations improve response fidelity and stimulus encoding.

Computation in the nervous system often relies on the integration of signals from parallel circuits with different functional properties. Correlated noise in these inputs can, in principle, have diverse and dramatic effects on the reliability of the resulting computations. Such theoretical predictions have rarely been tested experimentally because of a scarcity of preparations that permit measurement of both the covariation of a neuron's input signals and the effect on a cell's output of manipulating such covariation. Here we introduce a method to measure covariation of the excitatory and inhibitory inputs a cell receives. This method revealed strong correlated noise in the inputs to two types of retinal ganglion cell. Eliminating correlated noise without changing other input properties substantially decreased the accuracy with which a cell's spike outputs encoded light inputs. Thus, covariation of excitatory and inhibitory inputs can be a critical determinant of the reliability of neural coding and computation.

Brightness in human rod vision depends on slow neural adaptation to quantum statistics of light.

In human rod-mediated vision, threshold for small, brief flashes rises in proportion to the square root of adapting luminance at all but the lowest and highest adapting intensities. A classical signal detection theory from Rose (1942, 1948) and de Vries (1943) attributed this rise to the perceptual masking of weak flashes by Poisson fluctuations in photon absorptions from the adapting field. However, previous work by Brown and Rudd (1998) demonstrated that the square-root law also holds for suprathreshold brightness judgments, a finding that supports an alternative explanation of the square-root sensitivity changes as a consequence of physiological adaptation (i.e., neural gain control). Here, we employ a dichoptic matching technique to investigate the properties of this brightness gain control. We show that the brightness gain control: 1) affects the brightness of high-intensity suprathreshold flashes for which assumptions of the de Vries-Rose theory are strongly violated; 2) exhibits a long time course of 100-200 s; and 3) is subject to modulation by temporal contrast noise when the mean adapting luminance is held constant. These findings are consistent with the hypothesis that the square-root law results from a slow neural adaptation to statistical noise in the rod pool. We suggest that such adaptation may function to reduce the probability of spurious ganglion cell spiking activity due to photon fluctuation noise as the ambient illumination level is increased.

Distinctive receptive field and physiological properties of a wide-field amacrine cell in the macaque monkey retina.

At early stages of visual processing, receptive fields are typically described as subtending local regions of space and thus performing computations on a narrow spatial scale. Nevertheless, stimulation well outside of the classical receptive field can exert clear and significant effects on visual processing. Given the distances over which they occur, the retinal mechanisms responsible for these long-range effects would certainly require signal propagation via active membrane properties. Here the physiology of a wide-field amacrine cell-the wiry cell-in macaque monkey retina is explored, revealing receptive fields that represent a striking departure from the classic structure. A single wiry cell integrates signals over wide regions of retina, 5-10 times larger than the classic receptive fields of most retinal ganglion cells. Wiry cells integrate signals over space much more effectively than predicted from passive signal propagation, and spatial integration is strongly attenuated during blockade of NMDA spikes but integration is insensitive to blockade of NaV channels with TTX. Thus these cells appear well suited for contributing to the long-range interactions of visual signals that characterize many aspects of visual perception.

Complex inhibitory microcircuitry regulates retinal signaling near visual threshold.

Neuronal microcircuits, small, localized signaling motifs involving two or more neurons, underlie signal processing and computation in the brain. Compartmentalized signaling within a neuron may enable it to participate in multiple, independent microcircuits. Each A17 amacrine cell in the mammalian retina contains within its dendrites hundreds of synaptic feedback microcircuits that operate independently to modulate feedforward signaling in the inner retina. Each of these microcircuits comprises a small (<1 µm) synaptic varicosity that typically receives one excitatory synapse from a presynaptic rod bipolar cell (RBC) and returns two reciprocal inhibitory synapses back onto the same RBC terminal. Feedback inhibition from the A17 sculpts the feedforward signal from the RBC to the AII, a critical component of the circuitry mediating night vision. Here, we show that the two inhibitory synapses from the A17 to the RBC express kinetically distinct populations of GABA receptors: rapidly activating GABA(A)Rs are enriched at one synapse while more slowly activating GABA(C)Rs are enriched at the other. Anatomical and electrophysiological data suggest that macromolecular complexes of voltage-gated (Cav) channels and Ca(2+)-activated K(+) channels help to regulate GABA release from A17 varicosities and limit GABA(C)R activation under certain conditions. Finally, we find that selective elimination of A17-mediated feedback inhibition reduces the signal to noise ratio of responses to dim flashes recorded in the feedforward pathway (i.e., the AII amacrine cell). We conclude that A17-mediated feedback inhibition improves the signal to noise ratio of RBC-AII transmission near visual threshold, thereby improving visual sensitivity at night.