Distinct expressions of contrast gain control in parallel synaptic pathways converging on a retinal ganglion cell

Retinal Connectomics: A Review

The retina is an ideal model for understanding the fundamental rules for how neural networks are constructed. The compact neural networks of the retina perform all of the initial processing of visual information before transmission to higher visual centers in the brain. The field of retinal connectomics uses high-resolution electron microscopy datasets to map the intricate organization of these networks and further our understanding of how these computations are performed by revealing the fundamental topologies and allowable networks behind retinal computations. In this article, we review some of the notable advances that retinal connectomics has provided in our understanding of the specific cells and the organization of their connectivities within the retina, as well as how these are shaped in development and break down in disease. Using these anatomical maps to inform modeling has been, and will continue to be, instrumental in understanding how the retina processes visual signals.

GABA receptors mediate adaptation and sensitization processes in mouse retinal ganglion cells

Two coordinated dynamic properties (adaptation and sensitization) are observed in retinal ganglion cells (RGCs) under the contrast stimulation. During sustained high-contrast period, adaptation decreases RGCs' responses while sensitization increases RGCs' responses. In mouse retina, adaptation and sensitization respectively show OFF- and ON-pathway-dominance. However, the mechanisms which drive the differentiation between adaptation and sensitization remain unclear. In the present study, multi-electrode recordings were conducted on isolated mouse retina under full-field contrast stimulation. Dynamic property was quantified based on the trend of RGC's firing rate during high-contrast period, light sensitivity was estimated by linear-nonlinear analysis and coding ability was estimated through stimulus reconstruction algorism. γ-Aminobutyric acid (GABA) receptors were pharmacologically blocked to explore the relation between RGCs' dynamic property and the activity of GABA receptors. It was found that GABAA and GABAC receptors respectively mediated the adaptation and sensitization processes in RGCs' responses. RGCs' dynamic property changes occurred after the blockage of GABA receptors were related to the modulation of the cells' light sensitivity. Further, the blockage of GABAA (GABAC) receptor significantly decreased RGCs' overall coding ability and eliminated the functional benefits of adaptation (sensitization). Our work suggests that the dynamic property of individual RGC is related to the balance between its GABAA-receptor-mediated inputs and GABAC-receptor-mediated inputs. Blockage of GABA receptors breaks the balance of retinal circuitry for signal processing, and down-regulates the visual information coding ability.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-023-09950-2.

Case Report: Second-order Contrast Sensitivity in Tourette Syndrome

disease, characterized by motor and vocal tics with no changes in the ocular structures in the ophthalmological evaluations. The visual field evaluations suggest a reduction in central visual field sensitivity. The studies on visual function in this population is scarce. In this case report we present a patient with GTS who has significant alterations in the measure of contrast sensitivity for second order vision without any vision complaints. This reduction occurred in the measure of contrast sensitivity with a white noise carrier for practically all tested space frequencies. The mean contrast sensitivity for first and second-order stimuli with a pink-noise carrier was normal. The second order contrast sensitivity with a white noise carrier is dependent on local and lateral inhibition since it includes many local luminance components. The existence of this sensitivity suggests that specific visual processing mechanisms are affected. Keywords: Tourette Syndrome, Contrast Sensitivity, Contrast Psychophysical Channels, Second-Order Perception.

High Contrast Allows the Retina to Compute More Than Just Contrast

The goal of sensory processing is to represent the environment of an animal. All sensory systems share a similar constraint: they need to encode a wide range of stimulus magnitudes within their narrow neuronal response range. The most efficient way, exploited by even the simplest nervous systems, is to encode relative changes in stimulus magnitude rather than the absolute magnitudes. For instance, the retina encodes contrast, which are the variations of light intensity occurring in time and in space. From this perspective, it is easy to understand why the bright plumage of a moving bird gains a lot of attention, while an octopus remains motionless and mimics its surroundings for concealment. Stronger contrasts simply cause stronger visual signals. However, the gains in retinal performance associated with higher contrast are far more than what can be attributed to just a trivial linear increase in signal strength. Here we discuss how this improvement in performance is reflected throughout different parts of the neural circuitry, within its neural code and how high contrast activates many non-linear mechanisms to unlock several sophisticated retinal computations that are virtually impossible in low contrast conditions.

Inferring synaptic inputs from spikes with a conductance-based neural encoding model

Descriptive statistical models of neural responses generally aim to characterize the mapping from stimuli to spike responses while ignoring biophysical details of the encoding process. Here, we introduce an alternative approach, the conductance-based encoding model (CBEM), which describes a mapping from stimuli to excitatory and inhibitory synaptic conductances governing the dynamics of sub-threshold membrane potential. Remarkably, we show that the CBEM can be fit to extracellular spike train data and then used to predict excitatory and inhibitory synaptic currents. We validate these predictions with intracellular recordings from macaque retinal ganglion cells. Moreover, we offer a novel quasi-biophysical interpretation of the Poisson generalized linear model (GLM) as a special case of the CBEM in which excitation and inhibition are perfectly balanced. This work forges a new link between statistical and biophysical models of neural encoding and sheds new light on the biophysical variables that underlie spiking in the early visual pathway.

Neural sensitization improves encoding fidelity in the primate retina

An animal’s motion through the environment can induce large and frequent fluctuations in light intensity on the retina. These fluctuations pose a major challenge to neural circuits tasked with encoding visual information, as they can cause cells to adapt and lose sensitivity. Here, we report that sensitization, a short-term plasticity mechanism, solves this difficult computational problem by maintaining neuronal sensitivity in the face of these fluctuations. The numerically dominant output pathway in the macaque monkey retina, the midget (parvocellular-projecting) pathway, undergoes sensitization under specific conditions, including simulated eye movements. Sensitization is present in the excitatory synaptic inputs from midget bipolar cells and is mediated by presynaptic disinhibition from a wide-field mechanism extending >0.5 mm along the retinal surface. Direct physiological recordings and a computational model indicate that sensitization in the midget pathway supports accurate sensory encoding and prevents a loss of responsiveness during dynamic visual processing.

Light intensity on the retina can fluctuate rapidly during natural vision, posing a challenge for encoding visual information. Here, the authors report that mechanisms of sensitization/facilitation maintain the sensitivity of the numerically dominant neural pathway in the primate retina during dynamic vision.

Inhomogeneous Encoding of the Visual Field in the Mouse Retina

Stimulus characteristics of the mouse's visual field differ above and below the skyline. Here, we show for the first time that retinal ganglion cells (RGCs), the output neurons of the retina, gradually change their functional properties along the ventral-dorsal axis to allow better representation of the different stimulus characteristics. We conducted two-photon targeted recordings of transient-Offα-RGCs and found that they gradually became more sustained along the ventral-dorsal axis, revealing >5-fold-longer duration responses in the dorsal retina. Using voltage-clamp recordings, pharmacology, and genetic manipulation, we demonstrated that the primary rod pathway underlies this variance. Our findings challenge the current belief that RGCs of the same subtype exhibit the same light responses, regardless of retinal location, and suggest that networks underlying RGC responses may change with retinal location to enable optimized sampling of the visual image.

Selective synaptic connections in the retinal pathway for night vision

The mammalian retina encodes visual information in dim light using rod photoreceptors and a specialized circuit: rods→rod bipolar cells→AII amacrine cell. The AII amacrine cell uses sign-conserving electrical synapses to modulate ON cone bipolar cell terminals and sign-inverting chemical (glycinergic) synapses to modulate OFF cone cell bipolar terminals; these ON and OFF cone bipolar terminals then drive the output neurons, retinal ganglion cells (RGCs), following light increments and decrements, respectively. The AII amacrine cell also makes direct glycinergic synapses with certain RGCs, but it is not well established how many types receive this direct AII input. Here, we investigated functional AII amacrine→RGC synaptic connections in the retina of the guinea pig (Cavia porcellus) by recording inhibitory currents from RGCs in the presence of ionotropic glutamate receptor (iGluR) antagonists. This condition isolates a specific pathway through the AII amacrine cell that does not require iGluRs: cone→ON cone bipolar cell→AII amacrine cell→RGC. These recordings show that AII amacrine cells make direct synapses with OFF Alpha, OFF Delta and a smaller OFF transient RGC type that co-stratifies with OFF Alpha cells. However, AII amacrine cells avoid making synapses with numerous RGC types that co-stratify with the connected RGCs. Selective AII connections ensure that a privileged minority of RGC types receives direct input from the night-vision pathway, independent from OFF bipolar cell activity. Furthermore, these results illustrate the specificity of retinal connections, which cannot be predicted solely by co-stratification of dendrites and axons within the inner plexiform layer.

Response dynamics of rat barrel cortex neurons to repeated sensory stimulation

Neuronal adaptation is a common feature observed at various stages of sensory processing. Here, we quantified the time course of adaptation in rat somatosensory cortex. Under urethane anesthesia, we juxta-cellularly recorded single neurons (n = 147) while applying a series of whisker deflections at various frequencies (2-32 Hz). For ~90% of neurons, the response per unit of time decreased with frequency. The degree of adaptation increased along the train of deflections and was strongest at the highest frequency. However, a subset of neurons showed facilitation producing higher responses to subsequent deflections. The response latency to consecutive deflections increased both for neurons that exhibited adaptation and for those that exhibited response facilitation. Histological reconstruction of neurons (n = 45) did not reveal a systematic relationship between adaptation profiles and cell types. In addition to the periodic stimuli, we applied a temporally irregular train of deflections with a mean frequency of 8 Hz. For 70% of neurons, the response to the irregular stimulus was greater than that of the 8 Hz regular. This increased response to irregular stimulation was positively correlated with the degree of adaptation. Altogether, our findings demonstrate high levels of diversity among cortical neurons, with a proportion of neurons showing facilitation at specific temporal intervals.

Olfactory receptor neurons use gain control and complementary kinetics to encode intermittent odorant stimuli

Insects find food and mates by navigating odorant plumes that can be highly intermittent, with intensities and durations that vary rapidly over orders of magnitude. Much is known about olfactory responses to pulses and steps, but it remains unclear how olfactory receptor neurons (ORNs) detect the intensity and timing of natural stimuli, where the absence of scale in the signal makes detection a formidable olfactory task. By stimulating Drosophila ORNs in vivo with naturalistic and Gaussian stimuli, we show that ORNs adapt to stimulus mean and variance, and that adaptation and saturation contribute to naturalistic sensing. Mean-dependent gain control followed the Weber-Fechner relation and occurred primarily at odor transduction, while variance-dependent gain control occurred at both transduction and spiking. Transduction and spike generation possessed complementary kinetic properties, that together preserved the timing of odorant encounters in ORN spiking, regardless of intensity. Such scale-invariance could be critical during odor plume navigation.

A novel mechanism of cone photoreceptor adaptation

An animal’s ability to survive depends on its sensory systems being able to adapt to a wide range of environmental conditions, by maximizing the information extracted and reducing the noise transmitted. The visual system does this by adapting to luminance and contrast. While luminance adaptation can begin at the retinal photoreceptors, contrast adaptation has been shown to start at later stages in the retina. Photoreceptors adapt to changes in luminance over multiple time scales ranging from tens of milliseconds to minutes, with the adaptive changes arising from processes within the phototransduction cascade. Here we show a new form of adaptation in cones that is independent of the phototransduction process. Rather, it is mediated by voltage-gated ion channels in the cone membrane and acts by changing the frequency response of cones such that their responses speed up as the membrane potential modulation depth increases and slow down as the membrane potential modulation depth decreases. This mechanism is effectively activated by high-contrast stimuli dominated by low frequencies such as natural stimuli. However, the more generally used Gaussian white noise stimuli were not effective since they did not modulate the cone membrane potential to the same extent. This new adaptive process had a time constant of less than a second. A critical component of the underlying mechanism is the hyperpolarization-activated current, I_h, as pharmacologically blocking it prevented the long- and mid- wavelength sensitive cone photoreceptors (L- and M-cones) from adapting. Consistent with this, short- wavelength sensitive cone photoreceptors (S-cones) did not show the adaptive response, and we found they also lacked a prominent I_h. The adaptive filtering mechanism identified here improves the information flow by removing higher-frequency noise during lower signal-to-noise ratio conditions, as occurs when contrast levels are low. Although this new adaptive mechanism can be driven by contrast, it is not a contrast adaptation mechanism in its strictest sense, as will be argued in the Discussion.

An animal’s ability to survive depends on its ability to adapt to a wide range of light conditions, by maximizing the information flow through the retina. Here, we show a new form of adaptation in cone photoreceptors that helps them optimize the information they transmit by adjusting their response kinetics to better match the visual conditions. The adaptive mechanism we describe is independent of the cone phototransduction process and is instead mediated by membrane processes in which the hyperpolarization-activated current, I_h, plays a critical role. Consistent with the critical role of this current, we also found that cones sensitive to short wavelengths lacked a prominent I_h current and did not show this new form of adaptation. As voltage-dependent processes underlie the adaptational mechanism, it is only apparent when the stimuli are able to sufficiently modulate the membrane potential of cones. This happens with natural stimuli, which are able to deliver high levels of “effective” contrast. However, even though this new adaptive mechanism can be driven by contrast, we argue in the Discussion that in its strictest sense it is not a contrast adaptation mechanism per se.

Divisive suppression explains high-precision firing and contrast adaptation in retinal ganglion cells

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.

A Computational Framework for Realistic Retina Modeling

Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different visual processing pathways. While many of these models share common computational stages, previous efforts have been more focused on fitting specific retina functions rather than generalizing them beyond a particular model. Here, we define a set of computational retinal microcircuits that can be used as basic building blocks for the modeling of different retina mechanisms. To validate the hypothesis that similar processing structures may be repeatedly found in different retina functions, we implemented a series of retina models simply by combining these computational retinal microcircuits. Accuracy of the retina models for capturing neural behavior was assessed by fitting published electrophysiological recordings that characterize some of the best-known phenomena observed in the retina: adaptation to the mean light intensity and temporal contrast, and differential motion sensitivity. The retinal microcircuits are part of a new software platform for efficient computational retina modeling from single-cell to large-scale levels. It includes an interface with spiking neural networks that allows simulation of the spiking response of ganglion cells and integration with models of higher visual areas.

Inhibitory masking controls the threshold sensitivity of retinal ganglion cells

KEY POINTS

Retinal ganglion cells (RGCs) in dark-adapted retinas show a range of threshold sensitivities spanning ∼3 log units of illuminance. Here, we show that the different threshold sensitivities of RGCs reflect an inhibitory mechanism that masks inputs from certain rod pathways. The masking inhibition is subserved by GABA_C receptors, probably on bipolar cell axon terminals. The GABAergic masking inhibition appears independent of dopaminergic circuitry that has been shown also to affect RGC sensitivity. The results indicate a novel mechanism whereby inhibition controls the sensitivity of different cohorts of RGCs. This can limit and thereby ensure that appropriate signals are carried centrally in scotopic conditions when sensitivity rather than acuity is crucial.

ABSTRACT

The responses of rod photoreceptors, which subserve dim light vision, are carried through the retina by three independent pathways. These pathways carry signals with largely different sensitivities. Retinal ganglion cells (RGCs), the output neurons of the retina, show a wide range of sensitivities in the same dark-adapted conditions, suggesting a divergence of the rod pathways. However, this organization is not supported by the known synaptic morphology of the retina. Here, we tested an alternative idea that the rod pathways converge onto single RGCs, but inhibitory circuits selectively mask signals so that one pathway predominates. Indeed, we found that application of GABA receptor blockers increased the sensitivity of most RGCs by unmasking rod signals, which were suppressed. Our results indicate that inhibition controls the threshold responses of RGCs under dim ambient light. This mechanism can ensure that appropriate signals cross the bottleneck of the optic nerve in changing stimulus conditions.

Integrative properties of retinal ganglion cell electrical responsiveness depend on neurotrophic support and genotype in the mouse

Early stages of glaucoma and optic neuropathies are thought to show inner retina remodeling and functional changes of retinal ganglion cells (RGCs) before they die. To assess RGC functional plasticity, we investigated the contrast-gain control properties of the pattern electroretinogram (PERG), a sensitive measure of RGC function, as an index of spatio-temporal integration occurring in the inner retina circuitry subserving PERG generators. We studied the integrative properties of the PERG in mice exposed to different conditions of neurotrophic support. We also investigated the effect of genotypic differences among mouse strains with different susceptibility to glaucoma (C57BL/6J, DBA/2J, DBA/2.Gpnmb(+)). Results show that the integrative properties of the PERG recorded in the standard C57BL/6J inbred mouse strain are impaired after deficit of neurotrophic support and partially restored after exogenous neurotrophic administration. Changes in PERG amplitude, latency, and contrast-dependent responses differ between mouse strains with different susceptibility to glaucoma. Results represent a proof of concept that the PERG could be used as a tool for in-vivo monitoring of RGC functional plasticity before RGC death, the effect of neuroactive treatments, as well as for high-throughput tool for phenotypic screening of different mouse genotypes.

Circuit motifs for contrast-adaptive differentiation in early sensory systems: the role of presynaptic inhibition and short-term plasticity

In natural signals, such as the luminance value across of a visual scene, abrupt changes in intensity value are often more relevant to an organism than intensity values at other positions and times. Thus to reduce redundancy, sensory systems are specialized to detect the times and amplitudes of informative abrupt changes in the input stream rather than coding the intensity values at all times. In theory, a system that responds transiently to fast changes is called a differentiator. In principle, several different neural circuit mechanisms exist that are capable of responding transiently to abrupt input changes. However, it is unclear which circuit would be best suited for early sensory systems, where the dynamic range of the natural input signals can be very wide. We here compare the properties of different simple neural circuit motifs for implementing signal differentiation. We found that a circuit motif based on presynaptic inhibition (PI) is unique in a sense that the vesicle resources in the presynaptic site can be stably maintained over a wide range of stimulus intensities, making PI a biophysically plausible mechanism to implement a differentiator with a very wide dynamical range. Moreover, by additionally considering short-term plasticity (STP), differentiation becomes contrast adaptive in the PI-circuit but not in other potential neural circuit motifs. Numerical simulations show that the behavior of the adaptive PI-circuit is consistent with experimental observations suggesting that adaptive presynaptic inhibition might be a good candidate neural mechanism to achieve differentiation in early sensory systems.

The neural circuit mechanisms underlying the retinal response to motion reversal

To make up for delays in visual processing, retinal circuitry effectively predicts that a moving object will continue moving in a straight line, allowing retinal ganglion cells to anticipate the object's position. However, a sudden reversal of motion triggers a synchronous burst of firing from a large group of ganglion cells, possibly signaling a violation of the retina's motion prediction. To investigate the neural circuitry underlying this response, we used a combination of multielectrode array and whole-cell patch recordings to measure the responses of individual retinal ganglion cells in the tiger salamander to reversing stimuli. We found that different populations of ganglion cells were responsible for responding to the reversal of different kinds of objects, such as bright versus dark objects. Using pharmacology and designed stimuli, we concluded that ON and OFF bipolar cells both contributed to the reversal response, but that amacrine cells had, at best, a minor role. This allowed us to formulate an adaptive cascade model (ACM), similar to the one previously used to describe ganglion cell responses to motion onset. By incorporating the ON pathway into the ACM, we were able to reproduce the time-varying firing rate of fast OFF ganglion cells for all experimentally tested stimuli. Analysis of the ACM demonstrates that bipolar cell gain control is primarily responsible for generating the synchronized retinal response, as individual bipolar cells require a constant time delay before recovering from gain control.

Adeno-associated virus-RNAi of GlyRα1 and characterization of its synapse-specific inhibition in OFF alpha transient retinal ganglion cells

In the central nervous system, inhibition shapes neuronal excitation. In spinal cord glycinergic inhibition predominates, whereas GABAergic inhibition predominates in the brain. The retina uses GABA and glycine in approximately equal proportions. Glycinergic crossover inhibition, initiated in the On retinal pathway, controls glutamate release from presynaptic OFF cone bipolar cells (CBCs) and directly shapes temporal response properties of OFF retinal ganglion cells (RGCs). In the retina, four glycine receptor (GlyR) α-subunit isoforms are expressed in different sublaminae and their synaptic currents differ in decay kinetics. GlyRα1, expressed in both On and Off sublaminae of the inner plexiform layer, could be the glycinergic isoform that mediates On-to-Off crossover inhibition. However, subunit-selective glycine contributions remain unknown because we lack selective antagonists or cell class-specific subunit knockouts. To examine the role of GlyRα1 in direct inhibition in mature RGCs, we used retrogradely transported adeno-associated virus (AAV) that performed RNAi and eliminated almost all glycinergic spontaneous and visually evoked responses in PV5 (OFFα(Transient)) RGCs. Comparisons of responses in PV5 RGCs infected with AAV-scrambled-short hairpin RNA (shRNA) or AAV-Glra1-shRNA confirm a role for GlyRα1 in crossover inhibition in cone-driven circuits. Our results also define a role for direct GlyRα1 inhibition in setting the resting membrane potential of PV5 RGCs. The absence of GlyRα1 input unmasked a serial and a direct feedforward GABA(A)ergic modulation in PV5 RGCs, reflecting a complex interaction between glycinergic and GABA(A)ergic inhibition.

Kainate receptors mediate signaling in both transient and sustained OFF bipolar cell pathways in mouse retina

A fundamental question in sensory neuroscience is how parallel processing is implemented at the level of molecular and circuit mechanisms. In the retina, it has been proposed that distinct OFF cone bipolar cell types generate fast/transient and slow/sustained pathways by the differential expression of AMPA- and kainate-type glutamate receptors, respectively. However, the functional significance of these receptors in the intact circuit during light stimulation remains unclear. Here, we measured glutamate release from mouse bipolar cells by two-photon imaging of a glutamate sensor (iGluSnFR) expressed on postsynaptic amacrine and ganglion cell dendrites. In both transient and sustained OFF layers, cone-driven glutamate release from bipolar cells was blocked by antagonists to kainate receptors but not AMPA receptors. Electrophysiological recordings from bipolar and ganglion cells confirmed the essential role of kainate receptors for signaling in both transient and sustained OFF pathways. Kainate receptors mediated responses to contrast modulation up to 20 Hz. Light-evoked responses in all mouse OFF bipolar pathways depend on kainate, not AMPA, receptors.

Adaptation to background light enables contrast coding at rod bipolar cell synapses

Rod photoreceptors contribute to vision over an ∼ 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.

Synaptic noise is an information bottleneck in the inner retina during dynamic visual stimulation

In daylight, noise generated by cones determines the fidelity with which visual signals are initially encoded. Subsequent stages of visual processing require synapses from bipolar cells to ganglion cells, but whether these synapses generate a significant amount of noise was unknown. To characterize noise generated by these synapses, we recorded excitatory postsynaptic currents from mammalian retinal ganglion cells and subjected them to a computational noise analysis. The release of transmitter quanta at bipolar cell synapses contributed substantially to the noise variance found in the ganglion cell, causing a significant loss of fidelity from bipolar cell array to postsynaptic ganglion cell. Virtually all the remaining noise variance originated in the presynaptic circuit. Circuit noise had a frequency content similar to noise shared by ganglion cells but a very different frequency content from noise from bipolar cell synapses, indicating that these synapses constitute a source of independent noise not shared by ganglion cells. These findings contribute a picture of daylight retinal circuits where noise from cones and noise generated by synaptic transmission of cone signals significantly limit visual fidelity.

Adaptive colour contrast coding in the salamander retina efficiently matches natural scene statistics

The visual system continually adjusts its sensitivity to the statistical properties of the environment through an adaptation process that starts in the retina. Colour perception and processing is commonly thought to occur mainly in high visual areas, and indeed most evidence for chromatic colour contrast adaptation comes from cortical studies. We show that colour contrast adaptation starts in the retina where ganglion cells adjust their responses to the spectral properties of the environment. We demonstrate that the ganglion cells match their responses to red-blue stimulus combinations according to the relative contrast of each of the input channels by rotating their functional response properties in colour space. Using measurements of the chromatic statistics of natural environments, we show that the retina balances inputs from the two (red and blue) stimulated colour channels, as would be expected from theoretical optimal behaviour. Our results suggest that colour is encoded in the retina based on the efficient processing of spectral information that matches spectral combinations in natural scenes on the colour processing level.

Visual adaptation--a reinterpretation: discussion

This discussion paper seeks to reshape the contemporary understanding of visual adaptation. Received wisdom says that input luminance is scaled down in the retina. There is, first, a near-logarithmic compression described by the Naka-Rushton equation and, second, a control of gain (better attenuation) by feedback from the output of each ganglion cell that is equivalent to modifying the half-saturation constant in the Naka-Rushton equation. The reinterpretation proposed here asserts the following instead: (a) the scaling down in the retina is accomplished by receptive fields of different areas, which function over different ranges of luminance, ranges inversely proportional to the area of the receptive field. (b) The visual pathway is differentially coupled to the physical stimulus, so that the maintained discharge increases only as the square root of the luminance. (c) The Naka-Rushton equation describes merely the saturation of neural response as input increases; when a neuron is overloaded, output tends to regularity and onward transmission is blocked by a subsequent stage of differential coupling. Three existing studies of the relation between input to and output from retinal ganglion cells are reinterpreted in the light of this alternative view of visual adaptation.

Light adaptation alters the source of inhibition to the mouse retinal OFF pathway

Sensory systems must avoid saturation to encode a wide range of stimulus intensities. One way the retina accomplishes this is by using both dim-light-sensing rod and bright-light-sensing cone photoreceptor circuits. OFF cone bipolar cells are a key point in this process, as they receive both excitatory input from cones and inhibitory input from AII amacrine cells via the rod pathway. However, in addition to AII amacrine cell input, other inhibitory inputs from cone pathways also modulate OFF cone bipolar cell light signals. It is unknown how these inhibitory inputs to OFF cone bipolar cells change when switching between rod and cone pathways or whether all OFF cone bipolar cells receive rod pathway input. We found that one group of OFF cone bipolar cells (types 1, 2, and 4) receive rod-mediated inhibitory inputs that likely come from the rod-AII amacrine cell pathway, while another group of OFF cone bipolar cells (type 3) do not. In both cases, dark-adapted rod-dominant light responses showed a significant contribution of glycinergic inhibition, which decreased with light adaptation and was, surprisingly, compensated by an increase in GABAergic inhibition. As GABAergic input has distinct timing and spatial spread from glycinergic input, a shift from glycinergic to GABAergic inhibition could significantly alter OFF cone bipolar cell signaling to downstream OFF ganglion cells. Larger GABAergic input could reflect an adjustment of OFF bipolar cell spatial inhibition, which may be one mechanism that contributes to retinal spatial sensitivity in the light.

Excitatory and inhibitory contributions to receptive fields of alpha-like retinal ganglion cells in mouse

The ON and OFF pathways that emerge at the first synapse in the retina are generally thought to be streamed in parallel to higher visual areas, but recent work shows cross talk at the level of retinal ganglion cells. The ON pathway drives inhibitory inputs onto some OFF ganglion cells, such that these neurons show "push-pull" convergence of OFF-excitation and ON-disinhibition. In this study we measure the spatial receptive field of excitatory and inhibitory inputs to OFF-sustained (OFF-S) retinal ganglion cells of mouse, establish how contrast adaptation modulates excitatory and inhibitory synaptic inputs, and show the pharmacology of the inhibitory inputs. We find that the spatial tuning properties of excitatory and inhibitory inputs are sufficient to determine the spatial profile of the spike output and that high spatial acuity may be particularly reliant on disinhibitory circuits. Contrast adaptation reduced excitation to OFF-S ganglion cells, as expected, and also unmasked an asymmetry in inhibitory inputs: disinhibition at light-off was immune to contrast adaptation, but inhibition at light-on was substantially reduced. In pharmacological experiments we confirm that inhibitory inputs are partly mediated by glycine, but our measurements also suggest a substantial role for GABA. Our observations therefore reveal functional diversity in the inhibitory inputs to OFF ganglion cells and suggest that in addition to enhancing operational range these inputs help shape the spatial receptive fields of ganglion cells.

Local and global contrast adaptation in retinal ganglion cells

Retinal ganglion cells react to changes in visual contrast by adjusting their sensitivity and temporal filtering characteristics. This contrast adaptation has primarily been studied under spatially homogeneous stimulation. Yet, ganglion cell receptive fields are often characterized by spatial subfields, providing a substrate for nonlinear spatial processing. This raises the question whether contrast adaptation follows a similar subfield structure or whether it occurs globally over the receptive field even for local stimulation. We therefore recorded ganglion cell activity in isolated salamander retinas while locally changing visual contrast. Ganglion cells showed primarily global adaptation characteristics, with notable exceptions in certain aspects of temporal filtering. Surprisingly, some changes in filtering were most pronounced for locations where contrast did not change. This seemingly paradoxical effect can be explained by a simple computational model, which emphasizes the importance of local nonlinearities in the retina and suggests a reevaluation of previously reported local contrast adaptation.

A retinal source of spatial contrast gain control

Sensory cortex is able to encode a broad range of stimulus features despite a great variation in signal strength. In cat primary visual cortex (V1), for example, neurons are able to extract stimulus features like orientation or spatial configuration over a wide range of stimulus contrasts. The contrast-invariant spatial tuning found in V1 neuron responses has been modeled as a gain control mechanism, but at which stage of the visual pathway it emerges has remained unclear. Here we describe our findings that contrast-invariant spatial tuning occurs not only in the responses of lateral geniculate nucleus (LGN) relay cells but also in their afferent retinal input. Our evidence suggests that a similar contrast-invariant mechanism is found throughout the stages of the early visual pathway, and that the contrast-invariant spatial selectivity is evident in both retinal ganglion cell and LGN cell responses.

Intrinsic properties and functional circuitry of the AII amacrine cell

Amacrine cells represent the most diverse class of retinal neuron, comprising dozens of distinct cell types. Each type exhibits a unique morphology and generates specific visual computations through its synapses with a subset of excitatory interneurons (bipolar cells), other amacrine cells, and output neurons (ganglion cells). Here, we review the intrinsic and network properties that underlie the function of the most common amacrine cell in the mammalian retina, the AII amacrine cell. The AII connects rod and cone photoreceptor pathways, forming an essential link in the circuit for rod-mediated (scotopic) vision. As such, the AII has become known as the rod-amacrine cell. We, however, now understand that AII function extends to cone-mediated (photopic) vision, and AII function in scotopic and photopic conditions utilizes the same underlying circuit: AIIs are electrically coupled to each other and to the terminals of some types of ON cone bipolar cells. The direction of signal flow, however, varies with illumination. Under photopic conditions, the AII network constitutes a crossover inhibition pathway that allows ON signals to inhibit OFF ganglion cells and contributes to motion sensitivity in certain ganglion cell types. We discuss how the AII's combination of intrinsic and network properties accounts for its unique role in visual processing.

Linking the computational structure of variance adaptation to biophysical mechanisms

In multiple sensory systems, adaptation to the variance of a sensory input changes the sensitivity, kinetics, and average response over timescales ranging from < 100 ms to tens of seconds. Here, we present a simple, biophysically relevant model of retinal contrast adaptation that accurately captures both the membrane potential response and all adaptive properties. The adaptive component of this model is a first-order kinetic process of the type used to describe ion channel gating and synaptic transmission. From the model, we conclude that all adaptive dynamics can be accounted for by depletion of a signaling mechanism, and that variance adaptation can be explained as adaptation to the mean of a rectified signal. The model parameters show strong similarity to known properties of bipolar cell synaptic vesicle pools. Diverse types of adaptive properties that implement theoretical principles of efficient coding can be generated by a single type of molecule or synapse with just a few microscopic states.

A synaptic mechanism for retinal adaptation to luminance and contrast

The gain of signaling in primary sensory circuits is matched to the stimulus intensity by the process of adaptation. Retinal neural circuits adapt to visual scene statistics, including the mean (background adaptation) and the temporal variance (contrast adaptation) of the light stimulus. The intrinsic properties of retinal bipolar cells and synapses contribute to background and contrast adaptation, but it is unclear whether both forms of adaptation depend on the same cellular mechanisms. Studies of bipolar cell synapses identified synaptic mechanisms of gain control, but the relevance of these mechanisms to visual processing is uncertain because of the historical focus on fast, phasic transmission rather than the tonic transmission evoked by ambient light. Here, we studied use-dependent regulation of bipolar cell synaptic transmission evoked by small, ongoing modulations of membrane potential (V(M)) in the physiological range. We made paired whole-cell recordings from rod bipolar (RB) and AII amacrine cells in a mouse retinal slice preparation. Quasi-white noise voltage commands modulated RB V(M) and evoked EPSCs in the AII. We mimicked changes in background luminance or contrast, respectively, by depolarizing the V(M) or increasing its variance. A linear systems analysis of synaptic transmission showed that increasing either the mean or the variance of the presynaptic V(M) reduced gain. Further electrophysiological and computational analyses demonstrated that adaptation to mean potential resulted from both Ca channel inactivation and vesicle depletion, whereas adaptation to variance resulted from vesicle depletion alone. Thus, background and contrast adaptation apparently depend in part on a common synaptic mechanism.

Delayed-rectifier K channels contribute to contrast adaptation in mammalian retinal ganglion cells

Retinal ganglion cells adapt by reducing their sensitivity during periods of high contrast. Contrast adaptation in the firing response depends on both presynaptic and intrinsic mechanisms. Here, we investigated intrinsic mechanisms for contrast adaptation in OFF Alpha ganglion cells in the in vitro guinea pig retina. Using either visual stimulation or current injection, we show that brief depolarization evoked spiking and suppressed firing during subsequent depolarization. The suppression could be explained by Na channel inactivation, as shown in salamander cells. However, brief hyperpolarization in the physiological range (5-10 mV) also suppressed firing during subsequent depolarization. This suppression was selectively sensitive to blockers of delayed-rectifier K channels (K(DR)). In somatic membrane patches, we observed tetraethylammonium-sensitive K(DR) currents that activated near -25 mV. Recovery from inactivation occurred at potentials hyperpolarized to V(rest). Brief periods of hyperpolarization apparently remove K(DR) inactivation and thereby increase the channel pool available to suppress excitability during subsequent depolarization.

The retinal hypercircuit: a repeating synaptic interactive motif underlying visual function

Abstract

The vertebrate retina generates a stack of about a dozen different movies that represent the visual world as dynamic neural images or movies. The stack is embodied as separate strata that span the inner plexiform layer (IPL). At each stratum, ganglion cell dendrites reach up to read out inhibitory interactions between three different amacrine cell classes that shape bipolar-to-ganglion cell transmission. The nexus of these five cell classes represents a functional module, a retinal ‘hypercircuit’, that is repeated across the surface of each of the dozen strata that span the depth of the IPL. Individual differences in the characteristics of each cell class at each stratum lead to the unique processing characteristics of each neural image throughout the stack. This review shows how the interactions between the morphological and physiological characteristics of each cell class generate many of the known retinal visual functions including motion detection, directional selectivity, local edge detection, looming detection, object motion and looming detection.

Illuminating synapses and circuitry in the retina

In the central nervous system, space is at a premium. This is especially true in the retina, where synapses, cells, and circuitry have evolved to maximize signal-processing capacity within a thin, optically transparent tissue. For example, at some retinal synapses, single presynaptic active zones contact multiple postsynaptic targets; some individual neurons perform completely different tasks depending on visual conditions, while others execute hundreds of circuit computations in parallel; and the retinal network adapts, at various levels, to the ever-changing visual world. Each of these features reflects efficient use of limited cellular resources to optimally encode visual information.

Exploring the retinal connectome

PURPOSE

A connectome is a comprehensive description of synaptic connectivity for a neural domain. Our goal was to produce a connectome data set for the inner plexiform layer of the mammalian retina. This paper describes our first retinal connectome, validates the method, and provides key initial findings.

METHODS

We acquired and assembled a 16.5 terabyte connectome data set RC1 for the rabbit retina at ≈ 2 nm resolution using automated transmission electron microscope imaging, automated mosaicking, and automated volume registration. RC1 represents a column of tissue 0.25 mm in diameter, spanning the inner nuclear, inner plexiform, and ganglion cell layers. To enhance ultrastructural tracing, we included molecular markers for 4-aminobutyrate (GABA), glutamate, glycine, taurine, glutamine, and the in vivo activity marker, 1-amino-4-guanidobutane. This enabled us to distinguish GABAergic and glycinergic amacrine cells; to identify ON bipolar cells coupled to glycinergic cells; and to discriminate different kinds of bipolar, amacrine, and ganglion cells based on their molecular signatures and activity. The data set was explored and annotated with Viking, our multiuser navigation tool. Annotations were exported to additional applications to render cells, visualize network graphs, and query the database.

RESULTS

Exploration of RC1 showed that the 2 nm resolution readily recapitulated well known connections and revealed several new features of retinal organization: (1) The well known AII amacrine cell pathway displayed more complexity than previously reported, with no less than 17 distinct signaling modes, including ribbon synapse inputs from OFF bipolar cells, wide-field ON cone bipolar cells and rod bipolar cells, and extensive input from cone-pathway amacrine cells. (2) The axons of most cone bipolar cells formed a distinct signal integration compartment, with ON cone bipolar cell axonal synapses targeting diverse cell types. Both ON and OFF bipolar cells receive axonal veto synapses. (3) Chains of conventional synapses were very common, with intercalated glycinergic-GABAergic chains and very long chains associated with starburst amacrine cells. Glycinergic amacrine cells clearly play a major role in ON-OFF crossover inhibition. (4) Molecular and excitation mapping clearly segregates ultrastructurally defined bipolar cell groups into different response clusters. (5) Finally, low-resolution electron or optical imaging cannot reliably map synaptic connections by process geometry, as adjacency without synaptic contact is abundant in the retina. Only direct visualization of synapses and gap junctions suffices.

CONCLUSIONS

Connectome assembly and analysis using conventional transmission electron microscopy is now practical for network discovery. Our surveys of volume RC1 demonstrate that previously studied systems such as the AII amacrine cell network involve more network motifs than previously known. The AII network, primarily considered a scotopic pathway, clearly derives ribbon synapse input from photopic ON and OFF cone bipolar cell networks and extensive photopic GABAergic amacrine cell inputs. Further, bipolar cells show extensive inputs and outputs along their axons, similar to multistratified nonmammalian bipolar cells. Physiologic evidence of significant ON-OFF channel crossover is strongly supported by our anatomic data, showing alternating glycine-to-GABA paths. Long chains of amacrine cell networks likely arise from homocellular GABAergic synapses between starburst amacrine cells. Deeper analysis of RC1 offers the opportunity for more complete descriptions of specific networks.

NMDA receptor contributions to visual contrast coding

In the retina, it is not well understood how visual processing depends on AMPA- and NMDA-type glutamate receptors. Here we investigated how these receptors contribute to contrast coding in identified guinea pig ganglion cell types in vitro. NMDA-mediated responses were negligible in ON alpha cells but substantial in OFF alpha and delta cells. OFF delta cell NMDA receptors were composed of GluN2B subunits. Using a novel deconvolution method, we determined the individual contributions of AMPA, NMDA, and inhibitory currents to light responses of each cell type. OFF alpha and delta cells used NMDA receptors for encoding either the full contrast range (alpha), including near-threshold responses, or only a high range (delta). However, contrast sensitivity depended substantially on NMDA receptors only in OFF alpha cells. NMDA receptors contribute to visual contrast coding in a cell-type-specific manner. Certain cell types generate excitatory responses using primarily AMPA receptors or disinhibition.

The challenges natural images pose for visual adaptation

Advances in our understanding of natural image statistics and of gain control within the retinal circuitry are leading to new insights into the classic problem of retinal light adaptation. Here we review what we know about how rapid adaptation occurs during active exploration of the visual scene. Adaptational mechanisms must balance the competing demands of adapting quickly, locally, and reliably, and this balance must be maintained as lighting conditions change. Multiple adaptational mechanisms in different locations within the retina act in concert to accomplish this task, with lighting conditions dictating which mechanisms dominate.

Timescales of inference in visual adaptation

Adaptation is a hallmark of sensory function. Adapting optimally requires matching the dynamics of adaptation to those of changes in the stimulus distribution. Here we show that the dynamics of adaptation in the responses of mouse retinal ganglion cells depend on stimulus history. We hypothesized that the accumulation of evidence for a change in the stimulus distribution controls the dynamics of adaptation, and developed a model for adaptation as an ongoing inference problem. Guided by predictions of this model, we found that the dynamics of adaptation depend on the discriminability of the change in stimulus distribution and that the retina exploits information contained in properties of the stimulus beyond the mean and variance to adapt more quickly when possible.