Regulation of spatial selectivity by crossover inhibition

Dynamic Nonlinear Spatial Integrations on Encoding Contrasting Stimuli of Tectal Neurons

Animals detect targets using a variety of visual cues, with the visual salience of these cues determining which environmental features receive priority attention and further processing. Surround modulation plays a crucial role in generating visual saliency, which has been extensively studied in avian tectal neurons. Recent work has reported that the suppression of tectal neurons induced by motion contrasting stimulus is stronger than that by luminance contrasting stimulus. However, the underlying mechanism remains poorly understood. In this study, we built a computational model (called Generalized Linear-Dynamic Modulation) which incorporates independent nonlinear tuning mechanisms for excitatory and inhibitory inputs. This model aims to describe how tectal neurons encode contrasting stimuli. The results showed that: (1) The dynamic nonlinear integration structure substantially improved the accuracy (significant difference (p < 0.001, paired t-test) in the goodness of fit between the two models) of the predicted responses to contrasting stimuli, verifying the nonlinear processing performed by tectal neurons. (2) The modulation difference between luminance and motion contrasting stimuli emerged from the predicted response by the full model but not by that with only excitatory synaptic input (spatial luminance: 89 ± 2.8% (GL_DM) vs. 87 ± 2.1% (GL_DMexc); motion contrasting stimuli: 87 ± 1.7% (GL_DM) vs. 83 ± 2.2% (GL_DMexc)). These results validate the proposed model and further suggest the role of dynamic nonlinear spatial integrations in contextual visual information processing, especially in spatial integration, which is important for object detection performed by birds.

Diversity of Ganglion Cell Responses to Saccade-Like Image Shifts in the Primate Retina

Saccades are a fundamental part of natural vision. They interrupt fixations of the visual gaze and rapidly shift the image that falls onto the retina. These stimulus dynamics can cause activation or suppression of different retinal ganglion cells, but how they affect the encoding of visual information in different types of ganglion cells is largely unknown. Here, we recorded spiking responses to saccade-like shifts of luminance gratings from ganglion cells in isolated marmoset retinas and investigated how the activity depended on the combination of presaccadic and postsaccadic images. All identified cell types, On and Off parasol and midget cells, as well as a type of Large Off cells, displayed distinct response patterns, including particular sensitivity to either the presaccadic or the postsaccadic image or combinations thereof. In addition, Off parasol and Large Off cells, but not On cells, showed pronounced sensitivity to whether the image changed across the transition. Stimulus sensitivity of On cells could be explained based on their responses to step changes in light intensity, whereas Off cells, in particular, parasol and the Large Off cells, seem to be affected by additional interactions that are not triggered during simple light-intensity flashes. Together, our data show that ganglion cells in the primate retina are sensitive to different combinations of presaccadic and postsaccadic visual stimuli. This contributes to the functional diversity of the output signals of the retina and to asymmetries between On and Off pathways and provides evidence of signal processing beyond what is triggered by isolated steps in light intensity.SIGNIFICANCE STATEMENT Sudden eye movements (saccades) shift our direction of gaze, bringing new images in focus on our retinas. To study how retinal neurons deal with these rapid image transitions, we recorded spiking activity from ganglion cells, the output neurons of the retina, in isolated retinas of marmoset monkeys while shifting a projected image in a saccade-like fashion across the retina. We found that the cells do not just respond to the newly fixated image, but that different types of ganglion cells display different sensitivities to the presaccadic and postsaccadic stimulus patterns. Certain Off cells, for example, are sensitive to changes in the image across transitions, which contributes to differences between On and Off information channels and extends the range of encoded stimulus features.

Adaptation in cone photoreceptors contributes to an unexpected insensitivity of primate On parasol retinal ganglion cells to spatial structure in natural images

Neural circuits are constructed from nonlinear building blocks, and not surprisingly overall circuit behavior is often strongly nonlinear. But neural circuits can also behave near linearly, and some circuits shift from linear to nonlinear behavior depending on stimulus conditions. Such control of nonlinear circuit behavior is fundamental to neural computation. Here, we study a surprising stimulus dependence of the responses of macaque On (but not Off) parasol retinal ganglion cells: these cells respond nonlinearly to spatial structure in some stimuli but near linearly to spatial structure in others, including natural inputs. We show that these differences in the linearity of the integration of spatial inputs can be explained by a shift in the balance of excitatory and inhibitory synaptic inputs that originates at least partially from adaptation in the cone photoreceptors. More generally, this highlights how subtle asymmetries in signaling - here in the cone signals - can qualitatively alter circuit computation.

A novel theoretical framework for simultaneous measurement of excitatory and inhibitory conductances

The firing of neurons throughout the brain is determined by the precise relations between excitatory and inhibitory inputs, and disruption of their balance underlies many psychiatric diseases. Whether or not these inputs covary over time or between repeated stimuli remains unclear due to the lack of experimental methods for measuring both inputs simultaneously. We developed a new analytical framework for instantaneous and simultaneous measurements of both the excitatory and inhibitory neuronal inputs during a single trial under current clamp recording. This can be achieved by injecting a current composed of two high frequency sinusoidal components followed by analytical extraction of the conductances. We demonstrate the ability of this method to measure both inputs in a single trial under realistic recording constraints and from morphologically realistic CA1 pyramidal model cells. Future experimental implementation of our new method will facilitate the understanding of fundamental questions about the health and disease of the nervous system.

Most neurons in the brain receive synaptic inputs from both excitatory and inhibitory neurons. Together, these inputs determine neuronal activity: excitatory synapses shift the electrical potential across the membrane towards the threshold for generation of action potentials, whereas inhibitory synapses lower this potential away from the threshold. Action potentials are the rapid electrochemical signals that transmit information to other neurons and they are critical for the information processing abilities of the brain.

Although there are many ways to measure either excitatory or inhibitory inputs, these methods have been unable to measure both at the same time. Measuring both inputs together is essential towards understanding how neurons integrate information. We developed a new analytical method to measure excitatory and inhibitory inputs at the same time from the voltage response to injection of an alternating current into a neuron. We describe the foundation of this new method and find that it works in biologically realistic simulations of neurons. By using this technique in real neurons, scientists could investigate basic principles of information processing in the healthy and diseased brain.

Functional architecture of neural circuits for leg proprioception in Drosophila

To effectively control their bodies, animals rely on feedback from proprioceptive mechanosensory neurons. In the Drosophila leg, different proprioceptor subtypes monitor joint position, movement direction, and vibration. Here, we investigate how these diverse sensory signals are integrated by central proprioceptive circuits. We find that signals for leg joint position and directional movement converge in second-order neurons, revealing pathways for local feedback control of leg posture. Distinct populations of second-order neurons integrate tibia vibration signals across pairs of legs, suggesting a role in detecting external substrate vibration. In each pathway, the flow of sensory information is dynamically gated and sculpted by inhibition. Overall, our results reveal parallel pathways for processing of internal and external mechanosensory signals, which we propose mediate feedback control of leg movement and vibration sensing, respectively. The existence of a functional connectivity map also provides a resource for interpreting connectomic reconstruction of neural circuits for leg proprioception.

To understand how diverse proprioceptive signals from the Drosophila leg are integrated by downstream circuits, Chen et al. use optogenetics and calcium imaging to map functional connectivity between sensory and central neurons. This work identifies parallel neural pathways for processing leg vibration vs. joint position and movement.

Predictive encoding of motion begins in the primate retina

Predictive motion encoding is an important aspect of visually guided behavior that allows animals to estimate the trajectory of moving objects. Motion prediction is understood primarily in the context of translational motion, but the environment contains other types of behaviorally salient motion correlation such as those produced by approaching or receding objects. However, the neural mechanisms that detect and predictively encode these correlations remain unclear. We report here that four of the parallel output pathways in the primate retina encode predictive motion information, and this encoding occurs for several classes of spatiotemporal correlation that are found in natural vision. Such predictive coding can be explained by known nonlinear circuit mechanisms that produce a nearly optimal encoding, with transmitted information approaching the theoretical limit imposed by the stimulus itself. Thus, these neural circuit mechanisms efficiently separate predictive information from nonpredictive information during the encoding process.

Retinal ganglion cells and the magnocellular, parvocellular, and koniocellular subcortical visual pathways from the eye to the brain

In primates including humans, most retinal ganglion cells send signals to the lateral geniculate nucleus (LGN) of the thalamus. The anatomical and functional properties of the two major pathways through the LGN, the parvocellular (P) and magnocellular (M) pathways, are now well understood. Neurones in these pathways appear to convey a filtered version of the retinal image to primary visual cortex for further analysis. The properties of the P-pathway suggest it is important for high spatial acuity and red-green color vision, while those of the M-pathway suggest it is important for achromatic visual sensitivity and motion vision. Recent work has sharpened our understanding of how these properties are built in the retina, and described subtle but important nonlinearities that shape the signals that cortex receives. In addition to the P- and M-pathways, other retinal ganglion cells also project to the LGN. These ganglion cells are larger than those in the P- and M-pathways, have different retinal connectivity, and project to distinct regions of the LGN, together forming heterogenous koniocellular (K) pathways. Recent work has started to reveal the properties of these K-pathways, in the retina and in the LGN. The functional properties of K-pathways are more complex than those in the P- and M-pathways, and the K-pathways are likely to have a distinct contribution to vision. They provide a complementary pathway to the primary visual cortex, but can also send signals directly to extrastriate visual cortex. At the level of the LGN, many neurones in the K-pathways seem to integrate retinal with non-retinal inputs, and some may provide an early site of binocular convergence.

Wide-field amacrine cell inputs to ON parasol ganglion cells in macaque retina

Parasol cells are one of the major types of primate retinal ganglion cells. The goal of this study was to describe the synaptic inputs that shape the light responses of the ON type of parasol cells, which are excited by increments in light intensity. A connectome from central macaque retina was generated by serial blockface scanning electron microscopy. Six neighboring ON parasol cells were reconstructed, and their synaptic inputs were analyzed. On average, they received 21% of their input from bipolar cells, excitatory local circuit neurons receiving input from cones. The majority of their input was from amacrine cells, local circuit neurons of the inner retina that are typically inhibitory. Their contributions to the neural circuit providing input to parasol cells are not well-understood, and the focus of this study was on the presynaptic wide-field amacrine cells, which provided 17% of the input to ON parasol cells. These are GABAergic amacrine cells with long, relatively straight dendrites, and sometimes also axons, that run in a single, narrow stratum of the inner plexiform layer. The presynaptic wide-field amacrine cells were reconstructed, and two types were identified based on their characteristic morphology. One presynaptic amacrine cell was identified as semilunar type 2, a polyaxonal cell that is electrically coupled to ON parasol cells. A second amacrine was identified as wiry type 2, a type known to be sensitive to motion. These inputs likely make ON parasol cells more sensitive to stimuli that are rapidly changing outside their classical receptive fields.

Efficient Coding by Midget and Parasol Ganglion Cells in the Human Retina

In humans, midget and parasol ganglion cells account for most of the input from the eyes to the brain. Yet, how they encode visual information is unknown. Here, we perform large-scale multi-electrode array recordings from retinas of treatment-naive patients who underwent enucleation surgery for choroidal malignant melanomas. We identify robust differences in the function of midget and parasol ganglion cells, consistent asymmetries between their ON and OFF types (that signal light increments and decrements, respectively) and divergence in the function of human versus non-human primate retinas. Our computational analyses reveal that the receptive fields of human midget and parasol ganglion cells divide naturalistic movies into adjacent spatiotemporal frequency domains with equal stimulus power, while the asymmetric response functions of their ON and OFF types simultaneously maximize stimulus coverage and information transmission and minimize metabolic cost. Thus, midget and parasol ganglion cells in the human retina efficiently encode our visual environment.

Selectivity to approaching motion in retinal inputs to the dorsal visual pathway

To efficiently navigate through the environment and avoid potential threats, an animal must quickly detect the motion of approaching objects. Current models of primate vision place the origins of this complex computation in the visual cortex. Here, we report that detection of approaching motion begins in the retina. Several ganglion cell types, the retinal output neurons, show selectivity to approaching motion. Synaptic current recordings from these cells further reveal that this preference for approaching motion arises in the interplay between presynaptic excitatory and inhibitory circuit elements. These findings demonstrate how excitatory and inhibitory circuits interact to mediate an ethologically relevant neural function. Moreover, the elementary computations that detect approaching motion begin early in the visual stream of primates.

Cell types and cell circuits in human and non-human primate retina

This review summarizes our current knowledge of primate including human retina focusing on bipolar, amacrine and ganglion cells and their connectivity. We have two main motivations in writing. Firstly, recent progress in non-invasive imaging methods to study retinal diseases mean that better understanding of the primate retina is becoming an important goal both for basic and for clinical sciences. Secondly, genetically modified mice are increasingly used as animal models for human retinal diseases. Thus, it is important to understand to which extent the retinas of primates and rodents are comparable. We first compare cell populations in primate and rodent retinas, with emphasis on how the fovea (despite its small size) dominates the neural landscape of primate retina. We next summarise what is known, and what is not known, about the postreceptoral neurone populations in primate retina. The inventories of bipolar and ganglion cells in primates are now nearing completion, comprising ~12 types of bipolar cell and at least 17 types of ganglion cell. Primate ganglion cells show clear differences in dendritic field size across the retina, and their morphology differs clearly from that of mouse retinal ganglion cells. Compared to bipolar and ganglion cells, amacrine cells show even higher morphological diversity: they could comprise over 40 types. Many amacrine types appear conserved between primates and mice, but functions of only a few types are understood in any primate or non-primate retina. Amacrine cells appear as the final frontier for retinal research in monkeys and mice alike.

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.

A Pixel-Encoder Retinal Ganglion Cell with Spatially Offset Excitatory and Inhibitory Receptive Fields

The spike trains of retinal ganglion cells (RGCs) are the only source of visual information to the brain. Here, we genetically identify an RGC type in mice that functions as a pixel encoder and increases firing to light increments (Pix_ON-RGC). Pix_ON-RGCs have medium-sized dendritic arbors and non-canonical center-surround receptive fields. From their receptive field center, Pix_ON-RGCs receive only excitatory input, which encodes contrast and spatial information linearly. From their receptive field surround, Pix_ON-RGCs receive only inhibitory input, which is temporally matched to the excitatory center input. As a result, the firing rate of Pix_ON-RGCs linearly encodes local image contrast. Spatially offset (i.e., truly lateral) inhibition of Pix_ON-RGCs arises from spiking GABAergic amacrine cells. The receptive field organization of Pix_ON-RGCs is independent of stimulus wavelength (i.e., achromatic). Pix_ON-RGCs project predominantly to the dorsal lateral geniculate nucleus (dLGN) of the thalamus and likely contribute to visual perception.

Receptive field center-surround interactions mediate context-dependent spatial contrast encoding in the retina

Antagonistic receptive field surrounds are a near-universal property of early sensory processing. A key assumption in many models for retinal ganglion cell encoding is that receptive field surrounds are added only to the fully formed center signal. But anatomical and functional observations indicate that surrounds are added before the summation of signals across receptive field subunits that creates the center. Here, we show that this receptive field architecture has an important consequence for spatial contrast encoding in the macaque monkey retina: the surround can control sensitivity to fine spatial structure by changing the way the center integrates visual information over space. The impact of the surround is particularly prominent when center and surround signals are correlated, as they are in natural stimuli. This effect of the surround differs substantially from classic center-surround models and raises the possibility that the surround plays unappreciated roles in shaping ganglion cell sensitivity to natural inputs.

Harmonics added to a flickering light can upset the balance between ON and OFF pathways to produce illusory colors

By varying the temporal waveforms of complex flickering stimuli, we can produce alterations in their mean color that can be predicted by a physiologically based model of visual processing. The model highlights the perceptual effects of a well-known feature of most visual pathways, namely the early separation of visual signals into increments and decrements. The role of this separation in improving the efficiency and sensitivity of the visual system has been discussed before, but its effect on perception has been neglected. The application of a model incorporating half-wave rectification offers an exciting psychophysical method for investigating the inner workings of the human visual system.

The neural signals generated by the light-sensitive photoreceptors in the human eye are substantially processed and recoded in the retina before being transmitted to the brain via the optic nerve. A key aspect of this recoding is the splitting of the signals within the two major cone-driven visual pathways into distinct ON and OFF branches that transmit information about increases and decreases in the neural signal around its mean level. While this separation is clearly important physiologically, its effect on perception is unclear. We have developed a model of the ON and OFF pathways in early color processing. Using this model as a guide, we can produce imbalances in the ON and OFF pathways by changing the shapes of time-varying stimulus waveforms and thus make reliable and predictable alterations to the perceived average color of the stimulus—although the physical mean of the waveforms does not change. The key components in the model are the early half-wave rectifying synapses that split retinal photoreceptor outputs into the ON and OFF pathways and later sigmoidal nonlinearities in each pathway. The ability to systematically vary the waveforms to change a perceptual quality by changing the balance of signals between the ON and OFF visual pathways provides a powerful psychophysical tool for disentangling and investigating the neural workings of human vision.

Neural Mechanisms Mediating Motion Sensitivity in Parasol Ganglion Cells of the Primate Retina

Considerable theoretical and experimental effort has been dedicated to understanding how neural circuits detect visual motion. In primates, much is known about the cortical circuits that contribute to motion processing, but the role of the retina in this fundamental neural computation is poorly understood. Here, we used a combination of extracellular and whole-cell recording to test for motion sensitivity in the two main classes of output neurons in the primate retina-midget (parvocellular-projecting) and parasol (magnocellular-projecting) ganglion cells. We report that parasol, but not midget, ganglion cells are motion sensitive. This motion sensitivity is present in synaptic excitation and disinhibition from presynaptic bipolar cells and amacrine cells, respectively. Moreover, electrical coupling between neighboring bipolar cells and the nonlinear nature of synaptic release contribute to the observed motion sensitivity. Our findings indicate that motion computations arise far earlier in the primate visual stream than previously thought.

General features of inhibition in the inner retina

Visual processing starts in the retina. Within only two synaptic layers, a large number of parallel information channels emerge, each encoding a highly processed feature like edges or the direction of motion. Much of this functional diversity arises in the inner plexiform layer, where inhibitory amacrine cells modulate the excitatory signal of bipolar and ganglion cells. Studies investigating individual amacrine cell circuits like the starburst or A17 circuit have demonstrated that single types can possess specific morphological and functional adaptations to convey a particular function in one or a small number of inner retinal circuits. However, the interconnected and often stereotypical network formed by different types of amacrine cells across the inner plexiform layer prompts that they should be also involved in more general computations. In line with this notion, different recent studies systematically analysing inner retinal signalling at a population level provide evidence that general functions of the ensemble of amacrine cells across types are critical for establishing universal principles of retinal computation like parallel processing or motion anticipation. Combining recent advances in the development of indicators for imaging inhibition with large-scale morphological and genetic classifications will help to further our understanding of how single amacrine cell circuits act together to help decompose the visual scene into parallel information channels. In this review, we aim to summarise the current state-of-the-art in our understanding of how general features of amacrine cell inhibition lead to general features of computation.

Corticogeniculate feedback sharpens the temporal precision and spatial resolution of visual signals in the ferret

The corticogeniculate (CG) pathway connects the visual cortex with the visual thalamus (LGN) in the feedback direction and enables the cortex to directly influence its own input. Despite numerous investigations, the role of this feedback circuit in visual perception remained elusive. To probe the function of CG feedback in a causal manner, we selectively and reversibly manipulated the activity of CG neurons in anesthetized ferrets in vivo using a combined viral-infection and optogenetics approach to drive expression of channelrhodopsin2 (ChR2) in CG neurons. We observed significant increases in temporal precision and spatial resolution of LGN neuronal responses to drifting grating and white noise stimuli when CG neurons expressing ChR2 were light activated. Enhancing CG feedback reduced visually evoked response latencies, increased spike-timing precision, and reduced classical receptive field size. Increased precision among LGN neurons led to increased spike-timing precision among granular layer V1 neurons as well. Together, our findings suggest that the function of CG feedback is to control the timing and precision of thalamic responses to incoming visual signals.

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.

A Mechanosensory Circuit that Mixes Opponent Channels to Produce Selectivity for Complex Stimulus Features

Johnston's organ is the largest mechanosensory organ in Drosophila; it analyzes movements of the antenna due to sound, wind, gravity, and touch. Different Johnston's organ neurons (JONs) encode distinct stimulus features. Certain JONs respond in a sustained manner to steady displacements, and these JONs subdivide into opponent populations that prefer push or pull displacements. Here, we describe neurons in the brain (aPN3 neurons) that combine excitation and inhibition from push/pull JONs in different ratios. Consequently, different aPN3 neurons are sensitive to movement in different parts of the antenna's range, at different frequencies, or at different amplitude modulation rates. We use a model to show how the tuning of aPN3 neurons can arise from rectification and temporal filtering in JONs, followed by mixing of JON signals in different proportions. These results illustrate how several canonical neural circuit components-rectification, opponency, and filtering-can combine to produce selectivity for complex stimulus features.

Synaptic Rectification Controls Nonlinear Spatial Integration of Natural Visual Inputs

A central goal in the study of any sensory system is to predict neural responses to complex inputs, especially those encountered during natural stimulation. Nowhere is the transformation from stimulus to response better understood than the vertebrate retina. Nevertheless, descriptions of retinal computation are largely based on stimulation using artificial visual stimuli, and it is unclear how these descriptions map onto the encoding of natural stimuli. We demonstrate that nonlinear spatial integration, a common feature of retinal ganglion cell (RGC) processing, shapes neural responses to natural visual stimuli in primate Off parasol RGCs, whereas On parasol RGCs exhibit surprisingly linear spatial integration. Despite this asymmetry, both cell types show strong nonlinear integration when presented with artificial stimuli. We show that nonlinear integration of natural stimuli is a consequence of rectified excitatory synaptic input and that accounting for nonlinear spatial integration substantially improves models that predict RGC responses to natural images.

Crossover Inhibition Generates Sustained Visual Responses in the Inner Retina

In daylight, the input to the retinal circuit is provided primarily by cone photoreceptors acting as band-pass filters, but the retinal output also contains neuronal populations transmitting sustained signals. Using in vivo imaging of genetically encoded calcium reporters, we investigated the circuits that generate these sustained channels within the inner retina of zebrafish. In OFF bipolar cells, sustained transmission was found to depend on crossover inhibition from the ON pathway through GABAergic amacrine cells. In ON bipolar cells, the amplitude of low-frequency signals was regulated by glycinergic amacrine cells, while GABAergic inhibition regulated the gain of band-pass signals. We also provide the first functional description of a subset of sustained ON bipolar cells in which synaptic activity was suppressed by fluctuations at frequencies above ∼0.2 Hz. These results map out the basic circuitry by which the inner retina generates sustained visual signals and describes a new function of crossover inhibition.

The impact of inhibitory mechanisms in the inner retina on spatial tuning of RGCs

Spatial tuning properties of retinal ganglion cells (RGCs) are sharpened by lateral inhibition originating at both the outer and inner plexiform layers. Lateral inhibition in the retina contributes to local contrast enhancement and sharpens edges. In this study, we used dynamic clamp recordings to examine the contribution of inner plexiform inhibition, originating from spiking amacrine cells, to the spatial tuning of RGCs. This was achieved by injecting currents generated from physiologically recorded excitatory and inhibitory stimulus-evoked conductances, into different types of primate and mouse RGCs. We determined the effects of injections of size-dependent conductances in which presynaptic inhibition and/or direct inhibition onto RGCs were partly removed by blocking the activity of spiking amacrine cells. We found that inhibition originating from spiking amacrine cells onto bipolar cell terminals and onto RGCs, work together to sharpen the spatial tuning of RGCs. Furthermore, direct inhibition is crucial for preventing spike generation at stimulus offset. These results reveal how inhibitory mechanisms in the inner plexiform layer contribute to determining size tuning and provide specificity to stimulus polarity.

Functional Circuitry of the Retina

The mammalian retina is an important model system for studying neural circuitry: Its role in sensation is clear, its cell types are relatively well defined, and its responses to natural stimuli-light patterns-can be studied in vitro. To solve the retina, we need to understand how the circuits presynaptic to its output neurons, ganglion cells, divide the visual scene into parallel representations to be assembled and interpreted by the brain. This requires identifying the component interneurons and understanding how their intrinsic properties and synapses generate circuit behaviors. Because the cellular composition and fundamental properties of the retina are shared across species, basic mechanisms studied in the genetically modifiable mouse retina apply to primate vision. We propose that the apparent complexity of retinal computation derives from a straightforward mechanism-a dynamic balance of synaptic excitation and inhibition regulated by use-dependent synaptic depression-applied differentially to the parallel pathways that feed ganglion cells.

Mapping nonlinear receptive field structure in primate retina at single cone resolution

The function of a neural circuit is shaped by the computations performed by its interneurons, which in many cases are not easily accessible to experimental investigation. Here, we elucidate the transformation of visual signals flowing from the input to the output of the primate retina, using a combination of large-scale multi-electrode recordings from an identified ganglion cell type, visual stimulation targeted at individual cone photoreceptors, and a hierarchical computational model. The results reveal nonlinear subunits in the circuity of OFF midget ganglion cells, which subserve high-resolution vision. The model explains light responses to a variety of stimuli more accurately than a linear model, including stimuli targeted to cones within and across subunits. The recovered model components are consistent with known anatomical organization of midget bipolar interneurons. These results reveal the spatial structure of linear and nonlinear encoding, at the resolution of single cells and at the scale of complete circuits.

DOI:http://dx.doi.org/10.7554/eLife.05241.001

Light that enters the eye begins the process of vision by activating two types of photoreceptors: rods, which support vision under low light levels, and cones, which are responsible for fine detail and color vision. Activation of either type of photoreceptor triggers responses in bipolar cells, which activate the ganglion cells that transmit visual signals to the brain.

Bipolar cells therefore belong to a class of cells called interneurons, which relay information from certain cell types to others. Interneurons play an important role in information processing throughout the brain, but directly accessing them or characterizing their role in neural computation is often difficult.

To address this problem, Freeman, Field et al. have developed a combined computational and experimental approach to describe the flow of sensory signals through the circuits within the retina of primates. Large arrays of electrodes were used to record the responses of many retinal ganglion cells in response to the activation or de-activation of pairs of cones. These experiments revealed that the responses of ganglion cells are not simply the sum of the inputs that they receive from cones; specifically, the activation of one cone is not cancelled by the deactivation of another. Instead, the data suggest that bipolar cells add cone inputs together and then pass on the total activation (but not deactivation) to ganglion cells.

By analyzing the responses of ganglion cells to numerous random patterns of cone activation, Freeman, Field et al. were able to estimate the locations and arrangements of bipolar cells that connect to them. These predicted patterns of connectivity agreed with observations from anatomical studies. This work provides detailed insights into how the primate retina works. It also suggests that similar approaches may be used to characterize how signals flow across other brain networks in which large-scale recordings are now possible.

DOI:http://dx.doi.org/10.7554/eLife.05241.002

General features of the retinal connectome determine the computation of motion anticipation

Motion anticipation allows the visual system to compensate for the slow speed of phototransduction so that a moving object can be accurately located. This correction is already present in the signal that ganglion cells send from the retina but the biophysical mechanisms underlying this computation are not known. Here we demonstrate that motion anticipation is computed autonomously within the dendritic tree of each ganglion cell and relies on feedforward inhibition. The passive and non-linear interaction of excitatory and inhibitory synapses enables the somatic voltage to encode the actual position of a moving object instead of its delayed representation. General rather than specific features of the retinal connectome govern this computation: an excess of inhibitory inputs over excitatory, with both being randomly distributed, allows tracking of all directions of motion, while the average distance between inputs determines the object velocities that can be compensated for.

DOI:http://dx.doi.org/10.7554/eLife.06250.001

The retina is a structure at the back of the eye that converts light into nerve impulses, which are then processed in the brain to produce the images that we see. It normally takes about one-tenth of a second for the retina to send a signal to the brain after an object first moves into view. This is about the same time it takes a tennis ball to travel several meters during a tennis match, yet we are still able to see where the moving tennis ball is in real time. This is because a process called ‘motion anticipation’ is able to compensate for the delay in processing the position of a moving object. However, it was not known precisely how motion anticipation occurs.

Inside the retina, cells called photoreceptors detect light and ultimately send signals (via some intermediate cell types) to nerve cells known as retinal ganglion cells. These signals can either excite a retinal ganglion cell to cause it to send an electrical signal to the brain, or inhibit it, which temporarily prevents electrical activity. Each cell receives signals from several photoreceptors, which each connect to a different site along branch-like structures called dendrites that project out of the retinal ganglion cells.

Johnston and Lagnado have now investigated how motion anticipation occurs in the retina by using electrical recordings of the activity in the retinas of goldfish combined with computer simulations of this activity. This revealed inhibitory signals, sent from photoreceptors to retinal ganglion cells via a type of intermediate cell (called amacrine cells), play a key role in motion anticipation. The ability to track motion effectively in all directions requires more inhibitory signals to be sent to the dendrites of a retinal ganglion cell than excitatory signals. These two types of input must also be randomly distributed across the cell. Furthermore, it is the density of these input sites on a dendrite that determines how well the retina can compensate for the motion of a fast-moving object. The building blocks required for motion anticipation in the retina are also found in visual areas higher in the brain. Therefore, further work may reveal that higher visual areas also use this mechanism to predict the future location of moving objects.

DOI:http://dx.doi.org/10.7554/eLife.06250.002

A synaptic signature for ON- and OFF-center parasol ganglion cells of the primate retina

In the primate retina, parasol ganglion cells contribute to the primary visual pathway via the magnocellular division of the lateral geniculate nucleus, display ON and OFF concentric receptive field structure, nonlinear spatial summation, and high achromatic temporal-contrast sensitivity. Parasol cells may be homologous to the alpha-Y cells of nonprimate mammals where evidence suggests that N-methyl-D-aspartate (NMDA) receptor-mediated synaptic excitation as well as glycinergic disinhibition play critical roles in contrast sensitivity, acting asymmetrically in OFF- but not ON-pathways. Here, light-evoked synaptic currents were recorded in the macaque monkey retina in vitro to examine the circuitry underlying parasol cell receptive field properties. Synaptic excitation in both ON and OFF types was mediated by NMDA as well as α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)/kainate glutamate receptors. The NMDA-mediated current-voltage relationship suggested high Mg2+ affinity such that at physiological potentials, NMDA receptors contributed ∼20% of the total excitatory conductance evoked by moderate stimulus contrasts and temporal frequencies. Postsynaptic inhibition in both ON and OFF cells was dominated by a large glycinergic "crossover" conductance, with a relatively small contribution from GABAergic feedforward inhibition. However, crossover inhibition was largely rectified, greatly diminished at low stimulus contrasts, and did not contribute, via disinhibition, to contrast sensitivity. In addition, attenuation of GABAergic and glycinergic synaptic inhibition left center-surround and Y-type receptive field structure and high temporal sensitivity fundamentally intact and clearly derived from modulation of excitatory bipolar cell output. Thus, the characteristic spatial and temporal-contrast sensitivity of the primate parasol cell arises presynaptically and is governed primarily by modulation of the large AMPA/kainate receptor-mediated excitatory conductance. Moreover, the negative feedback responsible for the receptive field surround must derive from a nonGABAergic mechanism.

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.

Nonlinear spatial integration in the receptive field surround of retinal ganglion cells

Throughout different sensory systems, individual neurons integrate incoming signals over their receptive fields. The characteristics of this signal integration are crucial determinants for the neurons' functions. For ganglion cells in the vertebrate retina, receptive fields are characterized by the well-known center-surround structure and, although several studies have addressed spatial integration in the receptive field center, little is known about how visual signals are integrated in the surround. Therefore, we set out here to characterize signal integration and to identify relevant nonlinearities in the receptive field surround of ganglion cells in the isolated salamander retina by recording spiking activity with extracellular electrodes under visual stimulation of the center and surround. To quantify nonlinearities of spatial integration independently of subsequent nonlinearities of spike generation, we applied the technique of iso-response measurements as follows: using closed-loop experiments, we searched for different stimulus patterns in the surround that all reduced the center-evoked spiking activity by the same amount. The identified iso-response stimuli revealed strongly nonlinear spatial integration in the receptive field surrounds of all recorded cells. Furthermore, cell types that had been shown previously to have different nonlinearities in receptive field centers showed similar surround nonlinearities but differed systematically in the adaptive characteristics of the surround. Finally, we found that there is an optimal spatial scale of surround suppression; suppression was most effective when surround stimulation was organized into subregions of several hundred micrometers in diameter, indicating that the surround is composed of subunits that have strong center-surround organization themselves.