Effects of remote stimulation on the mean firing rate of cat retinal ganglion cells

A quantitative description of macaque ganglion cell responses to natural scenes: the interplay of time and space

KEY POINTS

Responses to natural scenes are the business of the retina. We find primate ganglion cell responses to such scenes consistent with those to simpler stimuli. A biophysical model confirmed this and predicted ganglion cell responses with close to retinal reliability. Primate ganglion cell responses to natural scenes were driven by temporal variations in colour and luminance over the receptive field centre caused by eye movements, and little influenced by interaction of centre and surround with structure in the scene. We discuss implications in the context of efficient coding of the visual environment. Much information in a higher spatiotemporal frequency band is concentrated in the magnocellular pathway.

ABSTRACT

Responses of visual neurons to natural scenes provide a link between classical descriptions of receptive field structure and visual perception of the natural environment. A natural scene video with a movement pattern resembling that of primate eye movements was used to evoke responses from macaque ganglion cells. Cell responses were well described through known properties of cell receptive fields. Different analyses converge to show that responses primarily derive from the temporal pattern of stimulation derived from eye movements, rather than spatial receptive field structure beyond centre size and position. This was confirmed using a model that predicted ganglion cell responses close to retinal reliability, with only a small contribution of the surround relative to the centre. We also found that the spatiotemporal spectrum of the stimulus is modified in ganglion cell responses, and this can reduce redundancy in the retinal signal. This is more pronounced in the magnocellular pathway, which is much better suited to transmit the detailed structure of natural scenes than the parvocellular pathway. Whitening is less important for chromatic channels. Taken together, this shows how a complex interplay across space, time and spectral content sculpts ganglion cell responses.

Electrical Imaging of Light-Induced Signals Across and Within Retinal Layers

The mammalian retina processes sensory signals through two major pathways: a vertical excitatory pathway, which involves photoreceptors, bipolar cells, and ganglion cells, and a horizontal inhibitory pathway, which involves horizontal cells, and amacrine cells. This concept explains the generation of an excitatory center—inhibitory surround sensory receptive fields—but fails to explain the modulation of the retinal output by stimuli outside the receptive field. Electrical imaging of light-induced signal propagation at high spatial and temporal resolution across and within different retinal layers might reveal mechanisms and circuits involved in the remote modulation of the retinal output. Here we took advantage of a high-density complementary metal oxide semiconductor-based microelectrode array and investigated the light-induced propagation of local field potentials (LFPs) in vertical mouse retina slices. Surprisingly, the LFP propagation within the different retinal layers depends on stimulus duration and stimulus background. Application of the same spatially restricted light stimuli to flat-mounted retina induced ganglion cell activity at remote distances from the stimulus center. This effect disappeared if a global background was provided or if gap junctions were blocked. We hereby present a neurotechnological approach and demonstrated its application, in which electrical imaging evaluates stimulus-dependent signal processing across different neural layers.

Information processing in the LGN: a comparison of neural codes and cell types

To understand how anatomy and physiology allow an organism to perform its function, it is important to know how information that is transmitted by spikes in the brain is received and encoded. A natural question is whether the spike rate alone encodes the information about a stimulus (rate code), or additional information is contained in the temporal pattern of the spikes (temporal code). Here we address this question using data from the cat Lateral Geniculate Nucleus (LGN), which is the visual portion of the thalamus, through which visual information from the retina is communicated to the visual cortex. We analyzed the responses of LGN neurons to spatially homogeneous spots of various sizes with temporally random luminance modulation. We compared the Firing Rate with the Shannon Information Transmission Rate , which quantifies the information contained in the temporal relationships between spikes. We found that the behavior of these two rates can differ quantitatively. This suggests that the energy used for spiking does not translate directly into the information to be transmitted. We also compared Firing Rates with Information Rates for X-ON and X-OFF cells. We found that, for X-ON cells the Firing Rate and Information Rate often behave in a completely different way, while for X-OFF cells these rates are much more highly correlated. Our results suggest that for X-ON cells a more efficient "temporal code" is employed, while for X-OFF cells a straightforward "rate code" is used, which is more reliable and is correlated with energy consumption.

Long-range neural inhibition and stimulus competition in the archerfish optic tectum

The archerfish, which is unique in its ability to hunt insects above the water level by shooting a jet of water at its prey, operates in a complex visual environment. The fish needs to quickly select one object from among many others. In animals other than the archerfish, long-range inhibition is considered to drive selection. As a result of long-range inhibition, a potential target outside a neuron's receptive field suppresses the activity elicited by another potential target within the receptive field. We tested whether a similar mechanism operates in the archerfish by recording the activity of neurons in the optic tectum while presenting a target stimulus inside the receptive field and a competing stimulus outside the receptive field. We held the features of the target constant while varying the size, speed, and distance of the competing stimulus. We found cells that exhibit long-range inhibition; i.e., inhibition that extends to a significant part of the entire visual field of the animal. The competing stimulus depressed the firing rate. In some neurons, this effect was dependent on the features of the competing stimulus. These findings suggest that long-range inhibition may play a crucial role in the target selection process in the archerfish.

Multiplexed computations in retinal ganglion cells of a single type

In the early visual system, cells of the same type perform the same computation in different places of the visual field. How these cells code together a complex visual scene is unclear. A common assumption is that cells of a single-type extract a single-stimulus feature to form a feature map, but this has rarely been observed directly. Using large-scale recordings in the rat retina, we show that a homogeneous population of fast OFF ganglion cells simultaneously encodes two radically different features of a visual scene. Cells close to a moving object code quasilinearly for its position, while distant cells remain largely invariant to the object's position and, instead, respond nonlinearly to changes in the object's speed. We develop a quantitative model that accounts for this effect and identify a disinhibitory circuit that mediates it. Ganglion cells of a single type thus do not code for one, but two features simultaneously. This richer, flexible neural map might also be present in other sensory systems.

Bioplausible multiscale filtering in retino-cortical processing as a mechanism in perceptual grouping

Why does our visual system fail to reconstruct reality, when we look at certain patterns? Where do Geometrical illusions start to emerge in the visual pathway? How far should we take computational models of vision with the same visual ability to detect illusions as we do? This study addresses these questions, by focusing on a specific underlying neural mechanism involved in our visual experiences that affects our final perception. Among many types of visual illusion, 'Geometrical' and, in particular, 'Tilt Illusions' are rather important, being characterized by misperception of geometric patterns involving lines and tiles in combination with contrasting orientation, size or position. Over the last decade, many new neurophysiological experiments have led to new insights as to how, when and where retinal processing takes place, and the encoding nature of the retinal representation that is sent to the cortex for further processing. Based on these neurobiological discoveries, we provide computer simulation evidence from modelling retinal ganglion cells responses to some complex Tilt Illusions, suggesting that the emergence of tilt in these illusions is partially related to the interaction of multiscale visual processing performed in the retina. The output of our low-level filtering model is presented for several types of Tilt Illusion, predicting that the final tilt percept arises from multiple-scale processing of the Differences of Gaussians and the perceptual interaction of foreground and background elements. The model is a variation of classical receptive field implementation for simple cells in early stages of vision with the scales tuned to the object/texture sizes in the pattern. Our results suggest that this model has a high potential in revealing the underlying mechanism connecting low-level filtering approaches to mid- and high-level explanations such as 'Anchoring theory' and 'Perceptual grouping'.

Sensitivity to image recurrence across eye-movement-like image transitions through local serial inhibition in the retina

Standard models of stimulus encoding in the retina postulate that image presentations activate neurons according to the increase of preferred contrast inside the receptive field. During natural vision, however, images do not arrive in isolation, but follow each other rapidly, separated by sudden gaze shifts. We here report that, contrary to standard models, specific ganglion cells in mouse retina are suppressed after a rapid image transition by changes in visual patterns across the transition, but respond with a distinct spike burst when the same pattern reappears. This sensitivity to image recurrence depends on opposing effects of glycinergic and GABAergic inhibition and can be explained by a circuit of local serial inhibition. Rapid image transitions thus trigger a mode of operation that differs from the processing of simpler stimuli and allows the retina to tag particular image parts or to detect transition types that lead to recurring stimulus patterns.

DOI:http://dx.doi.org/10.7554/eLife.22431.001

The Café Wall Illusion: Local and Global Perception from Multiple Scales to Multiscale

Geometrical illusions are a subclass of optical illusions in which the geometrical characteristics of patterns in particular orientations and angles are distorted and misperceived as a result of low-to-high-level retinal/cortical processing. Modelling the detection of tilt in these illusions, and its strength, is a challenging task and leads to the development of techniques that explain important features of human perception. We present here a predictive and quantitative approach for modelling foveal and peripheral vision for the induced tilt in the Café Wall illusion, in which parallel mortar lines between shifted rows of black and white tiles appear to converge and diverge. Difference of Gaussians is used to define a bioderived filtering model for the responses of retinal simple cells to the stimulus, while an analytical processing pipeline is developed to quantify the angle of tilt in the model and develop confidence intervals around them. Several sampling sizes and aspect ratios are explored to model variant foveal views, and a variety of pattern configurations are tested to model variant Gestalt views. The analysis of our model across this range of test configurations presents a precisely quantified comparison contrasting local tilt detection in the foveal sample sets with pattern-wide Gestalt tilt.

Retinal Lateral Inhibition Provides the Biological Basis of Long-Range Spatial Induction

Retinal lateral inhibition is one of the conventional efficient coding mechanisms in the visual system that is produced by interneurons that pool signals over a neighborhood of presynaptic feedforward cells and send inhibitory signals back to them. Thus, the receptive-field (RF) of a retinal ganglion cell has a center-surround receptive-field (RF) profile that is classically represented as a difference-of-Gaussian (DOG) adequate for efficient spatial contrast coding. The DOG RF profile has been attributed to produce the psychophysical phenomena of brightness induction, in which the perceived brightness of an object is affected by that of its vicinity, either shifting away from it (brightness contrast) or becoming more similar to it (brightness assimilation) depending on the size of the surfaces surrounding the object. While brightness contrast can be modeled using a DOG with a narrow surround, brightness assimilation requires a wide suppressive surround. Early retinal studies determined that the suppressive surround of a retinal ganglion cell is narrow (< 100–300 μm; ‘classic RF’), which led researchers to postulate that brightness assimilation must originate at some post-retinal, possibly cortical, stage where long-range interactions are feasible. However, more recent studies have reported that the retinal interneurons also exhibit a spatially wide component (> 500–1000 μm). In the current study, we examine the effect of this wide interneuron RF component in two biophysical retinal models and show that for both of the retinal models it explains the long-range effect evidenced in simultaneous brightness induction phenomena and that the spatial extent of this long-range effect of the retinal model responses matches that of perceptual data. These results suggest that the retinal lateral inhibition mechanism alone can regulate local as well as long-range spatial induction through the narrow and wide RF components of retinal interneurons, arguing against the existing view that spatial induction is operated by two separate local vs. long-range mechanisms.

Identification of a Retinal Circuit for Recurrent Suppression Using Indirect Electrical Imaging

Understanding the function of modulatory interneuron networks is a major challenge, because such networks typically operate over long spatial scales and involve many neurons of different types. Here, we use an indirect electrical imaging method to reveal the function of a spatially extended, recurrent retinal circuit composed of two cell types. This recurrent circuit produces peripheral response suppression of early visual signals in the primate magnocellular visual pathway. We identify a type of polyaxonal amacrine cell physiologically via its distinctive electrical signature, revealed by electrical coupling with ON parasol retinal ganglion cells recorded using a large-scale multi-electrode array. Coupling causes the amacrine cells to fire spikes that propagate radially over long distances, producing GABA-ergic inhibition of other ON parasol cells recorded near the amacrine cell axonal projections. We propose and test a model for the function of this amacrine cell type, in which the extra-classical receptive field of ON parasol cells is formed by reciprocal inhibition from other ON parasol cells in the periphery, via the electrically coupled amacrine cell network.

Contrast adaptation in the Limulus lateral eye

Luminance and contrast adaptation are neuronal mechanisms employed by the visual system to adjust our sensitivity to light. They are mediated by an assortment of cellular and network processes distributed across the retina and visual cortex. Both have been demonstrated in the eyes of many vertebrates, but only luminance adaptation has been shown in invertebrate eyes to date. Since the computational benefits of contrast adaptation should apply to all visual systems, we investigated whether this mechanism operates in horseshoe crab eyes, one of the best-understood neural networks in the animal kingdom. The spike trains of optic nerve fibers were recorded in response to light stimuli modulated randomly in time and delivered to single ommatidia or the whole eye. We found that the retina adapts to both the mean luminance and contrast of a white-noise stimulus, that luminance- and contrast-adaptive processes are largely independent, and that they originate within an ommatidium. Network interactions are not involved. A published computer model that simulates existing knowledge of the horseshoe crab eye did not show contrast adaptation, suggesting that a heretofore unknown mechanism may underlie the phenomenon. This mechanism does not appear to reside in photoreceptors because white-noise analysis of electroretinogram recordings did not show contrast adaptation. The likely site of origin is therefore the spike discharge mechanism of optic nerve fibers. The finding of contrast adaption in a retinal network as simple as the horseshoe crab eye underscores the broader importance of this image processing strategy to vision.

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

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

High Accuracy Decoding of Dynamical Motion from a Large Retinal Population

Motion tracking is a challenge the visual system has to solve by reading out the retinal population. It is still unclear how the information from different neurons can be combined together to estimate the position of an object. Here we recorded a large population of ganglion cells in a dense patch of salamander and guinea pig retinas while displaying a bar moving diffusively. We show that the bar's position can be reconstructed from retinal activity with a precision in the hyperacuity regime using a linear decoder acting on 100+ cells. We then took advantage of this unprecedented precision to explore the spatial structure of the retina's population code. The classical view would have suggested that the firing rates of the cells form a moving hill of activity tracking the bar's position. Instead, we found that most ganglion cells in the salamander fired sparsely and idiosyncratically, so that their neural image did not track the bar. Furthermore, ganglion cell activity spanned an area much larger than predicted by their receptive fields, with cells coding for motion far in their surround. As a result, population redundancy was high, and we could find multiple, disjoint subsets of neurons that encoded the trajectory with high precision. This organization allows for diverse collections of ganglion cells to represent high-accuracy motion information in a form easily read out by downstream neural circuits.

Surround suppression and temporal processing of visual signals

Extraclassical surround suppression strongly modulates responses of neurons in the retina, lateral geniculate nucleus (LGN), and primary visual cortex. Although a great deal is known about the spatial properties of extraclassical suppression and the role it serves in stimulus size tuning, relatively little is known about how extraclassical suppression shapes visual processing in the temporal domain. We recorded the spiking activity of retinal ganglion cells and LGN neurons in the cat to test the hypothesis that extraclassical suppression influences temporal features of visual responses in the early visual system. Our results demonstrate that extraclassical suppression not only shifts the distribution of interspike intervals in a manner that decreases the efficacy of neuronal communication, it also decreases the reliability of neuronal responses to visual stimuli and it decreases the duration of visual responses, an effect that underlies a rightward shift in the temporal frequency tuning of LGN neurons. Taken together, these results reveal a dynamic relationship between extraclassical suppression and the temporal features of neuronal responses.

Spectral characteristics of phase sensitivity and discharge rate of neurons in the ascending tectofugal visual system

Drifting gratings can modulate the activity of visual neurons at the temporal frequency of the stimulus. In order to characterize the temporal frequency modulation in the cat’s ascending tectofugal visual system, we recorded the activity of single neurons in the superior colliculus, the suprageniculate nucleus, and the anterior ectosylvian cortex during visual stimulation with drifting sine-wave gratings. In response to such stimuli, neurons in each structure showed an increase in firing rate and/or oscillatory modulated firing at the temporal frequency of the stimulus (phase sensitivity). To obtain a more complete characterization of the neural responses in spatiotemporal frequency domain, we analyzed the mean firing rate and the strength of the oscillatory modulations measured by the standardized Fourier component of the response at the temporal frequency of the stimulus. We show that the spatiotemporal stimulus parameters that elicit maximal oscillations often differ from those that elicit a maximal discharge rate. Furthermore, the temporal modulation and discharge-rate spectral receptive fields often do not overlap, suggesting that the detection range for visual stimuli provided jointly by modulated and unmodulated response components is larger than the range provided by a one response component.

Spatiotemporal characteristics of surround suppression in primary visual cortex and lateral geniculate nucleus of the cat

In the primary visual cortex (V1), a neuronal response to stimulation of the classical receptive field (CRF) is predominantly suppressed by a stimulus presented outside the CRF (extraclassical receptive field, ECRF), a phenomenon referred to as ECRF suppression. To elucidate the neuronal mechanisms and origin of ECRF suppression in V1 of anesthetized cats, we examined the temporal properties of the spatial extent and orientation specificity of ECRF suppression in V1 and the lateral geniculate nucleus (LGN), using stationary-flashed sinusoidal grating. In V1, we found three components of ECRF suppression: 1) local and fast, 2) global and fast, and 3) global and late. The local and fast component, which resulted from within 2° of the boundary of the CRF, started no more than 10 ms after the onset of the CRF response and exhibited low specificity for the orientation of the ECRF stimulus. These spatiotemporal properties corresponded to those of geniculate ECRF suppression, suggesting that the local and fast component of V1 is inherited from the LGN. In contrast, the two global components showed rather large spatial extents ∼5° from the CRF boundary and high specificity for orientation, suggesting that their possible origin is the cortex, not the LGN. Correspondingly, the local component was observed in all neurons of the thalamocortical recipient layer, while the global component was biased toward other layers. Therefore, we conclude that both subcortical and cortical mechanisms with different spatiotemporal properties are involved in ECRF suppression.

Reciprocal inhibition and slow calcium decay in perigeniculate interneurons explain changes of spontaneous firing of thalamic cells caused by cortical inactivation

The role of cortical feedback in the thalamocortical processing loop has been extensively investigated over the last decades. With an exception of several cases, these searches focused on the cortical feedback exerted onto thalamo-cortical relay (TC) cells of the dorsal lateral geniculate nucleus (LGN). In a previous, physiological study, we showed in the cat visual system that cessation of cortical input, despite decrease of spontaneous activity of TC cells, increased spontaneous firing of their recurrent inhibitory interneurons located in the perigeniculate nucleus (PGN). To identify mechanisms underlying such functional changes we conducted a modeling study in NEURON on several networks of point neurons with varied model parameters, such as membrane properties, synaptic weights and axonal delays. We considered six network topologies of the retino-geniculo-cortical system. All models were robust against changes of axonal delays except for the delay between the LGN feed-forward interneuron and the TC cell. The best representation of physiological results was obtained with models containing reciprocally connected PGN cells driven by the cortex and with relatively slow decay of intracellular calcium. This strongly indicates that the thalamic reticular nucleus plays an essential role in the cortical influence over thalamo-cortical relay cells while the thalamic feed-forward interneurons are not essential in this process. Further, we suggest that the dependence of the activity of PGN cells on the rate of calcium removal can be one of the key factors determining individual cell response to elimination of cortical input.

A possible role and basis of visual pathway selection in brightness induction

It is a well-known fact that the perceived brightness of any surface depends on the brightness of the surfaces that surround it. This phenomenon is termed as brightness induction. Isotropic arrays of multi-scale DoG (Difference of Gaussians) as well as cortical Oriented DoG (ODOG) and extensions thereof, like the Frequency-specific Locally Normalized ODOG (FLODOG) functions have been employed towards prediction of the direction of brightness induction in many brightness perception effects. But the neural basis of such spatial filters is seldom obvious. For instance, the visual information from retinal ganglion cells to such spatial filters, which have been generally speculated to appear at the early stage of cortical processing, are fed by at least three parallel channels viz. Parvocellular (P), Magnocellular (M) and Koniocellular (K) in the subcortical pathway, but the role of such pathways in brightness induction is generally not implicit. In this work, three different spatial filters based on an extended classical receptive field (ECRF) model of retinal ganglion cells, have been approximately related to the spatial contrast sensitivity functions of these three parallel channels. Based on our analysis involving different brightness perception effects, we propose that the M channel, with maximum conduction velocity, may have a special role for an initial sensorial perception. As a result, brightness assimilation may be the consequence of vision at a glance through the M pathway; contrast effect may be the consequence of a subsequent vision with scrutiny through the P channel; and the K pathway response may represent an intermediate situation resulting in ambiguity in brightness perception. The present work attempts to correlate this phenomenon of pathway selection with the complementary nature of these channels in terms of spatial frequency as well as contrast.

Spatial receptive field properties of rat retinal ganglion cells

The rat is a popular animal model for vision research, yet there is little quantitative information about the physiological properties of the cells that provide its brain with visual input, the retinal ganglion cells. It is not clear whether rats even possess the full complement of ganglion cell types found in other mammals. Since such information is important for evaluating rodent models of visual disease and elucidating the function of homologous and heterologous cells in different animals, we recorded from rat ganglion cells in vivo and systematically measured their spatial receptive field (RF) properties using spot, annulus, and grating patterns. Most of the recorded cells bore likeness to cat X and Y cells, exhibiting brisk responses, center-surround RFs, and linear or nonlinear spatial summation. The others resembled various types of mammalian W cell, including local-edge-detector cells, suppressed-by-contrast cells, and an unusual type with an ON-OFF surround. They generally exhibited sluggish responses, larger RFs, and lower responsiveness. The peak responsivity of brisk-nonlinear (Y-type) cells was around twice that of brisk-linear (X-type) cells and several fold that of sluggish cells. The RF size of brisk-linear and brisk-nonlinear cells was indistinguishable, with average center and surround diameters of 5.6 ± 1.3 and 26.4 ± 11.3 deg, respectively. In contrast, the center diameter of recorded sluggish cells averaged 12.8 ± 7.9 deg. The homogeneous RF size of rat brisk cells is unlike that of cat X and Y cells, and its implication regarding the putative roles of these two ganglion cell types in visual signaling is discussed.

Orientation-Specific Modulation of Rat Retinal Ganglion Cell Responses and Its Dependence on Relative Orientations of the Center and Surround Gratings

In the primary visual cortex (V1), it has been shown that the neuronal response elicited by a grating patch in the receptive field (RF) center can be suppressed or facilitated by an annular grating presented in the RF surround area; the effect depends on the relative orientations of the two gratings. The effect is thought to play a role in figure-ground segregation. Here we have found that response modulation similar to that reported in cortical area V1 can also be found in all major classes of retinal ganglion cells (RGCs), including “concentric” cells. Orientation-specific response modulation of this kind cannot result from interactions of independent RF mechanisms; therefore more complex mechanism, which takes into account the relative orientations of the gratings in the RF center and surround, or sensing the borders between texture regions, has to be present in RFs of RGCs, even of the concentric type. This challenges the consensus notion that their responses to visual stimuli are governed entirely by a RF composed of separate mechanisms: center, antagonistic surround, and modulatory extraclassical surround. Our findings raise the question of whether initial stages of complex analysis of visual input, normally attributed to the visual cortex, can be achieved within the retina.

Linear and Nonlinear Contributions to the Visual Sensitivity of Neurons in Primate Lateral Geniculate Nucleus

Several parallel pathways convey retinal signals to the visual cortex of primates. The signals of the parvocellular (P) and magnocellular (M) pathways are well characterized; the properties of other rarely encountered cell types are distinctive in many ways, but it is not clear that they can provide signals with the same fidelity. Here we study this by characterizing the temporal receptive field of neurons in the lateral geniculate nucleus of anesthetized marmosets. For each neuron, we measured the response to a flickering uniform field, and, from this, estimated the linear and nonlinear receptive fields using spike-triggered average (STA) and spike-triggered covariance (STC) analyses. As expected the response of most P-cells was dominated by the STA, but the response of most M-cells required additional nonlinear components, and these usually acted to suppress cell responses. The STC analysis showed stronger suppressive axes in suppressed-by-contrast cells, and both suppressive and excitatory axes in on-off cells. Together, the STA and the STC analyses form a model of the temporal response to a large uniform field: under this model, the information that was provided by suppressed-by-contrast cells or on-off cells approached that provided by the P- and M-cells. However, whereas P- and M-cells provided more information about luminance, the nonlinear cells provided more information about the contrast energy. This suggests that the nonlinear cells provide complimentary signals to those of P- and M-cells, with reasonably high fidelity, and may play an important role in normal visual processing.

Retinal ganglion cell adaptation to small luminance fluctuations

To accommodate the wide input range over which the visual system operates within the narrow output range of spiking neurons, the retina adjusts its sensitivity to the mean light level so that retinal ganglion cells can faithfully signal contrast, or relative deviations from the mean luminance. Given the large operating range of the visual system, the majority of work on luminance adaptation has involved logarithmic changes in light level. We report that luminance gain controls are recruited for remarkably small fluctuations in luminance as well. Using spike recordings from the rat optic tract, we show that ganglion cell responses to a brief flash of light are modulated in amplitude by local background fluctuations as little as 15% contrast. The time scale of the gain control is rapid (<125 ms), at least for on cells. The retinal locus of adaptation precedes the ganglion cell spike generator because response gain changes of on cells were uncorrelated with firing rate. The mechanism seems to reside within the inner retinal network and not in the photoreceptors, because the adaptation profiles of on and off cells differed markedly. The response gain changes follow Weber's law, suggesting that network mechanisms of luminance adaptation described in previous work modulates retinal ganglion cell sensitivity, not just when we move between different lighting environments, but also as our eyes scan a visual scene. Finally, we show that response amplitude is uniformly reduced for flashes on a modulated background that has spatial contrast, indicating that another gain control that integrates luminance signals nonlinearly over space operates within the receptive field center of rat ganglion cells.

Retinal synaptic pathways underlying the response of the rabbit local edge detector

We studied the circuitry that underlies the behavior of the local edge detector (LED) retinal ganglion cell in rabbit by measuring the spatial and temporal properties of excitatory and inhibitory currents under whole cell voltage clamp. Previous work showed that LED excitation is suppressed by activity in the surround. However, the contributions of outer and inner retina to this characteristic and the neurotransmitters used are currently unknown. Blockage of retinal inhibitory pathways (GABA(A), GABA(C), and glycine) eliminated edge selectivity. Inverting gratings in the surround with 50-microm stripe sizes did not stimulate horizontal cells, but suppressed on and off excitation by roughly 60%, indicating inhibition of bipolar terminals (feedback inhibition). On pharmacologic blockage, we showed that feedback inhibition used both GABA(A) and GABA(C) receptors, but not glycine. Glycinergic inhibition suppressed GABAergic feedback inhibition in the center, enabling larger excitatory currents in response to luminance changes. Excitation, feedback inhibition, and direct (feedforward) inhibition responded to luminance-neutral flipping gratings of 20- to 50-microm widths, showing they are driven by independent subunits within their receptive fields, which confers sensitivity to borders between areas of texture and nontexture. Feedforward inhibition was glycinergic, its rise time was faster than decay time, and did not function to delay spiking at the onset of a stimulus. Both the on and off phases could be triggered by luminance shifts as short in duration as 33 ms and could be triggered during scenes that already produced a high baseline level of feedforward inhibition. Our results show how LED circuitry can use subreceptive field sensitivity to detect visual edges via the interaction between excitation and feedback inhibition and also respond to rapid luminance shifts within a rapidly changing scene by producing feedforward inhibition.

Interneuron circuits tune inhibition in retinal bipolar cells

While connections between inhibitory interneurons are common circuit elements, it has been difficult to define their signal processing roles because of the inability to activate these circuits using natural stimuli. We overcame this limitation by studying connections between inhibitory amacrine cells in the retina. These interneurons form spatially extensive inhibitory networks that shape signaling between bipolar cell relay neurons to ganglion cell output neurons. We investigated how amacrine cell networks modulate these retinal signals by selectively activating the networks with spatially defined light stimuli. The roles of amacrine cell networks were assessed by recording their inhibitory synaptic outputs in bipolar cells that suppress bipolar cell output to ganglion cells. When the amacrine cell network was activated by large light stimuli, the inhibitory connections between amacrine cells unexpectedly depressed bipolar cell inhibition. Bipolar cell inhibition elicited by smaller light stimuli or electrically activated feedback inhibition was not suppressed because these stimuli did not activate the connections between amacrine cells. Thus the activation of amacrine cell circuits with large light stimuli can shape the spatial sensitivity of the retina by limiting the spatial extent of bipolar cell inhibition. Because inner retinal inhibition contributes to ganglion cell surround inhibition, in part, by controlling input from bipolar cells, these connections may refine the spatial properties of the retinal output. This functional role of interneuron connections may be repeated throughout the CNS.

A possible mechanism of stochastic resonance in the light of an extra-classical receptive field model of retinal ganglion cells

Traditionally the intensity discontinuities in an image are detected as zero-crossings of the second derivative with the help of a Laplacian of Gaussian (LOG) operator that models the receptive field of retinal Ganglion cells. Such zero-crossings supposedly form a raw primal sketch edge map of the external world in the primary visual cortex of the brain. Based on a new operator which is a linear combination of the LOG and a Dirac-delta function that models the extra-classical receptive field of the ganglion cells, we find that zero-crossing points thus generated, store in presence of noise, apart from the edge information, the shading information of the image in the form of density variation of these points. We have also shown that an optimal image contrast produces best mapping of the shading information to such zero-crossing density variation for a given amount of noise contamination. Furthermore, we have observed that an optimal amount of noise contamination reproduces the minimum optimal contrast and hence gives rise to the best representation of the original image. We show that this phenomenon is similar in nature to that of stochastic resonance phenomenon observed in psychophysical experiments.

A retinal circuit model accounting for wide-field amacrine cells

In previous experimental studies on the visual processing in vertebrates, higher-order visual functions such as the object segregation from background were found even in the retinal stage. Previously, the "linear-nonlinear" (LN) cascade models have been applied to the retinal circuit, and succeeded to describe the input-output dynamics for certain parts of the circuit, e.g., the receptive field of the outer retinal neurons. And recently, some abstract models composed of LN cascades as the circuit elements could explain the higher-order retinal functions. However, in such a model, each class of retinal neurons is mostly omitted and thus, how those neurons play roles in the visual computations cannot be explored. Here, we present a spatio-temporal computational model of the vertebrate retina, based on the response function for each class of retinal neurons and on the anatomical inter-cellular connections. This model was capable of not only reproducing the spatio-temporal filtering properties of the outer retinal neurons, but also realizing the object segregation mechanism in the inner retinal circuit involving the "wide-field" amacrine cells. Moreover, the first-order Wiener kernels calculated for the neurons in our model showed a reasonable fit to the kernels previously measured in the real retinal neuron in situ.

Retinomorphic image processing

The present work is aimed at understanding and explaining some of the aspects of visual signal processing at the retinal level while exploiting the same towards the development of some simple techniques in the domain of digital image processing. Classical studies on retinal physiology revealed the nature of contrast sensitivity of the receptive field of bipolar or ganglion cells, which lie in the outer and inner plexiform layers of the retina. To explain these observations, a difference of Gaussian (DOG) filter was suggested, which was subsequently modified to a Laplacian of Gaussian (LOG) filter for computational ease in handling two-dimensional retinal inputs. Till date almost all image processing algorithms, used in various branches of science and engineering had followed LOG or one of its variants. Recent observations in retinal physiology however, indicate that the retinal ganglion cells receive input from a larger area than the classical receptive fields. We have proposed an isotropic model for the non-classical receptive field of the retinal ganglion cells, corroborated from these recent observations, by introducing higher order derivatives of Gaussian expressed as linear combination of Gaussians only. In digital image processing, this provides a new mechanism of edge detection on one hand and image half-toning on the other. It has also been found that living systems may sometimes prefer to "perceive" the external scenario by adding noise to the received signals in the pre-processing level for arriving at better information on light and shade in the edge map. The proposed model also provides explanation to many brightness-contrast illusions hitherto unexplained not only by the classical isotropic model but also by some other Gestalt and Constructivist models or by non-isotropic multi-scale models. The proposed model is easy to implement both in the analog and digital domain. A scheme for implementation in the analog domain generates a new silicon retina model implemented on a hardware development platform.

Retinal ganglion cells can rapidly change polarity from Off to On

Retinal ganglion cells are commonly classified as On-center or Off-center depending on whether they are excited predominantly by brightening or dimming within the receptive field. Here we report that many ganglion cells in the salamander retina can switch from one response type to the other, depending on stimulus events far from the receptive field. Specifically, a shift of the peripheral image—as produced by a rapid eye movement—causes a brief transition in visual sensitivity from Off-type to On-type for approximately 100 ms. We show that these ganglion cells receive inputs from both On and Off bipolar cells, and the Off inputs are normally dominant. The peripheral shift strongly modulates the strength of these two inputs in opposite directions, facilitating the On pathway and suppressing the Off pathway. Furthermore, we identify certain wide-field amacrine cells that contribute to this modulation. Depolarizing such an amacrine cell affects nearby ganglion cells in the same way as the peripheral image shift, facilitating the On inputs and suppressing the Off inputs. This study illustrates how inhibitory interneurons can rapidly gate the flow of information within a circuit, dramatically altering the behavior of the principal neurons in the course of a computation.

The eye communicates to the brain all the information needed for vision in the form of electrical pulses, or spikes, on optic nerve fibers. These spikes are produced by retinal ganglion cells, the output neurons of the retina. In a popular view of retinal function, each ganglion cell responds to a small region of interest in the visual image, known as its receptive field, and is specialized for certain image features within that window. When a cell encounters that image feature, the neuron responds by firing one or more spikes. Different neurons are tuned to different features. For example, some ganglion cells fire when light dims, others when it brightens. Here we show that a rapid shift in the image on the retina can cause a dramatic change in a neuron's preferred feature: For example, a dimming-detector can briefly turn into a brightening-detector. We explore the mechanisms that implement such a switch of feature tuning, and the consequences it might have for visual processing.

A peripheral image shift produces a transient switch in retinal ganglion cell responses from Off-dominated to On-dominated. This modulation is exerted at least in part presynaptically, presumably at the bipolar cell synaptic terminal.

Information processing in the primate retina: circuitry and coding

The function of any neural circuit is governed by connectivity of neurons in the circuit and the computations performed by the neurons. Recent research on retinal function has substantially advanced understanding in both areas. First, visual information is transmitted to the brain by at least 17 distinct retinal ganglion cell types defined by characteristic morphology, light response properties, and central projections. These findings provide a much more accurate view of the parallel visual pathways emanating from the retina than do previous models, and they highlight the importance of identifying distinct cell types and their connectivity in other neural circuits. Second, encoding of visual information involves significant temporal structure and interactions in the spike trains of retinal neurons. The functional importance of this structure is revealed by computational analysis of encoding and decoding, an approach that may be applicable to understanding the function of other neural circuits.

Extracting number-selective responses from coherent oscillations in a computer model

Cortical neurons selective for numerosity may underlie an innate number sense in both animals and humans. We hypothesize that the number- selective responses of cortical neurons may in part be extracted from coherent, object-specific oscillations . Here, indirect evidence for this hypothesis is obtained by analyzing the numerosity information encoded by coherent oscillations in artificially generated spikes trains. Several experiments report that gamma-band oscillations evoked by the same object remain coherent, whereas oscillations evoked by separate objects are uncorrelated. Because the oscillations arising from separate objects would add in random phase to the total power summed across all stimulated neurons, we postulated that the total gamma activity, normalized by the number of spikes, should fall roughly as the square root of the number of objects in the scene, thereby implicitly encoding numerosity. To test the hypothesis, we examined the normalized gamma activity in multiunit spike trains, 50 to 1000 msec in duration, produced by a model feedback circuit previously shown to generate realistic coherent oscillations. In response to images containing different numbers of objects, regardless of their shape, size, or shading, the normalized gamma activity followed a square-root-of-n rule as long as the separation between objects was sufficiently large and their relative size and contrast differences were not too great. Arrays of winner-take-all numerosity detectors, each responding to normalized gamma activity within a particular band, exhibited tuning curves consistent with behavioral data. We conclude that coherent oscillations in principle could contribute to the number-selective responses of cortical neurons, although many critical issues await experimental resolution.

Functional circuitry for peripheral suppression in Mammalian Y-type retinal ganglion cells

A retinal ganglion cell receptive field is made up of an excitatory center and an inhibitory surround. The surround has two components: one driven by horizontal cells at the first synaptic layer and one driven by amacrine cells at the second synaptic layer. Here we characterized how amacrine cells inhibit the center response of on- and off-center Y-type ganglion cells in the in vitro guinea pig retina. A high spatial frequency grating (4-5 cyc/mm), beyond the spatial resolution of horizontal cells, drifted in the ganglion cell receptive field periphery to stimulate amacrine cells. The peripheral grating suppressed the ganglion cell spiking response to a central spot. Suppression of spiking was strongest and observed most consistently in off cells. In intracellular recordings, the grating suppressed the subthreshold membrane potential in two ways: a reduced slope (gain) of the stimulus-response curve by approximately 20-30% and, in off cells, a tonic approximately 1-mV hyperpolarization. In voltage clamp, the grating increased an inhibitory conductance in all cells and simultaneously decreased an excitatory conductance in off cells. To determine whether center response inhibition was presynaptic or postsynaptic (shunting), we measured center response gain under voltage-clamp and current-clamp conditions. Under both conditions, the peripheral grating reduced center response gain similarly. This result suggests that reduced gain in the ganglion cell subthreshold center response reflects inhibition of presynaptic bipolar terminals. Thus amacrine cells suppressed ganglion cell center response gain primarily by inhibiting bipolar cell glutamate release.

A new silicon retina model and its advantages

A new model of silicon retina based on the receptive field structure of retinal ganglion cells has been proposed. Unlike previous neuromorphic models, the proposed model directly incorporates into the receptive field model, contribution from both the inner and outer plexiform layer of the retina, as a linear combination of the two. It has been shown that such a system is capable of aiding in the computation of zero-crossing maps, in higher regions of the brain, using a fourth or higher order derivative. This model is likely to have a neuromorphic implication in generating and implementing a simplistic derivative analyzer mimetic of the Human Visual system (HVS) and is also endowed with additional advantages from the perspective of image retrieval.

A high frequency resonance in the responses of retinal ganglion cells to rapidly modulated stimuli: a computer model

Brisk Y-type ganglion cells in the cat retina exhibit a high frequency resonance (HFR) in their responses to large, rapidly modulated stimuli. We used a computer model to test whether negative feedback mediated by axon-bearing amacrine cells onto ganglion cells could account for the experimentally observed properties of HFRs. Temporal modulation transfer functions (tMTFs) recorded from model ganglion cells exhibited HFR peaks whose amplitude, width, and locations were qualitatively consistent with experimental data. Moreover, the wide spatial distribution of axon-mediated feedback accounted for the observed increase in HFR amplitude with stimulus size. Model phase plots were qualitatively similar to those recorded from Y ganglion cells, including an anomalous phase advance that in our model coincided with the amplification of low-order harmonics that overlapped the HFR peak. When axon-mediated feedback in the model was directed primarily to bipolar cells, whose synaptic output was graded, or else when the model was replaced with a simple cascade of linear filters, it was possible to produce large HFR peaks but the region of anomalous phase advance was always eliminated, suggesting the critical involvement of strongly non-linear feedback loops. To investigate whether HFRs might contribute to visual processing, we simulated high frequency ocular tremor by rapidly modulating a naturalistic image. Visual signals riding on top of the imposed jitter conveyed an enhanced representation of large objects. We conclude that by amplifying responses to ocular tremor, HFRs may selectively enhance the processing of large image features.

Smooth Gradient Representations as a Unifying Account of Chevreul's Illusion, Mach Bands, and a Variant of the Ehrenstein Disk

Recent evidence suggests that the primate visual system generates representations for object surfaces (where we consider representations for the surface attribute brightness). Object recognition can be expected to perform robustly if those representations are invariant despite environmental changes (e.g., in illumination). In real-world scenes, it happens, however, that surfaces are often overlaid by luminance gradients, which we define as smooth variations in intensity. Luminance gradients encode highly variable information, which may represent surface properties (curvature), nonsurface properties (e.g., specular highlights, cast shadows, illumination inhomogeneities), or information about depth relationships (cast shadows, blur). We argue, on grounds of the unpredictable nature of luminance gradients, that the visual system should establish corresponding representations, in addition to surface representations. We accordingly present a neuronal architecture, the so-called gradient system, which clarifies how spatially accurate gradient representations can be obtained by relying on only high-resolution retinal responses. Although the gradient system was designed and optimized for segregating, and generating, representations of luminance gradients with real-world luminance images, it is capable of quantitatively predicting psychophysical data on both Mach bands and Chevreul's illusion. It furthermore accounts qualitatively for a modified Ehrenstein disk.

A possible explanation of the low-level brightness-contrast illusions in the light of an extended classical receptive field model of retinal ganglion cells

The low-level brightness-contrast illusions constitute a special class within visual illusions. Speculations exist that these illusions may be processed through the filtering action of the retinal ganglion cells without necessitating much intervention from higher order processes of visual perception. Concept of the classical receptive field of the ganglion cell, derived from early physiological studies, prompted the idea that a Difference of Gaussian (DoG) model might explain the low-level illusions. In spite of its many successes, the DoG model fails to explain some of these illusions. It has been shown in this paper that it is possible to simulate those illusions with a model that takes into cognizance the role of the extended classical receptive field.

Recovering real-world images from single-scale boundaries with a novel filling-in architecture

Filling-in models were successful in predicting psychophysical data for brightness perception. Nevertheless, their suitability for real-world image processing has never been examined. A unified architecture for both predicting psychophysical data and real-world image processing would constitute a powerful theory for early visual information processing. As a first contribution of the present paper, we identified three principal problems with current filling-in architectures, which hamper the goal of having such a unified architecture. To overcome these problems we propose an advance to filling-in theory, called BEATS filling-in, which is based on a novel nonlinear diffusion operator. BEATS filling-in furthermore introduces novel boundary structures. We compare, by means of simulation studies with real-world images, the performance of BEATS filling-in with the recently proposed confidence-based filling-in. As a second contribution we propose a novel mechanism for encoding luminance information in contrast responses ('multiplex contrasts'), which is based on recent neurophysiological findings. Again, by simulations, we show that 'multiplex contrasts' at a single, high-resolution filter scale are sufficient for recovering absolute luminance levels. Hence, 'multiplex contrasts' represent a novel theory addressing how the brain encodes and decodes luminance information.

A possible mechanism of zero-crossing detection using the concept of the extended classical receptive field of retinal ganglion cells

The extended classical receptive field (ECRF) of retinal ganglion cells has been modelled as a combination of three zero-mean Gaussians at three different scales that has been shown to be equivalent to a Biharmonic or Bi-Laplacian of Gaussian filter. It has also been shown that the ECRF can be approximated by a combination of Laplacian of Gaussian (LoG) and the Dirac-delta function. Zero-crossings detected with this operator are more informative than those detected by the traditional filters like LoG or Difference of Gaussians (DoG) that had been devised using the classical receptive field of the ganglion cells. We have also explained that such an additional information processing is not in contradiction with the recent experimental findings on the physiology of retinal ganglion cells.

Inhibitory network properties shaping the light evoked responses of cat alpha retinal ganglion cells

Cat retinal ganglion cells of the Y (or alpha) type respond to luminance changes opposite those preferred by their receptive-field centers with a transient hyperpolarization. Here, we examine the spatial organization and synaptic basis of this light response by means of whole-cell current-clamp recordings made in vitro. The hyperpolarization was largest when stimulus spots approximated the size of the receptive-field center, and diminished substantially for larger spots. The hyperpolarization was largely abolished by bath application of strychnine, a blocker of glycinergic inhibition. Picrotoxin, an antagonist of ionotropic GABA receptors, greatly reduced the attenuation of the hyperpolarizing response for large spots. The data are consistent with a model in which (1) the hyperpolarization reflects inhibition by glycinergic amacrine cells of bipolar terminals presynaptic to the alpha cells, and perhaps direct inhibition of the alpha cell as well; and (2) the attenuation of the hyperpolarization by large spots reflects surround inhibition of the glycinergic amacrine by GABAergic amacrine cells. This circuitry may moderate nonlinearities in the alpha-cell light response and could account for some excitatory and inhibitory influences on alpha cells known to arise from outside the classical receptive field.

Astrocyte glycogen metabolism is required for neural activity during aglycemia or intense stimulation in mouse white matter

We tested the hypothesis that inhibiting glycogen degradation accelerates compound action potential (CAP) failure in mouse optic nerve (MON) during aglycemia or high-intensity stimulation. Axon function was assessed as the evoked CAP, and glycogen content was measured biochemically. Isofagomine, a novel inhibitor of central nervous system (CNS) glycogen phosphorylase, significantly increased glycogen content under normoglycemic conditions. When MONs were bathed in artificial cerebrospinal fluid (aCSF) containing 10 mM glucose, the CAP failed 16 min after exposure to glucose-free aCSF. MONs bathed in aCSF plus isofagomine displayed accelerated CAP failure on glucose removal. Similar results were obtained in MONs bathed in 30 mM glucose, which increased baseline glycogen concentration. The ability of isofagomine to increase glycogen content thus was not translated into delayed CAP failure. This is likely due to the inability of the tissue to metabolize glycogen in the presence of isofagomine, highlighting the importance of glycogen in sustaining neural function during aglycemia. The hypothesis that glycogen breakdown supports intense neural activity was tested by blocking glycogen breakdown during periods of high-frequency stimulation. The CAP area declined more rapidly when glycogen metabolism was inhibited by isofagomine, explicitly showing an important physiological role for glycogen metabolism during neural activity.

Segregation of object and background motion in the retina

An important task in vision is to detect objects moving within a stationary scene. During normal viewing this is complicated by the presence of eye movements that continually scan the image across the retina, even during fixation. To detect moving objects, the brain must distinguish local motion within the scene from the global retinal image drift due to fixational eye movements. We have found that this process begins in the retina: a subset of retinal ganglion cells responds to motion in the receptive field centre, but only if the wider surround moves with a different trajectory. This selectivity for differential motion is independent of direction, and can be explained by a model of retinal circuitry that invokes pooling over nonlinear interneurons. The suppression by global image motion is probably mediated by polyaxonal, wide-field amacrine cells with transient responses. We show how a population of ganglion cells selective for differential motion can rapidly flag moving objects, and even segregate multiple moving objects.

Different circuits for ON and OFF retinal ganglion cells cause different contrast sensitivities

The theory of "parallel pathways" predicts that, except for a sign reversal, ON and OFF ganglion cells are driven by a similar presynaptic circuit. To test this hypothesis, we measured synaptic inputs to ON and OFF cells as reflected in the subthreshold membrane potential. We made intracellular recordings from brisk-transient (Y) cells in the in vitro guinea pig retina and show that ON and OFF cells in fact express significant asymmetries in their synaptic inputs. An ON cell receives relatively linear input that modulates a single excitatory conductance; whereas an OFF cell receives rectified input that modulates both inhibitory and excitatory conductances. The ON pathway, blocked by L-AP-4, tonically inhibits an OFF cell at mean luminance and phasically inhibits an OFF cell during a light increment. Our results suggest that basal glutamate release is high at ON but not OFF bipolar terminals, and inhibition between pathways is unidirectional: ON --> OFF. These circuit asymmetries explain asymmetric contrast sensitivity observed in spiking behavior.