Cross-talk between ON and OFF channels in the salamander retina: Indirect bipolar cell inputs to ON–OFF ganglion cells

Interpreting the retinal neural code for natural scenes: From computations to neurons

Understanding the circuit mechanisms of the visual code for natural scenes is a central goal of sensory neuroscience. We show that a three-layer network model predicts retinal natural scene responses with an accuracy nearing experimental limits. The model's internal structure is interpretable, as interneurons recorded separately and not modeled directly are highly correlated with model interneurons. Models fitted only to natural scenes reproduce a diverse set of phenomena related to motion encoding, adaptation, and predictive coding, establishing their ethological relevance to natural visual computation. A new approach decomposes the computations of model ganglion cells into the contributions of model interneurons, allowing automatic generation of new hypotheses for how interneurons with different spatiotemporal responses are combined to generate retinal computations, including predictive phenomena currently lacking an explanation. Our results demonstrate a unified and general approach to study the circuit mechanisms of ethological retinal computations under natural visual scenes.

An uncommon neuronal class conveys visual signals from rods and cones to retinal ganglion cells

Neurons in the central nervous system (CNS) are distinguished by the neurotransmitter types they release, their synaptic connections, morphology, and genetic profiles. To fully understand how the CNS works, it is critical to identify all neuronal classes and reveal their synaptic connections. The retina has been extensively used to study neuronal development and circuit formation. Here, we describe a previously unidentified interneuron in mammalian retina. This interneuron shares some morphological, physiological, and molecular features with retinal bipolar cells, such as receiving input from photoreceptors and relaying visual signals to retinal ganglion cells. It also shares some features with amacrine cells (ACs), particularly Aii-ACs, such as their neurite morphology in the inner plexiform layer, the expression of some AC-specific markers, and possibly the release of the inhibitory neurotransmitter glycine. Thus, we unveil an uncommon interneuron, which may play an atypical role in vision.

What the salamander eye has been telling the vision scientist's brain

Salamanders have been habitual residents of research laboratories for more than a century, and their history in science is tightly interwoven with vision research. Nevertheless, many vision scientists - even those working with salamanders - may be unaware of how much our knowledge about vision, and particularly the retina, has been shaped by studying salamanders. In this review, we take a tour through the salamander history in vision science, highlighting the main contributions of salamanders to our understanding of the vertebrate retina. We further point out specificities of the salamander visual system and discuss the perspectives of this animal system for future vision research.

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.

Adaptive feature detection from differential processing in parallel retinal pathways

To transmit information efficiently in a changing environment, the retina adapts to visual contrast by adjusting its gain, latency and mean response. Additionally, the temporal frequency selectivity, or bandwidth changes to encode the absolute intensity when the stimulus environment is noisy, and intensity differences when noise is low. We show that the On pathway of On-Off retinal amacrine and ganglion cells is required to change temporal bandwidth but not other adaptive properties. This remarkably specific adaptive mechanism arises from differential effects of contrast on the On and Off pathways. We analyzed a biophysical model fit only to a cell’s membrane potential, and verified pharmacologically that it accurately revealed the two pathways. We conclude that changes in bandwidth arise mostly from differences in synaptic threshold in the two pathways, rather than synaptic release dynamics as has previously been proposed to underlie contrast adaptation. Different efficient codes are selected by different thresholds in two independently adapting neural pathways.

Neural Circuit Inference from Function to Structure

Advances in technology are opening new windows on the structural connectivity and functional dynamics of brain circuits. Quantitative frameworks are needed that integrate these data from anatomy and physiology. Here, we present a modeling approach that creates such a link. The goal is to infer the structure of a neural circuit from sparse neural recordings, using partial knowledge of its anatomy as a regularizing constraint. We recorded visual responses from the output neurons of the retina, the ganglion cells. We then generated a systematic sequence of circuit models that represents retinal neurons and connections and fitted them to the experimental data. The optimal models faithfully recapitulated the ganglion cell outputs. More importantly, they made predictions about dynamics and connectivity among unobserved neurons internal to the circuit, and these were subsequently confirmed by experiment. This circuit inference framework promises to facilitate the integration and understanding of big data in neuroscience.

The ON Crossover Circuitry Shapes Spatiotemporal Profile in the Center and Surround of Mouse OFF Retinal Ganglion Cells

Retinal ganglion cells (RGCs) are often grouped based on their functional properties. Many of these functional properties, such as receptive field (RF) size, are driven by specific retinal circuits. In this report, we determined the role of the ON bipolar cell (BC) mediated crossover circuitry in shaping the center and surround of OFF RGCs. We recorded from a large population of mouse RGCs using a multielectrode array (MEA) while pharmacologically removing the ON BC-mediated crossover circuit. OFF sustained and transient responses to whole field stimuli are lost under scotopic conditions, but maintained under photopic conditions. Though photopic light responses were grossly maintained, we found that photopic light response properties were altered. Using linear RF mapping, we found a significant reduction in the antagonistic surround and a decrease in size of the RF center. Using a novel approach to separate the distinct temporal filters present in the RF center, we see that the crossover pathway contributes specifically to the sluggish antagonistic filter in the center. These results provide new insight into the role of crossover pathways in driving RGCs and also demonstrate that the distinct inputs driving the RF center can be isolated and assayed by RGC activity.

The oscillation-like activity in bullfrog ON-OFF retinal ganglion cell

Oscillatory activity of retinal ganglion cell (RGC) has been observed in various species. It was reported such oscillatory activity is raised within large neural network and involved in retinal information coding. In the present research, we found an oscillation-like activity in ON-OFF RGC of bullfrog retina, and studied the mechanisms underlying the ON and OFF activities respectively. Pharmacological experiments revealed that the oscillation-like activity patterns in both ON and OFF pathways were abolished by GABA receptor antagonists, indicating GABAergic inhibition is essential for generating them. At the meantime, such activities in the ON and OFF pathways showed different responses to several other applied drugs. The oscillation-like pattern in the OFF pathway was abolished by glycine receptor antagonist or gap junction blocker, whereas that in the ON pathway was not affected. Furthermore, the blockade of the ON pathway by metabotropic glutamate receptor agonist led to suppression of the oscillation-like pattern in the OFF pathway. These results suggest that the ON pathway has modulatory effect on the oscillation-like activity in the OFF pathway. Therefore, the mechanisms underlying the oscillation-like activities in the ON and OFF pathways are different: the oscillation-like activity in the ON pathway is likely caused by GABAergic amacrine cell network, while that in the OFF pathway needs the contributions of GABAergic and glycinergic amacrine cell network, as well as gap junction connections.

GlyRα2, not GlyRα3, modulates the receptive field surround of OFF retinal ganglion cells

Receptive fields (RFs) of most retinal ganglion cells (RGCs) consist of an excitatory center and suppressive surround. The RF center arises from the summation of excitatory bipolar cell glutamatergic inputs, whereas the surround arises from lateral inhibitory inputs. In the retina, both gamma amino butyric acid (GABA) and glycine are inhibitory neurotransmitters. A clear role for GABAergic inhibition modulating the RGC RF surround has been demonstrated across species. Glycinergic inhibition is more commonly associated with RF center modulation, although there is some evidence that it may contribute to the RF surround. The synaptic glycinergic chloride channels are formed by three homomeric β and two homomeric α subunits that can be glycine receptor (GlyR) α1, α2, α3, or α4. GlyRα composition is responsible for currents with distinct decay kinetics. Their expression within the inner plexiform laminae and neuronal subtypes also differ. We studied the role of GlyR subunit selective modulation of RGC RF surrounds, using mice lacking GlyRα2 (Glra2 -/-), GlyRα3 (Glra3 -/-), or both (Glra2/3 -/-). We chose this molecular genetic approach instead of pharmacological manipulation because there are no subunit selective antagonists and strychnine blocks all GlyRs. Comparisons of annulus-evoked responses among wild type (WT) and GlyRα knockouts (Glra2 -/-, Glra3 -/- and Glra2/3 -/-) show that GlyRα2 inhibition enhances RF surround suppression and post-stimulus excitation in only WT OFF RGCs. Similarities in the responses in Glra2 -/- and Glra2/3 -/- RGCs verify these conclusions. Based on previous and current data, we propose that GlyRα2-mediated input uses a crossover inhibitory circuit. Further, we suggest that GlyRα2 modulates the OFF RGC RF center and surround independently. In summary, our results define a selective GlyR subunit-specific control of RF surround suppression in OFF RGCs.

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.

Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina

When visual contrast changes, retinal ganglion cells adapt by adjusting their sensitivity as well as their temporal filtering characteristics. The latter has classically been described by contrast-induced gain changes that depend on temporal frequency. Here, we explored a new perspective on contrast-induced changes in temporal filtering by using spike-triggered covariance analysis to extract multiple parallel temporal filters for individual ganglion cells. Based on multielectrode-array recordings from ganglion cells in the isolated salamander retina, we found that contrast adaptation of temporal filtering can largely be captured by contrast-invariant sets of filters with contrast-dependent weights. Moreover, differences among the ganglion cells in the filter sets and their contrast-dependent contributions allowed us to phenomenologically distinguish three types of filter changes. The first type is characterized by newly emerging features at higher contrast, which can be reproduced by computational models that contain response-triggered gain-control mechanisms. The second type follows from stronger adaptation in the Off pathway as compared to the On pathway in On-Off-type ganglion cells. Finally, we found that, in a subset of neurons, contrast-induced filter changes are governed by particularly strong spike-timing dynamics, in particular by pronounced stimulus-dependent latency shifts that can be observed in these cells. Together, our results show that the contrast dependence of temporal filtering in retinal ganglion cells has a multifaceted phenomenology and that a multi-filter analysis can provide a useful basis for capturing the underlying signal-processing dynamics.

Our sensory systems have to process stimuli under a wide range of environmental conditions. To cope with this challenge, the involved neurons adapt by adjusting their signal processing to the recently encountered intensity range. In the visual system, one finds, for example, that higher visual contrast leads to changes in how visual signals are temporally filtered, making signal processing faster and more band-pass-like at higher contrast. By analyzing signals from neurons in the retina of salamanders, we here found that these adaptation effects can be described by a fixed set of filters, independent of contrast, whose relative contributions change with contrast. Also, we found that different phenomena contribute to this adaptation. In particular, some cells change their relative sensitivity to light increments and light decrements, whereas other cells are influenced by a strong contrast-dependence of the exact timing of their responses. Our results show that contrast adaptation in the retina is not an entirely homogeneous phenomenon, and that models with multiple filters can help in characterizing sensory adaptation.

The neural circuit mechanisms underlying the retinal response to motion reversal

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

Disinhibitory recruitment of NMDA receptor pathways in retina

Glutamate release at bipolar to ganglion cell synapses activates NMDA and AMPA/kainic acid (KA) ionotropic glutamate receptors. Their relative strength determines the output signals of the retina. We found that this balance is tightly regulated by presynaptic inhibition that preferentially suppresses NMDA receptor (NMDAR) activation. In transient ON-OFF neurons, block of GABA and glycine feedback enhanced total NMDAR charge by 35-fold in the ON response and 9-fold in the OFF compared with a 1.7-fold enhancement of AMPA/KA receptors. Blocking only glycine receptors enhanced the NMDAR excitatory postsynaptic current 10-fold in the ON and 2-fold in the OFF pathway. Blocking GABA(A) or GABA(C) receptors (GABA(C)Rs or GABA(A)Rs) produced small changes in total NMDAR charge. When both GABA(A)Rs and GABA(C)Rs were blocked, the total NMDAR charge increased ninefold in the ON and fivefold in the OFF pathway. This exposed a strong GABA(C)R feedback to bipolar cells that was suppressed by serial amacrine cell synapses mediated by GABA(A)Rs. The results indicate that NMDAR currents are large but latent, held in check by dual GABA and glycine presynaptic inhibition. One example of this controlled NMDAR activation is the cross talk between ON and OFF pathways. Blocking the ON pathway increased NMDAR relative strength in the OFF pathway. Stimulus prolongation similarly increased the NMDAR relative strength in the OFF response. This NMDAR enhancement was produced by a diminution in GABA and glycine feedback. Thus the retinal network recruits NMDAR pathways through presynaptic disinhibition.

The projective field of retinal bipolar cells and its modulation by visual context

The receptive field of a sensory neuron spells out all the receptor inputs it receives. To understand a neuron's role in the circuit, one also needs to know its projective field, namely the outputs it sends to all downstream cells. Here we present the projective fields of the primary excitatory neurons in a sensory circuit. We stimulated single bipolar cells of the salamander retina and recorded simultaneously from a population of ganglion cells. Individual bipolar cell signals diverge through polysynaptic pathways into ganglion cells of many different types and over surprisingly large distance. However, the strength and polarity of the projection depend on the cell types involved. Furthermore, visual stimulation strongly modulates the bipolar cell projective field, in opposite direction for different cell types. In this way, the context from distant parts of the visual field can control the routing of signals in the inner retina.

Alert response to motion onset in the retina

Previous studies have shown that motion onset is very effective at capturing attention and is more salient than smooth motion. Here, we find that this salience ranking is present already in the firing rate of retinal ganglion cells. By stimulating the retina with a bar that appears, stays still, and then starts moving, we demonstrate that a subset of salamander retinal ganglion cells, fast OFF cells, responds significantly more strongly to motion onset than to smooth motion. We refer to this phenomenon as an alert response to motion onset. We develop a computational model that predicts the time-varying firing rate of ganglion cells responding to the appearance, onset, and smooth motion of a bar. This model, termed the adaptive cascade model, consists of a ganglion cell that receives input from a layer of bipolar cells, represented by individual rectified subunits. Additionally, both the bipolar and ganglion cells have separate contrast gain control mechanisms. This model captured the responses to our different motion stimuli over a wide range of contrasts, speeds, and locations. The alert response to motion onset, together with its computational model, introduces a new mechanism of sophisticated motion processing that occurs early in the visual system.

Light-evoked lateral GABAergic inhibition at single bipolar cell synaptic terminals is driven by distinct retinal microcircuits

Inhibitory amacrine cells (ACs) filter visual signals crossing the retina by modulating the excitatory, glutamatergic output of bipolar cells (BCs) on multiple temporal and spatial scales. Reciprocal feedback from ACs provides focal inhibition that is temporally locked to the activity of presynaptic BC activity, whereas lateral feedback originates from ACs excited by distant BCs. These distinct feedback mechanisms permit temporal and spatial computation at BC terminals. Here, we used a unique preparation to study light-evoked IPSCs recorded from axotomized terminals of ON-type mixed rod/cone BCs (Mb) in goldfish retinal slices. In this preparation, light-evoked IPSCs could only reach axotomized BC terminals via the lateral feedback pathway, allowing us to study lateral feedback in the absence of overlapping reciprocal feedback components. We found that light evokes ON and OFF lateral IPSCs (L-IPSCs) in Mb terminals having different temporal patterns and conveyed via distinct retinal pathways. The relative contribution of rods versus cones to ON and OFF L-IPSCs was light intensity dependent. ACs presynaptic to Mb BC terminals received inputs via AMPA/KA- and NMDA-type receptors in both the ON and OFF pathways, and used TTX-sensitive sodium channels to boost signal transfer along their processes. ON and OFF L-IPSCs, like reciprocal feedback IPSCs, were mediated by both GABA(A) and GABA(C) receptors. However, our results suggest that lateral and reciprocal feedback do not cross-depress each other, and are therefore mediated by distinct populations of ACs. These findings demonstrate that retinal inhibitory circuits are highly specialized to modulate BC output at different light intensities.

GABA(B) receptor feedback regulation of bipolar cell transmitter release

GABAergic amacrine cell feedback to bipolar cells in retina has been described, activating both GABA(A) and GABA(C) receptors. We explored whether metabotropic GABA(B) receptors also participate in this feedback pathway. CGP55845, a potent GABA(B) receptor antagonist, was employed to determine the endogenous role of these receptors. Ganglion cell EPSCs and IPSCs were monitored to measure the output of bipolar and amacrine cells. Using the tiger salamander slice preparation, we found that GABA(B) receptor pathways regulate bipolar cell release directly and indirectly. In the direct pathway, the GABA(B) receptor antagonist reduces EPSC amplitude, indicating that GABA(B) receptors cause enhanced glutamate release from bipolar cells to one set of ganglion cells. In the indirect pathway, the GABA(B) receptor antagonist reduces EPSC amplitude in another set of ganglion cells. The indirect pathway is only evident when GABA(A) receptors are inhibited, and is blocked by a glycine receptor antagonist. Thus, this second feedback pathway involves direct glycine feedback to the bipolar cell and this glycinergic amacrine cell is suppressed by GABAergic amacrine cells, through both GABA(A) and GABA(B) but not GABA(C) receptors. Overall, GABA(B) receptors do contribute to feedback regulation of bipolar cell transmitter release. However, unlike the ionotropic GABA receptor pathways, the metabotropic GABA receptor pathways act to enhance bipolar cell transmitter release. Furthermore, there are three discrete subsets of bipolar cell output regulated by GABA(B) receptor feedback (direct, indirect and null), implying three distinct, non-overlapping bipolar cell to ganglion cell circuits.

Effects of histamine on light responses of amacrine cells in tiger salamander retina

Using immunofluorescence, we showed that histamine receptor 1 is expressed by horizontal cell axons and a subset of amacrine cells in the tiger salamander retina. The effects of histamine on light responses of amacrine cells were studied in slice preparations. Histamine modulated the light responses of many salamander amacrine cells, depending upon the morphological type. The most pronounced effects of histamine were decreases in the light responses of broadly stratified amacrine cells, particularly those having medium-sized dendritic field diameters. To determine whether the effects of histamine were direct, Co(++) was substituted for Ca(++) in the extracellular medium to block synaptic transmission. Histamine still affected broadly stratified amacrine cells, but not narrowly stratified amacrine cells under these conditions. Taken together, these findings suggest that inhibitory interactions between strata of the IPL and within the classical receptive fields of the ganglion cells would be particularly sensitive to histamine released from retinopetal axons.

Six different roles for crossover inhibition in the retina: correcting the nonlinearities of synaptic transmission

Early retinal studies categorized ganglion cell behavior as either linear or nonlinear and rectifying as represented by the familiar X- and Y-type ganglion cells in cat. Nonlinear behavior is in large part a consequence of the rectifying nonlinearities inherent in synaptic transmission. These nonlinear signals underlie many special functions in retinal processing, including motion detection, motion in motion, and local edge detection. But linear behavior is also required for some visual processing tasks. For these tasks, the inherently nonlinear signals are "linearized" by "crossover inhibition." Linearization utilizes a circuitry whereby nonlinear ON inhibition adds with nonlinear OFF excitation or ON excitation adds with OFF inhibition to generate a more linear postsynaptic voltage response. Crossover inhibition has now been measured in most bipolar, amacrine, and ganglion cells. Functionally crossover inhibition enhances edge detection, allows ganglion cells to recognize luminance-neutral patterns with their receptive fields, permits ganglion cells to distinguish contrast from luminance, and maintains a more constant conductance during the light response. In some cases, crossover extends the operating range of cone-driven OFF ganglion cells into the scotopic levels. Crossover inhibition is also found in neurons of the lateral geniculate nucleus and V1.

Receptive fields of retinal bipolar cells are mediated by heterogeneous synaptic circuitry

Center-surround antagonistic receptive field (CSARF) organization is the basic synaptic circuit that serves as elementary building blocks for spatial information processing in the visual system. Cells with such receptive fields converge into higher-order visual neurons to form more complex receptive fields. Retinal bipolar cells (BCs) are the first neurons along the visual pathway that exhibit CSARF organization. BCs have been classified according to their response polarities and rod/cone inputs, and they project signals to target cells at different sublaminae of the inner plexiform layer. On the other hand, CSARFs of various types of BCs have been assumed be organized the same way. Here we examined center and surround responses of over 250 salamander BCs, and demonstrated that different types of BCs exhibit different patterns of dye coupling, receptive field center size, surround response strength, and conductance changes associated with center and surround responses. We show that BC receptive field center sizes varied with the degree of BC-BC coupling, and that surround responses of different BCs are mediated by different combinations of five lateral synaptic pathways mediated by the horizontal cells and amacrine cells. The finding of heterogeneous receptive field circuitry fundamentally challenges the common assumption that CSARFs of different subtypes of visual neurons are mediated by the same synaptic pathways. BCs carrying different visual signals use different synaptic circuits to process spatial information, allowing shape and contrast computation be differentially modulated by various lighting and adaptation conditions.

Comparisons of structural and functional abnormalities in mouse b-wave mutants

In the most simplistic view, the retinal circuit can be divided into vertical excitatory pathways that use glutamate as their neurotransmitter and lateral inhibitory pathways in the outer and inner synaptic layers that modulate excitation via glycine and GABA. Within the vertical excitatory pathways, the visual signal is initiated in the rod, cone or both photoreceptors, depending on the adaptation state of the retina. This signal is transmitted to the rest of the retina through the bipolar cells, which can be subdivided based on: the photoreceptor that provides their input, their dendritic and axonal morphology, and the polarity of their response evoked by a luminance increment, e.g. depolarizing or hyperpolarizing responses. The polarity of this response is controlled by the type of glutamatergic postsynaptic receptor that is expressed on their dendritic terminals. Hyperpolarizing bipolar cells express AMPA/kainate receptors, whereas depolarizing bipolar cells (DBCs) express the metabotropic glutamate receptor 6 (Grm6). The electroretinogram (ERG) is a non-invasive method used to assess overall retinal function. The initiation of the visual signal in the photoreceptors is reflected in the ERG a-wave and the ensuing depolarization of DBCs in the b-wave. When there is failure of signal transmission from photoreceptors to DBCs or signalling within DBCs, the ERG a-wave is present, while the b-wave is absent or significantly reduced. This ERG phenotype has been found in the human population and is referred to as congenital stationary night blindness. Until recently, it had been assumed that the absence of a b-wave was indicative of a lack of signalling through the On pathway, leaving the Off pathway unaffected. Here we review recent findings that demonstrate that many mouse mutants share a no b-wave ERG phenotype but their retinal morphology and RGC responses differ significantly, suggesting very different effects of the underlying mutations on output from the DBCs to the rest of the retinal circuit.

The ON–OFF dichotomy in visual processing: From receptors to perception

Vision scientists long ago pointed to black and white as separate sensations and saw confirmation in the fact that in the absence of light, one perceives the visual field as gray against which the negative after-image of a bright light appeared blacker. The first recordings from optic nerve fibers in vertebrates revealed ON and OFF signals, later associated with separate streams, arising already at the synapse between receptors and bipolar cells. These can be identified anatomically and physiologically and remain distinct all the way to the lateral geniculate nucleus, whose fibers form the input to the primary visual cortex. The dichotomy has been probed by electroretinography and analyzed by means of pharmacological agents and dysfunction due to genetic causes. The bi- rather than a unidirectional nature of the retinal output has advantages in allowing small signals to remain prominent over a greater dynamic range. The two streams innervate cortical neurons in a push-pull manner, generating receptive fields with spatial sensitivity profiles featuring ON and OFF subregions. Manifestations of the dichotomy appear in a variety of simple visual discriminations where there are often profound threshold differences in patterns with same polarity as compared with mixed contrast-polarity components. But even at levels in which the spatial, contrast and color attributes have already been securely established and black and white elements participate equally, a categorical difference between blackness and whiteness of a percept persists. It is an opponency, akin to the ones in the color domain, derived from the original ON and OFF signals and subsequently bound with the other attributes to yield a feature's unitary percept.