Divergence of visual channels in the inner retina

Cell firing between ON alpha retinal ganglion cells and coupled amacrine cells in the mouse retina

Gap junctions are channels that allow for direct transmission of electrical signals between cells. However, the ability of one cell to be impacted or controlled by other cells through gap junctions remains unclear. In this study, heterocellular coupling between ON α retinal ganglion cells (α-RGCs) and displaced amacrine cells (ACs) in the mouse retina was used as a model. The impact of the extent of coupling of interconnected ACs on the synchronized firing between coupled ON α-RGC-AC pair was investigated using the dopamine 1 receptor (D1R) antagonist-SCH23390 and agonist-SKF38393. It was observed that the synchronized firing between the ON α-RGC-ACs pairs was increased by the D1R antagonist SCH23390, whereas it was eradicated by the agonist SKF38393. Subsequently, the signaling drive was investigated by infecting coupled ON α-RGC-AC pairs with the channelrhodopsin-2(ChR2) mutation L132C engineered to enhance light sensitivities. The results demonstrated that the spikes of ON α-RGCs (without ChR2) could be triggered by ACs (with ChR2) through the gap junction, and vice versa. Furthermore, it was observed that ON α-RGCs stimulated with 3-10 Hz currents by whole cell patch could elicit synchronous spikes in the coupled ACs, and vice versa. This provided direct evidence that the firing of one cell could be influenced by another cell through gap junctions. However, this phenomenon was not observed between OFF α-RGC pairs. The study implied that the synchronized firing between ON α-RGC-AC pairs could potentially be affected by the coupling of interconnected ACs. Additionally, one cell type could selectively control the firing of another cell type, thereby forcefully transmitting information. The key role of gap junctions in synchronizing firing and driving cells between α-RGCs and coupled ACs in the mouse retina was highlighted.NEW & NOTEWORTHY This study investigates the role of gap junctions in transmitting electrical signals between cells and their potential for cell control. Using ON α retinal ganglion cells (α-RGCs) and amacrine cells (ACs) in the mouse retina, the researchers find that the extent of coupling between ACs affects synchronized firing. Bidirectional signaling occurs between ACs and ON α-RGCs through gap junctions.

Applying Super-Resolution and Tomography Concepts to Identify Receptive Field Subunits in the Retina

Spatially nonlinear stimulus integration by retinal ganglion cells lies at the heart of various computations performed by the retina. It arises from the nonlinear transmission of signals that ganglion cells receive from bipolar cells, which thereby constitute functional subunits within a ganglion cell's receptive field. Inferring these subunits from recorded ganglion cell activity promises a new avenue for studying the functional architecture of the retina. This calls for efficient methods, which leave sufficient experimental time to leverage the acquired knowledge for further investigating identified subunits. Here, we combine concepts from super-resolution microscopy and computed tomography and introduce super-resolved tomographic reconstruction (STR) as a technique to efficiently stimulate and locate receptive field subunits. Simulations demonstrate that this approach can reliably identify subunits across a wide range of model variations, and application in recordings of primate parasol ganglion cells validates the experimental feasibility. STR can potentially reveal comprehensive subunit layouts within only a few tens of minutes of recording time, making it ideal for online analysis and closed-loop investigations of receptive field substructure in retina recordings.

Stimulus invariant aspects of the retinal code drive discriminability of natural scenes

Everything that the brain sees must first be encoded by the retina, which maintains a reliable representation of the visual world in many different, complex natural scenes while also adapting to stimulus changes. This study quantifies whether and how the brain selectively encodes stimulus features about scene identity in complex naturalistic environments. While a wealth of previous work has dug into the static and dynamic features of the population code in retinal ganglion cells, less is known about how populations form both flexible and reliable encoding in natural moving scenes. We record from the larval salamander retina responding to five different natural movies, over many repeats, and use these data to characterize the population code in terms of single-cell fluctuations in rate and pairwise couplings between cells. Decomposing the population code into independent and cell-cell interactions reveals how broad scene structure is encoded in the retinal output. while the single-cell activity adapts to different stimuli, the population structure captured in the sparse, strong couplings is consistent across natural movies as well as synthetic stimuli. We show that these interactions contribute to encoding scene identity. We also demonstrate that this structure likely arises in part from shared bipolar cell input as well as from gap junctions between retinal ganglion cells and amacrine cells.

Gap junctions fine-tune ganglion cell signals to equalize response kinetics within a given electrically coupled array

Retinal ganglion cells (RGCs) summate inputs and forward a spike train code to the brain in the form of either maintained spiking (sustained) or a quickly decaying brief spike burst (transient). We report diverse response transience values across the RGC population and, contrary to the conventional transient/sustained scheme, responses with intermediary characteristics are the most abundant. Pharmacological tests showed that besides GABAergic inhibition, gap junction (GJ)-mediated excitation also plays a pivotal role in shaping response transience and thus visual coding. More precisely GJs connecting RGCs to nearby amacrine and RGCs play a defining role in the process. These GJs equalize kinetic features, including the response transience of transient OFF alpha (tOFFα) RGCs across a coupled array. We propose that GJs in other coupled neuron ensembles in the brain are also critical in the harmonization of response kinetics to enhance the population code and suit a corresponding task.

How Does the Inner Retinal Network Shape the Ganglion Cells Receptive Field? A Computational Study

We consider a model of basic inner retinal connectivity where bipolar and amacrine cells interconnect and both cell types project onto ganglion cells, modulating their response output to the brain visual areas. We derive an analytical formula for the spatiotemporal response of retinal ganglion cells to stimuli, taking into account the effects of amacrine cells inhibition. This analysis reveals two important functional parameters of the network: (1) the intensity of the interactions between bipolar and amacrine cells and (2) the characteristic timescale of these responses. Both parameters have a profound combined impact on the spatiotemporal features of retinal ganglion cells' responses to light. The validity of the model is confirmed by faithfully reproducing pharmacogenetic experimental results obtained by stimulating excitatory DREADDs (Designer Receptors Exclusively Activated by Designer Drugs) expressed on ganglion cells and amacrine cells' subclasses, thereby modifying the inner retinal network activity to visual stimuli in a complex, entangled manner. Our mathematical model allows us to explore and decipher these complex effects in a manner that would not be feasible experimentally and provides novel insights in retinal dynamics.

Distributed feature representations of natural stimuli across parallel retinal pathways

How sensory systems extract salient features from natural environments and organize them across neural pathways is unclear. Combining single-cell and population two-photon calcium imaging in mice, we discover that retinal ON bipolar cells (second-order neurons of the visual system) are divided into two blocks of four types. The two blocks distribute temporal and spatial information encoding, respectively. ON bipolar cell axons co-stratify within each block, but separate laminarly between them (upper block: diverse temporal, uniform spatial tuning; lower block: diverse spatial, uniform temporal tuning). ON bipolar cells extract temporal and spatial features similarly from artificial and naturalistic stimuli. In addition, they differ in sensitivity to coherent motion in naturalistic movies. Motion information is distributed across ON bipolar cells in the upper and the lower blocks, multiplexed with temporal and spatial contrast, independent features of natural scenes. Comparing the responses of different boutons within the same arbor, we find that axons of all ON bipolar cell types function as computational units. Thus, our results provide insights into the visual feature extraction from naturalistic stimuli and reveal how structural and functional organization cooperate to generate parallel ON pathways for temporal and spatial information in the mammalian retina.

A presynaptic source drives differing levels of surround suppression in two mouse retinal ganglion cell types

In early sensory systems, cell-type diversity generally increases from the periphery into the brain, resulting in a greater heterogeneity of responses to the same stimuli. Surround suppression is a canonical visual computation that begins within the retina and is found at varying levels across retinal ganglion cell types. Our results show that heterogeneity in the level of surround suppression occurs subcellularly at bipolar cell synapses. Using single-cell electrophysiology and serial block-face scanning electron microscopy, we show that two retinal ganglion cell types exhibit very different levels of surround suppression even though they receive input from the same bipolar cell types. This divergence of the bipolar cell signal occurs through synapse-specific regulation by amacrine cells at the scale of tens of microns. These findings indicate that each synapse of a single bipolar cell can carry a unique visual signal, expanding the number of possible functional channels at the earliest stages of visual processing.

Spike desensitisation as a mechanism for high-contrast selectivity in retinal ganglion cells

In the vertebrate retina, several dozens of parallel channels relay information about the visual world to the brain. These channels are represented by the different types of retinal ganglion cells (RGCs), whose responses are rendered selective for distinct sets of visual features by various mechanisms. These mechanisms can be roughly grouped into synaptic interactions and cell-intrinsic mechanisms, with the latter including dendritic morphology as well as ion channel complement and distribution. Here, we investigate how strongly ion channel complement can shape RGC output by comparing two mouse RGC types, the well-described ON alpha cell and a little-studied ON cell that is EGFP-labelled in the Igfbp5 mouse line and displays an unusual selectivity for stimuli with high contrast. Using patch-clamp recordings and computational modelling, we show that a higher activation threshold and a pronounced slow inactivation of the voltage-gated Na+ channels contribute to the distinct contrast tuning and transient responses in ON Igfbp5 RGCs, respectively. In contrast, such a mechanism could not be observed in ON alpha cells. This study provides an example for the powerful role that the last stage of retinal processing can play in shaping RGC responses.

Heterogeneous presynaptic receptive fields contribute to directional tuning in starburst amacrine cells

The processing of visual information by retinal starburst amacrine cells (SACs) involves transforming excitatory input from bipolar cells (BCs) into directional calcium output. While previous studies have suggested that an asymmetry in the kinetic properties of BCs along the soma-dendritic axes of the postsynaptic cell could enhance directional tuning at the level of individual branches, it remains unclear whether biologically relevant presynaptic kinetics contribute to direction selectivity (DS) when visual stimulation engages the entire dendritic tree. To address this question, we built multicompartmental models of the bipolar-SAC circuit and trained them to boost directional tuning. We report that despite significant dendritic crosstalk and dissimilar directional preferences along the dendrites that occur during whole-cell stimulation, the rules that guide BC kinetics leading to optimal DS are similar to the single-dendrite condition. To correlate model predictions to empirical findings, we utilized two-photon glutamate imaging to study the dynamics of bipolar release onto ON- and OFF-starburst dendrites in the murine retina. We reveal diverse presynaptic dynamics in response to motion in both BC populations; algorithms trained on the experimental data suggested that the differences in the temporal release kinetics are likely to correspond to heterogeneous receptive field properties among the different BC types, including the spatial extent of the center and surround components. In addition, we demonstrate that circuit architecture composed of presynaptic units with experimentally recorded dynamics could enhance directional drive but not to levels that replicate empirical findings, suggesting other DS mechanisms are required to explain SAC function. Our study provides new insights into the complex mechanisms underlying DS in retinal processing and highlights the potential contribution of presynaptic kinetics to the computation of visual information by SACs.

Regional variation in the organization and connectivity of the first synapse in the primate night vision pathway

Sensitivity of primate daylight vision varies across the visual field. This is attributed to regional variations in cone photoreceptor density and synaptic connectivity of the underlying circuitry. In contrast, we have limited understanding of how synapse organization of the primate night vision pathway changes across space. Using serial electron microscopy, we reconstructed the first synapse of the night vision pathway between rod photoreceptors and second-order neurons, at multiple locations from the central part of the primate retina, fovea, to the periphery. We find that most facets of the rod synapse connectivity vary across retinal regions. However, rod synaptic divergence and convergence patterns do not change in the same manner across locations. Moreover, patterns of rod synapse organization are tightly correlated with photoreceptor density. Such regional heterogeneities revise the connectivity diagram of the primate rod synapse which will shape synapse function and sensitivity of the night vision pathway across visual space.

Heterogeneous presynaptic receptive fields contribute to directional tuning in starburst amacrine cells

The processing of visual information by retinal starburst amacrine cells (SACs) involves transforming excitatory input from bipolar cells (BCs) into directional calcium output. While previous studies have suggested that an asymmetry in the kinetic properties of bipolar cells along the soma-dendritic axes of the postsynaptic cell could enhance directional tuning at the level of individual branches, it remains unclear whether biologically relevant presynaptic kinetics contribute to direction selectivity when visual stimulation engages the entire dendritic tree. To address this question, we built multicompartmental models of the bipolar-SAC circuit and trained them to boost directional tuning. We report that despite significant dendritic crosstalk and dissimilar directional preferences along the dendrites that occur during whole-cell stimulation, the rules that guide BC kinetics leading to optimal directional selectivity are similar to the single-dendrite condition. To correlate model predictions to empirical findings, we utilized two-photon glutamate imaging to study the dynamics of bipolar release onto ON- and OFF-starburst dendrites in the murine retina. We reveal diverse presynaptic dynamics in response to motion in both BC populations; algorithms trained on the experimental data suggested that the differences in the temporal release kinetics are likely to correspond to heterogeneous receptive field (RF) properties among the different BC types, including the spatial extent of the center and surround components. In addition, we demonstrate that circuit architecture composed of presynaptic units with experimentally recorded dynamics could enhance directional drive but not to levels that replicate empirical findings, suggesting other DS mechanisms are required to explain SAC function. Our study provides new insights into the complex mechanisms underlying direction selectivity in retinal processing and highlights the potential contribution of presynaptic kinetics to the computation of visual information by starburst amacrine cells.

All-optical inter-layers functional connectivity investigation in the mouse retina

We developed a multi-unit microscope for all-optical inter-layers circuits interrogation. The system performs two-photon (2P) functional imaging and 2P multiplexed holographic optogenetics at axially distinct planes. We demonstrated the capability of the system to map, in the mouse retina, the functional connectivity between rod bipolar cells (RBCs) and ganglion cells (GCs) by activating single or defined groups of RBCs while recording the evoked response in the GC layer with cell-type specificity and single-cell resolution. We then used a logistic model to probe the functional connectivity between cell types by deriving the "cellular receptive field" describing how RBCs impact each GC type. With the capability to simultaneously image and control neuronal activity at axially distinct planes, the system enables a precise interrogation of multi-layered circuits. Understanding this information transfer is a promising avenue to dissect complex neural circuits and understand the neural basis of computations.

Sensitivity to extracellular potassium underlies type-intrinsic differences in retinal ganglion cell excitability

Neuronal type-specific physiologic heterogeneity can be driven by both extrinsic and intrinsic mechanisms. In retinal ganglion cells (RGCs), which carry visual information from the retina to central targets, evidence suggests intrinsic properties shaping action potential (AP) generation significantly impact the responses of RGCs to visual stimuli. Here, we explored how differences in intrinsic excitability further distinguish two RCG types with distinct presynaptic circuits, alpha ON-sustained (αON-S) cells and alpha OFF-sustained (αOFF-S) cells. We found that αOFF-S RGCs are more excitable to modest depolarizing currents than αON-S RGCs but excitability plateaued earlier as depolarization increased (i.e., depolarization block). In addition to differences in depolarization block sensitivity, the two cell types also produced distinct AP shapes with increasing stimulation. αOFF-S AP width and variability increased with depolarization magnitude, which correlated with the onset of depolarization block, while αON-S AP width and variability remained stable. We then tested if differences in depolarization block observed in αON-S and αOFF-S RGCs were due to sensitivity to extracellular potassium. We found αOFF-S RGCs more sensitive to increased extracellular potassium concentration, which shifted αON-S RGC excitability to that of αOFF-S cells under baseline potassium conditions. Finally, we investigated the influence of the axon initial segment (AIS) dimensions on RGC spiking. We found that the relationship between AIS length and evoked spike rate varied not only by cell type, but also by the strength of stimulation, suggesting AIS structure alone cannot fully explain the observed differences RGC excitability. Thus, sensitivity to extracellular potassium contributes to differences in intrinsic excitability, a key factor that shapes how RGCs encode visual information.

Transience of the Retinal Output Is Determined by a Great Variety of Circuit Elements

Retinal ganglion cells (RGCs) encrypt stimulus features of the visual scene in action potentials and convey them toward higher visual centers in the brain. Although there are many visual features to encode, our recent understanding is that the ~46 different functional subtypes of RGCs in the retina share this task. In this scheme, each RGC subtype establishes a separate, parallel signaling route for a specific visual feature (e.g., contrast, the direction of motion, luminosity), through which information is conveyed. The efficiency of encoding depends on several factors, including signal strength, adaptational levels, and the actual efficacy of the underlying retinal microcircuits. Upon collecting inputs across their respective receptive field, RGCs perform further analysis (e.g., summation, subtraction, weighting) before they generate the final output spike train, which itself is characterized by multiple different features, such as the number of spikes, the inter-spike intervals, response delay, and the rundown time (transience) of the response. These specific kinetic features are essential for target postsynaptic neurons in the brain in order to effectively decode and interpret signals, thereby forming visual perception. We review recent knowledge regarding circuit elements of the mammalian retina that participate in shaping RGC response transience for optimal visual signaling.

Do epidermal keratinocytes have sensory and information processing systems?

It was long considered that the role of epidermal keratinocytes is solely to construct a water-impermeable protective membrane, the stratum corneum, at the uppermost layer of the skin. However, in the last two decades, it has been found that keratinocytes contain multiple sensory systems that detect environmental changes, including mechanical stimuli, sound, visible radiation, electric fields, magnetic fields, temperature and chemical stimuli, and also a variety of receptor molecules associated with olfactory or taste sensation. Moreover, neurotransmitters and their receptors that play crucial roles in the brain are functionally expressed in keratinocytes. Recent studies have demonstrated that excitation of keratinocytes can induce sensory perception in the brain. Here, we review the sensory and information processing capabilities of keratinocytes. We discuss the possibility that epidermal keratinocytes might represent the earliest stage in the development of the brain during the evolution of vertebrates.

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.

Computational and Molecular Properties of Starburst Amacrine Cell Synapses Differ With Postsynaptic Cell Type

A presynaptic neuron can increase its computational capacity by transmitting functionally distinct signals to each of its postsynaptic cell types. To determine whether such computational specialization occurs over fine spatial scales within a neurite arbor, we investigated computation at output synapses of the starburst amacrine cell (SAC), a critical component of the classical direction-selective (DS) circuit in the retina. The SAC is a non-spiking interneuron that co-releases GABA and acetylcholine and forms closely spaced (<5 μm) inhibitory synapses onto two postsynaptic cell types: DS ganglion cells (DSGCs) and neighboring SACs. During dynamic optogenetic stimulation of SACs in mouse retina, whole-cell recordings of inhibitory postsynaptic currents revealed that GABAergic synapses onto DSGCs exhibit stronger low-pass filtering than those onto neighboring SACs. Computational analyses suggest that this filtering difference can be explained primarily by presynaptic properties, rather than those of the postsynaptic cells per se. Consistent with functionally diverse SAC presynapses, blockade of N-type voltage-gated calcium channels abolished GABAergic currents in SACs but only moderately reduced GABAergic and cholinergic currents in DSGCs. These results jointly demonstrate how specialization of synaptic outputs could enhance parallel processing in a compact interneuron over fine spatial scales. Moreover, the distinct transmission kinetics of GABAergic SAC synapses are poised to support the functional diversity of inhibition within DS circuitry.

Feedback from retinal ganglion cells to the inner retina

Retinal ganglion cells (RGCs) are thought to be strictly postsynaptic within the retina. They carry visual signals from the eye to the brain, but do not make chemical synapses onto other retinal neurons. Nevertheless, they form gap junctions with other RGCs and amacrine cells, providing possibilities for RGC signals to feed back into the inner retina. Here we identified such feedback circuitry in the salamander and mouse retinas. First, using biologically inspired circuit models, we found mutual inhibition among RGCs of the same type. We then experimentally determined that this effect is mediated by gap junctions with amacrine cells. Finally, we found that this negative feedback lowers RGC visual response gain without affecting feature selectivity. The principal neurons of the retina therefore participate in a recurrent circuit much as those in other brain areas, not being a mere collector of retinal signals, but are actively involved in visual computations.

GABAA presynaptic inhibition regulates the gain and kinetics of retinal output neurons

Output signals of neural circuits, including the retina, are shaped by a combination of excitatory and inhibitory signals. Inhibitory signals can act presynaptically on axon terminals to control neurotransmitter release and regulate circuit function. However, it has been difficult to study the role of presynaptic inhibition in most neural circuits due to lack of cell type-specific and receptor type-specific perturbations. In this study, we used a transgenic approach to selectively eliminate GABA_A inhibitory receptors from select types of second-order neurons - bipolar cells - in mouse retina and examined how this affects the light response properties of the well-characterized ON alpha ganglion cell retinal circuit. Selective loss of GABA_A receptor-mediated presynaptic inhibition causes an enhanced sensitivity and slower kinetics of light-evoked responses from ON alpha ganglion cells thus highlighting the role of presynaptic inhibition in gain control and temporal filtering of sensory signals in a key neural circuit in the mammalian retina.

Nonlinear spatial integration in retinal bipolar cells shapes the encoding of artificial and natural stimuli

The retina dissects the visual scene into parallel information channels, which extract specific visual features through nonlinear processing. The first nonlinear stage is typically considered to occur at the output of bipolar cells, resulting from nonlinear transmitter release from synaptic terminals. In contrast, we show here that bipolar cells themselves can act as nonlinear processing elements at the level of their somatic membrane potential. Intracellular recordings from bipolar cells in the salamander retina revealed frequent nonlinear integration of visual signals within bipolar cell receptive field centers, affecting the encoding of artificial and natural stimuli. These nonlinearities provide sensitivity to spatial structure below the scale of bipolar cell receptive fields in both bipolar and downstream ganglion cells and appear to arise at the excitatory input into bipolar cells. Thus, our data suggest that nonlinear signal pooling starts earlier than previously thought: that is, at the input stage of bipolar cells.

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Some retinal bipolar cells represent visual contrast in a nonlinear fashion

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These bipolar cells also nonlinearly integrate visual signals over space

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The spatial nonlinearity affects the encoding of natural stimuli by bipolar cells

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The nonlinearity results from feedforward input, not from feedback inhibition

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.

Distinct Developmental Mechanisms Act Independently to Shape Biased Synaptic Divergence from an Inhibitory Neuron

Neurons often contact more than one postsynaptic partner type and display stereotypic patterns of synaptic divergence. Such synaptic patterns usually involve some partners receiving more synapses than others. The developmental strategies generating "biased" synaptic distributions remain largely unknown. To gain insight, we took advantage of a compact circuit in the vertebrate retina, whereby the AII amacrine cell (AII AC) provides inhibition onto cone bipolar cell (BC) axons and retinal ganglion cell (RGC) dendrites, but makes the majority of its synapses with the BCs. Using light and electron microscopy, we reconstructed the morphology and connectivity of mouse retinal AII ACs across postnatal development. We found that AII ACs do not elaborate their presynaptic structures, the lobular appendages, until BCs differentiate about a week after RGCs are present. Lobular appendages are present in mutant mice lacking BCs, implying that although synchronized with BC axonal differentiation, presynaptic differentiation of the AII ACs is not dependent on cues from BCs. With maturation, AII ACs maintain a constant number of synapses with RGCs, preferentially increase synaptogenesis with BCs, and eliminate synapses with wide-field amacrine cells. Thus, AII ACs undergo partner type-specific changes in connectivity to attain their mature pattern of synaptic divergence. Moreover, AII ACs contact non-BCs to the same extent in bipolarless retinas, indicating that AII ACs establish partner-type-specific connectivity using diverse mechanisms that operate in parallel but independently.

Defocused Images Change Multineuronal Firing Patterns in the Mouse Retina

Myopia is a major public health problem, affecting one third of the population over 12 years old in the United States and more than 80% of people in Hong Kong. Myopia is attributable to elongation of the eyeball in response to defocused images that alter eye growth and refraction. It is known that the retina can sense the focus of an image, but the effects of defocused images on signaling of population of retinal ganglion cells (RGCs) that account either for emmetropization or refractive errors has still to be elucidated. Thorough knowledge of the underlying mechanisms could provide insight to understanding myopia. In this study, we found that focused and defocused images can change both excitatory and inhibitory conductance of ON alpha, OFF alpha and ON–OFF retinal ganglion cells in the mouse retina. The firing patterns of population of RGCs vary under the different powers of defocused images and can be affected by dopamine receptor agonists/antagonists’ application. OFF-delayed RGCs or displaced amacrine cells (dACs) with time latency of more than 0.3 s had synchrony firing with other RGCs and/or dACs. These spatial synchrony firing patterns between OFF-delayed cell and other RGCs/dACs were significantly changed by defocused image, which may relate to edge detection. The results suggested that defocused images induced changes in the multineuronal firing patterns and whole cell conductance in the mouse retina. The multineuronal firing patterns can be affected by dopamine receptors’ agonists and antagonists. Synchronous firing of OFF-delayed cells is possibly related to edge detection, and understanding of this process may reveal a potential therapeutic target for myopia patients.

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.

Sensory Processing at Ribbon Synapses in the Retina and the Cochlea

In recent years, sensory neuroscientists have made major efforts to dissect the structure and function of ribbon synapses which process sensory information in the eye and ear. This review aims to summarize our current understanding of two key aspects of ribbon synapses: 1) their mechanisms of exocytosis and endocytosis and 2) their molecular anatomy and physiology. Our comparison of ribbon synapses in the cochlea and the retina reveals convergent signaling mechanisms, as well as divergent strategies in different sensory systems.

Spatiotemporally Asymmetric Excitation Supports Mammalian Retinal Motion Sensitivity

The detection of visual motion is a fundamental function of the visual system. How motion speed and direction are computed together at the cellular level, however, remains largely unknown. Here, we suggest a circuit mechanism by which excitatory inputs to direction-selective ganglion cells in the mouse retina become sensitive to the motion speed and direction of image motion. Electrophysiological, imaging, and connectomic analyses provide evidence that the dendrites of ON direction-selective cells receive spatially offset and asymmetrically filtered glutamatergic inputs along motion-preference axis from asymmetrically wired bipolar and amacrine cell types with distinct release dynamics. A computational model shows that, with this spatiotemporal structure, the input amplitude becomes sensitive to speed and direction by a preferred direction enhancement mechanism. Our results highlight the role of an excitatory mechanism in retinal motion computation by which feature selectivity emerges from non-selective inputs.

Bayesian hypothesis testing and experimental design for two-photon imaging data

Variability, stochastic or otherwise, is a central feature of neural activity. Yet the means by which estimates of variation and uncertainty are derived from noisy observations of neural activity is often heuristic, with more weight given to numerical convenience than statistical rigour. For two-photon imaging data, composed of fundamentally probabilistic streams of photon detections, the problem is particularly acute. Here, we present a statistical pipeline for the inference and analysis of neural activity using Gaussian Process regression, applied to two-photon recordings of light-driven activity in ex vivo mouse retina. We demonstrate the flexibility and extensibility of these models, considering cases with non-stationary statistics, driven by complex parametric stimuli, in signal discrimination, hierarchical clustering and other inference tasks. Sparse approximation methods allow these models to be fitted rapidly, permitting them to actively guide the design of light stimulation in the midst of ongoing two-photon experiments.

Defocused Image Changes Signaling of Ganglion Cells in the Mouse Retina

Myopia is a substantial public health problem worldwide. Although it is known that defocused images alter eye growth and refraction, their effects on retinal ganglion cell (RGC) signaling that lead to either emmetropization or refractive errors have remained elusive. This study aimed to determine if defocused images had an effect on signaling of RGCs in the mouse retina. ON and OFF alpha RGCs and ON-OFF RGCs were recorded from adult C57BL/6J wild-type mice. A mono green organic light-emitting display presented images generated by PsychoPy. The defocused images were projected on the retina under a microscope. Dark-adapted mouse RGCs were recorded under different powers of projected defocused images on the retina. Compared with focused images, defocused images showed a significantly decreased probability of spikes. More than half of OFF transient RGCs and ON sustained RGCs showed disparity in responses to the magnitude of plus and minus optical defocus (although remained RGCs we tested exhibited similar response to both types of defocus). ON and OFF units of ON-OFF RGCs also responded differently in the probability of spikes to defocused images and spatial frequency images. After application of a gap junction blocker, the probability of spikes of RGCs decreased with the presence of optical defocused image. At the same time, the RGCs also showed increased background noise. Therefore, defocused images changed the signaling of some ON and OFF alpha RGCs and ON-OFF RGCs in the mouse retina. The process may be the first step in the induction of myopia development. It appears that gap junctions also play a key role in this process.

Functional characterization of retinal ganglion cells using tailored nonlinear modeling

The mammalian retina encodes the visual world in action potentials generated by 20-50 functionally and anatomically-distinct types of retinal ganglion cell (RGC). Individual RGC types receive synaptic input from distinct presynaptic circuits; therefore, their responsiveness to specific features in the visual scene arises from the information encoded in synaptic input and shaped by postsynaptic signal integration and spike generation. Unfortunately, there is a dearth of tools for characterizing the computations reflected in RGC spike output. Therefore, we developed a statistical model, the separable Nonlinear Input Model, to characterize the excitatory and suppressive components of RGC receptive fields. We recorded RGC responses to a correlated noise ("cloud") stimulus in an in vitro preparation of mouse retina and found that our model accurately predicted RGC responses at high spatiotemporal resolution. It identified multiple receptive fields reflecting the main excitatory and suppressive components of the response of each neuron. Significantly, our model accurately identified ON-OFF cells and distinguished their distinct ON and OFF receptive fields, and it demonstrated a diversity of suppressive receptive fields in the RGC population. In total, our method offers a rich description of RGC computation and sets a foundation for relating it to retinal circuitry.

A Retinal Circuit Generating a Dynamic Predictive Code for Oriented Features

Sensory systems must reduce the transmission of redundant information to function efficiently. One strategy is to continuously adjust the sensitivity of neurons to suppress responses to common features of the input while enhancing responses to new ones. Here we image the excitatory synaptic inputs and outputs of retinal ganglion cells to understand how such dynamic predictive coding is implemented in the analysis of spatial patterns. Synapses of bipolar cells become tuned to orientation through presynaptic inhibition, generating lateral antagonism in the orientation domain. Individual ganglion cells receive excitatory synapses tuned to different orientations, but feedforward inhibition generates a high-pass filter that only transmits the initial activation of these inputs, removing redundancy. These results demonstrate how a dynamic predictive code can be implemented by circuit motifs common to many parts of the brain.

Functional Diversity in the Retina Improves the Population Code

Within a given brain region, individual neurons exhibit a wide variety of different feature selectivities. Here, we investigated the impact of this extensive functional diversity on the population neural code. Our approach was to build optimal decoders to discriminate among stimuli using the spiking output of a real, measured neural population and compare its performance against a matched, homogeneous neural population with the same number of cells and spikes. Analyzing large populations of retinal ganglion cells, we found that the real, heterogeneous population can yield a discrimination error lower than the homogeneous population by several orders of magnitude and consequently can encode much more visual information. This effect increases with population size and with graded degrees of heterogeneity. We complemented these results with an analysis of coding based on the Chernoff distance, as well as derivations of inequalities on coding in certain limits, from which we can conclude that the beneficial effect of heterogeneity occurs over a broad set of conditions. Together, our results indicate that the presence of functional diversity in neural populations can enhance their coding fidelity appreciably. A noteworthy outcome of our study is that this effect can be extremely strong and should be taken into account when investigating design principles for neural circuits.

Synaptic Convergence Patterns onto Retinal Ganglion Cells Are Preserved despite Topographic Variation in Pre- and Postsynaptic Territories

Sensory processing can be tuned by a neuron's integration area, the types of inputs, and the proportion and number of connections with those inputs. Integration areas often vary topographically to sample space differentially across regions. Here, we highlight two visual circuits in which topographic changes in the postsynaptic retinal ganglion cell (RGC) dendritic territories and their presynaptic bipolar cell (BC) axonal territories are either matched or unmatched. Despite this difference, in both circuits, the proportion of inputs from each BC type, i.e., synaptic convergence between specific BCs and RGCs, remained constant across varying dendritic territory sizes. Furthermore, synapse density between BCs and RGCs was invariant across topography. Our results demonstrate a wiring design, likely engaging homotypic axonal tiling of BCs, that ensures consistency in synaptic convergence between specific BC types onto their target RGCs while enabling independent regulation of pre- and postsynaptic territory sizes and synapse number between cell pairs.

Inferring hidden structure in multilayered neural circuits

A central challenge in sensory neuroscience involves understanding how neural circuits shape computations across cascaded cell layers. Here we attempt to reconstruct the response properties of experimentally unobserved neurons in the interior of a multilayered neural circuit, using cascaded linear-nonlinear (LN-LN) models. We combine non-smooth regularization with proximal consensus algorithms to overcome difficulties in fitting such models that arise from the high dimensionality of their parameter space. We apply this framework to retinal ganglion cell processing, learning LN-LN models of retinal circuitry consisting of thousands of parameters, using 40 minutes of responses to white noise. Our models demonstrate a 53% improvement in predicting ganglion cell spikes over classical linear-nonlinear (LN) models. Internal nonlinear subunits of the model match properties of retinal bipolar cells in both receptive field structure and number. Subunits have consistently high thresholds, supressing all but a small fraction of inputs, leading to sparse activity patterns in which only one subunit drives ganglion cell spiking at any time. From the model’s parameters, we predict that the removal of visual redundancies through stimulus decorrelation across space, a central tenet of efficient coding theory, originates primarily from bipolar cell synapses. Furthermore, the composite nonlinear computation performed by retinal circuitry corresponds to a boolean OR function applied to bipolar cell feature detectors. Our methods are statistically and computationally efficient, enabling us to rapidly learn hierarchical non-linear models as well as efficiently compute widely used descriptive statistics such as the spike triggered average (STA) and covariance (STC) for high dimensional stimuli. This general computational framework may aid in extracting principles of nonlinear hierarchical sensory processing across diverse modalities from limited data.

Computation in neural circuits arises from the cascaded processing of inputs through multiple cell layers. Each of these cell layers performs operations such as filtering and thresholding in order to shape a circuit’s output. It remains a challenge to describe both the computations and the mechanisms that mediate them given limited data recorded from a neural circuit. A standard approach to describing circuit computation involves building quantitative encoding models that predict the circuit response given its input, but these often fail to map in an interpretable way onto mechanisms within the circuit. In this work, we build two layer linear-nonlinear cascade models (LN-LN) in order to describe how the retinal output is shaped by nonlinear mechanisms in the inner retina. We find that these LN-LN models, fit to ganglion cell recordings alone, identify filters and nonlinearities that are readily mapped onto individual circuit components inside the retina, namely bipolar cells and the bipolar-to-ganglion cell synaptic threshold. This work demonstrates how combining simple prior knowledge of circuit properties with partial experimental recordings of a neural circuit’s output can yield interpretable models of the entire circuit computation, including parts of the circuit that are hidden or not directly observed in neural recordings.

Assembly and maintenance of GABAergic and Glycinergic circuits in the mammalian nervous system

Inhibition in the central nervous systems (CNS) is mediated by two neurotransmitters: gamma-aminobutyric acid (GABA) and glycine. Inhibitory synapses are generally GABAergic or glycinergic, although there are synapses that co-release both neurotransmitter types. Compared to excitatory circuits, much less is known about the cellular and molecular mechanisms that regulate synaptic partner selection and wiring patterns of inhibitory circuits. Recent work, however, has begun to fill this gap in knowledge, providing deeper insight into whether GABAergic and glycinergic circuit assembly and maintenance rely on common or distinct mechanisms. Here we summarize and contrast the developmental mechanisms that regulate the selection of synaptic partners, and that promote the formation, refinement, maturation and maintenance of GABAergic and glycinergic synapses and their respective wiring patterns. We highlight how some parts of the CNS demonstrate developmental changes in the type of inhibitory transmitter or receptor composition at their inhibitory synapses. We also consider how perturbation of the development or maintenance of one type of inhibitory connection affects other inhibitory synapse types in the same circuit. Mechanistic insight into the development and maintenance of GABAergic and glycinergic inputs, and inputs that co-release both these neurotransmitters could help formulate comprehensive therapeutic strategies for treating disorders of synaptic inhibition.

Formulation and Implementation of Nonlinear Integral Equations to Model Neural Dynamics Within the Vertebrate Retina

Existing computational models of the retina often compromise between the biophysical accuracy and a hardware-adaptable methodology of implementation. When compared to the current modes of vision restoration, algorithmic models often contain a greater correlation between stimuli and the affected neural network, but lack physical hardware practicality. Thus, if the present processing methods are adapted to complement very-large-scale circuit design techniques, it is anticipated that it will engender a more feasible approach to the physical construction of the artificial retina. The computational model presented in this research serves to provide a fast and accurate predictive model of the retina, a deeper understanding of neural responses to visual stimulation, and an architecture that can realistically be transformed into a hardware device. Traditionally, implicit (or semi-implicit) ordinary differential equations (OES) have been used for optimal speed and accuracy. We present a novel approach that requires the effective integration of different dynamical time scales within a unified framework of neural responses, where the rod, cone, amacrine, bipolar, and ganglion cells correspond to the implemented pathways. Furthermore, we show that adopting numerical integration can both accelerate retinal pathway simulations by more than 50% when compared with traditional ODE solvers in some cases, and prove to be a more realizable solution for the hardware implementation of predictive retinal models.

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

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

Electrical receptive fields of retinal ganglion cells: Influence of presynaptic neurons

Implantable retinal stimulators activate surviving neurons to restore a sense of vision in people who have lost their photoreceptors through degenerative diseases. Complex spatial and temporal interactions occur in the retina during multi-electrode stimulation. Due to these complexities, most existing implants activate only a few electrodes at a time, limiting the repertoire of available stimulation patterns. Measuring the spatiotemporal interactions between electrodes and retinal cells, and incorporating them into a model may lead to improved stimulation algorithms that exploit the interactions. Here, we present a computational model that accurately predicts both the spatial and temporal nonlinear interactions of multi-electrode stimulation of rat retinal ganglion cells (RGCs). The model was verified using in vitro recordings of ON, OFF, and ON-OFF RGCs in response to subretinal multi-electrode stimulation with biphasic pulses at three stimulation frequencies (10, 20, 30 Hz). The model gives an estimate of each cell’s spatiotemporal electrical receptive fields (ERFs); i.e., the pattern of stimulation leading to excitation or suppression in the neuron. All cells had excitatory ERFs and many also had suppressive sub-regions of their ERFs. We show that the nonlinearities in observed responses arise largely from activation of presynaptic interneurons. When synaptic transmission was blocked, the number of sub-regions of the ERF was reduced, usually to a single excitatory ERF. This suggests that direct cell activation can be modeled accurately by a one-dimensional model with linear interactions between electrodes, whereas indirect stimulation due to summated presynaptic responses is nonlinear.

Implantable neural stimulation devices are being widely used and clinically tested for the restoration of lost function (e.g. cochlear implants) and the treatment of neurological disorders. Smart devices that can combine sensing and stimulation will dramatically improve future patient outcomes. To this end, mathematical models that can accurately predict neural responses to electrical stimulation will be critical for the development of smart stimulation devices. Here, we demonstrate a model that predicts neural responses to simultaneous stimulation across multiple electrodes in the retina. We show that the activation of presynaptic neurons leads to nonlinearities in the responses of postsynaptic retinal ganglion cells. The model is accurate and is applicable to a wide range of neural stimulation devices.

Electrical Stimulation of the Retina to Produce Artificial Vision

Retinal prostheses aim to restore vision to blind individuals suffering from retinal diseases such as retinitis pigmentosa and age-related macular degeneration. These devices function by electrically stimulating surviving retinal neurons, whose activation is interpreted by the brain as a visual percept. Many prostheses are currently under development. They are categorized as epiretinal, subretinal, and suprachoroidal prostheses on the basis of the placement of the stimulating microelectrode array. Each can activate ganglion cells through direct or indirect stimulation. The response of retinal neurons to these modes of stimulation are discussed in detail and are placed in context of the visual percept they are likely to evoke. This article further reviews challenges faced by retinal prosthesis and discusses potential solutions to address them.

Diverse inhibitory and excitatory mechanisms shape temporal tuning in transient OFF α ganglion cells in the rabbit retina

KEY POINTS

Neurons combine excitatory and inhibitory signals to perform computations. In the retina, interactions between excitation and inhibition enable neurons to detect specific visual features. We describe how several excitatory and inhibitory mechanisms work together to allow transient OFF α ganglion cells in the rabbit retina to respond selectively to high temporal frequencies and thus detect faster image motion. The weightings of these different mechanisms change with the contrast and spatiotemporal properties of the visual input, and thereby support temporal tuning in α cells over a range of visual conditions. The results help us understand how ganglion cells selectively integrate excitatory and inhibitory signals to extract specific information from the visual input.

ABSTRACT

The 20 to 30 types of ganglion cell in the mammalian retina represent parallel signalling pathways that convey different information to the brain. α ganglion cells are selective for high temporal frequencies in visual inputs, which makes them particularly sensitive to rapid motion. Although α ganglion cells have been studied in several species, the synaptic basis for their selective temporal tuning remains unclear. Here, we analyse excitatory synaptic inputs to transient OFF α ganglion cells (t-OFF α GCs) in the rabbit retina. We show that convergence of excitatory and inhibitory synaptic inputs within the bipolar cell terminals presynaptic to the t-OFF α GCs shifts the temporal tuning to higher temporal frequencies. GABAergic inhibition suppresses the excitatory input at low frequencies, but potentiates it at high frequencies. Crossover glycinergic inhibition and sodium channel activity in the presynaptic bipolar cells also potentiate high frequency excitatory inputs. We found differences in the spatial and temporal properties, and contrast sensitivities of these mechanisms. These differences in stimulus selectivity allow these mechanisms to generate bandpass temporal tuning of t-OFF α GCs over a range of visual conditions.

Local processing in neurites of VGluT3-expressing amacrine cells differentially organizes visual information

Neurons receive synaptic inputs on extensive neurite arbors. How information is organized across arbors and how local processing in neurites contributes to circuit function is mostly unknown. Here, we used two-photon Ca²⁺ imaging to study visual processing in VGluT3-expressing amacrine cells (VG3-ACs) in the mouse retina. Contrast preferences (ON vs. OFF) varied across VG3-AC arbors depending on the laminar position of neurites, with ON responses preferring larger stimuli than OFF responses. Although arbors of neighboring cells overlap extensively, imaging population activity revealed continuous topographic maps of visual space in the VG3-AC plexus. All VG3-AC neurites responded strongly to object motion, but remained silent during global image motion. Thus, VG3-AC arbors limit vertical and lateral integration of contrast and location information, respectively. We propose that this local processing enables the dense VG3-AC plexus to contribute precise object motion signals to diverse targets without distorting target-specific contrast preferences and spatial receptive fields.

Different functional susceptibilities of mouse retinal ganglion cell subtypes to optic nerve crush injury

In optic neuropathies, the progressive deterioration of retinal ganglion cell (RGC) function leads to irreversible vision loss. Increasing experimental evidence suggests differing susceptibility for RGC functional subtypes. Here with multi-electrode array recordings, RGC functional loss was characterized at multiple time points in a mouse model of optic nerve crush. Firing rate, latency of response and receptive field size were analyzed for ON, OFF and ON-OFF RGCs separately. It was observed that responses and receptive fields of OFF cells were impaired earlier than ON cells after the injury. For the ON-OFF cells, the OFF component of response was also more susceptible to optic nerve injury than the ON component. Moreover, more ON transient cells survived than ON sustained cells post the crush, implying a diversified vulnerability for ON cells. Together, these data support the contention that RGCs' functional degeneration in optic nerve injury is subtype dependent, a fact that needs to be considered when developing treatments of glaucomatous retinal ganglion cell degeneration and other optic neuropathies.

General features of inhibition in the inner retina

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

Three Small-Receptive-Field Ganglion Cells in the Mouse Retina Are Distinctly Tuned to Size, Speed, and Object Motion

Retinal ganglion cells (RGCs) are frequently divided into functional types by their ability to extract and relay specific features from a visual scene, such as the capacity to discern local or global motion, direction of motion, stimulus orientation, contrast or uniformity, or the presence of large or small objects. Here we introduce three previously uncharacterized, nondirection-selective ON-OFF RGC types that represent a distinct set of feature detectors in the mouse retina. The three high-definition (HD) RGCs possess small receptive-field centers and strong surround suppression. They respond selectively to objects of specific sizes, speeds, and types of motion. We present comprehensive morphological characterization of the HD RGCs and physiological recordings of their light responses, receptive-field size and structure, and synaptic mechanisms of surround suppression. We also explore the similarities and differences between the HD RGCs and a well characterized RGC with a comparably small receptive field, the local edge detector, in response to moving objects and textures. We model populations of each RGC type to study how they differ in their performance tracking a moving object. These results, besides introducing three new RGC types that together constitute a substantial fraction of mouse RGCs, provide insights into the role of different circuits in shaping RGC receptive fields and establish a foundation for continued study of the mechanisms of surround suppression and the neural basis of motion detection.

SIGNIFICANCE STATEMENT

The output cells of the retina, retinal ganglion cells (RGCs), are a diverse group of ∼40 distinct neuron types that are often assigned "feature detection" profiles based on the specific aspects of the visual scene to which they respond. Here we describe, for the first time, morphological and physiological characterization of three new RGC types in the mouse retina, substantially augmenting our understanding of feature selectivity. Experiments and modeling show that while these three "high-definition" RGCs share certain receptive-field properties, they also have distinct tuning to the size, speed, and type of motion on the retina, enabling them to occupy different niches in stimulus space.

Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization

Neurons in sensory systems often pool inputs over arrays of presynaptic cells, giving rise to functional subunits inside a neuron’s receptive field. The organization of these subunits provides a signature of the neuron’s presynaptic functional connectivity and determines how the neuron integrates sensory stimuli. Here we introduce the method of spike-triggered non-negative matrix factorization for detecting the layout of subunits within a neuron’s receptive field. The method only requires the neuron’s spiking responses under finely structured sensory stimulation and is therefore applicable to large populations of simultaneously recorded neurons. Applied to recordings from ganglion cells in the salamander retina, the method retrieves the receptive fields of presynaptic bipolar cells, as verified by simultaneous bipolar and ganglion cell recordings. The identified subunit layouts allow improved predictions of ganglion cell responses to natural stimuli and reveal shared bipolar cell input into distinct types of ganglion cells.

How a neuron integrates sensory information requires knowledge about its functional presynaptic connections. Here the authors report a new method using non-negative matrix factorization to identify the layout of presynaptic bipolar cell inputs onto retinal ganglion cells and predict their responses to natural stimuli.

Homeostatic Plasticity Shapes Cell-Type-Specific Wiring in the Retina

Convergent input from different presynaptic partners shapes the responses of postsynaptic neurons. Whether developing postsynaptic neurons establish connections with each presynaptic partner independently or balance inputs to attain specific responses is unclear. Retinal ganglion cells (RGCs) receive convergent input from bipolar cell types with different contrast responses and temporal tuning. Here, using optogenetic activation and pharmacogenetic silencing, we found that type 6 bipolar (B6) cells dominate excitatory input to ONα-RGCs. We generated mice in which B6 cells were selectively removed from developing circuits (B6-DTA). In B6-DTA mice, ONα-RGCs adjusted connectivity with other bipolar cells in a cell-type-specific manner. They recruited new partners, increased synapses with some existing partners, and maintained constant input from others. Patch-clamp recordings revealed that anatomical rewiring precisely preserved contrast and temporal frequency response functions of ONα-RGCs, indicating that homeostatic plasticity shapes cell-type-specific wiring in the developing retina to stabilize visual information sent to the brain.

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

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

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.

Error-Robust Modes of the Retinal Population Code

Across the nervous system, certain population spiking patterns are observed far more frequently than others. A hypothesis about this structure is that these collective activity patterns function as population codewords–collective modes–carrying information distinct from that of any single cell. We investigate this phenomenon in recordings of ∼150 retinal ganglion cells, the retina’s output. We develop a novel statistical model that decomposes the population response into modes; it predicts the distribution of spiking activity in the ganglion cell population with high accuracy. We found that the modes represent localized features of the visual stimulus that are distinct from the features represented by single neurons. Modes form clusters of activity states that are readily discriminated from one another. When we repeated the same visual stimulus, we found that the same mode was robustly elicited. These results suggest that retinal ganglion cells’ collective signaling is endowed with a form of error-correcting code–a principle that may hold in brain areas beyond retina.

Neurons in most parts of the nervous system represent and process information in a collective fashion, yet the nature of this collective code is poorly understood. An important constraint placed on any such collective processing comes from the fact that individual neurons’ signaling is prone to corruption by noise. The information theory and engineering literatures have studied error-correcting codes that allow individual noise-prone coding units to “check” each other, forming an overall representation that is robust to errors. In this paper, we have analyzed the population code of one of the best-studied neural systems, the retina, and found that it is structured in a manner analogous to error-correcting schemes. Indeed, we found that the complex activity patterns over ~150 retinal ganglion cells, the output neurons of the retina, could be mapped onto collective code words, and that these code words represented precise visual information while suppressing noise. In order to analyze this coding scheme, we introduced a novel quantitative model of the retinal output that predicted neural activity patterns more accurately than existing state-of-the-art approaches.

Neural Mechanisms Generating Orientation Selectivity in the Retina

The orientation of visual stimuli is a salient feature of visual scenes. In vertebrates, the first neural processing steps generating orientation selectivity take place in the retina. Here, we dissect an orientation-selective circuit in the larval zebrafish retina and describe its underlying synaptic, cellular, and molecular mechanisms. We genetically identify a class of amacrine cells (ACs) with elongated dendritic arbors that show orientation tuning. Both selective optogenetic ablation of ACs marked by the cell-adhesion molecule Teneurin-3 (Tenm3) and pharmacological interference with their function demonstrate that these cells are critical components for orientation selectivity in retinal ganglion cells (RGCs) by being a source of tuned GABAergic inhibition. Moreover, our morphological analyses reveal that Tenm3⁺ ACs and orientation-selective RGCs co-stratify their dendrites in the inner plexiform layer, and that Tenm3⁺ ACs require Tenm3 to acquire their correct dendritic stratification. Finally, we show that orientation tuning is present also among bipolar cell presynaptic terminals. Our results define a neural circuit underlying orientation selectivity in the vertebrate retina and characterize cellular and molecular requirements for its assembly.

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We identify Tenm3⁺ ACs with elongated dendritic arbors showing orientation tuning

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Tenm3⁺ AC GABAergic inhibition is crucial for orientation-selective RGC tuning

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Orientation tuning is present also among some bipolar cell presynaptic terminals

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We propose a model of how orientation selectivity is generated in ganglion cells