Function first: classifying cell types and circuits of the retina

Spatial distribution and functional integration of displaced retinal ganglion cells

The retina contains distinct types of ganglion cells, which form mosaics with cells of each type at each position of the visual field. Displaced retinal ganglion cells (dRGCs) occur with cell bodies in the inner nuclear layer (INL), and regularly placed RGCs with cell bodies in the ganglion cell layer. An example of mammalian dRGCs are M1-type intrinsically photosensitive ganglion cells (ipRGCs). Little is known, however, about their relationship with regularly placed ipRGCs. We identified mouse ipRGC types M1, M2, and M4/sONɑ by immunohistochemistry and light microscopy. Reconstruction of immunolabeled mosaics from M1 and sONɑ RGCs indicated that dRGCs tiled the retina with their regular RGC partners. Multi-electrode array recordings revealed conventional receptive fields of displaced sONɑ RGCs which fit into the mosaic of their regular counterparts. An RGC distribution analysis showed type-specific dRGC patterns which followed neither the global density distribution of all RGCs nor the local densities of corresponding cell types. The displacement of RGC bodies into the INL occurs in a type-dependent manner, where dRGCs are positioned to form complete mosaics with their regular partners. Our data suggest that dRGCs and regular RGCs serve the same functional role within their corresponding population of RGCs.

A Complete Spatial Map of Mouse Retinal Ganglion Cells Reveals Density and Gene Expression Specializations

Retinal ganglion cells (RGCs) transmit visual information from the eye to the brain. In mice, several RGC subtypes show nonuniform spatial distributions, potentially mediating specific visual functions. However, the full extent of RGC specialization remains unknown. Here, we used en-face cryosectioning, spatial transcriptomics, and machine learning to map the spatial distribution of all RGC subtypes identified in previous single-cell studies. While two-thirds of RGC subtypes were evenly distributed, others showed strong biases toward ventral or dorso-temporal regions associated with sky vision and the area retinae temporalis (ART), the predicted homolog of the area centralis. Additionally, we observed unexpected spatial variation in gene expression within several subtypes along the dorso-ventral axis or within vs. outside the ART, independent of RGC density profiles. Finally, we found limited correlations between the gene profiles of the ART and the primate macula, suggesting divergent specialization between the mouse and primate central vision.

Transcriptomic neuron types vary topographically in function and morphology

Neuronal phenotypic traits such as morphology, connectivity and function are dictated, to a large extent, by a specific combination of differentially expressed genes. Clusters of neurons in transcriptomic space correspond to distinct cell types and in some cases-for example, Caenorhabditis elegans neurons1 and retinal ganglion cells2-4-have been shown to share morphology and function. The zebrafish optic tectum is composed of a spatial array of neurons that transforms visual inputs into motor outputs. Although the visuotopic map is continuous, subregions of the tectum are functionally specialized5,6. Here, to uncover the cell-type architecture of the tectum, we transcriptionally profiled its neurons, revealing more than 60 cell types that are organized in distinct anatomical layers. We measured the visual responses of thousands of tectal neurons by two-photon calcium imaging and matched them with their transcriptional profiles. Furthermore, we characterized the morphologies of transcriptionally identified neurons using specific transgenic lines. Notably, we found that neurons that are transcriptionally similar can diverge in shape, connectivity and visual responses. Incorporating the spatial coordinates of neurons within the tectal volume revealed functionally and morphologically defined anatomical subclusters within individual transcriptomic clusters. Our findings demonstrate that extrinsic, position-dependent factors expand the phenotypic repertoire of genetically similar neurons.

Resilience to diabetic retinopathy

Chronic elevation of blood glucose at first causes relatively minor changes to the neural and vascular components of the retina. As the duration of hyperglycemia persists, the nature and extent of damage increases and becomes readily detectable. While this second, overt manifestation of diabetic retinopathy (DR) has been studied extensively, what prevents maximal damage from the very start of hyperglycemia remains largely unexplored. Recent studies indicate that diabetes (DM) engages mitochondria-based defense during the retinopathy-resistant phase, and thereby enables the retina to remain healthy in the face of hyperglycemia. Such resilience is transient, and its deterioration results in progressive accumulation of retinal damage. The concepts that co-emerge with these discoveries set the stage for novel intellectual and therapeutic opportunities within the DR field. Identification of biomarkers and mediators of protection from DM-mediated damage will enable development of resilience-based therapies that will indefinitely delay the onset of DR.

Retinal ganglion cell topography and spatial resolving power in the pajama cardinalfish Sphaeramia nematoptera (Bleeker, 1856)

We studied the topography of retinal ganglion cells (GCs) and estimated spatial resolving power (SRP) in the pajama cardinalfish Sphaeramia nematoptera (Bleeker, 1856), a relatively small brightly colored fish inhabiting coral reefs and lagoons in the Western Pacific. S. nematoptera is an active night predator feeding on near-bottom animal plankton and benthos. DAPI staining was used to label nuclei of GCs and non-GCs in the inner plexiform and ganglion cell layers. Non-GCs were distinguished from GCs in Nissl-stained retinal wholemounts based on cell size, shape, and staining intensity. The proportion of displaced amacrine cells (DACs) varied from 15.46 ± 1.12 (visual streak [VS]) to 17.99 ± 1.06% (dorsal periphery) (mean ± S.E.M., N = 5); the respective proportions of glial cells were 6.61 ± 0.84 and 5.89 ± 0.76%. Thus, 76%-78% of cells in the ganglion cell layer and inner plexiform layer were GCs. The minimum spatial coverage of GCs (3600-4600 cells/mm2) was detected in the dorsal and ventral periphery. It gradually increased toward the central retina to form a moderate VS. The maximum GC density (11,400-12,400 cells/mm2) was registered in the central portion of the VS. No pronounced concentric retinal specializations were found. The total number of GCs ranged within 595.2-635.9 × 103. The anatomical spatial resolving power was minimum in the ventral periphery (4.91-5.53 cpd) and maximum in the central portion of the VS (8.47-9.07 cpd). The respective minimum separable angles were 0.18-0.20° and 0.11-0.12°. The relatively high spatial resolving power and presence of the VS in the pajama cardinalfish are in line with its highly visual behavior.

Optical coherence tomography as a potential surrogate marker of dopaminergic modulation across the life span

The retina has been considered a "window to the brain" and shares similar innervation by the dopaminergic system with the cortex in terms of an unequal distribution of D1 and D2 receptors. Here, we provide a comprehensive overview that Optical Coherence Tomography (OCT), a non-invasive imaging technique, which provides an "in vivo" representation of the retina, shows promise to be used as a surrogate marker of dopaminergic neuromodulation in cognition. Overall, most evidence supports reduced retinal thickness in individuals with dopaminergic dysregulation (e.g., patients with Parkinson's Disease, non-demented older adults) and with poor cognitive functioning. By using the theoretical framework of metacontrol, we derive hypotheses that retinal thinning associated to decreased dopamine (DA) levels affecting D1 families, might lead to a decrease in the signal-to-noise ratio (SNR) affecting cognitive persistence (depending on D1-modulated DA activity) but not cognitive flexibility (depending on D2-modulated DA activity). We argue that the use of OCT parameters might not only be an insightful for cognitive neuroscience research, but also a potentially effective tool for individualized medicine with a focus on cognition. As our society progressively ages in the forthcoming years and decades, the preservation of cognitive abilities and promoting healthy aging will hold of crucial significance. OCT has the potential to function as a swift, non-invasive, and economical method for promptly recognizing individuals with a heightened vulnerability to cognitive deterioration throughout all stages of life.

Atypical retinal function in a mouse model of Fragile X syndrome

Altered function of peripheral sensory neurons is an emerging mechanism for symptoms of autism spectrum disorders. Visual sensitivities are common in autism, but whether differences in the retina might underlie these sensitivities is not well-understood. We explored retinal function in the Fmr1 knockout model of Fragile X syndrome, focusing on a specific type of retinal neuron, the "sustained On alpha" retinal ganglion cell. We found that these cells exhibit changes in dendritic structure and dampened responses to light in the Fmr1 knockout. We show that decreased light sensitivity is due to increased inhibitory input and reduced E-I balance. The change in E-I balance supports maintenance of circuit excitability similar to what has been observed in cortex. These results show that loss of Fmr1 in the mouse retina affects sensory function of one retinal neuron type. Our findings suggest that the retina may be relevant for understanding visual function in Fragile X syndrome.

Heterogeneity of synaptic connectivity in the fly visual system

Visual systems are homogeneous structures, where repeating columnar units retinotopically cover the visual field. Each of these columns contain many of the same neuron types that are distinguished by anatomic, genetic and - generally - by functional properties. However, there are exceptions to this rule. In the 800 columns of the Drosophila eye, there is an anatomically and genetically identifiable cell type with variable functional properties, Tm9. Since anatomical connectivity shapes functional neuronal properties, we identified the presynaptic inputs of several hundred Tm9s across both optic lobes using the full adult female fly brain (FAFB) electron microscopic dataset and FlyWire connectome. Our work shows that Tm9 has three major and many sparsely distributed inputs. This differs from the presynaptic connectivity of other Tm neurons, which have only one major, and more stereotypic inputs than Tm9. Genetic synapse labeling showed that the heterogeneous wiring exists across individuals. Together, our data argue that the visual system uses heterogeneous, distributed circuit properties to achieve robust visual processing.

Differences in nonlinearities determine retinal cell types

Classifying neurons in different types is still an open challenge. In the retina, recent works have taken advantage of the ability to record from a large number of cells to classify ganglion cells into different types based on functional information. Although the first attempts in this direction used the receptive field properties of each cell to classify them, more recent approaches have proposed to cluster ganglion cells directly based on their response to stimuli. These two approaches have not been compared directly. Here, we recorded the responses of a large number of ganglion cells and compared two methods for classifying them into functional groups, one based on the receptive field properties, and the other one using directly their responses to stimuli with various temporal frequencies. We show that the response-based approach allows separation of more types than the receptive field-based method, leading to a better classification. This better granularity is due to the fact that the response-based method takes into account not only the linear part of ganglion cell function but also some of the nonlinearities. A careful characterization of nonlinear processing is thus key to allowing functional classification of sensory neurons.NEW & NOTEWORTHY In the retina, ganglion cells can be classified based on their response to visual stimuli. Although some methods are based on the modeling of receptive fields, others rely on responses to characteristic stimuli. We compared these two classes of methods and show that the latter provides a higher discrimination performance. We also show that this gain arises from the ability to account for the nonlinear behavior of neurons.

Mouse Lines with Cre-Mediated Recombination in Retinal Amacrine Cells

Amacrine cells (ACs) are the most diverse neuronal cell type in the vertebrate retina. Yet little is known about the contribution of ACs to visual processing and retinal disease. A major challenge in evaluating AC function is genetic accessibility. A classic tool of mouse genetics, Cre-mediated recombination, can provide such access. We have screened existing genetically-modified mouse strains and identified multiple candidates that express Cre-recombinase in subsets of retinal ACs. The Cre-expressing mice were crossed to fluorescent-reporter mice to assay Cre expression. In addition, a Cre-dependent fluorescent reporter plasmid was electroporated into the subretinal space of Cre strains. Herein, we report three mouse lines (Tac1::IRES-cre, Camk2a-cre, and Scx-cre) that express Cre recombinase in sub-populations of ACs. In two of these lines, recombination occurred in multiple AC types and a small number of other retinal cell types, while recombination in the Camk2a-cre line appears specific to a morphologically distinct AC. We anticipate that these characterized mouse lines will be valuable tools to the community of researchers who study retinal biology and disease.

Scalable and accurate method for neuronal ensemble detection in spiking neural networks

We propose a novel, scalable, and accurate method for detecting neuronal ensembles from a population of spiking neurons. Our approach offers a simple yet powerful tool to study ensemble activity. It relies on clustering synchronous population activity (population vectors), allows the participation of neurons in different ensembles, has few parameters to tune and is computationally efficient. To validate the performance and generality of our method, we generated synthetic data, where we found that our method accurately detects neuronal ensembles for a wide range of simulation parameters. We found that our method outperforms current alternative methodologies. We used spike trains of retinal ganglion cells obtained from multi-electrode array recordings under a simple ON-OFF light stimulus to test our method. We found a consistent stimuli-evoked ensemble activity intermingled with spontaneously active ensembles and irregular activity. Our results suggest that the early visual system activity could be organized in distinguishable functional ensembles. We provide a Graphic User Interface, which facilitates the use of our method by the scientific community.

Generating and Using Transcriptomically Based Retinal Cell Atlases

It has been known for over a century that the basic organization of the retina is conserved across vertebrates. It has been equally clear that retinal cells can be classified into numerous types, but only recently have methods been devised to explore this diversity in unbiased, scalable, and comprehensive ways. Advances in high-throughput single-cell RNA-sequencing (scRNA-seq) have played a pivotal role in this effort. In this article, we outline the experimental and computational components of scRNA-seq and review studies that have used them to generate retinal atlases of cell types in several vertebrate species. These atlases have enabled studies of retinal development, responses of retinal cells to injury, expression patterns of genes implicated in retinal disease, and the evolution of cell types. Recently, the inquiry has expanded to include the entire eye and visual centers in the brain. These studies have enhanced our understanding of retinal function and dysfunction and provided tools and insights for exploring neural diversity throughout the brain. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Molecular classification of zebrafish retinal ganglion cells links genes to cell types to behavior

Retinal ganglion cells (RGCs) form an array of feature detectors, which convey visual information to central brain regions. Characterizing RGC diversity is required to understand the logic of the underlying functional segregation. Using single-cell transcriptomics, we systematically classified RGCs in adult and larval zebrafish, thereby identifying marker genes for >30 mature types and several developmental intermediates. We used this dataset to engineer transgenic driver lines, enabling specific experimental access to a subset of RGC types. Expression of one or few transcription factors often predicts dendrite morphologies and axonal projections to specific tectal layers and extratectal targets. In vivo calcium imaging revealed that molecularly defined RGCs exhibit specific functional tuning. Finally, chemogenetic ablation of eomesa+ RGCs, which comprise melanopsin-expressing types with projections to a small subset of central targets, selectively impaired phototaxis. Together, our study establishes a framework for systematically studying the functional architecture of the visual system.

Retinal Ganglion Cells-Diversity of Cell Types and Clinical Relevance

Retinal ganglion cells (RGCs) are the bridging neurons that connect the retinal input to the visual processing centres within the central nervous system. There is a remarkable diversity of RGCs and the various subtypes have unique morphological features, distinct functions, and characteristic pathways linking the inner retina to the relevant brain areas. A number of psychophysical and electrophysiological tests have been refined to investigate this large and varied population of RGCs. Technological advances, such as high-resolution optical coherence tomography imaging, have provided additional tools to define the pattern of RGC involvement and the chronological sequence of events in both inherited and acquired optic neuropathies. The mechanistic insights gained from these studies, in particular the selective vulnerability and relative resilience of particular RGC subtypes, are of fundamental importance as they are directly relevant to the development of targeted therapies for these invariably progressive blinding diseases. This review provides a comprehensive description of the various types of RGCs, the developments in proposed methods of classification, and the current gaps in our knowledge of how these RGCs are differentially affected depending on the underlying aetiology. The synthesis of the current body of knowledge on the diversity of RGCs and the pathways that are potentially amenable to therapeutic modulation will hopefully lead to much needed effective treatments for patients with optic neuropathies.

Predicting synchronous firing of large neural populations from sequential recordings

A major goal in neuroscience is to understand how populations of neurons code for stimuli or actions. While the number of neurons that can be recorded simultaneously is increasing at a fast pace, in most cases these recordings cannot access a complete population: some neurons that carry relevant information remain unrecorded. In particular, it is hard to simultaneously record all the neurons of the same type in a given area. Recent progress have made possible to profile each recorded neuron in a given area thanks to genetic and physiological tools, and to pool together recordings from neurons of the same type across different experimental sessions. However, it is unclear how to infer the activity of a full population of neurons of the same type from these sequential recordings. Neural networks exhibit collective behaviour, e.g. noise correlations and synchronous activity, that are not directly captured by a conditionally-independent model that would just put together the spike trains from sequential recordings. Here we show that we can infer the activity of a full population of retina ganglion cells from sequential recordings, using a novel method based on copula distributions and maximum entropy modeling. From just the spiking response of each ganglion cell to a repeated stimulus, and a few pairwise recordings, we could predict the noise correlations using copulas, and then the full activity of a large population of ganglion cells of the same type using maximum entropy modeling. Remarkably, we could generalize to predict the population responses to different stimuli with similar light conditions and even to different experiments. We could therefore use our method to construct a very large population merging cells' responses from different experiments. We predicted that synchronous activity in ganglion cell populations saturates only for patches larger than 1.5mm in radius, beyond what is today experimentally accessible.

Topographic Variations in Retinal Encoding of Visual Space

A retina completely devoid of topographic variations would be homogenous, encoding any given feature uniformly across the visual field. In a naive view, such homogeneity would appear advantageous. However, it is now clear that retinal topographic variations exist across mammalian species in a variety of forms and patterns. We briefly review some of the more established topographic variations in retinas of different mammalian species and focus on the recent discovery that cells belonging to a single neuronal subtype may exhibit distinct topographic variations in distribution, morphology, and even function. We concentrate on the mouse retina-originally viewed as homogenous-in which genetic labeling of distinct neuronal subtypes and other advanced techniques have revealed unexpected anatomical and physiological topographic variations. Notably, different subtypes reveal different patterns of nonuniformity, which may even be opposite or orthogonal to one another. These topographic variations in the encoding of visual space should be considered when studying visual processing in the retina and beyond.

LRR-ning the Rules: Synapse Organization in the Primary Rod Pathway

In this issue of Neuron, Sinha et al. (2020) demonstrate that synaptic organization at rod bipolar cell terminals is regulated by a leucine-rich repeat protein, LRRTM4. LRRTM4 is expressed specifically by rod bipolar cells; eliminating it in mouse retina perturbs the organization of synaptic ribbons and impairs the function of inhibitory synapses.

Network Architecture of Gap Junctional Coupling among Parallel Processing Channels in the Mammalian Retina

Gap junctions are ubiquitous throughout the nervous system, mediating critical signal transmission and integration, as well as emergent network properties. In mammalian retina, gap junctions within the Aii amacrine cell-ON cone bipolar cell (CBC) network are essential for night vision, modulation of day vision, and contribute to visual impairment in retinal degenerations, yet neither the extended network topology nor its conservation is well established. Here, we map the network contribution of gap junctions using a high-resolution connectomics dataset of an adult female rabbit retina. Gap junctions are prominent synaptic components of ON CBC classes, constituting 5%-25% of all axonal synaptic contacts. Many of these mediate canonical transfer of rod signals from Aii cells to ON CBCs for night vision, and we find that the uneven distribution of Aii signals to ON CBCs is conserved in rabbit, including one class entirely lacking direct Aii coupling. However, the majority of gap junctions formed by ON CBCs unexpectedly occur between ON CBCs, rather than with Aii cells. Such coupling is extensive, creating an interconnected network with numerous lateral paths both within, and particularly across, these parallel processing streams. Coupling patterns are precise with ON CBCs accepting and rejecting unique combinations of partnerships according to robust rulesets. Coupling specificity extends to both size and spatial topologies, thereby rivaling the synaptic specificity of chemical synapses. These ON CBC coupling motifs dramatically extend the coupled Aii-ON CBC network, with implications for signal flow in both scotopic and photopic retinal networks during visual processing and disease.SIGNIFICANCE STATEMENT Electrical synapses mediated by gap junctions are fundamental components of neural networks. In retina, coupling within the Aii-ON CBC network shapes visual processing in both the scotopic and photopic networks. In retinal degenerations, these same gap junctions mediate oscillatory activity that contributes to visual impairment. Here, we use high-resolution connectomics strategies to identify gap junctions and cellular partnerships. We describe novel, pervasive motifs both within and across classes of ON CBCs that dramatically extend the Aii-ON CBC network. These motifs are highly specific with implications for both signal processing within the retina and therapeutic interventions for blinding conditions. These findings highlight the underappreciated contribution of coupling motifs in retinal circuitry and the necessity of their detection in connectomics studies.

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

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

Neurogenesis and Specification of Retinal Ganglion Cells

Across all species, retinal ganglion cells (RGCs) are the first retinal neurons generated during development, followed by the other retinal cell types. How are retinal progenitor cells (RPCs) able to produce these cell types in a specific and timely order? Here, we will review the different models of retinal neurogenesis proposed over the last decades as well as the extrinsic and intrinsic factors controlling it. We will then focus on the molecular mechanisms, especially the cascade of transcription factors that regulate, more specifically, RGC fate. We will also comment on the recent discovery that the ciliary marginal zone is a new stem cell niche in mice contributing to retinal neurogenesis, especially to the generation of ipsilateral RGCs. Furthermore, RGCs are composed of many different subtypes that are anatomically, physiologically, functionally, and molecularly defined. We will summarize the different classifications of RGC subtypes and will recapitulate the specification of some of them and describe how a genetic disease such as albinism affects neurogenesis, resulting in profound visual deficits.

Probe-Seq enables transcriptional profiling of specific cell types from heterogeneous tissue by RNA-based isolation

Recent transcriptional profiling technologies are uncovering previously-undefined cell populations and molecular markers at an unprecedented pace. While single cell RNA (scRNA) sequencing is an attractive approach for unbiased transcriptional profiling of all cell types, a complementary method to isolate and sequence specific cell populations from heterogeneous tissue remains challenging. Here, we developed Probe-Seq, which allows deep transcriptional profiling of specific cell types isolated using RNA as the defining feature. Dissociated cells are labeled using fluorescent in situ hybridization (FISH) for RNA, and then isolated by fluorescent activated cell sorting (FACS). We used Probe-Seq to purify and profile specific cell types from mouse, human, and chick retinas, as well as from Drosophila midguts. Probe-Seq is compatible with frozen nuclei, making cell types within archival tissue immediately accessible. As it can be multiplexed, combinations of markers can be used to create specificity. Multiplexing also allows for the isolation of multiple cell types from one cell preparation. Probe-Seq should enable RNA profiling of specific cell types from any organism.

Gap Junction Coupling Shapes the Encoding of Light in the Developing Retina

Detection of ambient illumination in the developing retina prior to maturation of conventional photoreceptors is mediated by intrinsically photosensitive retinal ganglion cells (ipRGCs) and is critical for driving several physiological processes, including light aversion, pupillary light reflexes, and photoentrainment of circadian rhythms. The strategies by which ipRGCs encode variations in ambient light intensity at these early ages are not known. Using unsupervised clustering of two-photon calcium responses followed by inspection of anatomical features, we found that the population activity of the neonatal retina could be modeled as six functional groups that were composed of mixtures of ipRGC subtypes and non-ipRGC cell types. By combining imaging, whole-cell recording, pharmacology, and anatomical techniques, we found that functional mixing of cell types is mediated in part by gap junction coupling. Together, these data show that both cell-autonomous intrinsic light responses and gap junction coupling among ipRGCs contribute to the proper encoding of light intensity in the developing retina.

Understanding the retinal basis of vision across species

The vertebrate retina first evolved some 500 million years ago in ancestral marine chordates. Since then, the eyes of different species have been tuned to best support their unique visuoecological lifestyles. Visual specializations in eye designs, large-scale inhomogeneities across the retinal surface and local circuit motifs mean that all species' retinas are unique. Computational theories, such as the efficient coding hypothesis, have come a long way towards an explanation of the basic features of retinal organization and function; however, they cannot explain the full extent of retinal diversity within and across species. To build a truly general understanding of vertebrate vision and the retina's computational purpose, it is therefore important to more quantitatively relate different species' retinal functions to their specific natural environments and behavioural requirements. Ultimately, the goal of such efforts should be to build up to a more general theory of vision.

Measurable Aspects of the Retinal Neurovascular Unit in Diabetes, Glaucoma, and Controls

PURPOSE

To study the structural and angiographic optical coherence tomography (OCT) data of the macula from controls, patients with diabetes, and patients with glaucoma to evaluate neurovascular and structural relationships.

METHODS

This was a retrospective study of 89 eyes from 49 patients in a community-based retinal referral practice with diabetes, glaucoma, and normal controls. The patients were evaluated with OCT to include retinal nerve fiber layer (RNFL) thickness measurement and ganglion cell layer (GCL) volume determination. The vascular density of the radial peripapillary capillary network and the vascular plexuses in the macula were evaluated with OCT angiography. The main outcome measures were the data obtained per disease state and the interrelationships the data displayed.

RESULTS

The mean GCL volumes were significantly lower than the control group in both the diabetic (P = .016) and glaucoma (P < .001) groups. The difference between the diabetic and glaucoma groups was not significant (P = .052). The mean global vascular density was greater in the control group than the diabetic group (P = .002) and the glaucoma group (P < .001). The mean RNFL thicknesses were lowest in the glaucoma group. Both the diabetic and glaucoma groups had significantly lower radial peripapillary network and deep vascular plexus density values compared to controls.

CONCLUSIONS

Although there are important differences in disease pathogenesis between diabetes and glaucoma, they share certain similarities in the structural and angiographic abnormalities eventually produced. This suggests that, in addition to canonical pathways of disease, a component of both could represent neurodegenerative disease, offering the possibility for the development of new treatments. NOTE: Publication of this article is sponsored by the American Ophthalmological Society.

Motion Vision: A New Mechanism in the Mammalian Retina

In animal eyes, the detection of slow global image motion is crucial to preventing blurry vision. A new study reveals how a mammalian global motion detector achieves this through 'space-time wiring' at its dendrites.

Voltage- and calcium-gated ion channels of neurons in the vertebrate retina

In this review, we summarize studies investigating the types and distribution of voltage- and calcium-gated ion channels in the different classes of retinal neurons: rods, cones, horizontal cells, bipolar cells, amacrine cells, interplexiform cells, and ganglion cells. We discuss differences among cell subtypes within these major cell classes, as well as differences among species, and consider how different ion channels shape the responses of different neurons. For example, even though second-order bipolar and horizontal cells do not typically generate fast sodium-dependent action potentials, many of these cells nevertheless possess fast sodium currents that can enhance their kinetic response capabilities. Ca2+ channel activity can also shape response kinetics as well as regulating synaptic release. The L-type Ca2+ channel subtype, CaV1.4, expressed in photoreceptor cells exhibits specific properties matching the particular needs of these cells such as limited inactivation which allows sustained channel activity and maintained synaptic release in darkness. The particular properties of K+ and Cl- channels in different retinal neurons shape resting membrane potentials, response kinetics and spiking behavior. A remaining challenge is to characterize the specific distributions of ion channels in the more than 100 individual cell types that have been identified in the retina and to describe how these particular ion channels sculpt neuronal responses to assist in the processing of visual information by the retina.

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.

Molecular and Cellular Mechanisms Underlying Somatostatin-Based Signaling in Two Model Neural Networks, the Retina and the Hippocampus

Neural inhibition plays a key role in determining the specific computational tasks of different brain circuitries. This functional "braking" activity is provided by inhibitory interneurons that use different neurochemicals for signaling. One of these substances, somatostatin, is found in several neural networks, raising questions about the significance of its widespread occurrence and usage. Here, we address this issue by analyzing the somatostatinergic system in two regions of the central nervous system: the retina and the hippocampus. By comparing the available information on these structures, we identify common motifs in the action of somatostatin that may explain its involvement in such diverse circuitries. The emerging concept is that somatostatin-based signaling, through conserved molecular and cellular mechanisms, allows neural networks to operate correctly.