A Computational Study on the Role of Gap Junctions and Rod Ih Conductance in the Enhancement of the Dynamic Range of the Retina

Recent works suggest that one of the roles of gap junctions in sensory systems is to enhance their dynamic range by avoiding early saturation in the first processing stages. In this work, we use a minimal conductance-based model of the ON rod pathways in the vertebrate retina to study the effects of electrical synaptic coupling via gap junctions among rods and among AII amacrine cells on the dynamic range of the retina. The model is also used to study the effects of the maximum conductance of rod hyperpolarization activated current Ih on the dynamic range of the retina, allowing a study of the interrelations between this intrinsic membrane parameter with those two retina connectivity characteristics. Our results show that for realistic values of Ih conductance the dynamic range is enhanced by rod-rod coupling, and that AII-AII coupling is less relevant to dynamic range amplification in comparison with receptor coupling. Furthermore, a plot of the retina output response versus input intensity for the optimal parameter configuration is well fitted by a power law with exponent . The results are consistent with predictions of more theoretical works and suggest that the earliest expression of gap junctions along the rod pathways, together with appropriate values of rod Ih conductance, has the highest impact on vertebrate retina dynamic range enhancement

A Neural Model of Surface Perception: Lightness, Anchoring, and Filling-in

This article develops a neural model of how the visual system processes natural images under variable illumination conditions to generate surface lightness percepts. Previous models have clarified how the brain can compute the relative contrast of images from variably illuminate scenes. How the brain determines an absolute lightness scale that "anchors" percepts of surface lightness to us the full dynamic range of neurons remains an unsolved problem. Lightness anchoring properties include articulation, insulation, configuration, and are effects. The model quantatively simulates these and other lightness data such as discounting the illuminant, the double brilliant illusion, lightness constancy and contrast, Mondrian contrast constancy, and the Craik-O'Brien-Cornsweet illusion. The model also clarifies the functional significance for lightness perception of anatomical and neurophysiological data, including gain control at retinal photoreceptors, and spatioal contrast adaptation at the negative feedback circuit between the inner segment of photoreceptors and interacting horizontal cells. The model retina can hereby adjust its sensitivity to input intensities ranging from dim moonlight to dazzling sunlight. A later model cortical processing stages, boundary representations gate the filling-in of surface lightness via long-range horizontal connections. Variants of this filling-in mechanism run 100-1000 times faster than diffusion mechanisms of previous biological filling-in models, and shows how filling-in can occur at realistic speeds. A new anchoring mechanism called the Blurred-Highest-Luminance-As-White (BHLAW) rule helps simulate how surface lightness becomes sensitive to the spatial scale of objects in a scene. The model is also able to process natural images under variable lighting conditions.Air Force Office of Scientific Research (F49620-01-1-0397); Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409); Office of Naval Research (N00014-01-1-0624

Retinal drug delivery: rethinking outcomes for the efficient replication of retinal behavior

The retina is a highly organized structure that is considered to be "an approachable part of the brain." It is attracting the interest of development scientists, as it provides a model neurovascular system. Over the last few years, we have been witnessing significant development in the knowledge of the mechanisms that induce the shape of the retinal vascular system, as well as knowledge of disease processes that lead to retina degeneration. Knowledge and understanding of how our vision works are crucial to creating a hardware-adaptive computational model that can replicate retinal behavior. The neuronal system is nonlinear and very intricate. It is thus instrumental to have a clear view of the neurophysiological and neuroanatomic processes and to take into account the underlying principles that govern the process of hardware transformation to produce an appropriate model that can be mapped to a physical device. The mechanistic and integrated computational models have enormous potential toward helping to understand disease mechanisms and to explain the associations identified in large model-free data sets. The approach used is modulated and based on different models of drug administration, including the geometry of the eye. This work aimed to review the recently used mathematical models to map a directed retinal network.The authors acknowledge the financial support received from the Portuguese Science and Technology Foundation (FCT/MCT) and the European Funds (PRODER/COMPETE) for the project UIDB/04469/2020 (strategic fund), co-financed by FEDER, under the Partnership Agreement PT2020. The authors also acknowledge FAPESP – São Paulo Research Foundation, for the financial support for the publication of the article.info:eu-repo/semantics/publishedVersio

Connectivity of the Outer Plexiform Layer of the Mouse Retina

The retina has two synaptic layers: In the outer plexiform layer (OPL), signals from the photoreceptors (PRs) are relayed to the bipolar cells (BCs) with one type of horizontal cell (HC) as interneuron. In the inner plexiform layer (IPL), the retinal ganglion cells (RGCs) receive input from the bipolar cells, modulated by multiple types of amacrine cells. The axons of the retinal ganglion cells form the optic nerve which transmit the visual signal to the higher regions of the brain (Masland 2012). Studies of signal processing in the retina usually focus on the inner plexiform layer. Here, the main computations take place such as direction selectivity, orientation selectivity and object motion detection (Gollisch and Meister 2010). However, to fully understand how these computations arise, it is also important to understand how the input to the ganglion cells is computed and thus to understand the functional differences between BC signals. While these are shaped to some extent in the IPL through amacrine cell feedback (Franke et al. 2017), they are also influenced by computations in the OPL (Drinnenberg et al. 2018). Accordingly, it is essential to understand how the bipolar cell signals are formed and what the exact connectivity in the OPL is. This thesis project aims at a quantitative picture of the mouse outer retina connectome. It takes the approach of systematically analyzing connectivity between the cell types in the OPL based on available high-resolution 3D electron microscopy imaging data (Helmstaedter et al. 2013). We reconstructed photoreceptor axon terminals, horizontal cells and bipolar cells, and quantified their contact statistics. We identified a new structure on HC dendrites which likely defines a second synaptic layer in the OPL below the PRs. Based on the reconstructed morphology, we created a biophysical model of a HC dendrite to gain insights into potential functional mechanisms. Our results reveal several new connectivity patterns in the mouse OPL and suggest that HCs perform two functional roles at two distinct output sites at the same time. The project emphasizes how large-scale EM data can boost research on anatomical connectivity and beyond and highlights the value of the resulting data for detailed biophysical modeling. Moreover, it shows how the known amount of complexity increases with the level of detail with which we can study a subject. Beyond that, this thesis project demonstrates the benefits of data sharing and open science which only enabled our studies

Dampening Spontaneous Activity Improves the Light Sensitivity and Spatial Acuity of Optogenetic Retinal Prosthetic Responses

Retinitis pigmentosa is a progressive retinal dystrophy that causes irreversible visual impairment and blindness. Retinal prostheses currently represent the only clinically available vision-restoring treatment, but the quality of vision returned remains poor. Recently, it has been suggested that the pathological spontaneous hyperactivity present in dystrophic retinas may contribute to the poor quality of vision returned by retinal prosthetics by reducing the signal-to-noise ratio of prosthetic responses. Here, we investigated to what extent blocking this hyperactivity can improve optogenetic retinal prosthetic responses. We recorded activity from channelrhodopsin-expressing retinal ganglion cells in retinal wholemounts in a mouse model of retinitis pigmentosa. Sophisticated stimuli, inspired by those used in clinical visual assessment, were used to assess light sensitivity, contrast sensitivity and spatial acuity of optogenetic responses; in all cases these were improved after blocking spontaneous hyperactivity using meclofenamic acid, a gap junction blocker. Our results suggest that this approach significantly improves the quality of vision returned by retinal prosthetics, paving the way to novel clinical applications. Moreover, the improvements in sensitivity achieved by blocking spontaneous hyperactivity may extend the dynamic range of optogenetic retinal prostheses, allowing them to be used at lower light intensities such as those encountered in everyday life

The Role of Non-Linearities in Visual Perception studied with a Computational Model of the Vertebrate Retina

Processing of visual stimuli in the vertebrate retina is complex and diverse. The retinal output to the higher centres of the nervous system, mediated by ganglion cells, consists of several different channels. Neurons in these channels can have very distinct response properties, which originate in different retinal pathways. In this work, the retinal origins and possible functional implications of the segregation of visual pathways will be investigated with a detailed, biologically realistic computational model of the retina. This investigation will focus on the two main retino-cortical pathways in the mammalian retina, the parvocellular and magnocellular systems, which are crucial for conscious visual perception. These pathways differ in two important aspects. The parvocellular system has a high spatial, but low temporal resolution. Conversely, the magnocellular system has a high temporal fidelity, spatial sampling however is less dense than for parvocellular cells. Additionally, the responses of magnocellular ganglion cells can show pronounced nonlinearities, while the parvocellular system is essentially linear. The origin of magnocellular nonlinearities is unknown and will be investigated in the first part of this work. As their main source, the results suggest specific properties of the photoreceptor response and a specialised amacrine cell circuit in the inner retina. The results further show that their effect combines in a multiplicative way. The model is then used to examine the influence of nonlinearities on the responses of ganglion cells in the presence of involuntary fixational eye movements. Two different stimulus conditions will be considered: visual hyperacuity and motion induced illusions. In both cases, it is possible to directly compare properties of the ganglion cell population response with psychophysical data, which allows for an analysis of the influence of different components of the retinal circuitry. The simulation results suggest an important role for nonlinearities in the magnocellular stream for visual perception in both cases. First, it will be shown how nonlinearities, triggered by fixational eye movements, can strongly enhance the spatial precision of magnocellular ganglion cells. As a result, their performance in a hyperacuity task can be equal to or even surpass that of the parvocellular system. Second, the simulations imply that the origin of some of the illusory percepts elicited by fixational eye movements could be traced back to the nonlinear properties of magnocellular ganglion cells. As these activity patterns strongly differ from those in the parvocellular system, it appears that the magnocellular system can strongly dominate visual perception in certain conditions. Taken together, the results of this theoretical study suggest that retinal nonlinearities may be important for and strongly influence visual perception. The model makes several experimentally verifiable predictions to further test and quantify these findings. Furthermore, models investigating higher visual processing stages may benefit from this work, which could provide the basis to produce realistic afferent input

Prospects for the application of Müller glia and their derivatives in retinal regenerative therapies

Neural cell death is the main feature of all retinal degenerative disorders that lead to blindness. Despite therapeutic advances, progression of retinal disease cannot always be prevented, and once neuronal cell damage occurs, visual loss cannot be reversed. Recent research in the stem cell field, and the identification of Müller glia with stem cell characteristics in the human eye, have provided hope for the use of these cells in retinal therapies to restore vision. Müller glial cells, which are the major structural cells of the retina, play a very important role in retinal homeostasis during health and disease. They are responsible for the spontaneous retinal regeneration observed in zebrafish and lower vertebrates during early postnatal life, and despite the presence of Müller glia with stem cell characteristics in the adult mammalian retina, there is no evidence that they promote regeneration in humans. Like many other stem cells and neurons derived from pluripotent stem cells, Müller glia with stem cell potential do not differentiate into retinal neurons or integrate into the retina when transplanted into the vitreous of experimental animals with retinal degeneration. However, despite their lack of integration, grafted Müller glia have been shown to induce partial restoration of visual function in spontaneous or induced experimental models of photoreceptor or retinal ganglion cell damage. This improvement in visual function observed after Müller cell transplantation has been ascribed to the release of neuroprotective factors that promote the repair and survival of damaged neurons. Due to the development and availability of pluripotent stem cell lines for therapeutic uses, derivation of Müller cells from retinal organoids formed by iPSC and ESC has provided more realistic prospects for the application of these cells to retinal therapies. Several opportunities for research in the regenerative field have also been unlocked in recent years due to a better understanding of the genomic and proteomic profiles of the developing and regenerating retina in zebrafish, providing the basis for further studies of the human retina. In addition, the increased interest on the nature and function of cellular organelle release and the characterization of molecular components of exosomes released by Müller glia, may help us to design new approaches that could be applied to the development of more effective treatments for retinal degenerative diseases

Digital reconstruction, quantitative morphometric analysis, and membrane properties of bipolar cells in the rat retina.

A basic principle of neuroscience is that structure reflects function. This has led to numerous attempts to characterize the complete morphology of types of neurons throughout the central nervous system. The ability to acquire and analyze complete neuronal morphologies has advanced with continuous technological developments for over 150 years, with progressive refinements and increased understanding of the precise anatomical details of different types of neurons. Bipolar cells of the mammalian retina are short-range projections neurons that link the outer and inner retina. Their dendrites contact and receive input from the terminals of the light-sensing photoreceptors in the outer plexiform layer and their axons descend through the inner nuclear and inner plexiform layers to stratify at different levels of the inner plexiform layer. The stratification level of the axon terminals of different types of bipolar cells in the inner plexiform layer determines their synaptic connectivity and is an important basis for the morphological classification of these cells. Between 10 and 15 different types of cone bipolar cells have been identified in different species and they can be divided into ON-cone bipolar cells (that depolarize to the onset of light) and OFF-cone bipolar cells (that depolarize to the offset of light). Different types of cone bipolar cells are thought to be responsible for coding and transmitting different features of our visual environment and generating parallel channels that uniquely filter and transform the inputs from the photoreceptors. There is a lack of detailed morphological data for bipolar cells, especially for the rat, where biophysical mechanisms have been most extensively studied. The work presented in this thesis provides the groundwork for the future goal of developing morphologically realistic compartmental models for cone and rod bipolar cells. First, the contribution of gap junctions to the membrane properties, specifically input resistance, of bipolar cells was investigated. Gap junctions are ubiquitous within the retina, but it remains to be determined whether the strength of coupling between specific cell types is sufficiently strong for the cells to be functionally coupled via electrical synapses. There are gap junctions between the same class of bipolar cells, and this appears to be a common circuit motif in the vertebrate retina. Surprisingly, our results suggested that the gap junctions between OFF-cone bipolar cells do not support consequential electrical coupling. This provides an important first step both to elucidate the potential roles for these gap junctions, and also for the development of compartmental models for cone bipolar cells. Second, from image stacks acquired from multiphoton excitation microscopy, quantitative morphological reconstructions and detailed morphological analysis were performed with fluorescent dye-filled cone and rod bipolar cells. Compared to previous descriptions, the extent and complexity of branching of the axon terminals was surprisingly high. By precisely quantifying the level of stratification of the axon terminals in the inner plexiform layer, we have generated a reference system for the reliable classification of individual cells in future studies that are focused on correlating physiological and morphological properties. The workflow that we have implemented can be readily extended to the development of morphologically realistic compartmental models for these neurons.Doktorgradsavhandlin