Characterization of Retinal Ganglion Cell Responses to Electrical Stimulation Using White Noise

Retinitis pigmentosa and age-related macular degeneration are two leading causes of degenerative blindness. While there is still not a definitive course of treatment for either of these diseases, there is currently the world over, many different treatment strategies being explored. Of these various strategies, one of the most successful has been retinal implants. Retinal implants are microelectrode or photodiode arrays, that are implanted in the eye of a patient, to electrically stimulate the degenerating retina. Clinical trials have shown that many patients implanted with such a device, are able to regain a certain degree of functional vision. However, while the results of these ongoing clinical trials have been promising, there are still many technical challenges that need to be overcome. One of the biggest challenges facing present implants is the inability to preferentially stimulate different retinal pathways. This is because retinal implants use large-amplitude current or voltage pulses. This in turn leads to the indiscriminate activation of multiple classes of retinal ganglion cells (RGCs), and therefore, an overall reduction in the restored visual acuity. To tackle this issue, we decided to explore a novel stimulus paradigm, in which we present to the retina, a stream of smaller-amplitude subthreshold voltage pulses. By then correlating the retinal spikes to the stimuli preceding them, we calculate temporal input filters for various classes of RGCs, using a technique called spike-triggered averaging (STA). In doing this, we found that ON and OFF RGCs have electrical filters, which are very distinct from each other. This finding creates the possibility for the selective activation of the retina through the use of STA-based waveforms. Finally, using statistical models, we verify how well these temporal filters can predict RGC responses to novel electrical stimuli. In a broad sense, our work represents the successful application of systems engineering tools to retinal prosthetics, in an attempt to answer one of the field’s most difficult questions, namely selective stimulation of the retina

Photogenetic Retinal Prosthesis

The last few decades have witnessed an immense effort to develop working retinal implants for patients suffering from retinal degeneration diseases such as retinitis pigmentosa. However, it is becoming apparent that this approach is unable to restore levels of vision that will be sufficient to offer significant improvement in the quality of life of patients. Herein, a new type of retinal prosthesis that is based on genetic expression of microbial light sensitive ion channel, Chanelrhodopsin-2 (ChR2), and a remote light stimulation is examined. First, the dynamics of the ChR2 stimulation is characterized and it is shown that (1) the temporal resolution of ChR2-evoked spiking is limited by a continuous drop in its depolarization efficiency that is due to (a) frequency-independent desensitization process and (b) slow photocurrent shutting, which leads to a frequency-dependent post-spike depolarization and (2) the ChR2 response to light can be accurately reproduced by a four-state model consisting of two interconnected branches of open and close states. Then, a stimulation prototype is developed and its functionality is demonstrated in-vitro. The prototype uses a new micro-emissive matrix which enables generating of two-dimensional stimulation patterns with enhanced resolution compared to the conventional retinal implants. Finally, based on the micro-emitters matrix, a new technique for sub-cellular and network-level neuroscience experimentations is shown. The capacity to excite sub-cellular compartments is demonstrated and an example utility to fast map variability in dendrites conductance is shown. The outcomes of this thesis present an outline and a first proof-of-concept for a future photogenetic retinal prosthesis. In addition, they provide the emerging optogenetic technology with a detailed analysis of its temporal resolution and a tool to expand its spatial resolution, which can have immediate high impact applications in modulating the activity of sub-cellular compartments, mapping neuronal networks and studying synchrony and plasticity effects

An Optoelectronic Stimulator for Retinal Prosthesis

Retinal prostheses require the presence of viable population of cells in the inner retina. Evaluations of retina with Age-Related Macular Degeneration (AMD) and Retinitis Pigmentosa (RP) have shown a large number of cells remain in the inner retina compared with the outer retina. Therefore, vision loss caused by AMD and RP is potentially treatable with retinal prostheses. Photostimulation based retinal prostheses have shown many advantages compared with retinal implants. In contrary to electrode based stimulation, light does not require mechanical contact. Therefore, the system can be completely external and not does have the power and degradation problems of implanted devices. In addition, the stimulating point is flexible and does not require a prior decision on the stimulation location. Furthermore, a beam of light can be projected on tissue with both temporal and spatial precision. This thesis aims at fi nding a feasible solution to such a system. Firstly, a prototype of an optoelectronic stimulator was proposed and implemented by using the Xilinx Virtex-4 FPGA evaluation board. The platform was used to demonstrate the possibility of photostimulation of the photosensitized neurons. Meanwhile, with the aim of developing a portable retinal prosthesis, a system on chip (SoC) architecture was proposed and a wide tuning range sinusoidal voltage-controlled oscillator (VCO) which is the pivotal component of the system was designed. The VCO is based on a new designed Complementary Metal Oxide Semiconductor (CMOS) Operational Transconductance Ampli er (OTA) which achieves a good linearity over a wide tuning range. Both the OTA and the VCO were fabricated in the AMS 0.35 µm CMOS process. Finally a 9X9 CMOS image sensor with spiking pixels was designed. Each pixel acts as an independent oscillator whose frequency is controlled by the incident light intensity. The sensor was fabricated in the AMS 0.35 µm CMOS Opto Process. Experimental validation and measured results are provided

Egocentric Computer Vision and Machine Learning for Simulated Prosthetic Vision

Las prótesis visuales actuales son capaces de proporcionar percepción visual a personas con cierta ceguera. Sin pasar por la parte dañada del camino visual, la estimulación eléctrica en la retina o en el sistema nervioso provoca percepciones puntuales conocidas como “fosfenos”. Debido a limitaciones fisiológicas y tecnológicas, la información que reciben los pacientes tiene una resolución muy baja y un campo de visión y rango dinámico reducido afectando seriamente la capacidad de la persona para reconocer y navegar en entornos desconocidos. En este contexto, la inclusión de nuevas técnicas de visión por computador es un tema clave activo y abierto. En esta tesis nos centramos especialmente en el problema de desarrollar técnicas para potenciar la información visual que recibe el paciente implantado y proponemos diferentes sistemas de visión protésica simulada para la experimentación.Primero, hemos combinado la salida de dos redes neuronales convolucionales para detectar bordes informativos estructurales y siluetas de objetos. Demostramos cómo se pueden reconocer rápidamente diferentes escenas y objetos incluso en las condiciones restringidas de la visión protésica. Nuestro método es muy adecuado para la comprensión de escenas de interiores comparado con los métodos tradicionales de procesamiento de imágenes utilizados en prótesis visuales.Segundo, presentamos un nuevo sistema de realidad virtual para entornos de visión protésica simulada más realistas usando escenas panorámicas, lo que nos permite estudiar sistemáticamente el rendimiento de la búsqueda y reconocimiento de objetos. Las escenas panorámicas permiten que los sujetos se sientan inmersos en la escena al percibir la escena completa (360 grados).En la tercera contribución demostramos cómo un sistema de navegación de realidad aumentada para visión protésica ayuda al rendimiento de la navegación al reducir el tiempo y la distancia para alcanzar los objetivos, incluso reduciendo significativamente el número de colisiones de obstáculos. Mediante el uso de un algoritmo de planificación de ruta, el sistema encamina al sujeto a través de una ruta más corta y sin obstáculos. Este trabajo está actualmente bajo revisión.En la cuarta contribución, evaluamos la agudeza visual midiendo la influencia del campo de visión con respecto a la resolución espacial en prótesis visuales a través de una pantalla montada en la cabeza. Para ello, usamos la visión protésica simulada en un entorno de realidad virtual para simular la experiencia de la vida real al usar una prótesis de retina. Este trabajo está actualmente bajo revisión.Finalmente, proponemos un modelo de Spiking Neural Network (SNN) que se basa en mecanismos biológicamente plausibles y utiliza un esquema de aprendizaje no supervisado para obtener mejores algoritmos computacionales y mejorar el rendimiento de las prótesis visuales actuales. El modelo SNN propuesto puede hacer uso de la señal de muestreo descendente de la unidad de procesamiento de información de las prótesis retinianas sin pasar por el análisis de imágenes retinianas, proporcionando información útil a los ciegos. Esté trabajo está actualmente en preparación.<br /

Elicitation of retinal neural circuitry with vision prosthetic devices

Vision prostheses currently under development by several research groups aim to restore functional sight to the profoundly blind suffering from retinal neural degenerative diseases. Human clinical trials in the last decade have demonstrated the ability of these devices to elicit simple percepts, such as bright spots of light. However, further improvements in implant perceptual efficacy will critically depend on improved understanding of the retinal neural mechanisms underlying the electrically evoked responses, and on how these mechanisms could be controlled artificially. In the first part of this thesis I quantitatively study, using a new statistical analysis technique, the temporal response properties of the retinal ganglion cells (RGCs) following electrical stimulation of the retina. I also demonstrate conclusively, for the first time, that small electrodes placed in the subretinal space could reliably elicit direct RGC spiking responses. In the second part of the thesis I investigate the mechanisms underlying the previously observed RGC response depression during repeated electrical stimulation of these cells. The experimental findings lead me to the development of a new stimulation method for preventing the response depression. The image processor is a crucial component of a vision prosthesis. It replaces some of the neural computations that occur in a healthy retina by converting visual stimuli into electrical stimuli. In the final part of the thesis I implement an image processor for a vision prosthesis. I show that such devices could be built with appropriate embedded hardware. Benchmark testing suggests that, depending on the complexity of the image processing strategies, care should be exercised in generalising the performance of algorithms developed on standard computers to these embedded devices

Using magnetic resonance imaging to assess visual deficits : a review

PURPOSE: Over the last two decades, magnetic resonance imaging (MRI) has been widely used in neuroscience research to assess both structure and function in the brain in health and disease. With regard to vision research, prior to the advent of MRI, researchers relied on animal physiology and human post-mortem work to assess the impact of eye disease on visual cortex and connecting structures. Using MRI, researchers can non-invasively examine the effects of eye disease on the whole visual pathway, including the lateral geniculate nucleus, striate and extrastriate cortex. This review aims to summarise research using MRI to investigate structural, chemical and functional effects of eye diseases, including: macular degeneration, retinitis pigmentosa, glaucoma, albinism, and amblyopia. RECENT FINDINGS: Structural MRI has demonstrated significant abnormalities within both grey and white matter densities across both visual and non-visual areas. Functional MRI studies have also provided extensive evidence of functional changes throughout the whole of the visual pathway following visual loss, particularly in amblyopia. MR spectroscopy techniques have also revealed several abnormalities in metabolite concentrations in both glaucoma and age-related macular degeneration. GABA-edited MR spectroscopy on the other hand has identified possible evidence of plasticity within visual cortex. SUMMARY: Collectively, using MRI to investigate the effects on the visual pathway following disease and dysfunction has revealed a rich pattern of results allowing for better characterisation of disease. In the future MRI will likely play an important role in assessing the impact of eye disease on the visual pathway and how it progresses over time

Analysis of Factors Affecting the Performance of Retinal Prostheses Using Finite Element Modelling of Electric Field Distribution in the Retina

This dissertation proposes a computational framework targeted at improving the design of currently employed retinal prostheses. The framework was used for analysing factors impacting the performance of prostheses in terms of electrical stimulation for retinal neurons, which might lead to a perception of pixelated vision. Despite their demonstrated effectiveness, the chronic and safe usage of these retinal prostheses in human and animal trials is jeopardised due to high stimulation thresholds. This is related to the distance between the stimulating electrodes and the retinal neurons resulting from the implantation procedure. The major goal of this dissertation was to evaluate the stimulation efficacy in current implantable planar microelectrode-based retinal prostheses and consequently demonstrate their weakness, thereby providing scope for the development of future implants. The effect of geometrical factors i.e., electrode-retina distance and electrode size on stimulation applied to the retina by retinal prostheses was studied. To this end, a finite element method based simulation framework to compute electric field distribution in the retina was constructed. An electrical model of the retina was an integral part of the framework, essentially represented by a resistivity profile of the multi-layered retina. The elements of a retinal prosthesis were modelled by incorporating realistic electrode sizes, an anatomical and electrical model of the retina, a precise positioning of stimulation and return electrodes and the location of the implant with respect to the retina representing the epiretinal and subretinal stimulation schemes. The simulations were carried out both in quasi-static and direct current (DC) modes. It was observed that electrode-electrolyte interface and tissue capacitance could be safely neglected in our model based on the magnitude of the applied voltage stimulus and frequencies under consideration. Therefore, all simulations were conducted in DC mode. Thresholds and lateral extents of the stimulation were computed for electrode sizes corresponding to existing and self-fabricated implants. The values and trends obtained were in agreement with experiments from literature and our collaborators at the les Hôpitaux Universitaires de Genève (HUG). In the subretinal stimulation scheme, the computed variation of impedance with electrode-retina distance correlated well with time varying in vivo impedance measurements in rats conducted in collaboration with the Institut de la Vision, INSERM, Paris. Finally, it was also reiterated that the currently employed retinal prostheses are not very efficient due to a significant distance between the stimulation electrode and the retinal cells. In addition, I present a new experimental technique for measuring the absolute and local resistivity profile in high-resolution along the retinal depth, based on impedance spectroscopy using a bipolar microprobe. This experiment was devised to extract the resistivity profile of an embryonic chick retina to construct an electrical model for the simulation framework to simulate in vitro retinal stimulation experiments conducted by HUG collaborators. We validated the capability of the technique in rat and embryonic chick retinas. In conclusion, the computational framework presented in this dissertation is more realistic than those found in literature, but represents only a preliminary step towards an accurate model of a real implantation scenario in vivo. The simulation results are in agreement with results from clinical trials in humans for epiretinal configuration (literature) and with in vitro results for epiretinal and subretinal stimulation applied to chick retinas (HUG). The developed simulation framework computes quantities that can form a reference for quality control during surgery while inserting implants in the eye and functionality checks by electrophysiologists. Furthermore, this framework is useful in deciding the specifications of stimulation electrodes such as optimal size, shape, material, array density, and the position of the reference electrode to name a few. The work presented here offers to aid in optimising retinal prostheses and implantation procedures for patients and eventually contributes towards improving their quality of life

Extracellular electrical stimulation of retinal ganglion cells

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (p. 106-110).by Andrew Eli Grumet.M.S