Tuesday, December 12, 2006 Visual Prostheses: A New Hope for the Blind?

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1 Tuesday, December 12, 2006 Visual Prostheses: A New Hope for the Blind? ABSTRACT Vision is our most heavily relied upon sense. Unfortunately, each year in the U.S alone 200,000 individuals develop age-related macular degeneration, and 12-24,000 lose their sight to diabetic retinopathy (3). An additional 3 million individuals are afflicted with irreversible damage from glaucoma (3), and many others are afflicted with different degenerative diseases or congenital blindness. It is believed that many of these individuals could benefit from an artificial system that would mimic the damaged portion of their visual systems a visual prosthesis. An increase in the understanding of visual systems, as well as developments in microcircuitry have allowed researchers to close in on visual prostheses capable of producing sight sufficient for basic tasks such as reading and navigating. A far cry from bulky electrodes used by researchers such as Harvey Dobelle in 1974 to directly stimulate the occipital lobe (where vision is ultimately processed), a large portion of current research focuses on creating circuits that mimic the behavior of the reception, rather than processing, portions of the visual system (2). Circuits replacing the inner retina attempt to reproduce the function of retinal pigment epithelial cells, while outer retinal circuits bypass the patient s own photoreceptors and directly stimulate the layer of the retina that outputs information to optic nerves (1). These circuits have been researched separately as well as in conjunction. Other approaches include stimulating higher level processing systems such as the optic nerve, or the visual cortex(1). This is not the preferential route however, because it is understood that these higher level systems are usually intact in blind persons and need not be replaced an advantage that should be used in conjunction with an artificial input system (1). Currently the most promising approach utilizes neuromorphic chips; they are constructed using circuits based on the various feedback loops that exist between neurons, and replicate neural behavior using a combination of stimulation from their environment and interactions with each other(4). To date, chips have succeeded in outputting signals that can be passed into a digital system(5). These signals result in images resembling the initial input, assuming this input is a static image(5). Though neuromorphic chips have succeeded in this process of filtering and encoding static 1

2 patterns of light with some satisfaction, visual implants still face issues of efficiency, as the circuits consume orders of magnitude more energy than do natural retinas, accuracy, as the images are fuzzy and vague, and an incomplete understanding of all of the interactions in the visual pathway (5). INTRODUCTION It is estimated that intraocular vision implants can significantly improve the visual perception of 100,000 U.S. citizens, including those suffering from diseases such as macular degeneration, diabetic retinopathy, infection, and injury (6). In order to discuss the construction of a functional sight replacement, the anatomy and physiology of the eye and the neurological components of sight must first be understood. ANATOMY OF THE EYE Figure 1 illustrates the major anatomical features of the eye. Light entering the eye first passes through the cornea, which keeps the shape of the eye, before passing through the lens, which focuses the incoming light on the retina - the light sensing structure (7). The outer layer of the retina is composed of two light sensing structures rods and cones (7). Rods are responsible for night vision, and therefore will not be discussed in this paper Figure 1 (7) Anatomy of the eye (however both structures operate in essentially the same manner chemically). Cones are responsible for color and high detail vision. While cones are present throughout the retina, the macula, or fovea, which is located in the center of the retina, contains almost exclusively cone cells, and is responsible for high acuity tasks such as reading and color vision (8). In macular degeneration, these cone cells degrade or malfunction resulting in blurred or missing central vision (3). Finally light incident on the cones causes the cones to release electrical signals which are then transferred to the optic nerve and are carried to processing centers in the brain. 2

3 ELECTRICAL SIGNAL PROCESSING Light entering the eye causes a complex chain of electrical signals that eventually results in vision perception. The first step in the chain involves a change in rhodopsin, a protein produced by cone cells (7). Light induces a physical change in the protein, causing it to degrade (7). This degradation causes the electrical charge in the cone cell Light to increase, producing an electric current (7). Electric The signal from the cone is then filtered by Signal Optic a network of interneurons, shown in figure 2, including horizontal, bipolar, and Figure 2 (8) Nerve Light enters the retina, travels past ganglion, amacrine, bipolar, and horizontal cells to the rods and cones where an electric signal is produced. amacrine cells(1). The horizontal and amacrine This signal travels back through the retina to the cells are not responsive to light like cones and ganglion cells, which join and form the optic rods are; instead, they serve to connect neighboring nerve. photoreceptors, bipolar cells, and ganglion cells (7). Bipolar cells carry signals from rods and cones to ganglion cells (7). The complexity of the interactions between neighboring cells serves to filter and begin processing the electrical signals produced by rods and cones processing that maintains details and enhances image contrast (1). The interneurons then pass the signal to ganglion cells which have long fibers connecting to the optic nerve(8). It is important to note that the rod and cone cells are actually located behind the interneurons and ganglion cells. There is a location in the retina where all of the ganglion nerve fibers join together and travel back through the retina to the optic nerve. This is known as the blind spot, because photoreceptor cells are not present in this spot. Luckily, this spot is not perceived because each eye covers the other eye s blind spot.(7,8) The optic nerve carries signals to several parts of the brain, however information that will reach the primary visual cortex must first be processed in the lateral genticulate nucleus 3

4 LGN)(8). The LGN separates signals into streams of information concerning color and fine structure, or contrast and motion(8). This information is sent to the primary visual cortex, which compares signals from both eyes to determine depth, and begins to process signals to determine the edges of objects (8). Figure 3 demonstrates the basic path of electrical signals from the retina. The left half of each retina produces signals that are carried to the left lateral genticulate nucleus via the optic nerve for complex processing that largely involves removing redundant signals and sending signals to the correct neurons in the left visual cortex (8). The same goes for the right half of each eye. DESIGN PARAMETERS As mentioned previously, this complex visual pathway is our primary means of perceiving our surroundings. Therefore, a prosthesis that is capable of reproducing one or multiple portions of this pathway in order to correctly signal the brain and induce sight would be beneficial to hundreds of thousands of blind individuals. Theoretically, if the signal is correct, stimulation at any point in the visual pathway will produce sight, and current approaches involve stimulation of the optic nerve or primary visual cortex, as well as implantation of artificial retinas that stimulate intact ganglion cells. Despite the various approaches, there are some universal design parameters that apply to all of the mentioned stimulation techniques, as well as to implantable devices in general. As discussed previously, a functional retina performs the job of taking in light and transforming it into electrical signals. In most blind individuals the retina is the damaged portion of the visual pathway, and so the step of transforming light into electrical signals 4

5 must be done artificially, regardless of what part of the visual pathway is going to be stimulated by the prosthesis (1). In other words, an interface that takes in light (usually with a camera), analyzes it, and transforms it into a signal appropriate for the target structure (i.e. the optic nerve, cortex, etc) must be produced(1). Another characteristic common to all approaches is an implantable electrode array. This electrode array or arrays must be safe biologically compatible materials must be used, and should produce as little of an immune response as possible, because biological responses such as the proliferation of nearby cells can cause damage to the electrode or can dampen the signals transmitted by the electrode enough to destroy its ability to actually stimulate cells (2). Because the function of the electrodes is to transfer electrical signals, energy efficiency is another concern; for example, current artificial retina models (either camera/electrode combinations or small implantable circuits) consume over than 1,000 times more energy than natural retinas(5). There are also issues that may not become overly relevant until visual prostheses become a reality and patients have to be considered. The first issue of this kind is the safety of implantation technique. Even devices that have been tested have been only experimentally implanted in subjects for a short period of time; therefore safe, consistent surgical techniques providing long term electrode stability have not yet been developed due to lack of opportunity. Another consideration is cost effectiveness. Cost effective solutions are always looked upon favorably, though actual costs are unknown, as there are no technologies currently available to the general public. Finally, a concern that may be more pertinent to patients than to researchers is whether the device is cosmetically acceptable many profoundly blind people cope very well and may not accept a prosthesis that does not perform well in all of these areas. (2,5) Perhaps most importantly, visual prostheses must produce visual perception adequate enough to allow the individual to perform activities that cannot be performed with current technologies, such as reading, recognizing faces, and navigating new spaces this includes the formulation of accurate processing algorithms and mapping of locations from the visual field to the optic nerve or visual cortex (1). CURRENT TECHNOLOGIES OVERVIEW 5

6 The concept of using electrical signals to produce the perception of sight first appeared in 1956, when Tassiker implanted a small, flat light-sensitive selenium cell behind the retina of a blind patient and observed that the patient could transiently perceive light (9). The ability to produce electrodes on the scale of neurons (micrometers), has allowed researchers to stimulate only a few neurons at a time. Because of this capability, researchers are attempting to stimulate the nervous system at four different stages in the visual perception process. Examples of each type of stimulation will each be discussed in more detail - direct stimulation of the visual cortex or the optic nerve, and sub or epiretinal modeling. STIMULATION OF THE VISUAL CORTEX A BRIEF HISTORY The idea of stimulating the brain in order to restore visual perception goes back to approximately the 1960 s, when Charles Brindley s research team implanted 180 electrodes on the surface of the visual cortex of a blind subject and used electrical currents to stimulate the neurons found therein(2). Both Brindley, and his contemporary Dobelle, found that this manner of stimulation produced phosphenes, or points of light, in the subjects visual fields. Additionally, Dobelle found that patterns of light resulted from stimulation of multiple electrodes at once, and that there was a logical mapping between the location of the perceived pattern in the visual field and the cortical stimulation site (1,2). In other words, the location of perceived light could be predicted based on the area of the brain that was stimulated, and stimulation of nearby areas of the brain would produce points of light that were also close together (though this is a simplification, it is often the case). However, the electrodes required 1-3mA to generate phosphenes, and the 1mm diameter electrode disks needed to be placed at least 3 mm apart in order to minimize interaction with one another (1). This precludes the ability to target specific neurons, which are on the micrometer scale(1) and can be stimulated with as little as.1 micro-amps using micro-electrodes(13). Electrode size, and therefore lack of precision in neuron stimulation, prevented progress until micromachining and manufacturing allowed the development of microelectrodes that could be spaced as closely 6

7 as 500 micrometers and penetrate the cortex (1). Whereas previous electrodes rested on the surface of the cortex, penetration of the brain allows for more specific targeting of neurons located deeper in the cortex (1). Figure 4 A hypothetical visual prosthesis set-up, including a camera, processor, and electrode array attached to the visual cortex. (2) (MORE) RECENT DEVELOPMENTS In functional visual systems, the retina transforms light into electrical signals that are interpreted by the visual cortex. Visual prostheses must therefore have a means of transforming light signals into electrical signals that can be properly interpreted by the brain. With stimulation the visual cortex, this means a video camera must be attached to a type of processor that uses a complicated algorithm to determine which electrodes to stimulate and what kind of current (length, strength, etc.) to stimulate them with.(1,7) As of 2003, several groups of researchers were still developing a preprocessor to provide an electrode array with input appropriate for simulating the signal sent to the visual cortex from the lateral genticulate nucleus. The preprocessor consisted of four components to represent the four main components of retinal processing: 1. The camera acted as a photosensor (cone). The following steps all require the use of a computer processor operating using a complex algorithm for interpreting the information received from the camera: 2. Yellow vs. blue, red vs. green, and visible light wavelength filters were used to enhance certain features. This function is meant to parallel extraction of important information performed by the ganglion cells. Specifically, the electrical output of the system to the electrodes is dependent on the differences in intensity between different wavelengths of light, not the actual wavelengths being recorded. This allows the system to increase the activity of certain electrodes when contrast is present, resulting in a greater contrast in the final picture. 7

8 3. A weighting module was used to weight the strength of each of the three filter outputs by producing a weighted sum of the three filter outputs. The weight on each filter output was user defined, and the goal was to weight the outputs such that the image contrast was enhanced further. 4. This particular study output the information to a computer A which then interpreted the signal (seen in figure 5). However, in an actual visual prosthesis, the selection of the output electrodes would need to take the image and map it B as it would be mapped from the retina to the visual cortex. This would likely include a complex mapping algorithm. Figure 5 demonstrates the current abilities of this technology. C Image A shows a simple recording of an image using a video Figure 5 (12) camera. In image B this signal is sent to an electrode array, where The top image is a simple video recording of the scene. the amount of electrical activity in each electrode is represented by The second image represents the the shade seen in B. Image C represents how a blind patient might activity level of each electrode. The third image attempts to perceive the signals from the electrode array C is an approximation determine how the visual cortex of how the cortex would process the electrical signal based on the would interpret the activity shown in the second image. current knowledge of cortical function. So, from image A to image C there is a progression image A uses pre-existing technology, image B exhibits the new ability to transmit a video signal to electrodes, and image C represents what will hopefully be seen by blind subjects in the future. As far as actual subjects are concerned, the signal would have to be carefully neuromorphically mapped if such a system was to be implemented in vivo that is, the video input would have to be transmitted to the same places in the visual cortex as actual retinal inputs(12). STIMULATION OF THE OPTIC NERVE METHOD OVERVIEW 8

9 The optic nerve is the last place in the visual pathway where the entire visual field is represented before the brain starts processing information. Inputting the proper signal at this level would therefore take advantage of the brain s complex signaling system. The system currently employed to stimulate, and therefore cause movement, in the mucles of paralyzed patients may be applicable to the stimulation of the optic nerve. In neuromuscular stimulation, sets of electrodes attached along a type of wire are spiraled around the target nerve. These sets of electrodes are known as spiral cuff electrodes. Such a cuff could potentially be wrapped around the optic nerve and, given the correct input signal, stimulate the optic nerve in the same manner as it is stimulated by the ganglion cells of the retina. Due to the relatively small space to which the visual field is reduced, such a cuff would require a complex electrical stimulation pattern. Another issue that needs to be addressed is possibility of needing a large number of electrodes, in order to very selectively stimulate single nerve fibers, which could damage the nerve. This situation may therefore benefit from the use of intraneural microelectrodes they require smaller currents and can be placed more closely, which provides higher selectivity and accuracy. Despite improved electrical accuracy, the mapping of the retina to the fibers in the optic nerve is only coarsely understood and animal studies have failed to show a finer organization. (1,14) PROOF OF CONCEPT In 2001 a Belgian group reported on their investigation into the stimulation of the optic nerve. The study aimed to determine the electrical threshold for phosphene perception and the relationship between electrical signal parameters and phosphene characteristics in order to accurately predict phosphene position. The system worked as follows: A camera was attached to an external computer, which acted to transform video input into electrical signals using pre-determined algorithms. A transcutaneous wire then transferred the data to an internal circuit which would subsequently output signals to one of four electrodes attached to a spiral cuff located on the optic nerve. For most of the study, the camera was bypassed, and the electrical pulses were artificially chosen with parameters corresponding to the wave shape, duration, frequency, amplitude, and number 9

10 of repetitions in order to gather data as to what effect each parameter had on the phosphene pattern reported by the subject. (10) The subject s optic nerve was surgically fitted with spiral cuffs containing a varying number of electrodes, and asked to identify the positions of phosphenes resulting from the chosen electrical stimulation. The data was then randomly split into a training data set and a validation set. The training set was used to formulate prediction equations. The parameters from the validation set were then plugged into these equations to determine the accuracy of the equations (i.e. were the phosphene locations predicted by the equations the same as the phosphene locations reported by the subject). Assuming a 180 degree range of vision, the equations were accurate to within 5 degrees horizontally and 10 degrees vertically, which is at worst a 5.5% prediction error. Figure 6 shows the error distribution using the most accurate prediction equation. Although the mathematics are difficult to understand for those not involved in this specific area of research, the conclusion is that, due to the subjective nature of the reported phosphene locations, these results are Figure 6 satisfactory. (10) These are error distribution graphs for the horizontal and vertical phosphene This approach seems rather invasive and even risky for locations using the most accurate a visual prosthesis. Wires and circuits need to be equation i.e. this equation yielded the lowest standard deviation. It is obvious in implanted very near to the center of the skull, and the first graph that most of the data points permanent links across the skin are known to be prone for the horizontal location were predicted to within 5 degrees of the actual value. It to infection(2). Additionally, the effects of constant is also possible to see in the second graph electrical stimulation of the optic nerve are unknown, that the vertical locations of phosphenes were most often predicted to within ten though possible risks include damage due to the degrees of the actual reported location. constant heat emitted by the electrical components (10) and/or relatively high voltages needed (similar to the energy situation previously discussed concerning cortical electrodes)(1). RETINAL IMPLANTS 10

11 It has been determined that most causes (whether congenital, pathological, or accidental) of blindness leave higher level processing structures such as the optic nerve and primary visual cortex intact. Therefore, replacing the retina, which is responsible for the initiation of an increasingly complex pathway takes advantage of the processing power of the optic nerve, lateral genticulate nucleus, primary visual cortex, etc. There are currently two approaches to retinal implant models the epi-retinal implant and the sub-retinal implant. Each has its pros and cons, and both seem to be technically viable.(1) Development of either type of retinal implant follows the same procedure. First of all, a microelectrode array or arrays must be created, preferably using the most biocompatible materials possible. Such an array would act as the retina itself in the case of the subretinal implant(taking in light and emitting electrical signals), or would transfer a processed external electrical signal to the ganglion cells in the retina in the case of an epiretinal implant. Circuits capable of mimicking retinal neuron interactions must then be developed for the electrode array. The devices would eventually require implantation, and so surgical techniques must be developed to implant, remove, and repair the electronic components. Animal models must eventually be tested before human tests are approved, a process which involves the consideration of ethical and regulatory issues (9). EPI-RETINAL IMPLANTS Epi-retinal implants are located directly on the ganglion cells that later form the optic nerve (9). This means that the system contains no light sensitive elements (9) in fact it requires an external system to preprocess images (11). An electrode array is secured to the inner-retinal membrane (near the ganglion cells) using a microtack (9). A camera or similar device is then used to process images into electrical waves (9). An algorithm then analyzes these waves and determines which electrodes in an electrode array to signal (9). This is a difficult procedure, and the cells in this area of the retina have a greater chance of proliferating and disturbing the array (9). One potential complication with this set-up is the proximity of epi-retinal implants to the axons of ganglion cells usually the implants would stimulate what is called the cell body and that stimulation would travel to the axon 11

12 (9). Because axons both branch out from a central location and become more spatially concentrated as they join to form the optic nerve, electrical signals received directly by axons would more easily spread and affect neighboring cells (9). In other words, attempted stimulation of a specific ganglion cell would produce an unpredictable signal to surrounding cells as well(9). Figure 7 depicts the locations of the various cell types located in the retina, as well as the locations of the subretinal and epiretinal implants. One particular study of epiretinal implants involved the actual implantation of an electrode array on the ganglion side of the retina of a blind subject. The electrodes were selectively stimulated and the subject was asked to report either the location of the phosphene or which electrode had been stimulated. While phosphenes evoked by electrodes nearer the center of the retina were more easily perceived, in general the subject repeatedly accurately reported which electrodes were being stimulated and was capable of detecting the motion of bright points of light as well as location and motion of dark objects under normal lighting conditions (11). SUB-RETINAL IMPLANTS Figure 7 (9) An energy signal from an external source is received by the implant, which subsequently sends electrical pulses to specific ganglion cells. Unlike epi-retinal implants, sub-retinal implants are passive, which means that they do not require an external processor (1). Arrays of photodiodes, which send out an electrical pulse when struck with light of sufficient energy, convert light directly into electrical signals that are then sent to the other layers of the retina, taking full advantage of the body s vision processing capabilities(1). Electrode arrays made for this purpose have been implanted in rats, rabbits, cats and pigs to determine long term viability, and have remained intact and induced little biological response, even after years under the retina 12

13 (15). However, natural light is not strong enough to generate a large enough current in the electrodes to evoke phosphenes, and an external power source may therefore be required (9). Unlike the epiretinal implant, however, there has yet to be an in vivo human study involving a sub-retinal implant. This is unfortunate because, power concerns notwithstanding, the sub-retinal implant approach is the only approach that does not require a transdermal electrical link. THE FUTURE OF RETINAL IMPLANTS Current research into retinal implants involves using what is known about cell interactions within the retina to construct circuits that model this behavior. In 1994, Boahen and Zaghloul published two papers concerning such an approach. The first paper outlined the highly complex circuitry which represented both the outer and the inner retina, while the second paper reported the results of introducing stimuli to these circuits. Very simply, photodiodes were connected to circuits meant to act as an inner and an outer retina. The electrical signals produced by each diode were linked, via circuit, to the signals of the six closest diodes. Complex equations and additional circuitry was used to analyze this combined output and enhance image contrast as well as Figure 8 (5) allow the final output to change over time. For example, a The first image is the actual electrical output from the medium strength signal from a diode surrounded by diodes circuit. The bottom image is emitting no signal may be further strengthened for contrast identical but with inverse shading, representing what enhancement. someone would (hopefully) In order to test the circuit, digital input was sent directly to the actually see. inner retinal model, electrical signals passed through the circuit, and the output was again encoded into a digital format, and displayed on a screen. Figure 8 shows the output given a static input image. This is promising, however the purely digital format does not address the fact that, despite the 13

14 direct conversion of light to electricity by the inner retinal model, the circuits may not output a signal that is appropriately interpreted by the optic nerve. (4,5) EVALUATION OF METHODS Each of the four discussed methods has both advantages and drawbacks. While the complexity of the visual system has prevented any of the interactions between components from being fully understood, I believe the optic nerve model is particularly so, and that the lack of a specific mapping from retina to nerve, as well as the potential risk of damaging then nerve fibers makes it an unlikely candidate for a functional prosthesis. Stimulation of the cortex has proven that electrical signals can cause the perception of sight, though there are still logistical issues such as the need for portability of the preprocessing unit one estimate is that five to ten years will be needed before a functional unit is developed (12). When input and output are controlled with electronic devices, retinal implants perform well enough to allow the detection of basic shapes (5), and an epi-retinal implant has even been tested in vivo with similar results however more complex stimulation is required for an ideal system (11). While power input to both artificial retinal models is a concern (5), I believe that a device that could fully utilize the visual preprocessing power of the brain seems optimal. CONCLUSION THE FUTURE OF VISUAL PROSTHESES Although neural implants have been developed to perform tasks such as hearing restoration and prevention of epileptic seizures, a significantly more complex system is needed to restore visual function (1). Current prostheses allow individuals to detect light, motion, and simple shapes, though in a limited manner (11). Current concerns are similar to those expressed nearly a decade ago electrodes may have diminished in size, however there are still power, accuracy, and overall safety issues to be addressed. However, visual prostheses have come a long way in a short period of time, and all available sources are optimistic about the eventual success of a visual prosthesis. Bibliography 14

15 (1) Maynard, Edwin M. (2001, August). Visual Prosthesis. In Annual Review of Biomedical Engineering, 3, Retrieved October 1, 2006 from Annual Reviews database. (2) Normann, Richard A., et al. (1996, May) Cortical implants for the blind. IEEE Spectrum, Retrieved October 1, 2006, from IEEE database. (3) Wrong Diagnosis. Retrieved October 5, 2006 from (4) Zaghloul, Kareem A., and Boahen, Kwabena. (2004, April). Optic Nerve Signals in a Neuromorphic Chip I: Outer and Inner Retina Models. IEEE Transactions on Biomedical Engineering, 51(4), Retrieved October 3, 2006, from IEEE database. (5) Zaghloul, Kareem A., and Boahen, Kwabena. (2004, April). Optic Nerve Signals in a Neuromorphic Chip II: Testing and Results. IEEE Transactions on Biomedical Engineering, 51(4), Retrieved October 3, 2006, from IEEE database. (6) Schmid, Andreas. (2004) Stimulation Signal Processing for Intraocular Vision Implants. Proceedings of the 17 th IEEE Symposium on Computer-Based Medical Systems. (7) Bianco, Carl. How Vision Works. Retrieved December 4, 2006, from (8) Sceintific Learning Corporation. How Vision Works. Retrieved on December 4, 2006, from (9) Zrenner, Eberhart. (2002, February). Will Retinal Implants Restore Vision? Science, (10) Verleysen, Michel, et al. (2001) Phosphene Evaluation in a Visual Prosthesis with Artificial Neural Networks. Eunite 2001 proceedings, (11) Humayun, Mark S. et al.(2003) Visual Perception in a Blind Subject with a Chronic Microelectronic Retinal Prosthesis. Vision Research, 43, Retrieved December 4, 2006, from Science Direct. (12) Pelayo, F.J, et al.(2003) Cortical Visual Neuro-Prosthesis for the Blind: Retina-Like Software/Hardware Preprocessor. Proceedings of the 1 st International IEEE EMBS. (13) Normann, Richard A., et al. (1999) A neural interface for a cortical vision prosthesis. Vision Research, 39, Retrieved December 4, 2006, from Science Direct. (14) Functional Neuromuscular Stimulation in Walking and Pedaling, 15

16 (15) Sachs, Helmut G., and Gabel, Veit-Peter. (2004) Retinal Replacement- the development of microelectronic retinal prostheses- experience with subretinal implants and new aspects. Graefe s Archive of Experimental Ophthalmology, 242: