neural stimulation for visual rehabilitation: advances and...

Journal of Physiology - Paris xxx (2012) xxx–xxx

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Journal of Physiology - Paris

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Review Paper

Neural stimulation for visual rehabilitation: Advances and challenges

Henri Lorach a,b,c,⇑, Olivier Marre a,b,c, José-Alain Sahel a,b,c,f,g,h, Ryad Benosman a,b,c,d,e, Serge Picaud a,b,c,h

a INSERM, U968, Institut de la Vision, 17 rue Moreau, Paris F-75012, Franceb UPMC Univ Paris 06, UMR S968, Institut de la Vision, 17 rue Moreau, Paris F-75012, Francec CNRS, UMR 7210, Institut de la Vision, 17 rue Moreau, Paris F-75012, Franced UPMC, ISIR, 4 Place Jussieu, Paris F-75005, Francee CNRS, UMR 7222, ISIR, 4 Place Jussieu, Paris F-75005, Francef Centre Hospitalier National d’Ophtalmologie des Quinze-Vingts, 28 rue de Charenton, Paris F-75012, Franceg Institute of Ophthalmology, University College of London, UKh Fondation Ophtalmologique Adolphe de Rothschild, 25 rue Manin, Paris F-75019, France

a r t i c l e i n f o a b s t r a c t

Article history:Available online xxxx

Keywords:Visual information codingVisual perceptionProstheticsImplantsBlindness

0928-4257/$ - see front matter � 2012 Elsevier Ltd. Ahttp://dx.doi.org/10.1016/j.jphysparis.2012.10.003

⇑ Corresponding author at: Institut de la Vision, 17France. Tel.: +33 1 53 46 26 66.

E-mail address: [email protected] (H. Lorach)

Please cite this article in press as: Lorach, H.,dx.doi.org/10.1016/j.jphysparis.2012.10.003

Blindness affects tens of million people worldwide and its prevalence constantly increases along withpopulation aging. In some pathologies leading to vision loss, prosthetic approaches are currently the onlyhope for the patient to recover some visual perception. Here, we review the latest advances in visualprosthetic strategies with their respective strength and weakness. The principle is to electrically stimu-late neurons along the visual pathway. Ocular approaches target the remaining retinal cells whereasbrain stimulation aims at stimulating higher visual structures directly. Even though ocular approachesare less invasive and easier to implement, brain stimulation can be applied to diseases where the connec-tion between the retina and the brain is lost such as in glaucoma and could therefore benefit to patientswith different pathologies. Today, numbers of groups are investigating these strategies and the firstdevices start being commercialized. However, critical bottlenecks still impair our scientific effortstowards efficient visual implants. These challenges include electrode miniaturization, material optimiza-tion, multiplexing of stimulation channels and encoding of visual information into electrical stimuli.

� 2012 Elsevier Ltd. All rights reserved.

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 002. Prosthetic rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00

2.1. Epiretinal implants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 002.2. Subretinal implants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 002.3. Transchoroidal prostheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 002.4. Optic nerve prostheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 002.5. Cortical and LGN implants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00

3. Global challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00
3.1. Electrode configuration and materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 003.2. Image processing for visual rehabilitation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 003.3. Importance of ocular movements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 003.4. Comparison of the different strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00
4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00

ll rights reserved.

rue Moreau, Paris F-75012,

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et al. Neural stimulation for visual rehabilitation: Advances and challenges. J. Physiol. (2012), http://

http://dx.doi.org/10.1016/j.jphysparis.2012.10.003

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Fig. 1. Global causes of blindness. Percentages of blindness causes in 2010 (AMD:Age-related Macular Degeneration). Retinitis pigmentosa and age-related maculardegeneration account for 9% of blindness cases. Data from the World HealthOrganization (2010).

2 H. Lorach et al. / Journal of Physiology - Paris xxx (2012) xxx–xxx

1. Introduction

Blindness is one of the most debilitating sensory impairmentaffecting 39 million people worldwide. The leading cause of this

Fig. 2. LeRoy’s experimental procedure for ocular stimulation in 1755. A conductivewire was place around the head of a patient blind from cataract with another onearound his leg. The discharge of a Leyden jar passed through the eye of the patientevoking vivid flashes of light.

Please cite this article in press as: Lorach, H., et al. Neural stimulation for vdx.doi.org/10.1016/j.jphysparis.2012.10.003

sensory disability is cataract accounting for 51% of cases, however,it can be treated very efficiently, but access to treatment remainsan issue in most underdeveloped countries. The remaining causesof acquired blindness are glaucoma, age-related macular degener-ation (AMD), diabetic retinopathy, and retinitis pigmentosa (RP).Fig. 1 summarizes the global causes of blindness and their preva-lence. In these diseases, different cell types can be deficient anddegenerate, thereby triggering blindness. For instance, photorecep-tors are degenerating in RP and AMD whereas retinal ganglion cellssending visual information to the brain are lost in diabetic retinop-athy or glaucoma. For some of these diseases, there is currently noefficient treatment for preventing severe visual loss or blindness.This is the case for RP accounting for 1 million patients worldwide.In these pathologies, photoreceptor degeneration leads to a pro-gressive reduction of the visual field often declining to legal blind-ness. For the past 40 years, tremendous efforts towards visualrehabilitation through electrical stimulation of the neural tissuewith implanted electrodes have been conducted. We will presenthere the recent developments and our latest advances in the fieldof visual prosthetics and the current technological and conceptualbottlenecks that will need to be overcome to restore functional vi-sion in blind patients.

2. Prosthetic rehabilitation

In 1755, Charles LeRoy applied the electric discharge of aLeyden jar – an ancestor of capacitors – on the ocular surface ofa patient blind from cataract (Fig. 2). This stimulation elicited vividflashes of light or phosphenes, reported by the patient. It was thestarting point of visual prosthetics and from this point, variousstrategies have been investigated to restore visual perceptionthrough electrical stimulation.

Electrical stimulation of the visual system can be performed onmultiple locations along the sensory pathway. First, the retina canbe stimulated in case of ganglion cell survival and preservation ofthe information flow through the optic nerve. Stimulating the opticnerve directly is also possible, although the high density of nervefibers is an issue for stimulation control. And finally, it is possibleto stimulate brain structures such as the lateral geniculate nucleus(LGN) or the visual cortex directly, even in case of complete retinaldegeneration or optic nerve injury. However, these strategies aremuch more invasive. In all cases, the device consists in a photosen-sitive part – i.e. camera – a processing stage and an array of elec-trodes in contact with the targeted structure (Fig. 3).

We will present here the latest advances in visual implants andthe major challenges that need to be addressed.

2.1. Epiretinal implants

Epiretinal implants electrically target the ganglion cell layer. Amatrix of electrodes is directly fixed on the surface of the retinawith a tack and connected to a stimulator receiving data and powerthrough coil–coil interaction and radio-frequency (RF) signal.

Humayun et al. were the pioneer of epiretinal implants(Humayun et al., 2003, 2009, 2012). The first epiretinal device tobe chronically implanted in patients – the Argus I – developed bySecond Sight Medical Products was composed of 16 Pt electrodes(Humayun et al., 2003; Caspi et al., 2009). Their report confirmedthat light perception could be achieved through epiretinal stimula-tion. The implanted patient was able to recognize shapes, gratingsorientations, and had a restored visual acuity of 20/3240.

The next generation of their epiretinal device named Argus IIwas designed to reach a higher resolution. Fig. 4 describes the Ar-gus II device containing a 6 � 10 electrode matrix implanted in 30subjects from 2007 to 2009.

isual rehabilitation: Advances and challenges. J. Physiol. (2012), http://



Epiretinal

Subretinal

Optic nerveSecond Sight Medical Products, USEPI-RET group, Germany

Intelligent Medical Implants, SwitzerlandBionic Vision, Australia

SuprachoroidalRetina Implant AG, Germany

Stanford group, USBoston Retinal Implant Project, US

University of Louvain, BelgiumJia-Tong Universuty Shanghai, China

Seoul National University, South KoreaOsaka University, JapanBionic Vision, Australia

CorticalUniversity of Utah, US

Illinois Institute of Technology, US

LGNHarvard Medical School, US

Fig. 3. Summary diagram of the visual system and approaches to restore vision. Six main strategies are currently investigated to restore vision through electrical stimulation.Retinal approaches including subretinal, epiretinal and suprachoroidal strategies; optic nerve stimulation and brain stimulation including lateral geniculate nucleus (LGN)and cortical targets. Among the suprachoroidal strategies, both Osaka University and Seoul National University devices are inserted between the sclera and the choroidwhereas Bionic Vision Australia is developing a completely extra-ocular strategy.

Fig. 4. The first commercialized visual implant: the ARGUS II from Second Sight Medical Products. (A) External part of the device consisting in a pair of glasses carrying thecamera and the Video Processing Unit (VPU). (B) The implanted components including the coil for RF communication, the stimulators and the electrode array. (C) Fundus ofthe implanted retina. (D) Optical Coherence Tomography (OCT) image of the implanted retina with the 60-electrode array. Reproduced with permission from Elsevier from(Humayun et al., 2012).

H. Lorach et al. / Journal of Physiology - Paris xxx (2012) xxx–xxx 3

This implant recently received CE mark for commercializationin Europe and will be sold around 100,000$. With this device, a sig-nificant ratio of patients could achieve complex visually guided


tasks such as object localization (96% of subjects), motion discrim-ination (57%), and discrimination of oriented gratings (23%)(Humayun et al., 2012). The best acuity that could be measured




Fig. 5. Summary picture of the different visual prosthetic devices discussed here. (A) Argus I device from second sight (from Humayun et al. (2003)). (B) The Argus II devicewith 60 electrodes, first prototype on the market (from Humayun et al. (2012)). (C) The IRIS device from Intelligent Medical Implant AG (from Hornig et al. (2008)). (D) TheEPIRET-3 device (from Roessler et al. (2009)). (E) The STS suprachoroidal implant (from Fujikado et al. (2011)). F) The optic nerve implant developed by Louvain’s university(from Veraart et al. (2003)). (G) Dobelle’s seminal cortical implant (from Dobelle (2000)). (H) The Boston Retina Implant Project device (from Rizzo (2011)). (I) The subretinaldevice from Retina Implant AG (from Zrenner et al. (2010)). (J) The subretinal microphotodiode array developed by Pr. Palanker’s group at Stanford university (from Wanget al. (2012). (K) The ASR device from Optobionics (from Chow et al. (2004)). (L) The diamond coated subretinal implant from our group at the Vision Institute of Paris. (M) TheUtah electrode array for cortical stimulation (from Normann et al. (2009)). All figures were reproduced with permission from their respective editors.


with the system was 20/1260, still six times lower than the legalblindness limit of 20/200. Two of the implanted patient could alsoperform reading task with a rate of up to 10 words per minute.

The device stimulates epiretinally by modulating current ampli-tude linearly with pixel intensity. The stimulus frequency (around20 Hz), the pulse duration (100 ls to 1 ms), the polarity (cathodicfirst versus anodic first) are set equally for all the electrodes(Mcclure et al., 2009). This strategy provides the same informationto all ganglion cell types and does not account for retinal adapta-tion. ON and OFF ganglion cells are stimulated according to thesame pattern so that conflicting information reaches the brain. Itmight explain why there is a large variability in patients perfor-mances – with only 7 out of 30 patients able to reliably performvisual acuity tasks (Humayun et al., 2012).


Other groups are investigating epiretinal stimulation. Intelli-gent Medical Implants (IMIs) in Switzerland developed a 49 plati-num electrode prosthesis in which power is transmitted through aRF-link and data, through infra-red pulses. Four patients werechronically implanted with this device (Hornig et al., 2008) andwere able to perform localization tasks and recognize simple lightpatterns.

The EPI-RET group in Germany also performed clinical trialswith their EPIRET3 device implanted in six patients (Klauke et al.,2011). This epiretinal prosthesis contained 25 stimulating goldelectrodes coated with iridium oxide. In all patients, electricalstimulation could elicit visual percepts. Some of them were evenable to discriminate stimuli applied at different locations of the ar-ray as well as discriminate pattern orientations. Interestingly, they





found that, for the same amount of injected charges, longer pulseswere more efficient to elicit visual perception and the authors sug-gest to use �1 ms pulse durations.

Epiretinal strategies provide some great advantages such as thedirect immersion in the vitreous which dissipates heat from elec-trical stimulation. Moreover, it is easily implantable and is lesslikely to induce retinal detachment or injury compared to subreti-nal prostheses (Fernandes et al., 2012). However, some drawbacksare also inherent to such a strategy. First, the high density of axonfibers in the central area of the retina introduces a collateral stim-ulation of cell that are located far from the area of interest (Wilmsand Eckhorn, 2005; Behrend et al., 2011; Rizzo et al., 2003),although modulated 20 Hz sine wave stimulation could limit axo-nal stimulation (Weitz et al., 2012). As a consequence of this stim-ulation of passing fibers the retinotopy of the stimulation patternscould be lost in some cases (Humayun et al., 2003). Moreover, asstated earlier, epiretinal implants do not benefit the inner layersof the retina that naturally act as an amplification and encodingsystem. Therefore, the adequate encoding of stimulation pulses re-mains an unsolved issue. That is why other groups focused their ef-forts on subretinal strategies.

2.2. Subretinal implants

Subretinal implants primarily target the inner nuclear layer ofthe retina. In retinitis pigmentosa, the primary loss of photorecep-tors is followed by a reorganization process (Marc et al., 2003; Jonesand Marc, 2005) and the partial degeneration of the other retinalcell types. However, morphometric analyses of post-mortem eyesfrom RP patients showed a significant preservation of neurons inthe inner nuclear layer as well as in the ganglion cell layer, evenin late stages of the disease (Santos et al., 1997; Humayun et al.,1999). In the macular region, Santos et al. showed that 78% and88% of the inner nuclear layer cells were preserved in moderateand severe RP respectively. This survival was not statisticallydependent on the inheritance mode of the disease. Moreover,Busskamp et al. were able to show that optogenetic reactivationof cone cell bodies in a mouse model of retinal degeneration couldrestore natural processing such as lateral inhibition and even direc-tion selectivity (Busskamp et al., 2010). These findings suggest thatthe inner retinal network remains functional even in a late stage ofretinal degeneration. Therefore, despite the wide heterogeneity ofRP types, there is a good chance that the subretinal approach couldbe relevant and effective in a majority of cases.

Subretinal implants are inserted below the retina and are there-fore maintained between the choroid and the retina itself withoutadditional tack for fixation. This position increases implant stabil-ity along with risk of retinal detachments. In 2001, Optobionics,Inc. developed the first implanted subretinal device called ArtificialSilicon Retina (ASR). This device consisted in a 2 mm diameterautonomous array of 5000 photodiodes directly converting lightinto electrical stimulation. This very elegant strategy did not re-quire any power supply nor data transmission to the chip. Onceimplanted, the device was completely autonomous, thereby limit-ing the risks of complications. A pilot clinical trial was conductedand in six patients were implanted (Chow et al., 2004, 2010). Thesepatients suffered from autosomal dominant, isolated, X-linked andUsher II RP. Vision improvement was found in the implanted pa-tients, however, they were not necessarily correlated with the chiplocation, suggesting that the implantation benefits were indirect –through neuroprotection for instance. These results suggested thatambient natural light was not powerful enough to provide supra-threshold stimulation of the retina. Therefore, subsequent researchintroduced amplification systems for subretinal implants.

The first strategy to amplify the signal was developed by thegroup of Pr. Zrenner in Tübingen. They coupled each photodiode


to an amplifying circuit. This device required a battery to powerthe circuit delivering current to the electrodes. This battery was lo-cated at the eye periphery whereas the implant was in a very cen-tral position. The device contained 38 � 40 photodiodes (Zrenneret al., 2010) plus 16 larger electrodes (50 lm) that were used inlight independent stimulation (Wilke et al., 2011). With this sys-tem, the implanted patients could perceive bright objects, discrim-inate simple grating patterns and read letters in some cases. Theyreported a visual acuity of 20/1000 in these patients that is no bet-ter than patient implanted with the Argus II and its 60 electrodes.It was somehow disappointing that 25 times more electrodes didnot improve visual restoration. This could be explained by thecrosstalk between neighboring electrodes that are separated byonly 70 lm and share a distant ground (see (Joucla and Yvert,2009) for the effect of the ground on stimulus focalization).

Retina Implant AG device uses limited processing. The lightreaching the photosensitive array is converted into electrical cur-rent according to a sigmoidal law. The operating range of the sig-moid is set by a voltage bias thus providing sensitivity acrossfour log units and a dynamic range of two log units when this volt-age is set. The stimulation frequency is set from 2 to 20 Hz with apulse duration of 1–4 ms. More recently, D. Palanker’s group atStanford reintroduced the concept of an autonomous implantedchip (Mathieson et al., 2012; Wang et al., 2012) similar to theASR device. In this prototype, each electrode is connected to threephotodiodes in series providing enough current to reliably evokeganglion cell spiking. The photodiodes are sensitive to infraredlight that is projected by an head mounted beamer. An externalcamera acquires the visual information that is processed to providethe stimulation pattern. With this device, the authors were able toshow a reliable activation of ganglion cells in both normal rats andRoyal College Surgeon (RCS) rats – animal models of retinal degen-eration. This subretinal autonomous strategy offers appealingadvantages because infrared light provides enough power to thephotodiodes to elicit reliable responses while avoiding photopho-bic effects that have been previously described in RP patients(Hamel, 2006). Moreover, the photosensitive elements areenslaved to ocular movements meaning that the patient will scanthe projected image naturally without any need of eye trackingsystem. Finally this procedure allows the implantation of multipleindependent units under the same retina to increase the coverageof the visual field without increasing retinal detachment risks. Thisdevice is still on a preclinical stage but should be implanted in pa-tients in the following years and should progressively catch upwith already clinically tested implants.

In addition, the same group has addressed the difficulty to gen-erate very focal stimulation and prevent spill over activation fromone electrode to another. They indeed proposed to generate 3D im-plant designs to restrict activation to cells between bipolar elec-trodes (Palanker et al., 2004). Using blind rats and polyimideprototypes, they could show further that retinal cells can integrateinto cavities of 3D implants (Butterwick et al., 2009). However, thetechnology retained to examine the tissue did not allow them tocontrol the neuronal nature of these cells. In reaction to theimplant, one could easily imagine that fibrotic or glial cells couldmultiply to fill empty cavities.

The Boston Retinal Implant Project that started in the 80s in-tends to achieve maximum development before starting clinicaltrials in human (Rizzo, 2011). They developed a first generationof implant containing 15 electrodes that were implanted inanimals for biocompatibility and insulation assessment. Their nextgeneration will contain more than 200 electrodes to provide usefulperceptions to human patients.

Subretinal approaches present multiple advantages. First,the implantation under the retina guarantees a good contactbetween the electrodes and the targeted bipolar cells after retinal





reattachment. Some studies even reported bipolar cell integrationin three dimensional implant structures (Palanker et al., 2004; But-terwick et al., 2009), thereby increasing implant stability. More-over, subretinal stimulation threshold were found to be lowerthan for epiretinal stimulation (Jensen and Rizzo, 2006). This lowerthreshold could be due to the better contact between the electrodeand the retina, or to an amplification mediated by convergence ofbipolar cells onto ganglion cells.

As for epiretinal implants one of the remaining challenges forsubretinal strategies is to achieve selective activation of ON andOFF pathways separately. ON and OFF bipolar cells morphologicallydiffer in the depth of their axon terminal. OFF bipolar cells contactganglion cells in the outer part of the inner plexiform layer, whereasON bipolar cell terminals are located in the inner part of the layer. Atheoretical study has quantified the effect of stratification depth onthe response to electrical stimulation (Gerhardt et al., 2010) andshowed that OFF bipolar cells would be preferentially addressedby small bipolar electrodes (diameter <100 lm) and short pulsedurations (<150 ls) whereas ON bipolar cells would be selectivelyactivated by large monopolar electrodes (diameter >100 lm) andlong pulse durations (>150 ls). However, this study modeled bipo-lar cells as linear passive and single-compartment components.They did not include morphological properties such as dendriticarborization and soma size nor physiological properties of specificionic channels. A more recent study (Freeman et al., 2011)accounted for these properties and in particular for the effect ofcalcium channel subtypes, differentially expressed in bipolar cells(Muller et al., 2003; Ivanova and Muller, 2006; Hu et al., 2009). Theystudied the effect of calcium channel expression, axonal resistivityand soma size on the responses to a sinusoidal electrical stimula-tion. They conclude that high frequency stimulations (500 Hz)cannot preferentially activate ON or OFF bipolar cells specifically.At lower frequencies (20 Hz) ON bipolar cells would be 20% moresensitive than OFF bipolar cells. However, the lack of knowledgeon the distribution of other voltage gated ion channels acrossdifferent bipolar cell types does not allow to conclude on thespecific activation of different subtypes of bipolar cells.

Finally, important reorganization of the inner retina occurs afterphotoreceptor degeneration (Marc et al., 2003; Jones and Marc,2005). These studies describe the reorganization process startingbefore any detectable cell death: photoreceptor terminal projec-tion into the inner nuclear layer and ganglion cell layer, horizontalcell dendritic reorganization, Muller cell hypertrophy, amacrinecell migration and general cellular death. Subretinal strategies willneed to account for this remodeling process or try to delay it.

2.3. Transchoroidal prostheses

Transchoroidal implants stimulate the retina from the outerpart. This approach benefits from an easier implantation with norisk of retinal detachment or choroidal hemorrhage. With thisstrategy, two patients were implanted and stimulated for fewweeks (Fujikado et al., 2011). Although this device developed byOsaka University contained 49 electrodes in theory, only 9 were ac-tive and among these nine electrodes, they were only able to elicitphosphenes through 5 and 6 of them in each patient respectively.However, this was sufficient to allow object localization and grat-ing discrimination. In this prototype, the active electrode array wasplaced in a scleral pocket and a return electrode was inserted in-side the vitreous cavity allowing the current to flow across theretina.

Benefiting from a strong background in cochlear implants, a re-cent Australian initiative led by Bionic Vision Australia is alsodeveloping suprachoroidal devices. In initial studies in cats, theyshowed that they could evoke cortical activity by stimulating theretina from outside the sclera (Chowdhury et al., 2005). The


strategy was efficient in different stimulation configurations –monopolar between an electrode of the implant and a corneal re-turn electrode, monopolar between one of the electrodes and allthe others acting as a common ground, and bipolar stimulation be-tween two neighboring electrodes. In all these configurations, noincision of the sclera was necessary. Very recently, they implantedthree patients with a 24 channel implant that could already evokevisual percepts. A next generation of implant called ‘‘Wide-viewdevice’’ consisting in 98 electrodes is under development and willbe implanted in the suprachoroidal space. They are expecting thefirst clinical trials with this device by 2013 while they will keepon developing the second ‘‘High-acuity device’’ with 1024 elec-trodes. This latest version should be implanted in patients by 2014.

Finally, another Korean team is experimenting suprachoroidalstimulation (Zhou et al., 2008). Similarly to the device from Osakauniversity, the device containing 7 electrodes was inserted be-tween the sclera and the choroid. However, in this case, the returnelectrode was not inserted inside the vitreous cavity but placed onthe posterior surface of the sclera, reducing thereby the risk ofcomplications.

Although the suprachoroidal technique allows low tissue dam-age when implanted, it requires higher current intensities to elicitvisual percepts because of the increased distance between the elec-trodes and the inner retinal neurons.

2.4. Optic nerve prostheses

Optic nerve stimulation has been investigated as a potential tar-get for electrical stimulation because it conveys the information ofthe entire visual field in a very small area. It is possible to stimulateperipheral and central vision at the same time. However, this nervefiber concentration is also a disadvantage for very focal stimulationas more than 1 million axons are contained into the 2 mm diame-ter optic nerve.

One patient with retinitis pigmentosa was implanted with anoptic nerve prosthesis (Veraart et al., 1998; Veraart et al., 2003).This device consisted in a 4 contact cuff-electrode placed aroundthe optic nerve. The four contacts were placed around the cuff at90� intervals, allowing to stimulate the four quadrants of the visualfield. The stimulations were biphasic, charge balanced with dura-tions varying from 20 ls to 420 ls (Veraart et al., 1998). By varyingthe stimulation amplitude, duration, frequency and number ofpulses per phase, the patient was able to perceive different phos-phenes (Delbeke et al., 2003). More than 100 of them could be reli-ably elicited and were used to encode a visual scene from a camerainto electrical stimulations. With this strategy, the patient was ableto reach 85% success rate on a pattern recognition task where sym-bols consisting in two or three bars randomly oriented were pre-sented (Brelén et al., 2005). This high recognition score could beachieved with only four electrodes, suggesting that precise encod-ing of the visual stimulus is critical in the case of optic nerve stim-ulation. More recently, a second patient was implanted with aeight contact electrodes and the cortical evoked potentials were re-corded as an objective measurement to better understand opticnerve stimulation (Brelén et al., 2010).

A chinese initiative – the C-sight project – is also developing op-tic nerve stimulation (Chai et al., 2008; Wu et al., 2010). Instead ofsurface stimulation the authors designed penetrating electrodes.They implanted rabbits with two-electrode devices and recordedcortically evoke potentials. They showed that different stimulationparameters could result in different cortical activity and thereforethat the resolution of the device was not limited by the number ofelectrodes only. This group also developed image processing strat-egies in order to encode complex visual scenes with a limited num-ber of pixels. They established different processing algorithms





according to the complexity of the scene and tested these strate-gies in psychophysiological experiments in healthy subjects.

Finally, a Japanese group is also investigating optic nerve stim-ulation but through an intraocular prosthesis, stimulating the opticnerve head (Fang et al., 2006). This strategy would benefit the lessinvasive surgical approach of retinal implants as well as the cover-age of the entire visual field in a limited stimulation surface. Such adevice with four electrodes has been implanted in rabbits andcould evoke cortical activity. However, they observed an increaseof perceptual threshold after 1 month of implantation that couldbe due to a glial coverage of the electrodes as revealed by histolog-ical evaluation.

Together, these studies have demonstrated that optic nervestimulation is an appealing strategy but that stimulation designwill remain a major challenge to achieve fine spatial resolutionrehabilitation in patients.

2.5. Cortical and LGN implants

Whenever retinal ganglion cells degenerate or after optic nerveinjury, it is no longer possible to use the previous strategies. This isthe case for glaucoma and optic neuropathy. Brain stimulation be-comes the only available strategy for prosthetic visualrehabilitation.

The seminal work of Brindley and Lewin (1968) followed byDobelle et al. (1974); Dobelle (2000) were the first attempts in pro-viding a functional cortical prosthesis. Dobelle’s implant wasplaced on the surface of the visual cortex in eight blind patients.Some of them were implanted for 20 years without infection orother complication. With this device containing 64 electrodes,one patient was able to reach 20/1200 visual acuity. With a digitalzooming function, he was even able to recognize 2-inch high let-ters at 5-feet distance corresponding to 20/400 visual acuity. Thispatient had been able to learn to interpret this stimulation in oneday and could to use it for 20 years. He was able to recognize char-acters and navigate in a room, performing complex tasks such asfinding a hat and placing it over a mannequin’s head. This earlybreakthrough opened the field of cortical visual implants.

Because superficial stimulation of the visual cortex is not veryefficient and in order to reduce perceptual thresholds, some teamsinvestigated cortical penetrating electrodes. Penetrating electrodeswere shown to elicit visual percepts with stimulation thresholdstwo to three times lower than for surface stimulation (Schmidtet al., 1996). The Utah Electrode Array consists in a device with100 electrodes at the tip of acute pillars. This device that has beenextensively used for neuronal recordings (Maynard, 2001) will beused for stimulation. The first functional experiments in non-hu-man primates confirmed the perception of electrically elicitedphosphenes (Torab et al., 2011). However, behavioral responsesof monkeys could be observed on 8 electrodes out of 82 only. Thislow success rate could be due to the positioning of the electrodeswithin V1 (because the majority of successful electrodes were spa-tially clustered) or to the inability of non-human primates to reportvisual phosphenes. The authors observed a cellular death aroundthe electrodes but without apparent impairment in visual function.Although this cortical strategy provides the only hope of visual res-toration in case of ganglion cells and optic nerve degeneration, itstill need to face critical challenges. The implantation itself ishighly invasive with major risks of infection and inflammationdue to foreign body introduction. Additionally, cellular deatharound the electrodes occurring after electrical stimulation(McCreery et al., 2010) could lead to an increase of activationthresholds.

Stimulation of the lateral geniculate nucleus (LGN) is also underinvestigation. It presents the advantage of targeting relatively sim-ple and well characterized cells compared to cortical neurons.


Moreover, magnocellular and parvocellular pathways are spatiallysegregated in the LGN, allowing to adapt image processing to thetargeted area. Additionally, the foveal region projected on theLGN is larger than on the retina, allowing to achieve higher resolu-tion with a given electrode size and finally, implantation tech-niques are similar to those already implemented for deep brainstimulation. Performing stimulation of the LGN in alert monkeys,Pezaris and Reid (2007) confirmed the evocation of visual perceptsand their spatial localization. However, this proof of concept wasperformed with only two tetrodes implanted at the same timeand the increase in number of electrodes may represent an addi-tional challenge.

3. Global challenges

3.1. Electrode configuration and materials

In order to provide the best visual acuity to the patient, the res-olution of the implant must be maximum. Psychophysical experi-ments (Sommerhalder et al., 2004) estimated that 1000 pixelswhere sufficient to perform basic tasks such as face recognitionor reading. Fig. 6 summarizes the relationship between electrodesize and restored acuity in the best patients for the different im-planted devices. In theory, the acuity is linearly dependent onthe size of the stimulation and a 20/20 acuity corresponds to astimulation surface of 1 arcmin on the retina. Although the exper-imental curve does not follow the theoretical relationship exactly,there is a strong correlation between electrode size and restoredacuity. Interestingly, the early device from Dobelle as well as Sec-ond Sight Argus I and II are close from their theoretical limit sug-gesting that the stimulation extent does not exceed the size ofthe electrode. In contrast, the ASR device from Optobionics andthe MDPA chip from Retina Implant AG perform much worse thanexpected from the size of their electrodes, suggesting a saturationof the restored acuity. However, this saturation may be due tocrosstalk between neighboring electrodes. The retina behaves asan inhomogeneous conductive medium in which ionic speciesare acting as charge carriers. A good electrical contact betweenthe electrodes and the tissue is critical for local stimulations alongwith the location of the return electrode. It was recently shownthat local grounds surrounding each electrodes could provide morefocal stimulations (Joucla and Yvert, 2009). Geometric properties ofthe electrodes can also contribute to a better resolution of the im-plant (Palanker et al., 2005) and three dimensional structures havebeen shown to allow retinal integration with limited glial reactionand reduce the spatial extent of electrical stimulation (Djilas et al.,2011).

Developments in electrode miniaturization are also tightlylinked to materials engineering. Any electrical stimulation of aneural structure involves an electrode-tissue interface wherecharge movements occur. Two types of currents can be generatedby the electrodes: Faradic currents involve chemical reactions –oxidation/reduction – at the interface whereas capacitive currentsare induced by charge accumulation only. In the case of neuralprosthetics, capacitive stimulations are preferred because theylimit modifications of the electrode surface as well as pH modifica-tions in the tissue (Cogan, 2008). In the context of visual implants,smaller electrodes introduce higher charge densities and thereforehigher risks of irreversible reactions with risks of electrode degra-dation and tissue damage. Finding materials with high charge-injection limits is critical to decrease electrode size. Platinum(injection limit �0.35 mC cm�2) (Robblee et al., 1983), titanium ni-tride (1 mC cm�2) and iridium oxide (4 mC cm�2) are the com-monly used material for neural stimulation. In order to improvebiocompatibility and charge injection limits, some teams are




1 10 100

20/200

light perception

shape recognition

20/2000

20/20

ASR2003

indirect effect

MDPA2010

DOBELLE1974

ARGUS II2009

ARGUS I2002

IRIS2005

EPIRET32008

STS2011

Theoreticalrelationship

Legal blindness

Electrode size (arcmin)

Acuity

LOUVAIN1998

Fig. 6. Acuity and electrode size. Correlation between electrode size and measured visual acuity is present although it does not follow perfectly the theoretical relationship –i.e. 5 lm � 1 arcmin � 20/20.


investigating the behavior of doped-diamond electrodes (Bongrainet al., 2011; Kiran et al., 2012; Hadjinicolaou et al., 2012) that willbe incorporated in future generations of implants.

3.2. Image processing for visual rehabilitation

Obviously, the amount of processing necessary to translate theacquired image into useful electrical stimulation patterns dependson the targeted structure. Stimulating retinal cells will – a priori –be easier than mimicking the entire visual processing up to the vi-sual cortex.

One hypothesis is that the visual system is still plastic enoughto interpret non-physiological stimulation patterns. This theory issupported by several experiments underlining the reorganizationand physiological modifications of the visual system after blind-ness onset (Bavelier and Neville, 2002; Merabet et al., 2005). Inblind patients, indeed, the visual cortex can be recruited by othersensory modalities introducing a cross-modal plasticity (Cohenet al., 1997). In this study, Braille reading performances of blindsubjects were altered by transcranial magnetic stimulation of theprimary visual cortex, thus implying a functional activation ofthe visual cortex by tactile inputs. It would suggest that the adultvisual system is still plastic and that this plasticity would allow pa-tients to learn and interpret new kinds of signals. With thishypothesis, processing algorithm should focus on conveying amaximum amount of relevant information through the limitednumber of electrodes. Some teams are currently simulating com-plex processing such as contour extraction (Dobelle, 2000), motiondetection (Ouarti et al., 2012), saliency extraction (Parikh et al.,2009), complexity analysis (Sui et al., 2009) or even non purely vi-sual inputs such as depth encoding (Lieby et al., 2012). All thesestrategies suppose that the visual structures downstream to thetargeted cells will be able to interpret such signals. However,current experiments in implanted patients showed that only aminority of them were actually able to interpret complex visual in-puts such as letters when non-physiological signals were applied(Humayun et al., 2012). This suggests that the plasticity of the sys-tem is limited and that providing more physiological signal wouldimprove patients percepts and reduce the learning phase.

In this context, one of the major challenges in visual prostheticsis to develop real time processing algorithms to provide relevantphysiological stimuli. Regardless of the implant location, it is


necessary to perform the adequate filtering corresponding to theupstream computation. Subretinal stimulation targets bipolar cellterminals and requires to account for photoreceptor adaptation(Schnapf et al., 1990; Schneeweis and Schnapf, 1999), surroundinhibition from horizontal cells (Yang and Wu, 1991) as well asactivation kinetics. Epiretinal approaches need to predict actionpotential patterns for different subtypes of ganglion cells. Finally,cortical stimulation needs to account for specialized areas andcomplex processing such as orientation, color and motion. Currentdevices do not allow single cell stimulation and generally targetmany cells with different functions. In the primate retina,some 20 types of ganglion cells are meshed together (Field andChichilnisky, 2007) and electrical stimulation from a single elec-trode will correlate the activity of all these cell types, introducinginterferences between the information channels. Because of thislack of specificity, current image processing strategies are rela-tively simple and do not account for specific cell types.

There is no need of cell specific processing as long as eachelectrode elicits a phosphene with a broad spatial extent. But asmicro-fabrication processes are developed, it will soon be possibleto target a small group of neurons (Sekirnjak et al., 2008). In thiscontext, it is critical to study information coding by specificganglion cell types and to predict the accurate spike train for eachcell. First models of ganglion cell behavior emerged from earlyelectrophysiological experiments (Enroth-Cugell and Robson,1966; Victor, 1988; Victor, 1987) in cat ganglion cells. These stud-ies already emphasized major differences between X and Y gan-glion cell types. The X type was found to exhibit a roughly linearresponse to spatial gratings while Y-cells behaved non-linearly tothe same stimulus. More recent models successfully reproducedsome ganglion cell properties. Linear non-linear Poisson (LNP)models consist in modeling ganglions cells as spatial and temporallinear filters followed by non-linearites and a Poisson process forspike generation. This method has been extensively used (Berryet al., 1997; Keat et al., 2001; Chichilnisky and Kalmar, 2002; Uzzelland Chichilnisky, 2004; Pillow et al., 2005; Pitkow and Meister,2012) and provided satisfying predictions of ganglion cellresponses to simple stimuli. However, having a model that predictsthe responses to complex natural stimuli remains an openchallenge (review in Gollisch and Meister, 2010).

In particular, Nirenberg and Pandarinath recently implementeda LNP-like model to encode visual scenes into stimulation patterns





for ganglion cells (Nirenberg and Pandarinath, 2012). In theirstudy, they did not use electrical but optogenetic stimulation usingexpression of channel-rhodopsin 2 (ChR-2) in ganglion cells. Thisprinciple allowed them to reliably evoke ganglion cell activitymatching natural responses to some stimuli. Stimulus reconstruc-tion accuracy as well as performances in behavioral tasks wereshown to depend on the encoding process. Therefore, this workprovides evidence that accurate encoding of ganglion cell activitywill increase prosthetic efficacy. A major challenge is now to beable to target specific cell types independently (e.g. ON and OFF)in degenerated retinas.

3.3. Importance of ocular movements

Our eye is in constant motion. These movements are key com-ponents of normal vision and their disruption – in case of nystag-mus – can lead to severe vision impairments. Ocular movementsallow to scan the environment and center the foveal part of the ret-ina on a region of interest to achieve high acuity tasks. They pre-vent perceptual fading due to photoreceptor adaptation andallow super-resolution (Martinez-Conde et al., 2009). Gilchristet al. described a patient who completely lost the ability to performocular motions (Gilchrist et al., 1997). This patient performed headscanning of the scene, matching natural eye movements, to pre-vent perceptual fading and achieve high acuity tasks.

Visual prosthetic strategies need to account for this critical fea-ture of natural vision. Blindness triggers the loss of the oculomotorcontrol pathway and blind patients are not able to direct their gazeanymore. However, electrical stimulation of the optic nerve andcortex of blind patients confirmed that the expected location of astimulus was highly dependent of the gaze direction (Dobelle,2000; Veraart et al., 1998). Moreover, stimulating the retina inde-pendently of the eye position leads to unwanted pursuit motions(Wang et al., 2008). It is therefore crucial to be able to enslavethe electrical stimulation to the position of the eye.

Table 2Prosthetic strategies advantages and drawbacks. Retinal and optic nerve implantations are stechniques however, the electrode-tissue contact is improved in subretinal approaches. Thonly need limited computation. The potential acuity restoration is highly dependent on thethe brain and smaller in the optic nerve, therefore resulting in different angular resolutionpatients with intact ganglion cells and optic nerve – mainly retinitis pigmentosa and AMD.solution.

Implantation safety Implant stability

Epiretinal ++ +Subretinal + ++Suprachoroidal ++ ++Optic nerve + +Brain � +

Table 1History of clinical trials in visual prosthetics. Inter-electrode distance for cortical imcorresponding to the cortical extent at foveal position (Cowey and Rolls, 1974). For retinalimplant from Louvain University, the conversion from electrode size to visual field could nothe implant. ASR: Artificial silicon retina, SSMP: Second Sight Medical Products, IMI: IntelligUniversity), MDPA: Microphotodiode array, RIAG: Retina Implant AG, STS: Subretinal tran

Date Prototype Team Electrodes Size (�) Distan

1974 Cortical Dobelle 64 0.25 0.751998 Spiral Cuff Louvain University 4 1 –2000 ASR Optobionics 5000 0.031 0.0872002 Argus I SSMP 16 1.6–0.8 2.82005 IRIS IMI 49 1.25 1.42006 Argus II SSMP 60 0.69 1.72008 EPIRET3 RWTH 25 0.34 1.72010 MDPA RIAG 1500 0.17 0.252011 STS Osaka University 49 1.7 2.4


This can be achieved by placing the photosensitive elements ofthe implant inside the eye. This is the case with the currently im-planted device from Retina Implant AG and the Stanford prototype.In these implants, the photodiodes are located below the retinaand therefore follow the ocular movements. Whenever the camerais located outside the eye, it will be necessary to use an eye track-ing system to select in real time the part of the image correspond-ing to the gaze direction. Mobile eye trackers are already on themarket (EyeTechMobile, Tobii Glasses) and should be integratedin prosthetic devices within the next few years.

3.4. Comparison of the different strategies

In Table 1, we summarize the major clinical trials that havebeen conducted so far. It presents the different prototypes withthe number of implanted patients along with the implant charac-teristics and the restored acuity while Fig. 5 presents the physicalaspect of the different devices.

Each of the targeted locations that we described above presentsits own advantages and drawbacks. While cortical prostheses canbenefit to all kind of blindness conditions including glaucoma,the other strategies require an intact connection between the ret-ina and the brain, thereby reducing the number of potential pa-tients. The downside of such an approach is the highly invasivesurgical procedure with non-zero risk of lethal complications –hemorrhages and infections.

Non cortical approaches would apply to a smaller number of pa-tients – 9% of blindness cases. However, they are much less inva-sive and do not threaten the life of the patients. We can dividethem between optic nerve stimulation and retinal approaches. De-spite a relatively preserved retinotopy inside the optic nerve, thevery high fiber density is a real challenge for focal stimulation.More than 1 million axons are packed within a two millimeterdiameter fiber so that the retinal surface is projected to the opticnerve section.

afer than brain stimulation approaches. Implant stability has been demonstrated in alle processing complexity increases in higher visual streams so that retinal approachesability to stimulate a limited corresponding visual field. Retinotopic area is higher in

for a given electrode size. Finally, retinal and optic nerve strategies are only suited forBrain stimulation in contrast can be used in any visual impairment when it is the only

Processing ease Spatial resolution Potential patients

+ – +++ + –++ – –– � +� ++ ++

plants were calculated by applying the magnification factor Mcortex = 4 mm deg�1

implants, we used the magnification factor Mretina = 288 lm deg�1. For the optic nervet be determined. However, we reported the size of the smallest phosphene evoked byent Medical Implants, RWTH: Rheinisch-Westfälische Technische Hochschule (Aachensretinal stimulation, LP: Light perception, OL: Object localization.

ce (�) Type Patients Acuity Refs.

Cortical 2 20/400 Dobelle (2000)Optic Nerve 1 OL Veraart et al. (1998)Subretinal 6 20/400 Chow et al. (2004)Epiretinal 6 20/3200 Caspi et al. (2009)Epiretinal 20 OL Hornig et al. (2008)Epiretinal 32 20/1260 Humayun et al. (2012)Epiretinal 6 LP Roessler et al. (2009)Subretinal 3 20/1000 Zrenner et al. (2010)Suprachoroidal 2 OL Fujikado et al. (2011)





Among retinal approaches, suprachoroidal implantations arethe safest ones because they do not imply incision of the choroid,thus limiting risks of hemorrhages and retinal damage. However,the electrical threshold and current diffusion will be higher be-cause of choroidal and pigmented epithelium resistivity. Finally,epiretinal and subretinal approaches differ in a few ways. Epireti-nal devices benefit from the vitreous as a natural cooling systembut the contact between the retina and the electrodes is only main-tained by a single tack, thereby reducing the electrical contact. Tar-geting ganglion cells directly also implies a complex imageprocessing before electrical stimulation whereas subretinal stimu-lation assumes that only photoreceptor function should be ac-counted for. Table 2 summarizes this comparison of the differentstrategies.

4. Conclusion

We presented here the current prosthetic strategies for visualrehabilitation in blind patients. The variety of possible locationsfor stimulation offers a wide field of research. Current implanteddevices allow patients to perceive light, recognize shapes and ob-jects and even read for some patients reaching 20/1200 visual acu-ity. However, it is still well below the legal blindness limit (20/200)and does not allow patients to recover their autonomy. Currenttechnological bottlenecks include electrode miniaturization main-taining safe stimulations; design of hundreds-channel stimulatorsand the associated data and power transmission; and design of realtime video processing algorithms providing useful percepts to thepatient.

Although other promising strategies are emerging such asoptogenetics or cell therapy, visual prosthetic approaches are themost advanced and offer promising perspectives to face blindness.

Acknowledgments

We would like to thank the reviewers for their constructive re-marks. This work was supported by INSERM, Université Pierre etMarie Curie (Paris VI), Fondation Ophtalmologique A. de Rothschild(Paris), Agence Nationale pour la Recherche (ANR RETINE, ANR OP-TIMA), ITMO Technologie pour la santé, the Fédération des Aveu-gles de France, IRRP, the city of Paris, the Regional Council of Ile-de-France and the Fondation pour la Recherche Médicale. HL re-ceived a doctoral fellowship from the Ecole Polytechnique.

References

Bavelier, D., Neville, H., 2002. Cross-modal plasticity: where and how? NatureReviews Neuroscience 3, 443–452.

Behrend, M., Ahuja, A., Humayun, M., Chow, R., Weiland, J., 2011. Resolution of theepiretinal prosthesis is not limited by electrode size. IEEE Transactions onNeural Systems and Rehabilitation Engineering 19 (4), 436–442.

Berry, M.J., Warland, D.K., Meister, M., 1997. The structure and precision of retinalspike trains. Proceedings of the National Academy of Sciences 94 (10), 5411–5416.

Bongrain, A., Bendali, A., Lissorgues, G., Rousseau, L., Yvert, B., Scorsone, E.,Bergonzo, P., Picaud, S. 2011. Diamond-based technology dedicated to microelectrode arrays for neuronal prostheses. In: Design, Test, Integration andPackaging of MEMS/MOEMS (DTIP), 2011 Symposium on. pp. 378 –384.

Brelén, M.E., Duret, F., Gérard, B., Delbeke, J., Veraart, C., 2005. Creating a meaningfulvisual perception in blind volunteers by optic nerve stimulation. Journal ofNeural Engineering 2 (1), S22.

Brelén, M.E., Vince, V., Gérard, B., Veraart, C., Delbeke, J., 2010. Measurement ofevoked potentials after electrical stimulation of the human optic nerve.Investigative Ophthalmology & Visual Science 51 (10), 5351–5355.

Brindley, G.S., Lewin, W.S., 1968. The sensations produced by electrical stimulationof the visual cortex. The Journal of Physiology 196, 479–493.

Busskamp, V., Duebel, J., Balya, D., Fradot, M., Viney, T.J., Siegert, S., Groner, A.C.,Cabuy, E., Forster, V., Seeliger, M., Biel, M., Humphries, P., Paques, M., Mohand-Said, S., Trono, D., Deisseroth, K., Sahel, J.A., Picaud, S., Roska, B., 2010. Geneticreactivation of cone photoreceptors restores visual responses in retinitispigmentosa. Science 329 (5990), 413–417.


Butterwick, A., Huie, P., Jones, B.W., Marc, R.E., Marmor, M., Palanker, D., 2009. Effectof shape and coating of a subretinal prosthesis on its integration with the retina.Experimental Eye Research 88 (1), 22–29.

Caspi, A., Dorn, J.D., McClure, K.H., Humayun, M.S., Greenberg, R.J., McMahon, M.J.,2009. Feasibility study of a retinal prosthesisspatial vision with a 16-electrodeimplant. Archives of Ophthalmology 127 (4), 398–401.

Chai, X., Li, L., Wu, K., Zhou, C., Cao, P., Ren, Q., 2008. C-sight visual prostheses for theblind. Engineering in Medicine and Biology Magazine, IEEE 27 (5), 20–28.

Chichilnisky, E.J., Kalmar, R.S., 2002. Functional asymmetries in on and off ganglioncells of primate retina. The Journal of Neuroscience 22 (7), 2737–2747.

Chow, A.Y., Bittner, A.K., Pardue, M.T., 2010. The artificial silicon retina in retinitispigmentosa patients (an american ophthalmological association thesis).Transactions of the American Ophthalmological Society 108, 120–154.

Chow, A.Y., Chow, V.Y., Packo, K.H., Pollack, J.S., Peyman, G.A., Schuchard, R., 2004.The artificial silicon retina microchip for the treatment of vision loss fromretinitis pigmentosa. Archives of Ophthalmology 122, 460–469.

Chowdhury, V., Morley, J.W., Coroneo, M.T., 2005. Feasibility of extraocularstimulation for a retinal prosthesis. Canadian Journal of OphthalmologyJournal Canadien d’Ophtalmologie 40 (5), 563–572.

Cogan, S.F., 2008. Neural stimulation and recording electrodes. Annual Review ofBiomedical Engineering 10 (1), 275–309.

Cohen, L.G., Celnik, P., Pascual-Leone, A., Corwell, B., Faiz, L., Dambrosia, J., Honda,M., Sadato, N., Gerloff, C., Catala, M.D., Hallett, M., 1997. Functional relevance ofcross-modal plasticity in blind humans. Nature 389 (6647), 180–183.

Cowey, A., Rolls, E.T., 1974. Human cortical magnification factor and its relation tovisual acuity. Experimental Brain Research 21, 447–454. http://dx.doi.org/10.1007/BF00237163.

Delbeke, J., Oozeer, M., Veraart, C., 2003. Position, size and luminosity ofphosphenes generated by direct optic nerve stimulation. Vision Research 43(9), 1091–1102.

Djilas, M., Olès, C., Lorach, H., Bendali, A., Dégardin, J., Dubus, E., Lissorgues-Bazin,G., Rousseau, L., Benosman, R., Ieng, S.-H., Joucla, S., Yvert, B., Bergonzo, P., Sahel,J., Picaud, S., 2011. Three-dimensional electrode arrays for retinal prostheses:modeling, geometry optimization and experimental validation. Journal ofNeural Engineering 8 (4), 046020.

Dobelle, W.H., 2000. Artificial vision for the blind by connecting a television camerato the visual cortex. American Society for Artificial Internal Organs Journal 46,3–9.

Dobelle, W.H., Mladejovsky, M.G., Girvin, J.P., 1974. Artificial vision for the blind:electrical stimulation of visual cortex offers hope for a functional prosthesis.Science 183 (4123), 440–444.

Enroth-Cugell, C., Robson, J.G., 1966. The contrast sensitivity of retinal ganglion cellsof the cat. The Journal of Physiology 187 (3), 517–552.

Fang, X., Sakaguchi, H., Fujikado, T., Osanai, M., Ikuno, Y., Kamei, M., Ohji, M., Yagi, T.,Tano, Y., 2006. Electrophysiological and histological studies of chronicallyimplanted intrapapillary microelectrodes in rabbit eyes. Graefe’s Archive forClinical and Experimental Ophthalmology 244, 364–375. http://dx.doi.org/10.1007/s00417-005-0073-9.

Fernandes, R.A.B., Diniz, B., Ribeiro, R., Humayun, M., 2012. Artificial vision throughneuronal stimulation. Neuroscience Letters 519 (2), 122–128.

Field, G., Chichilnisky, E., 2007. Information processing in the primate retina:circuitry and coding. Annual Review of Neuroscience 30 (1), 1–30.

Freeman, D.K., Jeng, J.S., Kelly, S.K., Hartveit, E., Fried, S.I., 2011. Calcium channeldynamics limit synaptic release in response to prosthetic stimulation withsinusoidal waveforms. Journal of Neural Engineering 8 (4), 046005.

Fujikado, T., Kamei, M., Sakaguchi, H., Kanda, H., Morimoto, T., Ikuno, Y., Nishida, K.,Kishima, H., Maruo, T., Konoma, K., Ozawa, M., Nishida, K., 2011. Testing ofsemichronically implanted retinal prosthesis by suprachoroidal-transretinalstimulation in patients with retinitis pigmentosa. Investigative Ophthalmology& Visual Science 52 (7), 4726–4733.

Gerhardt, M., Alderman, J., Stett, A., 2010. Electric field stimulation of bipolar cells ina degenerated retina: a theoretical study. IEEE Transactions on Neural Systemsand Rehabilitation Engineering 18 (1), 1–10.

Gilchrist, I.D., Brown, V., Findlay, J.M., 1997. Saccades without eye movements.Nature 390 (6656), 130–131.

Gollisch, T., Meister, M., 2010. Eye smarter than scientists believed: neuralcomputations in circuits of the retina. Neuron 65 (2), 150–164.

Hadjinicolaou, A.E., Leung, R.T., Garrett, D.J., Ganesan, K., Fox, K., Nayagam, D.A.,Shivdasani, M.N., Meffin, H., Ibbotson, M.R., Prawer, S., O’Brien, B.J., 2012.Electrical stimulation of retinal ganglion cells with diamond and thedevelopment of an all diamond retinal prosthesis. Biomaterials 33 (24),5812–5820.

Hamel, C., 2006. Retinitis pigmentosa. Orphanet Journal of Rare Diseases 1 (1), 40.Hornig, R., Zehnder, T., Velikay-Parel, M., Laube, T., Feucht, M., Richard, G., 2008. The

imi retinal implant system. In: Humayun, M., Weiland, J., Chader, G.,Greenbaum, E. (Eds.), Artificial Sight, Biological and Medical Physics,Biomedical Engineering. Springer, New York, pp. 111–128.

Hu, C., Bi, A., Pan, Z.-H., 2009. Differential expression of three t-type calciumchannels in retinal bipolar cells in rats. Visual Neuroscience 26 (02), 177–187.

Humayun, M., Dorn, J., Ahuja, A., Caspi, A., Filley, E., Dagnelie, G., Salzmann, J.,Santos, A., Duncan, J., daCruz, L., Mohand-Said, S., Eliott, D., McMahon, M., andGreenberg, R. 2009. Preliminary 6 month results from the argus™ II epiretinalprosthesis feasibility study. In: Engineering in Medicine and Biology Society,2009. Annual International Conference of the IEEE, pp. 4566–4568.

Humayun, M.S., Dorn, J.D., da Cruz, L., Dagnelie, G., Sahel, J.-A., Stanga, P.E.,Cideciyan, A.V., Duncan, J.L., Eliott, D., Filley, E., Ho, A.C., Santos, A., Safran, A.B.,


http://dx.doi.org/10.1007/BF00237163

http://dx.doi.org/10.1007/s00417-005-0073-9




Arditi, Priore, L.V.D., Greenberg, R.J., 2010. Interim results from the internationaltrial of second sight’s visual prosthesis. Ophthalmology 119 (4), 779–788.

Humayun, M.S., Prince, M., de Juan, E., Barron, Y., Moskowitz, M., Klock, I.B., Milam,A.H., 1999. Morphometric analysis of the extramacular retina from postmortemeyes with retinitis pigmentosa. Investigative Ophthalmology & Visual Science40 (1), 143–148.

Humayun, M.S., Weiland, J.D., Fujii, G.Y., Greenberg, R., Williamson, R., Little, J.,Mech, B., Cimmarusti, V., Boemel, G.V., Dagnelie, G., de Juan Jr., E., 2003. Visualperception in a blind subject with a chronic microelectronic retinal prosthesis.Vision Research 43, 2573–2581.

Ivanova, E., Muller, F., 2006. Retinal bipolar cell types differ in their inventory of ionchannels. Visual Neuroscience 23 (02), 143–154.

Jensen, R.J., Rizzo, J.F., 2006. Thresholds for activation of rabbit retinal ganglion cellswith a subretinal electrode. Experimental Eye Research 83 (2), 367–373.

Jones, B.W., Marc, R.E., 2005. Retinal remodeling during retinal degeneration.Experimental Eye Research 81 (2), 123–137.

Joucla, S., Yvert, B., 2009. Improved focalization of electrical microstimulation usingmicroelectrode arrays: a modeling study. PLoS ONE 4 (3), e4828.

Keat, J., Reinagel, P., Reid, R.C., Meister, M., 2001. Predicting every spike: a model forthe responses of visual neurons. Neuron 30 (3), 803–817.

Kiran, R., Rousseau, L., Lissorgues, G., Scorsone, E., Bongrain, A., Yvert, B., Picaud, S.,Mailley, P., Bergonzo, P., 2012. Multichannel boron doped nanocrystallinediamond ultramicroelectrode arrays: design, fabrication and characterization.Sensors 12 (6), 7669–7681.

Klauke, S., Goertz, M., Rein, S., Hoehl, D., Thomas, U., Eckhorn, R., Bremmer, F.,Wachtler, T., 2011. Stimulation with a wireless intraocular epiretinal implantelicits visual percepts in blind humans. Investigative Ophthalmology & VisualScience 52 (1), 449–455.

Lieby, P., Barnes, N., McCarthy, C., Scott, A., Botea, V., Walker, J. 2012. Mobilityexperiments using simulated prosthetic vision with 98 phosphenes of limiteddynamic range. In: ARVO 2012.

Marc, R.E., Jones, B.W., Watt, C.B., Strettoi, E., 2003. Neural remodeling in retinaldegeneration. Progress in Retinal and Eye Research 22 (5), 607–655.

Martinez-Conde, S., Macknik, S.L., Troncoso, X.G., Hubel, D.H., 2009. Microsaccades:a neurophysiological analysis. Trends in Neurosciences 32 (9), 463–475.

Mathieson, K., Loudin, J., Goetz, G., Huie, P., Wang, L., Kamins, T.I., Galambos, L.,Smith, R., Harris, J.S., Sher, A., Palanker, D., 2012. Photovoltaic retinal prosthesiswith high pixel density. Nature Photonics 6 (6), 391–397.

Maynard, E.M., 2001. Visual prostheses. Annual Review of Biomedical Engineering3, 145–168.

Mcclure, K.H., Roy, A., Castro, R.A., Yadav, S., Dai, R., Greenberg, R.J., Chang, D.-y., Wu,X., Loftin, S., Mccord, S. 2009. Video processing unit for a visual prostheticapparatus. US patent 20090118794.

McCreery, D., Pikov, V., Troyk, P.R., 2010. Neuronal loss due to prolonged controlled-current stimulation with chronically implanted microelectrodes in the catcerebral cortex. Journal of Neural Engineering 7 (3), 036005.

Merabet, L.B., Rizzo, J.F., Amedi, A., Somers, D.C., Pascual-Leone, A., 2005. Whatblindness can tell us about seeing again: merging neuroplasticity andneuroprostheses. Nature Reviews Neuroscience 6 (1), 71–77.

Muller, F., Scholten, A., Ivanova, E., Haverkamp, S., Kremmer, E., Kaupp, U.B., 2003.Hcn channels are expressed differentially in retinal bipolar cells andconcentrated at synaptic terminals. European Journal of Neuroscience 17 (10),2084–2096.

Nirenberg, S., Pandarinath, C., 2012. Retinal prosthetic strategy with the capacity torestore normal vision. Proceedings of the National Academy of Sciences 109(37), 15012–15017.

Normann, R.A., Greger, B.A., House, P., Romero, S.F., Pelayo, F., Fernandez, E., 2009.Toward the development of a cortically based visual neuroprosthesis. Journal ofNeural Engineering 6 (3), 035001.

Ouarti, N., Sanda, N., Brun, J.L., Pineau, S., Sahel, J.-A., Safran, A. Real-time videoprocessing to specifically highlight the moving parts of the image, and alleviatevisual handicap. In: ARVO 2012.

Palanker, D., Huie, P., Vankov, A., Aramant, R., Seiler, M., Fishman, H., Marmor, M.,Blumenkranz, M., 2004. Migration of retinal cells through a perforatedmembrane: implications for a high-resolution prosthesis. InvestigativeOphthalmology & Visual Science 45 (9), 3266–3270.

Palanker, D., Vankov, A., Huie, P., Baccus, S., 2005. Design of a high-resolutionoptoelectronic retinal prosthesis. Journal of Neural Engineering 2 (1), S105.

Parikh, N., McIntosh, B., Tanguay, A., Humayun, M., Weiland, J. 2009. Biomimeticimage processing for retinal prostheses: peripheral saliency cues. In:Engineering in Medicine and Biology Society, 2009. Annual InternationalConference of the IEEE, pp. 4569–4572.

Pezaris, J.S., Reid, R.C., 2007. Demonstration of artificial visual percepts generatedthrough thalamic microstimulation. Proceedings of the National Academy ofSciences 104 (18), 7670–7675.

Pillow, J.W., Paninski, L., Uzzell, V.J., Simoncelli, E.P., Chichilnisky, E.J., 2005.Prediction and decoding of retinal ganglion cell responses with a probabilisticspiking model. The Journal of Neuroscience 25 (47), 11003–11013.

Pitkow, X., Meister, M., 2012. Decorrelation and efficient coding by retinal ganglioncells. Nature Neuroscience 15 (4), 628–635.

Rizzo, J.F., 2011. Update on retinal prosthetic research: the boston retinal implantproject. Journal of Neuroophthalmology 31 (2), 160–168.

Rizzo, J.F., Wyatt, J., Loewenstein, J., Kelly, S., Shire, D., 2003. Perceptual efficacy ofelectrical stimulation of human retina with a microelectrode array during


short-term surgical trials. Investigative Ophthalmology & Visual Science 44(12), 5362–5369.

Robblee, L., McHardy, J., Agnew, W., Bullara, L., 1983. Electrical stimulation with ptelectrodes. vii. dissolution of pt electrodes during electrical stimulation of thecat cerebral cortex. Journal of Neuroscience Methods 9 (4), 301–308.

Roessler, G., Laube, T., Brockmann, C., Kirschkamp, T., Mazinani, B., Goertz, M., Koch,C., Krisch, I., Sellhaus, B., Trieu, H.K., Weis, J., Bornfeld, N., Röthgen, H., Messner,A., Mokwa, W., Walter, P., 2009. Implantation and explantation of a wirelessepiretinal retina implant device: observations during the EPIRET3 prospectiveclinical trial. Investigative Ophthalmology & Visual Science 50 (6), 3003–3008.

Santos, A., Humayun, M.S., Eugene de Juan, J., Greenburg, R.J., Marsh, M.J., Klock, I.B.,Milam, A.H., 1997. Preservation of the inner retina in retinitis pigmentosa: amorphometric analysis. Archives of Ophthalmology 115 (4), 511–515.

Schmidt, E.M., Bak, M.J., Hambrecht, F.T., Kufta, C.V., O’Rourke, D.K., Vallabhanath,P., 1996. Feasibility of a visual prosthesis for the blind based on intracorticalmicro stimulation of the visual cortex. Brain 119 (2), 507–522.

Schnapf, J., Nunn, B., Meister, M., Baylor, D., 1990. Visual transduction in cones ofthe monkey macaca fascicularis. The Journal of Physiology 427, 681–713.

Schneeweis, D.M., Schnapf, J.L., 1999. The photovoltage of macaque conephotoreceptors: adaptation, noise, and kinetics. The Journal of Neuroscience19 (4), 1203–1216.

Sekirnjak, C., Hottowy, P., Sher, A., Dabrowski, W., Litke, A.M., Chichilnisky, E.J.,2008. High-resolution electrical stimulation of primate retina for epiretinalimplant design. The Journal of Neuroscience 28 (17), 4446–4456.

Sommerhalder, J., Rappaz, B., de Haller, R., Fornos, A.P., Safran, A.B., Pelizzone, M.,2004. Simulation of artificial vision: II. eccentric reading of full-page text andthe learning of this task. Vision Research 44 (14), 1693–1706.

Sui, X., Li, L., Chai, X., Wu, K., Zhou, C., Sun, X., Xu, X., Li, X., Ren, Q., 2009. Visualprosthesis for optic nerve stimulation. In: Greenbaum, E., Zhou, D. (Eds.),Implantable Neural Prostheses 1, Biological and Medical Physics, BiomedicalEngineering. Springer, US, pp. 43–83.

Torab, K., Davis, T.S., Warren, D.J., House, P.A., Normann, R.A., Greger, B., 2011.Multiple factors may influence the performance of a visual prosthesis based onintracortical microstimulation: nonhuman primate behavioralexperimentation. Journal of Neural Engineering 8 (3), 035001.

Uzzell, V.J., Chichilnisky, E.J., 2004. Precision of spike trains in primate retinalganglion cells. Journal of Neurophysiology 92 (2), 780–789.

Veraart, C., Raftopoulos, C., Mortimer, J.T., Delbeke, J., Pins, D., Michaux, G.,Vanlierde, A., Parrini, S., Wanet-Defalque, M.-C., 1998. Visual sensationsproduced by optic nerve stimulation using an implanted self-sizing spiral cuffelectrode. Brain Research 813 (1), 181–186.

Veraart, C., Wanet-Defalque, M.C., Gerard, B., Vanlierde, A., Delbeke, J., 2003. Patternrecognition with the optic nerve visual prosthesis. Artificial Organs 27 (11),996–1004.

Victor, J.D., 1987. The dynamics of the cat retinal x cell centre. The Journal ofPhysiology 386 (1), 219–246.

Victor, J.D., 1988. The dynamics of the cat retinal y cell subunit. The Journal ofPhysiology 405 (1), 289–320.

Wang, L., Mathieson, K., Kamins, T.I., Loudin, J.D., Galambos, L., Goetz, G., Sher, A.,Mandel, Y., Huie, P., Lavinsky, D., Harris, J.S., Palanker, D.V., 2012. Photovoltaicretinal prosthesis: implant fabrication and performance. Journal of NeuralEngineering 9 (4), 046014.

Wang, L., Yang, L., Dagnelie, G., 2008. Initiation and stability of pursuit eyemovements in simulated retinal prosthesis at different implant locations.Investigative Ophthalmology & Visual Science 49 (9), 3933–3939.

Weitz, A.C., Humayun, M.S., Chow, R.H., Weiland, J.D. 2012. Electrical stimulationwith 20-hz sinusoids activates focal regions of retinal ganglion cells. In: ARVO2012.

Wilke, R., Gabel, V.-P., Sachs, H., Bartz Schmidt, K.-U., Gekeler, F., Besch, D., Szurman,P., Stett, A., Wilhelm, B., Peters, T., Harscher, A., Greppmaier, U., Kibbel, S., Benav,H., Bruckmann, A., Stingl, K., Kusnyerik, A., Zrenner, E., 2011. Spatial resolutionand perception of patterns mediated by a subretinal 16-electrode array inpatients blinded by hereditary retinal dystrophies. Investigative Ophthalmology& Visual Science 52 (8), 5995–6003.

Wilms, M., Eckhorn, R., 2005. Spatiotemporal receptive field properties ofepiretinally recorded spikes and local electroretinograms in cats. BMCNeuroscience 6 (1), 50.

Wu, K., Zhang, C., Huang, W., Li, L., Ren, Q. 2010. Current research of c-sightvisual prosthesis for the blind. In: Engineering in Medicine and BiologySociety (EMBC), 2010 Annual International Conference of the IEEE, pp. 5875–5878.

Yang, X.L., Wu, S.M., 1991. Feedforward lateral inhibition in retinal bipolar cells:input–output relation of the horizontal cell-depolarizing bipolar cell synapse.Proceedings of the National Academy of Sciences 88 (8), 3310–3313.

Zhou, J.A., Woo, S.J., Park, S.I., Kim, E.T., Seo, J.M., Chung, H., Kim, S.J., 2008. Asuprachoroidal electrical retinal stimulator design for long-term animalexperiments and in vivo assessment of its feasibility and biocompatibility inrabbits. Journal of Biomedicine and Biotechnology, 547428.

Zrenner, E., Bartz-Schmidt, K.U., Benav, H., Besch, D., Bruckmann, A., Gabel, V.-P.,Gekeler, F., Greppmaier, U., Harscher, A., Kibbel, S., Koch, J., Kusnyerik, A., Peters,T., Stingl, K., Sachs, H., Stett, A., Szurman, P., Wilhelm, B., Wilke, R., 2010.Subretinal electronic chips allow blind patients to read letters and combinethem to words. Proceedings of the Royal Society B: Biological Sciences.




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