Effects of different three-dimensional electrodes on epiretinal electrical stimulation by modeling analysis

Patient-specific computational models of retinal prostheses

Retinal prostheses stimulate inner retinal neurons to create visual perception for blind patients. Implanted arrays have many small electrodes. Not all electrodes induce perception at the same stimulus amplitude, requiring clinicians to manually establish a visual perception threshold for each one. Phosphenes created by single-electrode stimuli can also vary in shape, size, and brightness. Computational models provide a tool to predict inter-electrode variability and automate device programming. In this study, we created statistical and patient-specific field-cable models to investigate inter-electrode variability across seven epiretinal prosthesis users. Our statistical analysis revealed that retinal thickness beneath the electrode correlated with perceptual threshold, with a significant fixed effect across participants. Electrode-retina distance and electrode impedance also correlated with perceptual threshold for some participants, but these effects varied by individual. We developed a novel method to construct patient-specific field-cable models from optical coherence tomography images. Predictions with these models significantly correlated with perceptual threshold for 80% of participants. Additionally, we demonstrated that patient-specific field-cable models could predict retinal activity and phosphene size. These computational models could be beneficial for determining optimal stimulation settings in silico, circumventing the trial-and-error testing of a large parameter space in clinic.

Effects on Retinal Stimulation of the Geometry and the Insertion Location of Penetrating Electrodes

Retinal implants have been developed and implanted to restore vision from outer retinal degeneration, but their performance is still limited due to the poor spatial resolution. To improve the localization of stimulation, microelectrodes in various three-dimensional (3D) shapes have been investigated. In particular, computational simulation is crucial for optimizing the performance of a novel microelectrode design before actual fabrication. However, most previous studies have assumed a uniform conductivity for the entire retina without testing the effect of electrodes placement in different layers. In this study, we used the finite element method to simulate electric fields created by 3D microelectrodes of three different designs in a retina model with a stratified conductivity profile. The three electrode designs included two conventional shapes - a conical electrode (CE) and a pillar electrode (PE); we also proposed a novel structure of pillar electrode with an insulating wall (PEIW). A quantitative comparison of these designs shows the PEIW generates a stronger and more confined electric field with the same current injection, which is preferred for high-resolution retinal prostheses. Moreover, our results demonstrate both the magnitude and the shape of potential distribution generated by a penetrating electrode depend not only on the geometry, but also substantially on the insertion depth of the electrode. Although epiretinal insertions are mainly discussed, we also compared results for subretinal insertions. The results provide valuable insights for improving the spatial resolution of retinal implants using 3D penetrating microelectrodes and highlight the importance of considering the heterogeneity of conductivities in the retina.

Inference of Electrical Stimulation Sensitivity from Recorded Activity of Primate Retinal Ganglion Cells

High-fidelity electronic implants can in principle restore the function of neural circuits by precisely activating neurons via extracellular stimulation. However, direct characterization of the individual electrical sensitivity of a large population of target neurons, to precisely control their activity, can be difficult or impossible. A potential solution is to leverage biophysical principles to infer sensitivity to electrical stimulation from features of spontaneous electrical activity, which can be recorded relatively easily. Here, this approach is developed and its potential value for vision restoration is tested quantitatively using large-scale multielectrode stimulation and recording from retinal ganglion cells (RGCs) of male and female macaque monkeys ex vivo Electrodes recording larger spikes from a given cell exhibited lower stimulation thresholds across cell types, retinas, and eccentricities, with systematic and distinct trends for somas and axons. Thresholds for somatic stimulation increased with distance from the axon initial segment. The dependence of spike probability on injected current was inversely related to threshold, and was substantially steeper for axonal than somatic compartments, which could be identified by their recorded electrical signatures. Dendritic stimulation was largely ineffective for eliciting spikes. These trends were quantitatively reproduced with biophysical simulations. Results from human RGCs were broadly similar. The inference of stimulation sensitivity from recorded electrical features was tested in a data-driven simulation of visual reconstruction, revealing that the approach could significantly improve the function of future high-fidelity retinal implants.SIGNIFICANCE STATEMENT This study demonstrates that individual in situ primate retinal ganglion cells of different types respond to artificially generated, external electrical fields in a systematic manner, in accordance with theoretical predictions, that allows for prediction of electrical stimulus sensitivity from recorded spontaneous activity. It also provides evidence that such an approach could be immensely helpful in the calibration of clinical retinal implants.

Simulating the impact of photoreceptor loss and inner retinal network changes on electrical activity of the retina

Objective.A major reason for poor visual outcomes provided by existing retinal prostheses is the limited knowledge of the impact of photoreceptor loss on retinal remodelling and its subsequent impact on neural responses to electrical stimulation. Computational network models of the neural retina assist in the understanding of normal retinal function but can be also useful for investigating diseased retinal responses to electrical stimulation.Approach.We developed and validated a biophysically detailed discrete neuronal network model of the retina in the software package NEURON. The model includes rod and cone photoreceptors, ON and OFF bipolar cell pathways, amacrine and horizontal cells and finally, ON and OFF retinal ganglion cells with detailed network connectivity and neural intrinsic properties. By accurately controlling the network parameters, we simulated the impact of varying levels of degeneration on retinal electrical function.Main results.Our model was able to reproduce characteristic monophasic and biphasic oscillatory patterns seen in ON and OFF neurons during retinal degeneration (RD). Oscillatory activity occurred at 3 Hz with partial photoreceptor loss and at 6 Hz when all photoreceptor input to the retina was removed. Oscillations were found to gradually weaken, then disappear when synapses and gap junctions were destroyed in the inner retina. Without requiring any changes to intrinsic cellular properties of individual inner retinal neurons, our results suggest that changes in connectivity alone were sufficient to give rise to neural oscillations during photoreceptor degeneration, and significant network connectivity destruction in the inner retina terminated the oscillations.Significance.Our results provide a platform for further understanding physiological retinal changes with progressive photoreceptor and inner RD. Furthermore, our model can be used to guide future stimulation strategies for retinal prostheses to benefit patients at different stages of disease progression, particularly in the early and mid-stages of RD.

An in-silico analysis of electrically-evoked responses of midget and parasol retinal ganglion cells in different retinal regions

BACKGROUND

Visual outcomes provided by present retinal prostheses that primarily target retinal ganglion cells (RGCs) through epiretinal stimulation remain rudimentary, partly due to the limited knowledge of retinal responses under electrical stimulation. Better understanding of how different retinal regions can be quantitatively controlled with high spatial accuracy, will be beneficial to the design of micro-electrode arrays (MEAs) and stimulation strategies for next-generation wide-view, high-resolution epiretinal implants.

METHODS

A computational model was developed to assess neural activity at different eccentricities (2 mm and 5 mm) within the human retina. This model included midget and parasol RGCs with anatomically accurate cell distribution and cell-specific morphological information. We then performed in silico investigations of region-specific RGC responses to epiretinal electrical stimulation using varied electrode sizes (5 µm - 210 µm diameter), emulating both commercialized retinal implants and recently-developed prototype devices.

RESULTS

Our model of epiretinal stimulation predicted RGC population excitation analogous to the complex percepts reported in human subjects. Following this, our simulations suggest that midget and parasol RGCs have characteristic regional differences in excitation under preferred electrode sizes. Relatively central (2 mm) regions demonstrated higher number of excited RGCs but lower overall activated receptive field (RF) areas under the same stimulus amplitudes (two-way ANOVA, p < 0.05). Furthermore, the activated RGC numbers per unit active RF area (number-RF ratio) were significantly higher in central than in peripheral regions, and higher in the midget than in the parasol population under all tested electrode sizes (two-way ANOVA, p < 0.05). Our simulations also suggested that smaller electrodes exhibit a higher range of controllable stimulation parameters to achieve pre-defined performance of RGC excitation. ..

Discrimination of simple objects decoded from the output of retinal ganglion cells upon sinusoidal electrical stimulation

Objective. Most neuroprosthetic implants employ pulsatile square-wave electrical stimuli, which are significantly different from physiological inter-neuronal communication. In case of retinal neuroprosthetics, which use a certain type of pulsatile stimuli, reliable object and contrast discrimination by implanted blind patients remained challenging. Here we investigated to what extent simple objects can be discriminated from the output of retinal ganglion cells (RGCs) upon sinusoidal stimulation.Approach. Spatially confined objects were formed by different combinations of 1024 stimulating microelectrodes. The RGC activity in theex vivoretina of photoreceptor-degenerated mouse, of healthy mouse or of primate was recorded simultaneously using an interleaved recording microelectrode array implemented in a CMOS-based chip.Main results. We report that application of sinusoidal electrical stimuli (40 Hz) in epiretinal configuration instantaneously and reliably modulates the RGC activity in spatially confined areas at low stimulation threshold charge densities (40 nC mm^-2). Classification of overlapping but spatially displaced objects (1° separation) was achieved by distinct spiking activity of selected RGCs. A classifier (regularized logistic regression) discriminated spatially displaced objects (size: 5.5° or 3.5°) with high accuracy (90% or 62%). Stimulation with low artificial contrast (10%) encoded by different stimulus amplitudes generated RGC activity, which was classified with an accuracy of 80% for large objects (5.5°).Significance. We conclude that time-continuous smooth-wave stimulation provides robust, localized neuronal activation in photoreceptor-degenerated retina, which may enable future artificial vision at high temporal, spatial and contrast resolution.

Modelling the visual response to an OUReP retinal prosthesis with photoelectric dye coupled to polyethylene film

Objective.Retinal prostheses have been developed to restore vision in blind patients suffering from diseases like retinitis pigmentosa.Approach.A new type of retinal prosthesis called the Okayama University-type retinal prosthesis (OUReP) was developed by chemically coupling photoelectric dyes to a polyethylene film surface. The prosthesis works by passively generating an electric potential when stimulated by light. However, the neurophysiological mechanism of how OUReP stimulates the degenerated retina is unknown.Main results.Here, we explore how the OUReP affects retinal tissues using a finite element model to solve for the potential inside the tissue and an active Hodgkin-Huxley model based on rat vision to predict the corresponding retinal bipolar response.Significance.We show that the OUReP is likely capable of eliciting responses in retinal bipolar cells necessary to generate vision under most ambient conditions.

Creation of virtual channels in the retina using synchronous and asynchronous stimulation - a modelling study

OBJECTIVE

Implantable retinal prostheses aim to provide artificial vision to those suffering from retinal degenerative diseases by electrically stimulating the remaining retinal neurons using a multi-electrode array. The spatial resolution of these devices can be improved by creation of so-called virtual channels (VCs) that are commonly achieved through synchronized stimulation of multiple electrodes. It is largely unclear though if VCs can be created using asynchronous stimulation, which was the primary aim of this study.

APPROACH

A computational model of multi-layered retina and epi-retinal dual-electrode stimulation was developed to simulate the neural activity of populations of retinal ganglion cells (RGCs) using the VC strategy under both synchronous and asynchronous stimulation conditions.

MAIN RESULTS

Our simulation suggests that VCs can be created using asynchronous stimulation. VC performance under both synchronous and asynchronous stimulation conditions can be improved by optimizing stimulation parameters such as current intensity, current ratio (α) between two electrodes, electrode spacing and the stimulation waveform. In particular, two VC performance measures; (1) linear displacement of the centroid of RGC activation, and (2) the RGC activation size consistency as a function of different current ratios α, have comparable performance under asynchronous and synchronous stimulation with appropriately selected stimulation parameters.

SIGNIFICANCE

Our findings support the possibility of creating VCs in the retina under both synchronous and asynchronous stimulation conditions. The results provide theoretical evidence for future retinal prosthesis designs with higher spatial resolution and power efficiency whilst reducing the number of current sources required to achieve these outcomes.

A Computational Study of Graphene as a Prospective Material for Microelectrodes in Retinal Prosthesis and Electric Crosstalk Analysis

The computational model plays a vital role in the design and optimization of microelectrodes for efficient electrical stimulation and recording in the retinal prosthesis. Moreover, the material choice acts decisively in ensuring that the electronic device delivers sufficient stimulating current to the retina without harming the neighboring tissue. Recently, due to the enhanced electrical and electrochemical properties of graphene, it has become a viable material in biomedical applications. In this study, we analyzed the computational model for the retinal prosthesis by the novel use of graphene-based microelectrodes. For this, different topologies of the electrode arrangement were investigated. The most suitable configuration involves the arrangement of electrodes serving as the ground in a hexagonal fashion around the central stimulating electrode. We observed that the performance of graphene as the stimulating electrodes is comparable to the existing noble metal-based electrodes. Moreover, we found that optimizing the microelectrode design resulted in uniform electric potential distribution, and this eventually led to an increased electric field intensity at the desired activation point. Additionally, we analyzed the crosstalk phenomenon, and we observed from the results that it is better to implant such an electrode array in the vicinity of the targeted volume to minimize the effect of crosstalk.Clinical relevance- The present study can help in the improvement of the retinal prosthesis by analyzing the quantitative and qualitative effects of graphene-based microelectrodes on producing the threshold electric field in the retina tissue. The results obtained can be used to optimize the implantable microelectrode design and thus is a step forward in finding a cure to vision impairment diseases.

Retinal Prosthetic Approaches to Enhance Visual Perception for Blind Patients

Retinal prostheses are implantable devices that aim to restore the vision of blind patients suffering from retinal degeneration, mainly by artificially stimulating the remaining retinal neurons. Some retinal prostheses have successfully reached the stage of clinical trials; however, these devices can only restore vision partially and remain insufficient to enable patients to conduct everyday life independently. The visual acuity of the artificial vision is limited by various factors from both engineering and physiological perspectives. To overcome those issues and further enhance the visual resolution of retinal prostheses, a variety of retinal prosthetic approaches have been proposed, based on optimization of the geometries of electrode arrays and stimulation pulse parameters. Other retinal stimulation modalities such as optics, ultrasound, and magnetics have also been utilized to address the limitations in conventional electrical stimulation. Although none of these approaches have been clinically proven to fully restore the function of a degenerated retina, the extensive efforts made in this field have demonstrated a series of encouraging findings for the next generation of retinal prostheses, and these could potentially enhance the visual acuity of retinal prostheses. In this article, a comprehensive and up-to-date overview of retinal prosthetic strategies is provided, with a specific focus on a quantitative assessment of visual acuity results from various retinal stimulation technologies. The aim is to highlight future directions toward high-resolution retinal prostheses.

A Three-Dimensional Microelectrode Array to Generate Virtual Electrodes for Epiretinal Prosthesis Based on a Modeling Study

Despite many advances in the development of retinal prostheses, clinical reports show that current retinal prosthesis subjects can only perceive prosthetic vision with poor visual acuity. A possible approach for improving visual acuity is to produce virtual electrodes (VEs) through electric field modulation. Generating controllable and localized VEs is a crucial factor in effectively improving the perceptive resolution of the retinal prostheses. In this paper, we aimed to design a microelectrode array (MEA) that can produce converged and controllable VEs by current steering stimulation strategies. Through computational modeling, we designed a three-dimensional concentric ring–disc MEA and evaluated its performance with different stimulation strategies. Our simulation results showed that electrode–retina distance (ERD) and inter-electrode distance (IED) can dramatically affect the distribution of electric field. Also the converged VEs could be produced when the parameters of the three-dimensional MEA were appropriately set. VE sites can be controlled by manipulating the proportion of current on each adjacent electrode in a current steering group (CSG). In addition, spatial localization of electrical stimulation can be greatly improved under quasi-monopolar (QMP) stimulation. This study may provide support for future application of VEs in epiretinal prosthesis for potentially increasing the visual acuity of prosthetic vision.

Computational Design of FastFES Treatment to Improve Propulsive Force Symmetry During Post-stroke Gait: A Feasibility Study

Stroke is a leading cause of long-term disability worldwide and often impairs walking ability. To improve recovery of walking function post-stroke, researchers have investigated the use of treatments such as fast functional electrical stimulation (FastFES). During FastFES treatments, individuals post-stroke walk on a treadmill at their fastest comfortable speed while electrical stimulation is delivered to two muscles of the paretic ankle, ideally to improve paretic leg propulsion and toe clearance. However, muscle selection and stimulation timing are currently standardized based on clinical intuition and a one-size-fits-all approach, which may explain in part why some patients respond to FastFES training while others do not. This study explores how personalized neuromusculoskeletal models could potentially be used to enable individual-specific selection of target muscles and stimulation timing to address unique functional limitations of individual patients post-stroke. Treadmill gait data, including EMG, surface marker positions, and ground reactions, were collected from an individual post-stroke who was a non-responder to FastFES treatment. The patient's gait data were used to personalize key aspects of a full-body neuromusculoskeletal walking model, including lower-body joint functional axes, lower-body muscle force generating properties, deformable foot-ground contact properties, and paretic and non-paretic leg neural control properties. The personalized model was utilized within a direct collocation optimal control framework to reproduce the patient's unstimulated treadmill gait data (verification problem) and to generate three stimulated walking predictions that sought to minimize inter-limb propulsive force asymmetry (prediction problems). The three predictions used: (1) Standard muscle selection (gastrocnemius and tibialis anterior) with standard stimulation timing, (2) Standard muscle selection with optimized stimulation timing, and (3) Optimized muscle selection (soleus and semimembranosus) with optimized stimulation timing. Relative to unstimulated walking, the optimal control problems predicted a 41% reduction in propulsive force asymmetry for scenario (1), a 45% reduction for scenario (2), and a 64% reduction for scenario (3), suggesting that non-standard muscle selection may be superior for this patient. Despite these predicted improvements, kinematic symmetry was not noticeably improved for any of the walking predictions. These results suggest that personalized neuromusculoskeletal models may be able to predict personalized FastFES training prescriptions that could improve propulsive force symmetry, though inclusion of kinematic requirements would be necessary to improve kinematic symmetry as well.

Minimizing activation of overlying axons with epiretinal stimulation: The role of fiber orientation and electrode configuration

Currently, a challenge in electrical stimulation of the retina with a visual prosthesis (bionic eye) is to excite only the cells lying directly under the electrode in the ganglion cell layer, while avoiding excitation of axon bundles that pass over the surface of the retina in the nerve fiber layer. Stimulation of overlying axons results in irregular visual percepts, limiting perceptual efficacy. This research explores how differences in fiber orientation between the nerve fiber layer and ganglion cell layer leads to differences in the electrical activation of the axon initial segment and axons of passage. Approach. Axons of passage of retinal ganglion cells in the nerve fiber layer are characterized by a narrow distribution of fiber orientations, causing highly anisotropic spread of applied current. In contrast, proximal axons in the ganglion cell layer have a wider distribution of orientations. A four-layer computational model of epiretinal extracellular stimulation that captures the effect of neurite orientation in anisotropic tissue has been developed using a volume conductor model known as the cellular composite model. Simulations are conducted to investigate the interaction of neural tissue orientation, stimulating electrode configuration, and stimulation pulse duration and amplitude. Main results. Our model shows that simultaneous stimulation with multiple electrodes aligned with the nerve fiber layer can be used to achieve selective activation of axon initial segments rather than passing fibers. This result can be achieved while reducing required stimulus charge density and with only modest increases in the spread of activation in the ganglion cell layer, and is shown to extend to the general case of arbitrary electrode array positioning and arbitrary target volume. Significance. These results elucidate a strategy for more targeted stimulation of retinal ganglion cells with experimentally-relevant multi-electrode geometries and achievable stimulation requirements.

Human Interactive Triboelectric Nanogenerator as a Self-Powered Smart Seat

A lightweight, flexible, cost-effective, and robust, single-electrode-based Smart Seat-Triboelectric Nanogenerator (SS-TENG) is introduced as a promising eco-friendly approach for harvesting energy from the living environment, for use in integrated self-powered systems. An effective method for harvesting biomechanical energy from human motion such as walking, running, and sitting, utilizing widely adaptable everyday contact materials (newspaper, denim, polyethylene covers, and bus cards) is demonstrated. The working mechanism of the SS-TENG is based on the generation and transfer of triboelectric charge carriers between the active layer and user-friendly contact materials. The performance of SS-TENG (52 V and 5.2 μA for a multiunit SS-TENG) is systematically studied and demonstrated in a range of applications including a self-powered passenger seat number indicator and a STOP-indicator using LEDs, using a simple logical circuit. Harvested energy is used as a direct power source to drive 60 blue and green commercially available LEDs and a monochrome LCD. This feasibility study confirms that triboelectric nanogenerators are a suitable technology for energy harvesting from human motion during transportation, which could be used to operate a variety of wireless devices, GPS systems, electronic devices, and other sensors during travel.