A continuum model of retinal electrical stimulation

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.

A multi-scale simulation of retinal physiology

We present a detailed physiological model of the (human) retina that includes the biochemistry and electrophysiology of phototransduction, neuronal electrical coupling, and the spherical geometry of the eye. The model is a parabolic-elliptic system of partial differential equations based on the mathematical framework of the bi-domain equations, which we have generalized to account for multiple cell-types. We discretize in space with non-uniform finite differences and step through time with a custom adaptive time-stepper that employs a backward differentiation formula and an inexact Newton method. A refinement study confirms the accuracy and efficiency of our numerical method. Numerical simulations using the model compare favorably with experimental findings, such as desensitization to light stimuli and calcium buffering in photoreceptors. Other numerical simulations suggest an interplay between photoreceptor gap junctions and inner segment, but not outer segment, calcium concentration. Applications of this model and simulation include analysis of retinal calcium imaging experiments, the design of electroretinograms, the design of visual prosthetics, and studies of ephaptic coupling within the retina.

Modulating individual axons and axonal populations in the peripheral nerve using transverse intrafascicular multichannel electrodes

Objective.A transverse intrafascicular multichannel electrode (TIME) may offer advantages over more conventional cuff electrodes including higher spatial selectivity and reduced stimulation charge requirements. However, the performance of TIME, especially in the context of non-conventional stimulation waveforms, remains relatively unexplored. As part of our overarching goal of investigating stimulation efficacy of TIME, we developed a computational toolkit that automates the creation and usage ofin siliconerve models with TIME setup, which solves nerve responses using cable equations and computes extracellular potentials using finite element method.Approach.We began by implementing a flexible and scalable Python/MATLAB-based toolkit for automatically creating models of nerve stimulation in the hybrid NEURON/COMSOL ecosystems. We then developed a sciatic nerve model containing 14 fascicles with 1,170 myelinated (A-type, 30%) and unmyelinated (C-type, 70%) fibers to study fiber responses over a variety of TIME arrangements (monopolar and hexapolar) and stimulation waveforms (kilohertz stimulation and cathodic ramp modulation).Main results.Our toolkit obviates the conventional need to re-create the same nerve in two disparate modeling environments and automates bi-directional transfer of results. Our population-based simulations suggested that kilohertz stimuli provide selective activation of targeted C fibers near the stimulating electrodes but also tended to activate non-targeted A fibers further away. However, C fiber selectivity can be enhanced by hexapolar TIME arrangements that confined the spatial extent of electrical stimuli. Improved upon prior findings, we devised a high-frequency waveform that incorporates cathodic DC ramp to completely remove undesirable onset responses.Conclusion.Our toolkit allows agile, iterative design cycles involving the nerve and TIME, while minimizing the potential operator errors during complex simulation. The nerve model created by our toolkit allowed us to study and optimize the design of next-generation intrafascicular implants for improved spatial and fiber-type selectivity.

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, which act as pixels. 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.

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.

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.

Computational challenges and opportunities for a bi-directional artificial retina

A future artificial retina that can restore high acuity vision in blind people will rely on the capability to both read (observe) and write (control) the spiking activity of neurons using an adaptive, bi-directional and high-resolution device. Although current research is focused on overcoming the technical challenges of building and implanting such a device, exploiting its capabilities to achieve more acute visual perception will also require substantial computational advances. Using high-density large-scale recording and stimulation in the primate retina with an ex vivo multi-electrode array lab prototype, we frame several of the major computational problems, and describe current progress and future opportunities in solving them. First, we identify cell types and locations from spontaneous activity in the blind retina, and then efficiently estimate their visual response properties by using a low-dimensional manifold of inter-retina variability learned from a large experimental dataset. Second, we estimate retinal responses to a large collection of relevant electrical stimuli by passing current patterns through an electrode array, spike sorting the resulting recordings and using the results to develop a model of evoked responses. Third, we reproduce the desired responses for a given visual target by temporally dithering a diverse collection of electrical stimuli within the integration time of the visual system. Together, these novel approaches may substantially enhance artificial vision in a next-generation device.

A Multi-Domain Continuum Model of Electrical Stimulation of Healthy and Degenerate Retina

A continuum multi-domain model of electrical stimulation of the retina is presented and validated against retinal ganglion cell (RGC) excitation thresholds reported in a recently published in vitro experimental study. We applied our model to investigate the response of the RGC layer to electrical stimulation during mid-to-late stage retinal degeneration for both epiretinal and suprachoroidal configurations. Interestingly, our model predicted that suprachoroidal stimulation of the degenerate retina required increased current thresholds, mainly because of the presence of the glial scar layer. In contrast, epiretinal stimulation thresholds were almost similar for both healthy and degenerate models. The latter finding implies that there is no influence of the glial scar layer on epiretinal stimulation current thresholds.

Epiretinal stimulation with local returns enhances selectivity at cellular resolution

OBJECTIVE

Epiretinal prostheses are designed to restore vision in people blinded by photoreceptor degenerative diseases, by directly activating retinal ganglion cells (RGCs) using an electrode array implanted on the retina. In present-day clinical devices, current spread from the stimulating electrode to a distant return electrode often results in the activation of many cells, potentially limiting the quality of artificial vision. In the laboratory, epiretinal activation of RGCs with cellular resolution has been demonstrated with small electrodes, but distant returns may still cause undesirable current spread. Here, the ability of local return stimulation to improve the selective activation of RGCs at cellular resolution was evaluated.

APPROACH

A custom multi-electrode array (512 electrodes, 10 μm diameter, 60 μm pitch) was used to simultaneously stimulate and record from RGCs in isolated primate retina. Stimulation near the RGC soma with a single electrode and a distant return was compared to stimulation in which the return was provided by six neighboring electrodes.

MAIN RESULTS

Local return stimulation enhanced the capability to activate cells near the central electrode (<30 μm) while avoiding cells farther away (>30 μm). This resulted in an improved ability to selectively activate ON and OFF cells, including cells encoding immediately adjacent regions in the visual field.

SIGNIFICANCE

These results suggest that a device that restricts the electric field through local returns could optimize activation of neurons at cellular resolution, improving the quality of artificial vision.

A continuum model of electrical stimulation of multi-compartmental retinal ganglion cells

A continuum multi-domain model of electrical stimulation of the retina is presented. Each point in the retinal ganglion cell layer could be thought of as representing a single cell, whose biophysics is described using a four-compartment formulation incorporating varying ion channel expressions in the soma, axon initial segment, dendrites and axon. Our continuum model was validated against a discrete morphologically-realistic OFF RGC model, using intra- and extra-cellular electrical stimulation scenarios. Simulations from the continuum model reproduced the same results as that of the discrete model. Our continuum model is the first multi-domain model to represent all main RGC compartments, not just the soma. Moreover, we demonstrated that this model allows the investigation of axonal activation which has been observed to influence the perception of phosphenes.

Electrical activity of ON and OFF retinal ganglion cells: a modelling study

OBJECTIVE

Retinal ganglion cells (RGCs) demonstrate a large range of variation in their ionic channel properties and morphologies. Cell-specific properties are responsible for the unique way RGCs process synaptic inputs, as well as artificial electrical signals such as that from a visual prosthesis. A cell-specific computational modelling approach allows us to examine the functional significance of regional membrane channel expression and cell morphology.

APPROACH

In this study, an existing RGC ionic model was extended by including a hyperpolarization activated non-selective cationic current as well as a T-type calcium current identified in recent experimental findings. Biophysically-defined model parameters were simultaneously optimized against multiple experimental recordings from ON and OFF RGCs.

MAIN RESULTS

With well-defined cell-specific model parameters and the incorporation of detailed cell morphologies, these models were able to closely reconstruct and predict ON and OFF RGC response properties recorded experimentally.

SIGNIFICANCE

The resulting models were used to study the contribution of different ion channel properties and spatial structure of neurons to RGC activation. The techniques of this study are generally applicable to other excitable cell models, increasing the utility of theoretical models in accurately predicting the response of real biological neurons.

A 3D-continuum bidomain model of retinal electrical stimulation using an anatomically detailed mesh

A continuum bidomain model of sub-retinal electrical stimulation on an anatomically detailed mesh of retina is presented. The underlying geometry is made up of 256 B-scans of optical coherence tomography (OCT) images of a healthy human retina, covering approximately 6×2 mm(2) centered on the macula. The OCT images are initially segmented and digitized into five major retinal layers comprising passive and active retinal cell types. This computational mesh is then used to model a subretinal hexapolar biphasic electrical stimulation. Our results indicate that the ultra-structure of the retina results in an asymmetric spatial extracellular potential distribution, leading to an irregular pattern of retinal ganglion cell activation. This finding is in contrast to focal circular activation previously reported in retinal electrical stimulation modeling with a uniform mesh.

Quasi-monopolar electrical stimulation of the retina: a computational modelling study

OBJECTIVE

In this study we investigated the feasibility of quasi-monopolar (QMP) electrical stimulation for retinal implant devices, using a computational model of the retinal ganglion cell layer.

APPROACH

When used with hexagonally arrayed multiple electrodes, QMP stimulation is a hybrid of hexapolar and conventional monopolar stimulus modes. In hexapolar mode, each active electrode is surrounded by six guards which collectively return the stimulus current, whereas in monopolar mode the injected stimulus current is returned through a distant return electrode. The QMP paradigm, on the other hand, distributes the return current between the guard electrodes as well as the distant return. The electrodes tested were 25, 50 and 100 µm in diameter, with hexagonally arranged centre-to-centre spacing of either double or quadruple this diameter.

MAIN RESULTS

Simulation results indicated that electrode size had minimal effects on subretinal threshold currents, whilst electrode configuration and centre-to-centre spacing played major roles in determining thresholds and spatial activation patterns. Threshold charge densities for 50 and 100 µm electrodes were generally within the safe limit.

SIGNIFICANCE

We found that QMP stimulation offers greater advantages compared to monopolar and hexapolar stimulation, in that it combines the low thresholds of monopolar stimulation with the localized spatial activation achieved with hexapolar electrodes during parallel stimulation.

Quasi-monopolar stimulation: a novel electrode design configuration for performance optimization of a retinal neuroprosthesis

In retinal neuroprostheses, spatial interaction between electric fields from various electrodes – electric crosstalk – may occur in multielectrode arrays during simultaneous stimulation of the retina. Depending on the electrode design and placement, this crosstalk can either enhance or degrade the functional characteristics of a visual prosthesis. To optimize the device performance, a balance must be satisfied between the constructive interference of crosstalk on dynamic range and power consumption and its negative effect on artificial visual acuity. In the present computational modeling study, we have examined the trade-off in these positive and negative effects using a range of currently available electrode array configurations, compared to a recently proposed stimulation strategy – the quasi monopolar (QMP) configuration – in which the return current is shared between local bipolar guards and a distant monopolar electrode. We evaluate the performance of the QMP configuration with respect to the implantation site and electrode geometry parameters. Our simulation results demonstrate that the beneficial effects of QMP are only significant at electrode-to-cell distances greater than the electrode dimensions. Possessing a relatively lower activation threshold, QMP was found to be superior to the bipolar configuration in terms of providing a relatively higher visual acuity. However, the threshold for QMP was more sensitive to the topological location of the electrode in the array, which may need to be considered when programming the manner in which electrode are simultaneously activated. This drawback can be offset with a wider dynamic range and lower power consumption of QMP. Furthermore, the ratio of monopolar return current to total return can be used to adjust the functional performance of QMP for a given implantation site and electrode parameters. We conclude that the QMP configuration can be used to improve visual information-to-stimulation mapping in a visual prosthesis, while maintaining low power consumption.

Implantable multilayer microstrip antenna for retinal prosthesis: antenna testing

Retinal prosthesis has come to a more mature stage and become a very strategic answer to Retinitis Pigmentosa (RP) and Age-related Macular Degeneration (AMD) diseases. In a retinal prosthesis system, wireless link holds a great importance for the continuity of the system. In this paper, an implantable multilayer microstrip antenna was proposed for the retinal prosthesis system. Simulations were performed in High Frequency Structure Simulator (HFSS) with the surrounding material of air and Vitreous Humor fluid. The fabricated antenna was measured for characteristic validation in free space. The results showed that the real antenna possessed similar return loss and radiation pattern, while there was discrepancy with the gain values.

Model-based analysis of multiple electrode array stimulation for epiretinal visual prostheses

OBJECTIVE

Epiretinal stimulation, which uses an array of electrodes implanted on the inner retinal surface to relay a representation of the visual scene to the neuronal elements of the retina, has seen considerable success. The objective of the present study was to quantify the effects of multi-electrode stimulation on the patterns of neural excitation in a computational model of epiretinal stimulation.

APPROACH

A computational model of retinal ganglion cells was modified to represent the morphology of human retinal ganglion cells and validated against published experimental data. The ganglion cell model was then combined with a model of an axon of the nerve fiber layer to produce a population model of the inner retina. The response of the population of model neurons to epiretinal stimulation with a multi-electrode array was quantified across a range of electrode geometries using a novel means to quantify the model response-the minimum radius circle bounding the activated model neurons as a proxy for the evoked phosphene.

MAIN RESULTS

Multi-electrode stimulation created unique phosphenes, uch that the number of potential phosphenes can far exceed the number of electrode contacts.

SIGNIFICANCE

The ability to exploit the spatial and temporal interactions of stimulation may be critical to improvements in the performance of epiretinal prostheses.