Increasing Electrical Stimulation Efficacy in Degenerated Retina: Stimulus Waveform Design in a Multiscale Computational Model

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.

Adaptive octree meshes for simulation of extracellular electrophysiology

Objective.The interaction between neural tissues and artificial electrodes is crucial for understanding and advancing neuroscientific research and therapeutic applications. However, accurately modeling this space around the neurons rapidly increases the computational complexity of neural simulations.Approach.This study demonstrates a dynamically adaptive simulation method that greatly accelerates computation by adjusting spatial resolution of the simulation as needed. Use of an octree structure for the mesh, in combination with the admittance method for discretizing conductivity, provides both accurate approximation and ease of modification on-the-fly.Main results.In tests of both local field potential estimation and multi-electrode stimulation, dynamically adapted meshes achieve accuracy comparable to high-resolution static meshes in an order of magnitude less time.Significance.The proposed simulation pipeline improves model scalability, allowing greater detail with fewer computational resources. The implementation is available as an open-source Python module, providing flexibility and ease of reuse for the broader research community.

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.

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.

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.

Retinal ganglion cells undergo cell type-specific functional changes in a computational model of cone-mediated retinal degeneration

Introduction

Understanding the retina in health and disease is a key issue for neuroscience and neuroengineering applications such as retinal prostheses. During degeneration, the retinal network undergoes complex and multi-stage neuroanatomical alterations, which drastically impact the retinal ganglion cell (RGC) response and are of clinical importance. Here we present a biophysically detailed in silico model of the cone pathway in the retina that simulates the network-level response to both light and electrical stimulation.

Methods

The model included 11, 138 cells belonging to nine different cell types (cone photoreceptors, horizontal cells, ON/OFF bipolar cells, ON/OFF amacrine cells, and ON/OFF ganglion cells) confined to a 300 × 300 × 210μm patch of the parafoveal retina. After verifying that the model reproduced seminal findings about the light response of retinal ganglion cells (RGCs), we systematically introduced anatomical and neurophysiological changes (e.g., reduced light sensitivity of photoreceptor, cell death, cell migration) to the network and studied their effect on network activity.

Results

The model was not only able to reproduce common findings about RGC activity in the degenerated retina, such as hyperactivity and increased electrical thresholds, but also offers testable predictions about the underlying neuroanatomical mechanisms.

Discussion

Overall, our findings demonstrate how biophysical changes typified by cone-mediated retinal degeneration may impact retinal responses to light and electrical stimulation. These insights may further our understanding of retinal processing and inform the design of retinal prostheses.

Modeling extracellular stimulation of retinal ganglion cells: theoretical and practical aspects

Objective.Retinal prostheses use electric current to activate inner retinal neurons, providing artificial vision for blind people. Epiretinal stimulation primarily targets retinal ganglion cells (RGCs), which can be modeled with cable equations. Computational models provide a tool to investigate the mechanisms of retinal activation, and improve stimulation paradigms. However, documentation of RGC model structure and parameters is limited, and model implementation can influence model predictions.Approach.We created a functional guide for building a mammalian RGC multi-compartment cable model and applying extracellular stimuli. Next, we investigated how the neuron's three-dimensional shape will influence model predictions. Finally, we tested several strategies to maximize computational efficiency.Main results.We conducted sensitivity analyses to examine how dendrite representation, axon trajectory, and axon diameter influence membrane dynamics and corresponding activation thresholds. We optimized the spatial and temporal discretization of our multi-compartment cable model. We also implemented several simplified threshold prediction theories based on activating function, but these did not match the prediction accuracy achieved by the cable equations.Significance.Through this work, we provide practical guidance for modeling the extracellular stimulation of RGCs to produce reliable and meaningful predictions. Robust computational models lay the groundwork for improving the performance of retinal prostheses.

Retinal ganglion cells undergo cell typeâ€"specific functional changes in a biophysically detailed model of retinal degeneration

Understanding the retina in health and disease is a key issue for neuroscience and neuroengineering applications such as retinal prostheses. During degeneration, the retinal network undergoes complex and multi-stage neuroanatomical alterations, which drastically impact the retinal ganglion cell (RGC) response and are of clinical importance. Here we present a biophysically detailed in silico model of retinal degeneration that simulates the network-level response to both light and electrical stimulation as a function of disease progression. The model is not only able to reproduce common findings about RGC activity in the degenerated retina, such as hyperactivity and increased electrical thresholds, but also offers testable predictions about the underlying neuroanatomical mechanisms. Overall, our findings demonstrate how biophysical changes associated with retinal degeneration affect retinal responses to both light and electrical stimulation, which may further our understanding of visual processing in the retina as well as inform the design and application of retinal prostheses.

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.

Correlated Activity in the Degenerate Retina Inhibits Focal Response to Electrical Stimulation

Retinal prostheses have shown some clinical success in patients with retinitis pigmentosa and age-related macular degeneration. However, even after the implantation of a retinal prosthesis, the patient’s visual acuity is at best less than 20/420. Reduced visual acuity may be explained by a decrease in the signal-to-noise ratio due to the spontaneous hyperactivity of retinal ganglion cells (RGCs) found in degenerate retinas. Unfortunately, abnormal retinal rewiring, commonly observed in degenerate retinas, has rarely been considered for the development of retinal prostheses. The purpose of this study was to investigate the aberrant retinal network response to electrical stimulation in terms of the spatial distribution of the electrically evoked RGC population. An 8 × 8 multielectrode array was used to measure the spiking activity of the RGC population. RGC spikes were recorded in wild-type [C57BL/6J; P56 (postnatal day 56)], rd1 (P56), rd10 (P14 and P56) mice, and macaque [wild-type and drug-induced retinal degeneration (RD) model] retinas. First, we performed a spike correlation analysis between RGCs to determine RGC connectivity. No correlation was observed between RGCs in the control group, including wild-type mice, rd10 P14 mice, and wild-type macaque retinas. In contrast, for the RD group, including rd1, rd10 P56, and RD macaque retinas, RGCs, up to approximately 400–600 μm apart, were significantly correlated. Moreover, to investigate the RGC population response to electrical stimulation, the number of electrically evoked RGC spikes was measured as a function of the distance between the stimulation and recording electrodes. With an increase in the interelectrode distance, the number of electrically evoked RGC spikes decreased exponentially in the control group. In contrast, electrically evoked RGC spikes were observed throughout the retina in the RD group, regardless of the inter-electrode distance. Taken together, in the degenerate retina, a more strongly coupled retinal network resulted in the widespread distribution of electrically evoked RGC spikes. This finding could explain the low-resolution vision in prosthesis-implanted patients.

Selective Activation of Retinal Ganglion Cell Subtypes Through Targeted Electrical Stimulation Parameters

To restore vision to the low vision, epiretinal implants have been developed to electrically stimulate the healthy retinal ganglion cells (RGCs) in the degenerate retina. Given the diversity of retinal ganglion cells as well as the difference in their visual function, selective activation of RGCs subtypes can significantly improve the quality of the restored vision. Our recent results demonstrated that with the proper modulation of the current amplitude, small D1-bistratified cells with the contribution to blue/yellow color opponent pathway can be selectively activated at high frequency (200 Hz). The computational results correlated with the clinical findings revealing the blue sensation of 5/7 subjects with epiretinal implants at high frequency. Here we further explored the impacts of alterations in pulse duration and interphase gap on the response of RGCs at high frequency. We used the developed RGCs, A2-monostratified and D1-bistratified, and examined their response to a range of pulse durations (0.1−1.2 ms) and interphase gaps (0−1 ms). We found that the use of short pulse durations with no interphase gap at high frequency increases the differential response of RGCs, offering better opportunities for selective activation of D1 cells. The presence of the interphase gap has shown to reduce the overall differential response of RGCs. We also explored how the low density of calcium channels enhances the responsiveness of RGCs at high frequency.

Mechanisms underlying activation of retinal bipolar cells through targeted electrical stimulation: a computational study

Objective. Retinal implants have been developed to electrically stimulate healthy retinal neurons in the progressively degenerated retina. Several stimulation approaches have been proposed to improve the visual percept induced in patients with retinal prostheses. We introduce a computational model capable of simulating the effects of electrical stimulation on retinal neurons. Leveraging this computational platform, we delve into the underlying mechanisms influencing the sensitivity of retinal neurons' response to various stimulus waveforms.Approach. We implemented a model of spiking bipolar cells (BCs) in the magnocellular pathway of the primate retina, diffuse BC subtypes (DB4), and utilized our multiscale admittance method (AM)-NEURON computational platform to characterize the response of BCs to epiretinal electrical stimulation with monophasic, symmetric, and asymmetric biphasic pulses.Main results. Our investigations yielded four notable results: (a) the latency of BCs increases as stimulation pulse duration lengthens; conversely, this latency decreases as the current amplitude increases. (b) Stimulation with a long anodic-first symmetric biphasic pulse (duration > 8 ms) results in a significant decrease in spiking threshold compared to stimulation with similar cathodic-first pulses (from 98.2 to 57.5µA). (c) The hyperpolarization-activated cyclic nucleotide-gated channel was a prominent contributor to the reduced threshold of BCs in response to long anodic-first stimulus pulses. (d) Finally, extending the study to asymmetric waveforms, our results predict a lower BCs threshold using asymmetric long anodic-first pulses compared to that of asymmetric short cathodic-first stimulation.Significance. This study predicts the effects of several stimulation parameters on spiking BCs response to electrical stimulation. Of importance, our findings shed light on mechanisms underlying the experimental observations from the literature, thus highlighting the capability of the methodology to predict and guide the development of electrical stimulation protocols to generate a desired biological response, thereby constituting an ideal testbed for the development of electroceutical devices.

A Computational Model Simulates Light-Evoked Responses in the Retinal Cone Pathway

Partial vision restoration on degenerated retina can be achieved by electrically stimulating the surviving retinal ganglion cells via implanted electrodes to elicit a signal corresponding to the natural response of the cells. Realistic computational models of electrical stimulation of the retina can prove useful to test different stimulation strategies and improve the performance of retinal implants. Simulation of healthy retinal networks and their dynamical response to natural light stimulation may also help us understand how retinal processing takes place via a series of electrical signals flowing through different stages of retinal processing, ultimately giving rise to visual percepts. Such models may provide further insights on retinal network processing and thus guide the design of retinal prostheses and their stimulation protocols to generate more natural percepts. This work aims to characterize the photocurrent generated by healthy cone photoreceptors in response to a light flash stimulation and the resulting membrane potential for the photoreceptors and its postsynaptic cone bipolar cells. A simple network of ten cone photoreceptors synapsing with a cone bipolar cell is simulated using the NEURON environment and validated against patch-clamp recordings of cone photoreceptors and ON-type bipolar cells (ON-BC). The results presented will be valuable in modeling light-evoked or electrically stimulated retinal networks that comprise cone pathways. The computational models and methods developed in this work will serve as an integral building block in the development of large and realistic retinal networks.Clinical Relevance- Accurate computational model of a retinal neural network can help in predicting cell responses to electrical stimulation in vision restoration therapies using prostheses. It can be leveraged to optimize the stimulation parameters to match the natural light response of the network as closely as possible.

Modeling ON Cone Bipolar Cells for Electrical Stimulation

Retinal prosthetic systems have been developed to help blind patients suffering from retinal degenerative diseases gain some useful form of vision. Various experimental and computational studies have been performed to test electrical stimulation strategies that can improve the performance of these devices. Detailed computational models of retinal neurons, such as retinal ganglion cells (RGCs) and bipolar cells (BCs), allow us to explore the mechanisms underlying the response of cells to electrical stimulation. While electrophysiological studies have shown the presence of voltage-gated ionic channels in different regions of BCs, many of the existing cone BCs models are assumed to be passive or only contain calcium channels at the synaptic terminals. We have utilized our Admittance Method (AM)-NEURON computational platform to implement a more realistic model of ON-BCs. Our model closely replicates the recent patch-clamp experiments directly measuring the response of ON-BCs to epiretinal electrical stimulation and thereby predicts the regional distributions of the ionic channels. Our computational results further indicate that outward potassium current strongly contributes to the depolarizing voltage transient of ON-BCs in response to electrical stimulation.

The role of gap junctions in cell death and neuromodulation in the retina

Vision altering diseases, such as glaucoma, diabetic retinopathy, age-related macular degeneration, myopia, retinal vascular disease, traumatic brain injuries and others cripple many lives and are projected to continue to cause anguish in the foreseeable future. Gap junctions serve as an emerging target for neuromodulation and possible regeneration as they directly connect healthy and/or diseased cells, thereby playing a crucial role in pathophysiology. Since they are permeable for macromolecules, able to cross the cellular barriers, they show duality in illness as a cause and as a therapeutic target. In this review, we take recent advancements in gap junction neuromodulation (pharmacological blockade, gene therapy, electrical and light stimulation) into account, to show the gap junction's role in neuronal cell death and the possible routes of rescuing neuronal and glial cells in the retina succeeding illness or injury.

The effect of axon trajectory on retinal ganglion cell activation with epiretinal stimulation

For epiretinal prostheses, disc electrodes stimulate retinal ganglion cells (RGCs) with electric current to create visual percepts. Prior studies have determined that the sodium channel band (SOCB), located on the RGC axon (30-50 μm from the soma) is the most sensitive site to extracellular stimulation because of its high sodium channel density. Biophysical cable models used to study RGC activation in silico often rely on simplified axon trajectories, disregarding the non-uniform paths that axons follow to the optic disc. However, since axonal activation is a critical mechanism in epiretinal stimulation, it is important to investigate variable RGC axon trajectories. In this study, we use a computational model to perform a sensitivity analysis examining how the morphology of an RGC axon affects predictions of retinal activation. We determine that RGC cable models are sensitive to changes in the ascending axon trajectory between the soma and nerve fiber layer. On the other hand, RGC cable models are relatively robust to trajectory deviations in the plane parallel to the disc electrode's surface. Overall, our results suggest that incorporating natural variations of soma depth and nerve fiber layer entry angle could result in a more realistic model of the retina's response to epiretinal stimulation and a better understanding of elicited visual percepts.

Model-based comparison of current flow in rod bipolar cells of healthy and early-stage degenerated retina

Retinal degenerative diseases, such as retinitis pigmentosa, are generally thought to initiate with the loss of photoreceptors, though recent work suggests that plasticity and remodeling occurs prior to photoreceptor cell loss. This degeneration subsequently leads to death of other retinal neurons, creating functional alterations and extensive remodeling of retinal networks. Retinal prosthetic devices stimulate the surviving retinal cells by applying external current using implanted electrodes. Although these devices restore partial vision, the quality of restored vision is limited. Further knowledge about the precise changes in degenerated retina as the disease progresses is essential to understand how current flows in retinas undergoing degenerative disease and to improve the performance of retinal prostheses. We developed computational models that describe current flow from rod photoreceptors to rod bipolar cells (RodBCs) in the healthy and early-stage degenerated retina. Morphologically accurate models of retinal cells with their synapses are constructed based on retinal connectome datasets, created using serial section transmission electron microscopy (TEM) images of 70 nm-thick slices of either healthy (RC1) or early-stage degenerated (RPC1) rabbit retina. The passive membrane and active ion currents of each cell are implemented using conductance-based models in the Neuron simulation environment. In response to photocurrent input at rod photoreceptors, the simulated membrane potential at RodBCs in early degenerate tissue is approximately 10-20 mV lower than that of RodBCs of that observed in wild type retina. Results presented here suggest that although RodBCs in RPC1 show early, altered morphology compared to RC1, the lower membrane potential is primarily a consequence of reduced rod photoreceptor input to RodBCs in the degenerated retina. Frequency response and step input analyses suggest that individual cell responses of RodBCs in either healthy or early-degenerated retina, prior to substantial photoreceptor cell loss, do not differ significantly.

Color and cellular selectivity of retinal ganglion cell subtypes through frequency modulation of electrical stimulation

Epiretinal prostheses aim at electrically stimulating the inner most surviving retinal cells-retinal ganglion cells (RGCs)-to restore partial sight to the blind. Recent tests in patients with epiretinal implants have revealed that electrical stimulation of the retina results in the percept of color of the elicited phosphenes, which depends on the frequency of stimulation. This paper presents computational results that are predictive of this finding and further support our understanding of the mechanisms of color encoding in electrical stimulation of retina, which could prove pivotal for the design of advanced retinal prosthetics that elicit both percept and color. This provides, for the first time, a directly applicable "amplitude-frequency" stimulation strategy to "encode color" in future retinal prosthetics through a predictive computational tool to selectively target small bistratified cells, which have been shown to contribute to "blue-yellow" color opponency in the retinal circuitry. The presented results are validated with experimental data reported in the literature and correlated with findings in blind patients with a retinal prosthetic implant collected by our group.

Targeted Stimulation of Retinal Ganglion Cells in Epiretinal Prostheses: A Multiscale Computational Study

Retinal prostheses aim at restoring partial sight to patients that are blind due to retinal degenerative diseases by electrically stimulating the surviving healthy retinal neurons. Ideally, the electrical stimulation of the retina is intended to induce localized, focused, percepts only; however, some epiretinal implant subjects have reported seeing elongated phosphenes in a single electrode stimulation due to the axonal activation of retinal ganglion cells (RGCs). This issue can be addressed by properly devising stimulation waveforms so that the possibility of inducing axonal activation of RGCs is minimized. While strategies to devise electrical stimulation waveforms to achieve a focal RGCs response have been reported in literature, the underlying mechanisms are not well understood. This article intends to address this gap; we developed morphologically and biophysically realistic computational models of two classified RGCs: D1-bistratified and A2-monostratified. Computational results suggest that the sodium channel band (SOCB) is less sensitive to modulations in stimulation parameters than the distal axon (DA), and DA stimulus threshold is less sensitive to physiological differences among RGCs. Therefore, over a range of RGCs distal axon diameters, short-pulse symmetric biphasic waveforms can enhance the stimulation threshold difference between the SOCB and the DA. Appropriately designed waveforms can avoid axonal activation of RGCs, implying a consequential reduction of undesired strikes in the visual field.

Responsiveness of Retinal Ganglion Cells Through Frequency Modulation of Electrical Stimulation: A Computational Modeling Study

Electrical stimulation of surviving retinal neurons has proven effective in restoring sight to totally blind patients affected by retinal degenerative diseases. Morphological and biophysical differences among retinal ganglion cells (RGCs) are important factors affecting their response to epiretinal electrical stimulation. Although detailed models of ON and OFF RGCs have already been investigated, here we developed morphologically and biophysically realistic computational models of two classified RGCs, D1-bistratified and A2-monostratified, and analyzed their response to alternations in stimulation frequency (up to 200 Hz). Results show that the D1-bistratified cell is more responsive to high frequency stimulation compared to the A2-monostratified cell. This differential RGCs response suggests a potential avenue for selective activation, and in turn different encoded percept of RGCs.

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.

Stimulus waveform design for decreasing charge and increasing stimulation selectivity in retinal prostheses

Retinal degenerative diseases, such as retinitis pigmentosa, begin with damage to the photoreceptor layer of the retina. In the absence of presynaptic input from photoreceptors, networks of electrically coupled AII amacrine and cone bipolar cells have been observed to exhibit oscillatory behaviour and result in spontaneous firing of ganglion cells. This ganglion cell activity could interfere with external stimuli provided by retinal prosthetic devices and potentially degrade their performance. In this work, the authors computationally investigate stimulus waveform designs, which can improve the performance of retinal prostheses by suppressing undesired spontaneous firing of ganglion cells and generating precise temporal spiking patterns. They utilise a multi-scale computational model for electrical stimulation of degenerated retina based on the admittance method and NEURON simulation environments. They present a class of asymmetric biphasic pulses that can generate precise ganglion cell firing patterns with up to 55% lower current requirements compared to traditional symmetric biphasic pulses. This lower current results in activation of only proximal ganglion cells, provides more focused stimulation and lowers the risk of tissue damage.

Retinal Drug Delivery: Rethinking Outcomes for the Efficient Replication of Retinal Behavior

The retina is a highly organized structure that is considered to be "an approachable part of the brain." It is attracting the interest of development scientists, as it provides a model neurovascular system. Over the last few years, we have been witnessing significant development in the knowledge of the mechanisms that induce the shape of the retinal vascular system, as well as knowledge of disease processes that lead to retina degeneration. Knowledge and understanding of how our vision works are crucial to creating a hardware-adaptive computational model that can replicate retinal behavior. The neuronal system is nonlinear and very intricate. It is thus instrumental to have a clear view of the neurophysiological and neuroanatomic processes and to take into account the underlying principles that govern the process of hardware transformation to produce an appropriate model that can be mapped to a physical device. The mechanistic and integrated computational models have enormous potential toward helping to understand disease mechanisms and to explain the associations identified in large model-free data sets. The approach used is modulated and based on different models of drug administration, including the geometry of the eye. This work aimed to review the recently used mathematical models to map a directed retinal network.

A Patient-Specific Computational Framework for the Argus II Implant

Goal

Retinal prosthesis performance is limited by the variability of elicited phosphenes. The stimulating electrode's position with respect to retinal ganglion cells (RGCs) affects both perceptual threshold and phosphene shape. We created a modeling framework incorporating patient-specific anatomy and electrode location to investigate RGC activation and predict inter-electrode differences for one Argus II user.

Methods

We used ocular imaging to build a three-dimensional finite element model characterizing retinal morphology and implant placement. To predict the neural response to stimulation, we coupled electric fields with multi-compartment cable models of RGCs. We evaluated our model predictions by comparing them to patient-reported perceptual threshold measurements.

Results

Our model was validated by the ability to replicate clinical impedance and threshold values, along with known neurophysiological trends. Inter-electrode threshold differences in silico correlated with in vivo results.

Conclusions

We developed a patient-specific retinal stimulation framework to quantitatively predict RGC activation and better explain phosphene variations.

Stimulation strategies for selective activation of retinal ganglion cell soma and threshold reduction

OBJECTIVE

Retinal prosthetic implants restore partial vision to patients blinded due to outer retinal degeneration, using a camera-guided multielectrode array (MEA) that electrically stimulates surviving retinal neurons. Commercial epi-retinal prostheses use millisecond-scale charge-balanced, symmetric, cathodic-first biphasic pulses to depolarize retinal ganglion cells (RGCs) and bipolar cells (BCs), frequently creating oblong perceptions of light related to axonal activation of RGCs. Stimulation strategies that avoid axonal stimulation and decrease the threshold of targeted neurons may significantly improve prosthetic vision in terms of spatial resolution and power efficiency.

APPROACH

We developed a virus-transduced genetically encoded calcium indicator (GECI) GCaMP6f and microscopy platform for calcium imaging to record the neural activity from RGCs at single-cell resolution in wholemount retinas. Multiple stimulation paradigms were applied through a microelectrode array (MEA) with transparent indium tin oxide electrodes. The evoked neuronal activities were converted to corresponding 2D calcium imaging transient pattern and spatial threshold map to identify the ideal focal response which corresponds to optimal percept in patient.

MAIN RESULTS

The proposed optical system with GCaMP6f is capable of recording from population of mouse RGCs in real time during electrical stimulation with precise location information relative to the stimulation sites. Optimal duration and phase order of pulse were identified to avoid axonal stimulation and selectively activate targeted RGC somas, without requiring a significant increase in stimulation charge. Additionally, we show that reduced stimulus threshold can be achieved with the special design of asymmetric anodic-first pulse.

SIGNIFICANCE

Our findings support the possibility of manipulating the responses of RGCs through varying the stimulation waveform. Focal response can be achieved with relative short duration (⩽120 μs) pulses, and can be improved by reversing the standard phase order. The RGCs threshold can be significantly reduced by 33.3%-50% in terms of charge through applying hyperpolarizing pre-pulses with a 20:1 ratio (pre-pulse:stimulus pulse). The results support the future retinal prosthesis design that potentially forms more ideal shape perception with higher spatial resolution and power efficiency.