Spatially Selective Retinal Ganglion Cell Activation Using Low Invasive Extraocular Temporal Interference Stimulation

Conventional retinal implants involve complex surgical procedures and require invasive implantation. Temporal Interference Stimulation (TIS) has achieved noninvasive and focused stimulation of deep brain regions by delivering high-frequency currents with small frequency differences on multiple electrodes. In this study, we conducted in silico investigations to evaluate extraocular TIS's potential as a novel visual restoration approach. Different from the previously published retinal TIS model, the new model of extraocular TIS incorporated a biophysically detailed retinal ganglion cell (RGC) population, enabling a more accurate simulation of retinal outputs under electrical stimulation. Using this improved model, we made the following major discoveries: (1) the maximum value of TIS envelope electric potential ([Formula: see text] showed a strong correlation with TIS-induced RGC activation; (2) the preferred stimulating/return electrode (SE/RE) locations to achieve focalized TIS were predicted; (3) the performance of extraocular TIS was better than same-frequency sinusoidal stimulation (SSS) in terms of lower RGC threshold and more focused RGC activation; (4) the optimal stimulation parameters to achieve lower threshold and focused activation were identified; and (5) spatial selectivity of TIS could be improved by integrating current steering strategy and reducing electrode size. This study provides insights into the feasibility and effectiveness of a low-invasive stimulation approach in enhancing vision restoration.

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.

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 retinal electric field distribution induced by different electrode design of trans-corneal electrical stimulation

OBJECTIVE

Trans-corneal electrical stimulation (TcES) produces therapeutic effects on many ophthalmic diseases non-invasively. Existing clinical TcES devices use largely variable design of electrode distribution and stimulation parameters. Better understanding of how electrode configuration paradigms and stimulation parameters influence the electric field distribution on the retina, will be beneficial to the design of next-generation TcES devices.

APPROACH

In this study, we constructed a realistic finite element human head model with fine eyeball structure. Commonly used DTL-Plus and ERG-Jet electrodes were simulated. We then conducted in silico investigations of retina observation surface (ROS) electric field distributions induced by different return electrode configuration paradigms and different stimulus intensities.

MAIN RESULTS

Our results suggested that the ROS electric field distribution could be modulated by re-designing TcES electrode settings and stimulus parameters. Under far return location (FRL) paradigms, either DTL-Plus or ERG-Jet approach could induce almost identical ROS electric field distribution regardless where the far return was located. However, compared with the ERG-Jet mode, DTL-Plus stimulation induced stronger nasal lateralization. In contrast, ERG-Jet stimulation induced relatively stronger temporal lateralization. The ROS lateralization can be further tweaked by changing the DTL-Plus electrode length.

SIGNIFICANCE

These results may contribute to the understanding of the characteristics of DTL-Plus and ERG-Jet electrodes based electric field distribution on the retina, providing practical implications for the therapeutic application of TcES.

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. ..

Microelectrode Array With Integrated Pneumatic Channels for Dynamic Control of Electrode Position in Retinal Implants

Retinal prostheses are biomedical devices that directly utilize electrical stimulation to create an artificial vision to help patients with retinal diseases such as retinitis pigmentosa. A major challenge in the microelectrode array (MEA) design for retinal prosthesis is to have a close topographical fit on the retinal surface. The local retinal topography can cause the electrodes in certain areas to have gaps up to several hundred micrometers from the retinal surface, resulting in impaired, or totally lost electrode functions in specific areas of the MEA. In this manuscript, an MEA with dynamically controlled electrode positions was proposed to reduce the electrode-retina distance and eliminate areas with poor contact after implantation. The MEA prototype had a polydimethylsiloxane and polyimide hybrid flexible substrate with gold interconnect lines and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate electrodes. Ring shaped counter electrodes were placed around the main electrodes to measure the distance between the electrode and the model retinal surface in real time. The results showed that this MEA design could reduce electrode-retina distance up to [Formula: see text] with 200 kPa pressure. Meanwhile, the impedance between the main and counter electrodes increased with smaller electrode-model retinal surface distance. Thus, the change of electrode-counter electrode impedance could be used to measure the separation gap and to confirm successful electrode contact without the need of optical coherence tomography scan. The amplitude of the stimulation signal on the model retinal surface with originally poor contact could be significantly improved after pressure was applied to reduce the gap.

Compositional and morphological properties of platinum-iridium electrodeposited on carbon fiber microelectrodes

Objective. Neural interfaces based on carbon fiber (CF) electrodes have demonstrated key positive attributes such as minimal foreign body response and mechanical strength to self-insert in brain tissue. However, carbon does not form a low impedance electrode interface with neural tissue. Electrodeposited platinum iridium (PtIr) has been used to improve electrode interface properties for metallic bioelectrodes.Approach. In this study, a PtIr electrodeposition process has been performed on CF microelectrode arrays to improve the interfacial properties of these arrays. We study the film morphology and composition as well as electrode durability and impedance.Results. A PtIr coating with a composition of 70% Pt, 30% Ir and a thickness of ∼400 nm was observed. Pt and Ir were evenly distributed within the film. Impedance was decreased by 89% @ 1 kHz. Accelerated soak testing in a heated (T= 50∘C) saline solution showed impedance increase (@ 1 kHz) of ∼12% after 36 days (89 equivalent) of soaking.

Optimization of Model Training Based on Iterative Minimum Covariance Determinant In Motor-Imagery BCI

The common spatial patterns (CSP) algorithm is one of the most frequently used and effective spatial filtering methods for extracting relevant features for use in motor imagery brain-computer interfaces (MI-BCIs). However, the inherent defect of the traditional CSP algorithm is that it is highly sensitive to potential outliers, which adversely affects its performance in practical applications. In this work, we propose a novel feature optimization and outlier detection method for the CSP algorithm. Specifically, we use the minimum covariance determinant (MCD) to detect and remove outliers in the dataset, then we use the Fisher score to evaluate and select features. In addition, in order to prevent the emergence of new outliers, we propose an iterative minimum covariance determinant (IMCD) algorithm. We evaluate our proposed algorithm in terms of iteration times, classification accuracy and feature distribution using two BCI competition datasets. The experimental results show that the average classification performance of our proposed method is 12% and 22.9% higher than that of the traditional CSP method in two datasets ([Formula: see text]), and our proposed method obtains better performance in comparison with other competing methods. The results show that our method improves the performance of MI-BCI systems.

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.

Computational Modeling of Spatially Selective Retinal Stimulation With Temporally Interfering Electric Fields

Retinal electrical stimulation is a widely utilized method to restore visual function for patients with retinal degenerative diseases. Transcorneal electrical stimulation (TES) represents an effective way to improve the visual function due to its potential neuroprotective effect. However, TES with single electrode fails to spatially and selectively stimulate retinal neurons. Herein, a computational modeling method was proposed to explore the feasibility of spatially selective retinal stimulation via temporally interfering electric fields. An eyeball model with multiple electrodes was constructed to simulate the interferential electric fields with various electrode montages and current ratios. The results demonstrated that the temporal interference (TI) stimulation would gradually generate an increasingly localized high-intensity region on retina as the return electrodes moved towards the posterior of the eyeball and got closer. Additionally, the position of the convergent region could be modulated by regulating the current ratio of different electrode channels. The TI strategy with multisite and steerable stimulation can stimulate local retinal region with certain convergence and a relatively large stimulation range, which would be a feasible approach for the spatially selective retinal neuromodulation.

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 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.