Objective . 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 and stimulation strategies for next-generation wide-view, high-resolution epiretinal implants. Approach . 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 (5–210 µ m diameter), emulating both commercialized retinal implants and recently developed prototype devices. Main 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 analysis of variance (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. An empirical model: I = a · exp ( b · D ) + c of the stimulus amplitude ( I )–electrode diameter ( D ) relationship was constructed to achieve the pre-defined objective function values in different retinal regions, indicating the ability of controlling retinal outputs by fine-tuning the stimulation amplitude with different electrode sizes. Finally, our multielectrode simulations predicted differential neural crosstalk between adjacent electrodes in central temporal and peripheral temporal regions, providing insights towards establishing a non-uniformly distributed multielectrode array geometry for wide-view retinal implants. Significance. Stimulus–response properties in central and peripheral retina can provide useful information to estimate electrode parameters for region-specific activation by retinal stimulation. Our findings support the possibility of improving the performance of epiretinal prostheses by exploring the influence of electrode array geometry on activation of different retinal regions.

Objective. The spatial resolution of an implantable neural stimulator can be improved by creation of virtual channels (VCs). VCs are commonly achieved through synchronized stimulation of multiple electrodes. It remains unknown whether asynchronous stimulation is able to generate comparable VC performance in retinal stimulation, and how VC can be optimized by re-designing stimulation settings. This study begins with exploring the feasibility of creating VCs using synchronous and asynchronous epiretinal stimulation, and ending with predicting the possible VC performance with a thorough exploration of stimulation parameter space. Approach. A computational model of epiretinal dual-electrode stimulation is developed to simulate the neural activity of a population of retinal ganglion cells (RGCs) under both synchronous and asynchronous stimulation conditions. The interaction between the electrode and RGCs under a range of stimulation parameters are simulated. Main results. Our simulation based on direct RGC activation suggests that VCs can be created using asynchronous stimulation. Two VC performance measures: 1) linearity in the change in centroid location of activated RGC populations, and 2) consistency in the size of activated RGC populations, have comparable performance under asynchronous and synchronous stimulation with appropriately selected stimulation parameters. Significance. Our findings support the possibility of creating VCs by directly activating RGCs under synchronous and asynchronous stimulation conditions. This study establishes the fundamental capability of VC creation based on temporal interactions within the RGC population alone and does not include the effects of potential indirect activation of any surviving inner retinal network neurons. Our results provide theoretical evidence for designing next-generation retinal prosthesis with higher spatial resolution.

Temporal Interference Stimulation (TIS) is a low invasive technique for retinal modulation that utilizes the interference of high-frequency electric fields. Compared to conventional transcorneal electrical stimulation, TIS, by virtue of its enhanced depth penetration capabilities, enables selective modulation of deep-seated central retina, thereby establishing itself as a promising precise-therapeutic modality for diverse retinal pathologies. Clinically, retinal pathologies frequently coexist with concurrent lens pathologies. However, the functional efficacy of TIS in ocular systems with lens pathologies remains undocumented in current scientific literature. To explore intraocular electrical convergence under TIS, this study constructed multi-layered finite element models of normal aged and lens diseased human eyeball (NAE and LDE) with detailed anterior segment structures. The results firstly demonstrated a stable ground setting with compromising computational efficiency in NAE model. Subsequently, we found that lens lesions elevate the Lens Potential Convergence (LPC) up to 36.05% ± 0.06% (SD) of retinal potential levels in LDE model (compared with 28.10% ± 0.09% (SD) in NAE model as a reference). Using Axial Current Steering (ACS) by adjusting the current ratio between electrodes within paired channels, LPC was successfully reduced to 3.62% ± 0.01% (SD), accompanied by a 28% reduction in 90% retinal potential peak width surprisingly. This work elucidates the interference mechanisms of TIS targeting in enriched eye model and validates the effectiveness of the proposed ACS strategy, providing theoretical support for the future clinical application of TIS.

Visual prostheses aim to approximate biomimetic visual function by electrically simulating surviving retinal neurons. Improving the spatial resolution of electrically elicited artificial vision remains a critical challenge for retinal prostheses. We investigate how dynamic virtual channel (DVC) parameters shape retinal ganglion cell (RGC) population responses to improve spatial precision and activation efficiency in epiretinal stimulation. We developed a computational modeling framework to quantify DVC performance using a hierarchical optimization strategy. First, static virtual channels (SVCs) were used to map how current ratio (α) and stimulus intensity govern RGC activation, defining an optimal SVC parameter space. Building on this baseline, DVC protocols were refined by evaluating the combined effects of inter-virtual–channel interval (ΔT), α, and intensity. This strategy significantly reduces the complexity of DVC parameter optimization. Under SVC stimulation, increasing intensity improved the linearity of receptive field (RF) centroid displacement with α, while α and intensity jointly set RF centroid location and activated area. Under DVC stimulation, ΔT strongly modulated RGC activation, especially at short intervals. Initializing from SVC-optimized parameters, tuning ΔT and intensity produced more confined activation at lower stimulus intensities than SVC, indicating that DVC can serve as a novel stimulation strategy to enhance spatial precision and activation efficiency in retinal stimulation. This study provides the first systematic analysis of retinal DVC stimulation and a practical optimization framework for next-generation prostheses.