Activation of retinal ganglion cells using a biomimetic artificial retina

Advances in the application of smart materials in the treatment of ophthalmic diseases

Smart materials dynamically sense and respond to physiological signals like reactive oxygen species (ROS), pH, and light, surpassing traditional materials such as poly(lactic-co-glycolic acid), which have high drug loss rates and limited spatiotemporal control. These innovative materials offer new strategies for ophthalmic treatments, with core advantages including targeted delivery via ROS-sensitive nanocarriers, precise regulation through microvalves, and multifunctional integration, such as glucose-responsive contact lenses that create a "sensing-treatment" loop. However, challenges remain, like pathological microenvironment interference with material response specificity, and the need to address long-term biocompatibility and energy dependence issues. This article systematically examines three key treatment barriers: the blood-ocular barrier, immune rejection, and physiological fluctuations, while reviewing innovative smart material design strategies. Future research should focus on biomimetic interface engineering, for example, cornea mimicking nanostructures, AI-driven dynamic optimization like causal network-regulated drug release, and multidisciplinary approaches combining gene editing with smart materials. These efforts aim to shift from structural replacement to physiological function simulation, enabling precise treatment of ophthalmic diseases. Clinical translation must balance innovation with safety, prioritizing clinical value to ensure reliable, widespread application of smart materials in ophthalmology.

Exploring retinal ganglion cells encoding to multi-modal stimulation using 3D microelectrodes arrays

Microelectrode arrays (MEA) are extensively utilized in encoding studies of retinal ganglion cells (RGCs) due to their capacity for simultaneous recording of neural activity across multiple channels. However, conventional planar MEAs face limitations in studying RGCs due to poor coupling between electrodes and RGCs, resulting in low signal-to-noise ratio (SNR) and limited recording sensitivity. To overcome these challenges, we employed photolithography, electroplating, and other processes to fabricate a 3D MEA based on the planar MEA platform. The 3D MEA exhibited several improvements compared to planar MEA, including lower impedance (8.73 ± 1.66 kΩ) and phase delay (-15.11° ± 1.27°), as well as higher charge storage capacity (CSC = 10.16 ± 0.81 mC/cm2), cathodic charge storage capacity (CSCc = 7.10 ± 0.55 mC/cm2), and SNR (SNR = 8.91 ± 0.57). Leveraging the advanced 3D MEA, we investigated the encoding characteristics of RGCs under multi-modal stimulation. Optical, electrical, and chemical stimulation were applied as sensory inputs, and distinct response patterns and response times of RGCs were detected, as well as variations in rate encoding and temporal encoding. Specifically, electrical stimulation elicited more effective RGC firing, while optical stimulation enhanced RGC synchrony. These findings hold promise for advancing the field of neural encoding.

Progressive Retinal Degeneration Increases Cortical Response Latency of Light Stimulation but Not of Electric Stimulation

Purpose

The brain is known to change functionally and structurally in response to blindness, but less is known about the effects of restoration of cortical input on brain function. Here, we present a preliminary study to observe alterations in visual and electrical evoked cortical potentials as a function of age in a clinically relevant animal model of retinitis pigmentosa.

Methods

We recorded brain potentials elicited by light (visual evoked potentials [VEPs]) or corneal electrical stimulation (electrical evoked response [EER]) in retinal degenerate animal model LE-P23H-1. We used a linear mixed model to examine the effects of age on latency and amplitude of VEP and EER age groups P120, P180, and P360.

Results

VEP N1, P1, and N2 latency and amplitude were analyzed across animal age. For 1 Hz VEP, N1 latency increased significantly with animal age (slope = 0.053 ± 0.020 ms/day, P < 0.01). For 10 Hz VEP, N1, P1, and N2 latency increased significantly with animal age (slope = 0.104 ± 0.011, 0.135 ± 0.011, 0.087 ± 0.023 ms/day, and P < 0.001 for all VEP peaks). Conversely, EER latency did not change with age. Signal amplitude of VEP or EER did not change with age.

Conclusions

Cortical potentials evoked by electrical stimulation of the retina do not diminish in spite of continued retinal degeneration in P23H rats.

Translational Relevance

These findings suggest that retinal bioelectronic treatments of retinitis pigmentosa will activate cortex consistently despite variations in outer retinal degeneration. Clinical studies of retinal stimulation should consider varying retinitis pigmentosa genotypes as part of the experimental design.