Visual Prosthesis: Interfacing Stimulating Electrodes with Retinal Neurons to Restore Vision

Abstract

The bypassing of degenerated photoreceptors using retinal neurostimulators is helping the blind to recover functional vision. Researchers are investigating new ways to improve visual percepts elicited by these means as the vision produced by these early devices remain rudimentary. However, several factors are hampering the progression of bionic technologies: the charge injection limits of metallic electrodes, the mechanical mismatch between excitable tissue and the stimulating elements, neural and electric crosstalk, the physical size of the implanted devices, and the inability to selectively activate different types of retinal neurons. Electrochemical and mechanical limitations are being addressed by the application of electromaterials such as conducting polymers, carbon nanotubes and nanocrystalline diamonds, among other biomaterials, to electrical neuromodulation. In addition, the use of synthetic hydrogels and cell-laden biomaterials is promising better interfaces, as it opens a door to establishing synaptic connections between the electrode material and the excitable cells. Finally, new electrostimulation approaches relying on the use of high-frequency stimulation and field overlapping techniques are being developed to better replicate the neural code of the retina. All these elements combined will bring bionic vision beyond its present state and into the realm of a viable, mainstream therapy for vision loss.

Probing and predicting ganglion cell responses to smooth electrical stimulation in healthy and blind mouse retina

“…One major challenge in bionic vision is the selective activation of different information channels such as the ON and the OFF channel 42,43 . In order to be able to evaluate whether RGCs belonging to these retinal processing pathways are differently affected by our stimulus, we classified RGCs from healthy retina as ON, OFF or ON-OFF based on their light response.…”

Probing and predicting ganglion cell responses to smooth electrical stimulation in healthy and blind mouse retina

“…2 g); however, the levels of reliability among above-threshold cells were comparable between rd10 and wt retina. One major challenge in bionic vision is the selective activation of different information channels such as the ON and the OFF channel 21,36 . In order to be able to evaluate whether RGCs pertaining to these retinal processing pathways are differently affected by our stimulus, we classified RGCs from healthy retina as ON, OFF or ON-OFF based on their light response.…”

“…Acuity of prosthesis-mediated vision therefore reaches only a fraction of healthy visual acuity, leaving patients legally blind despite wearing a retinal implant 20 . Another reason why bionic vision comes short of natural vision is that the image processing mechanisms of the intricate retinal network cannot be triggered selectively by retinal implants; pulsatile stimuli do not separately activate channels like the ON and the OFF pathway 21 . Different approaches have been suggested to tackle these problems, including sinusoidal stimulation as an alternative to pulsatile stimulation 22 .…”

Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics

“…While existing implants have been reported to provide basic vision [76][77][78] , they are far from perfect. For example, most current stimulation strategies likely activate OFF-and ON-pathways at the same time 79 . To this end, we created a simulation framework for subretinal electrical stimulation of retinal tissue with micro-electrode arrays.…”

“…While many experimental studies have explored different strategies of stimulation [95][96][97][98] , most of them are restricted to very specific stimulus types such as current or voltages pulses. As a consequence, retinal implants are not able to specifically target cell types such as the independent stimulation of the ON and OFF pathways of the retina 79,99,100 . To facilitate a systematic stimulus optimization in 25/34 silico, we developed a simulation framework for electrical stimulation of the retina.…”