Selective neuromodulation of retinal ganglion cells via a hybrid optic-nerve and retinal neuroprosthesis for visual restoration.

A visual neuroprosthesis delivers electrical stimulation to the surviving neural cells of the visual pathway to produce prosthetic vision. While the retina is often chosen as the stimulation site, current retinal prostheses are hindered by the lack of functional selectivity that impairs the resolution. A possible strategy to improve the resolution is to combine the retinal stimulation and the stimulation of the optic nerve bundle, which contains myelinated fibres of retinal ganglion cells (RGCs) axons that vary in diameter. In this study, we used a computational model of retinal ganglion cells (RGCs) with myelinated axons to predict whether the frequency of electrical stimulation delivered to the optic nerve can be modulated to preferentially inhibit a subset of optic nerve fibres classified by diameter. The model combined a finite element model of bipolar penetrating electrodes delivering sinusoidal stimulation in the range of 25-10000 Hz to the optic nerve, and a double-cable model, to represent an optic nerve fibre. We found that the diameter of the axon fibre and ion kinetic properties of the RGC affect the neuron's frequency response, demonstrating the potential of an optic nerve stimulation to produce selective inhibition based on the axon fibre size. Clinical Relevance-This establishes the importance of considering the size of the nerve cell axons, as well as the functional type of the RGC, in stimulating the optic nerve. This can be exploited to facilitate functionally selective neuromodulation when used in conjunction with retinal stimulation.

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches.

Computational modeling has become an increasingly important method in neural engineering due to its capacity to predict behaviors of in vivo and in vitro systems. This has the key advantage of minimizing the number of animals required in a given study by providing an often very precise prediction of physiological outcomes. In the field of visual prosthesis, computational modeling has an array of practical applications, including informing the design of an implantable electrode array and prediction of visual percepts that may be elicited through the delivery of electrical impulses from the said array. Some models described in the literature combine a three-dimensional (3D) morphology to compute the electric field and a cable model of the neuron or neural network of interest. To increase the accessibility of this two-step method to researchers who may have limited prior experience in computational modeling, we provide a video of the fundamental approaches to be taken in order to construct a computational model and utilize it in predicting the physiological and psychophysical outcomes of stimulation protocols deployed via a visual prosthesis. The guide comprises the steps to build a 3D model in a finite element modeling (FEM) software, the construction of a retinal ganglion cell model in a multi-compartmental neuron computational software, followed by the amalgamation of the two. A finite element modeling software to numerically solve physical equations would be used to solve electric field distribution in the electrical stimulations of tissue. Then, specialized software to simulate the electrical activities of a neural cell or network was used. To follow this tutorial, familiarity with the working principle of a neuroprosthesis, as well as neurophysiological concepts (e.g., action potential mechanism and an understanding of the Hodgkin-Huxley model), would be required.

Spatially selective activation of the visual cortex via intraneural stimulation of the optic nerve.

Retinal prostheses can restore a functional form of vision in patients affected by dystrophies of the outer retinal layer. Beyond clinical utility, prostheses for the stimulation of the optic nerve, the visual thalamus or the visual cortex could also serve as tools for studying the visual system. Optic-nerve stimulation is particularly promising because it directly activates nerve fibres, takes advantage of the high-level information processing occurring downstream in the visual pathway, does not require optical transparency and could be effective in cases of eye trauma. Here we show, in anaesthetized rabbits and with support from numerical modelling, that an intraneural electrode array with high mechanical stability placed in the intracranial segment of the optic nerve induces, on electrical stimulation, selective activation patterns in the visual cortex. These patterns are measured as electrically evoked cortical potentials via an ECoG array placed in the contralateral cortex. The intraneural electrode array should enable further investigations of the effects of electrical stimulation in the visual system and could be further developed as a visual prosthesis for blind patients.