A Biologically-Informed Computational Framework for Pathway-Specific Spiking Patterns Generation and Efficacy Evaluation in Retinal Neurostimulators

Precise control of neuronal pathways is of critical importance for the efficacy of neuro-modulation prostheses designed to restore vision in patients with retinal degeneration. In this paper, a biologically-informed computational framework that enables generation and optimization of pathway-specific spiking patterns for retina ganglion cells (RGCs) is presented. The developed model is used to generate control signals for an implantable optical retinal neurostimulator device to modulate genetically-modified RGCs, thus enable cell-type-specific neural excitation. The model is also used to compare electrical and optical neuro-stimulations with respect to the quality of the visual perception they induce in the brain for the same visual stimulus. Our simulation results show that the type-specific activation of RGCs (an inherent advantage of optogenetics) makes optical stimulation significantly more effective than electrical stimulation in achieving high structural similarity between the visual stimulus and the estimated perception. The effect of increasing /-Lelectrode//-LLED array density to achieve a better performance in terms of the induced visual perception quality by optical and electrical stimulations was also studied using the developed model. The superiority of optical stimulation in this aspect was demonstrated through simulation results.