Characterizing Retinal Ganglion Cell Responses to Electrical Stimulation Using Generalized Linear Models.

The ability to preferentially stimulate different retinal pathways is an important area of research for improving visual prosthetics. Recent work has shown that different classes of retinal ganglion cells (RGCs) have distinct linear electrical input filters for low-amplitude white noise stimulation. The aim of this study is to provide a statistical framework for characterizing how RGCs respond to white-noise electrical stimulation.

Optimal voltage stimulation parameters for network-mediated responses in wild type and rd10 mouse retinal ganglion cells.

To further improve the quality of visual percepts elicited by microelectronic retinal prosthetics, substantial efforts have been made to understand how retinal neurons respond to electrical stimulation. It is generally assumed that a sufficiently strong stimulus will recruit most retinal neurons. However, recent evidence has shown that the responses of some retinal neurons decrease with excessively strong stimuli (a non-monotonic response function).

Energetics based spike generation of a single neuron: simulation results and analysis.

Existing current based models that capture spike activity, though useful in studying information processing capabilities of neurons, fail to throw light on their internal functioning. It is imperative to develop a model that captures the spike train of a neuron as a function of its intracellular parameters for non-invasive diagnosis of diseased neurons. This is the first ever article to present such an integrated model that quantifies the inter-dependency between spike activity and intracellular energetics.