Prediction of cortical responses to simultaneous electrical stimulation of the retina. (30th November 2016) - Halupka, Kerry J; Shivdasani, Mohit N; Cloherty, Shaun L; Grayden, David B; Wong, Yan T; Burkitt, Anthony N; Meffin, Hamish
Abstract: Objective. Simultaneous electrical stimulation of multiple electrodes has shown promise in diversifying the responses that can be elicited by retinal prostheses compared to interleaved single electrode stimulation. However, the effects of interactions between electrodes are not well understood and clinical trials with simultaneous stimulation have produced inconsistent results. We investigated the effects of multiple electrode stimulation of the retina by developing a model of cortical responses to retinal stimulation. Approach. Electrical stimuli consisting of temporally sparse, biphasic current pulses, with amplitudes sampled from a bi-dimensional Gaussian distribution, were simultaneously delivered to the retina across a 42-channel electrode array implanted in the suprachoroidal space of anesthetized cats. Visual cortex activity was recorded using penetrating microelectrode arrays. These data were used to identify a linear–nonlinear model of cortical responses to retinal stimulation. The ability of the model to generalize was tested by predicting responses to non-white patterned stimuli. Main results. The model accurately predicted two cortical activity measures: multi-unit neural responses and evoked potential responses to white noise stimuli. The model also provides information about electrical receptive fields, including the relative effects of each stimulating electrode on every recording site. Significance. We have demonstrated a simple model that accurately describes cortical responses to simultaneous stimulation of a suprachoroidal retinal prosthesis. Overall, our results demonstrate that cortical responses to simultaneous multi-electrode stimulation of the retina are repeatable and predictable, and that interactions between electrodes during simultaneous stimulation are predominantly linear. The model shows promise for determining optimal stimulation paradigms for exploiting interactions between electrodes to shape neural activity, thereby improving outcomes for patients with retinal prostheses.