Understanding responses to multi-electrode epiretinal stimulation using a biophysical model.

Autor:	Vilkhu R; Electrical Engineering, Stanford University, 452 Lomita Mall, Stanford, California, 94305-6104, UNITED STATES., Vasireddy P; Electrical Engineering, Stanford University, 452 Lomita Mall, Stanford, California, 94305-6104, UNITED STATES., Kish KE; University of Michigan, 500 S State St., Ann Arbor, Michigan, 48109, UNITED STATES., Gogliettino AR; Stanford University, 452 Lomita Mall, Stanford, California, 94305-6104, UNITED STATES., Lotlikar A; Stanford, 452 Lomita Mall, Stanford, California, 94305-6104, UNITED STATES., Hottowy P; Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Al. Mickiewicza 30, Krakow, 30-059, POLAND., Dabrowski W; Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Al. Mickiewicza 30, Krakow, 30-059, POLAND., Sher A; University of California Santa Cruz, 1156 High St, Santa Cruz, California, 95064, UNITED STATES., Litke AM; Santa Cruz Institute for Particle Physics, 552 Red Hill Rd, Santa Cruz, California, 95064, UNITED STATES., Mitra S; Department of Electrical Engineering and Department of Computer Science, Stanford University, 353 JANE STANFORD WAY, Stanford, California, 94305, UNITED STATES., Chichilnisky EJ; Stanford University, 452 Lomita Mall, Stanford, California, 94305, UNITED STATES.
Jazyk:	angličtina
Zdroj:	Journal of neural engineering [J Neural Eng] 2024 Dec 20. Date of Electronic Publication: 2024 Dec 20.
DOI:	10.1088/1741-2552/ada1fe
Abstrakt:	Objective: Neural interfaces are designed to evoke specific patterns of electrical activity in populations of neurons by stimulating with many electrodes. However, currents passed simultaneously through multiple electrodes often combine nonlinearly to drive neural responses, making evoked responses difficult to predict and control. This response nonlinearity could arise from the interaction of many excitable sites in each cell, any of which can produce a spike. However, this multi-site activation hypothesis is difficult to verify experimentally. Approach: We developed a biophysical model to study retinal ganglion cell (RGC) responses to multi-electrode stimulation and validated it using data collected from ex vivo preparations of the macaque retina using a microelectrode array (512 electrodes; 30µm pitch; 10µm diameter). Results: First, the model was validated by using it to reproduce essential empirical findings from single-electrode recording and stimulation, including recorded spike voltage waveforms at multiple locations and sigmoidal responses to injected current. Then, stimulation with two electrodes was modeled to test how the positioning of the electrodes relative to the cell affected the degree of response nonlinearity. Currents passed through pairs of electrodes positioned near the cell body or far from the axon (>40 µm) exhibited approximately linear summation in evoking spikes. Currents passed through pairs of electrodes close to the axon summed linearly when their locations along the axon were similar, and nonlinearly otherwise. Over a range of electrode placements, several localized spike initiation sites were observed, and the number of these sites covaried with the degree of response nonlinearity. Similar trends were observed for three-electrode stimuli. All of these trends in the simulation were consistent with experimental observations. Significance: These findings support the multi-site activation hypothesis for nonlinear activation of neurons, providing a biophysical interpretation of previous experimental results and potentially enabling more efficient use of multi-electrode stimuli in future neural implants. (© 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)
Databáze:	MEDLINE
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