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Closed-Loop Efficient Searching of Optimal Electrical Stimulation Parameters for Preferential Excitation of Retinal Ganglion Cells

Authors :
Tianruo Guo
Chih Yu Yang
David Tsai
Madhuvanthi Muralidharan
Gregg J. Suaning
John W. Morley
Socrates Dokos
Nigel H. Lovell
Source :
Frontiers in Neuroscience, Vol 12 (2018)
Publication Year :
2018
Publisher :
Frontiers Media S.A., 2018.

Abstract

The ability for visual prostheses to preferentially activate functionally-distinct retinal ganglion cells (RGCs) is important for improving visual perception. This study investigates the use of high frequency stimulation (HFS) to elicit RGC activation, using a closed-loop algorithm to search for optimal stimulation parameters for preferential ON and OFF RGC activation, resembling natural physiological neural encoding in response to visual stimuli. We evaluated the performance of a wide range of electrical stimulation amplitudes and frequencies on RGC responses in vitro using murine retinal preparations. It was possible to preferentially excite either ON or OFF RGCs by adjusting amplitudes and frequencies in HFS. ON RGCs can be preferentially activated at relatively higher stimulation amplitudes (>150 μA) and frequencies (2–6.25 kHz) while OFF RGCs are activated by lower stimulation amplitudes (40–90 μA) across all tested frequencies (1–6.25 kHz). These stimuli also showed great promise in eliciting RGC responses that parallel natural RGC encoding: ON RGCs exhibited an increase in spiking activity during electrical stimulation while OFF RGCs exhibited decreased spiking activity, given the same stimulation amplitude. In conjunction with the in vitro studies, in silico simulations indicated that optimal HFS parameters could be rapidly identified in practice, whilst sampling spiking activity of relevant neuronal subtypes. This closed-loop approach represents a step forward in modulating stimulation parameters to achieve appropriate neural encoding in retinal prostheses, advancing control over RGC subtypes activated by electrical stimulation.

Details

Language :
English
ISSN :
1662453X
Volume :
12
Database :
Directory of Open Access Journals
Journal :
Frontiers in Neuroscience
Publication Type :
Academic Journal
Accession number :
edsdoj.3624bef495254df1a4a19fc2b30fb721
Document Type :
article
Full Text :
https://doi.org/10.3389/fnins.2018.00168