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Precise control of neural activity using dynamically optimized electrical stimulation

delete2024-11-07
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OA
AI
N
Nishal P. Shah *
A
AJ Phillips *
S
Sasidhar Madugula
A
Amrith Lotlikar
A
Alex Gogliettino
M
Madeline Hays
L
Lauren E. Grosberg
J
Jeff Brown
A
Aditya Dusi
P
Pulkit Tandon
P
Paweł Hottowy
W
W. Dąbrowski
A
Alexander Sher
A
A. M. Litke
S
Subhasish Mitra
E
E. J. Chichilnisky
DOI:10.7554/eLife.83424delete
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摘要

摘要

En 中文
Neural implants have the potential to restore lost sensory function by electrically evoking the complex naturalistic activity patterns of neural populations. However, it can be difficult to predict and control evoked neural responses to simultaneous multi-electrode stimulation due to nonlinearity of the responses. We present a solution to this problem and demonstrate its utility in the context of a bidirectional retinal implant for restoring vision. A dynamically optimized stimulation approach encodes incoming visual stimuli into a rapid, greedily chosen, temporally dithered and spatially multiplexed sequence of simple stimulation patterns. Stimuli are selected to optimize the reconstruction of the visual stimulus from the evoked responses. Temporal dithering exploits the slow time scales of downstream neural processing, and spatial multiplexing exploits the independence of responses generated by distant electrodes. The approach was evaluated using an experimental laboratory prototype of a retinal implant: large-scale, high-resolution multi-electrode stimulation and recording of macaque and rat retinal ganglion cells ex vivo. The dynamically optimized stimulation approach substantially enhanced performance compared to existing approaches based on static mapping between visual stimulus intensity and current amplitude. The modular framework enabled parallel extensions to naturalistic viewing conditions, incorporation of perceptual similarity measures, and efficient implementation for an implantable device. A direct closed-loop test of the approach supported its potential use in vision restoration.
Keyword:
sensory prosthesis
electrical stimulation
brain-computer interface
retina

期刊

eLife 封面图
eLife
IF:
0
论文数:
1.8W
被引数:
16

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AGH University of Krakow
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9.2K
论文数: 9.4K
被引数: 1.2W
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Stanford University
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9.6W
论文数: 8.2W
被引数: 17.0W
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University of California System
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37.7W
论文数: 33.8W
被引数: 6.6K
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