End-to-end Learning of Safe Stimulation Parameters for Cortical Neuroprosthetic Vision

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发表在:bioRxiv (Jan 26, 2025)
主要作者: Küçükoğlu, Burcu
其他作者: Rueckauer, Bodo, Jaap De Ruyter Van Steveninck, Van Der Grinten, Maureen, Güçlütürk, Yağmur, Roelfsema, Pieter R, Güçlü, Umut, Marcel Van Gerven
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Cold Spring Harbor Laboratory Press
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001 3159906414
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022 |a 2692-8205 
024 7 |a 10.1101/2025.01.23.634543  |2 doi 
035 |a 3159906414 
045 0 |b d20250126 
100 1 |a Küçükoğlu, Burcu 
245 1 |a End-to-end Learning of Safe Stimulation Parameters for Cortical Neuroprosthetic Vision 
260 |b Cold Spring Harbor Laboratory Press  |c Jan 26, 2025 
513 |a Working Paper 
520 3 |a Direct electrical stimulation of the brain via cortical visual neuroprostheses is a promising approach to restore basic sight for the visually impaired by inducing a percept of localized light called 'phosphenes'. Apart from the challenge of condensing complex sensory information into meaningful stimulation patterns at low temporal and spatial resolution, providing safe stimulation levels to the brain is crucial. We propose an end-to-end framework to learn optimal stimulation parameters (amplitude, pulse width and frequency) within safe biological constraints. The learned stimulation parameters are passed to a biologically plausible phosphene simulator which takes into account the size, brightness, and temporal dynamics of perceived phosphenes. Our experiments on naturalistic navigation videos demonstrate that constraining stimulation parameters to safe levels not only maintains task performance in image reconstruction from phosphenes but consistently results in more meaningful phosphene vision, while providing insights into the optimal range of stimulation parameters. Our study presents a stimulus-generating encoder that learns stimulation parameters (1) satisfying safety constraints, and (2) maximizing the combined objective of image reconstruction and phosphene interpretability with a highly realistic phosphene simulator accounting for temporal dynamics of stimulation. End-to-end learning of stimulation parameters this way enables enforcement of critical biological safety constraints as well as technical limits of the hardware at hand.Competing Interest StatementThe authors have declared no competing interest. 
653 |a Phosphenes 
653 |a Vision 
653 |a Image processing 
653 |a Visual discrimination learning 
653 |a Visual stimuli 
653 |a Prosthetics 
653 |a Electrical stimulation of the brain--ESB 
653 |a Spatial discrimination learning 
653 |a Electrical stimuli 
700 1 |a Rueckauer, Bodo 
700 1 |a Jaap De Ruyter Van Steveninck 
700 1 |a Van Der Grinten, Maureen 
700 1 |a Güçlütürk, Yağmur 
700 1 |a Roelfsema, Pieter R 
700 1 |a Güçlü, Umut 
700 1 |a Marcel Van Gerven 
773 0 |t bioRxiv  |g (Jan 26, 2025) 
786 0 |d ProQuest  |t Biological Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3159906414/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u https://www.biorxiv.org/content/10.1101/2025.01.23.634543v1