ReviewFrontiers in cellular neuroscience2022
Artificial Visual Information Produced by Retinal Prostheses.
Review in Frontiers in cellular neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Machine Learning Techniques for Simulating Human Psychophysical Testing of Low-Resolution Phosphene Face Images in Artificial Vision.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Review
- Quantitative analyses of how optimally heterogeneous neural codes maximize neural information in jittery transmission environments.Scientific reports · 2024Article
- Electrically-evoked responses for retinal prostheses are differentially altered depending on ganglion cell types in outer retinal neurodegeneration caused byFrontiers in cellular neuroscience · 2023Article
- Potential therapeutic strategies for photoreceptor degeneration: the path to restore vision.Journal of translational medicine · 2022Review
- Structure-Function Relationship in Patients with Retinitis Pigmentosa and Hyperautofluorescent Rings.Journal of clinical medicine · 2022Article
- Ultrasound stimulation for non-invasive visual prostheses.Frontiers in cellular neuroscience · 2022Review
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Authors and funding
3 authors.
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Abstract
Numerous retinal prosthetic systems have demonstrated somewhat useful vision can be restored to individuals who had lost their sight due to outer retinal degenerative diseases. Earlier prosthetic studies have mostly focused on the confinement of electrical stimulation for improved spatial resolution and/or the biased stimulation of specific retinal ganglion cell (RGC) types for selective activation of retinal ON/OFF pathway for enhanced visual percepts. To better replicate normal vision, it would be also crucial to consider information transmission by spiking activities arising in the RGC population since an incredible amount of visual information is transferred from the eye to the brain. In previous studies, however, it has not been well explored how much artificial visual information is created in response to electrical stimuli delivered by microelectrodes. In the present work, we discuss the importance of the neural information for high-quality artificial vision. First, we summarize the previous literatures which have computed information transmission rates from spiking activities of RGCs in response to visual stimuli. Second, we exemplify a couple of studies which computed the neural information from electrically evoked responses. Third, we briefly introduce how information rates can be computed in the representative two ways - direct method and reconstruction method. Fourth, we introduce
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