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A cascade model of information processing and encoding for retinal prosthesis
Retinal prosthesis offers a potential treatment for individuals suffering from photoreceptor degeneration diseases. Establishing biological retinal models and simulating how the biological retina convert incoming light signal into spike trains that can be properly decoded by the brain is a key issue...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4870925/ https://www.ncbi.nlm.nih.gov/pubmed/27212929 http://dx.doi.org/10.4103/1673-5374.180752 |
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author | Pei, Zhi-jun Gao, Guan-xin Hao, Bo Qiao, Qing-li Ai, Hui-jian |
author_facet | Pei, Zhi-jun Gao, Guan-xin Hao, Bo Qiao, Qing-li Ai, Hui-jian |
author_sort | Pei, Zhi-jun |
collection | PubMed |
description | Retinal prosthesis offers a potential treatment for individuals suffering from photoreceptor degeneration diseases. Establishing biological retinal models and simulating how the biological retina convert incoming light signal into spike trains that can be properly decoded by the brain is a key issue. Some retinal models have been presented, ranking from structural models inspired by the layered architecture to functional models originated from a set of specific physiological phenomena. However, Most of these focus on stimulus image compression, edge detection and reconstruction, but do not generate spike trains corresponding to visual image. In this study, based on state-of-the-art retinal physiological mechanism, including effective visual information extraction, static nonlinear rectification of biological systems and neurons Poisson coding, a cascade model of the retina including the out plexiform layer for information processing and the inner plexiform layer for information encoding was brought forward, which integrates both anatomic connections and functional computations of retina. Using MATLAB software, spike trains corresponding to stimulus image were numerically computed by four steps: linear spatiotemporal filtering, static nonlinear rectification, radial sampling and then Poisson spike generation. The simulated results suggested that such a cascade model could recreate visual information processing and encoding functionalities of the retina, which is helpful in developing artificial retina for the retinally blind. |
format | Online Article Text |
id | pubmed-4870925 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-48709252016-05-20 A cascade model of information processing and encoding for retinal prosthesis Pei, Zhi-jun Gao, Guan-xin Hao, Bo Qiao, Qing-li Ai, Hui-jian Neural Regen Res Research Article Retinal prosthesis offers a potential treatment for individuals suffering from photoreceptor degeneration diseases. Establishing biological retinal models and simulating how the biological retina convert incoming light signal into spike trains that can be properly decoded by the brain is a key issue. Some retinal models have been presented, ranking from structural models inspired by the layered architecture to functional models originated from a set of specific physiological phenomena. However, Most of these focus on stimulus image compression, edge detection and reconstruction, but do not generate spike trains corresponding to visual image. In this study, based on state-of-the-art retinal physiological mechanism, including effective visual information extraction, static nonlinear rectification of biological systems and neurons Poisson coding, a cascade model of the retina including the out plexiform layer for information processing and the inner plexiform layer for information encoding was brought forward, which integrates both anatomic connections and functional computations of retina. Using MATLAB software, spike trains corresponding to stimulus image were numerically computed by four steps: linear spatiotemporal filtering, static nonlinear rectification, radial sampling and then Poisson spike generation. The simulated results suggested that such a cascade model could recreate visual information processing and encoding functionalities of the retina, which is helpful in developing artificial retina for the retinally blind. Medknow Publications & Media Pvt Ltd 2016-04 /pmc/articles/PMC4870925/ /pubmed/27212929 http://dx.doi.org/10.4103/1673-5374.180752 Text en Copyright: © Neural Regeneration Research http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. |
spellingShingle | Research Article Pei, Zhi-jun Gao, Guan-xin Hao, Bo Qiao, Qing-li Ai, Hui-jian A cascade model of information processing and encoding for retinal prosthesis |
title | A cascade model of information processing and encoding for retinal prosthesis |
title_full | A cascade model of information processing and encoding for retinal prosthesis |
title_fullStr | A cascade model of information processing and encoding for retinal prosthesis |
title_full_unstemmed | A cascade model of information processing and encoding for retinal prosthesis |
title_short | A cascade model of information processing and encoding for retinal prosthesis |
title_sort | cascade model of information processing and encoding for retinal prosthesis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4870925/ https://www.ncbi.nlm.nih.gov/pubmed/27212929 http://dx.doi.org/10.4103/1673-5374.180752 |
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