A cascade model of information processing and encoding for retinal prosthesis  

作　　者：Zhi-jun Pei Guan-xin Gao Bo Hao Qing-li Qiao Hui-jian Ai 

机构地区：[1]Department of Clinical Engineering,Inner Mongolia Autonomous Region People's Hospital [2]School of Biomedical Engineering,Tianjin Medical University [3]School of Biomedical Engineering,Chongqing Medical University

出　　处：《Neural Regeneration Research》2016年第4期646-651,共6页中国神经再生研究（英文版）

基　　金：supported by the National Natural Science Foundation of China,No.30870649;the National Program on Key Basic Research Project of China (973 Program),No.2005CB724302

摘　　要：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 stateof-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.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 stateof-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.

关 键 词：nerve regeneration photoreceptor degeneration retinal prosthesis linear spatiotemporal filter static non-linear rectification spike trains Poisson spike generation synaptic transmission firing rate contrast gain control NSFC grants neural regeneration 

分 类 号：R774.1[医药卫生—眼科] R318.18[医药卫生—临床医学]