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A Model of Information Processing in the Retina
Author: PeiZhiJun
Tutor: QiaoQingLi
School: Tianjin Medical University
Course: Biomedical Engineering
Keywords: Retina Spatio-temporal filter Nonlinear static rectification Sampling Poisson spike occurs
CLC: R318.04
Type: Master's thesis
Year: 2011
Downloads: 28
Quote: 0
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Abstract
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Objective: visual prosthesis directly stimulate microelectrode array structure as the path on the important input of outside information for the blind. Retinal information processing model can replace the biological retina, the image will stimulate driven stimulating electrode array into spike sequence for to carry effective visual information is a necessary part of the visual prosthesis research. In this paper, the theoretical analysis of retinal electrical stimulation signal flow generated visual perception and at all stages of the transfer function, retinal bionic model input simulation and static grayscale images. Solve the input to the visual center of what information, how effective input information, to neural computing support for the design and development of practical implantable visual Microelectronic Systems. Methods: In this study, starting the retina from known physiological mechanism: visual neurons function contact mainly occurs in the synaptic layer. The outer plexiform layer and the inner plexiform layer as two separate information processing unit, to create a two-layer structure of the retina information processing model, and on the Matlab platform static grayscale image as an input for simulation studies. Outer plexiform layer of visual information extraction. Neuron receptive field characteristics of: - surrounding structure, spatial distribution and time trajectory. Central and peripheral signals corresponding to different linear spatio-temporal filter, the spatial component of the model is a Gaussian function, the time component cascade exponential function, ultimately by the bipolar cell layer integration antagonistic signal of the central and peripheral signals. 2 of the inner plexiform layer visual information coding. To characterize the the nonlinear modulation functions of the human visual system, using a simplified synaptic transfer function external stimulation intensity discharge rate; in simple homogeneous Poisson model joined neuron spike refractory period for neuronal firing Feng Feng interval, the final spike sequence to pass effective visual information. Provided by Matlab graphical user interface integrated development environment GUIDE, according to the type of model structure and its function to achieve, the design and development of graphical user interface. Results: 1. Established retinal outer plexiform layer model can realize the visual information extraction, clear edge contour contrast information; mathematical model of the inner plexiform layer visual information coding, access to the sequence of the spike passes visual information. Input static grayscale image processing time and space by the outer plexiform layer filtering model, compared to traditional spatial difference of Gaussian model, the edge of the image information has been retained at the same time a large area of ??luminance contrast information also to some extent been retained. Enter the static grayscale images, the outer plexiform layer central excitatory signal and peripheral inhibitory signal relative weights ω = 0.95, the clear edge contour contrast information can be obtained. 4 the static nonlinearity rectified function of the inner plexiform layer, different brightness different scaling factors, is consistent with the other experimental results. Graphical user interface: The main interface displays the system name and Features; stimulus image loading times the interface four sub module in turn achieve spatial and temporal filtering, static nonlinear adjustment, non-uniform radial sampling and Poisson spike sequence, which will eventually The points of light flashing animated simulation shows the discharge process of retinal ganglion cells. Conclusions: 1. This thesis is built on top of in Matlab7.7 simulation platform for retinal information processing model, the application of the model can be the complete simulation retinal static visual information processing function. The outer plexiform layer spatial and temporal filtering model to achieve the extraction of low-level visual elements, compared with the traditional difference of Gaussian model, at the same time retain the high spatial frequency components of the visual image, but also to some extent better low spatial visual images reserved frequency components. Sigmoid nonlinear static rectifier function, the non-linear characteristics of the biological visual system fit to ensure that the discharge rate of retinal ganglion cells kept within reasonable limits. 4. Graphical user interface parameter settings, dynamic simulation in one set, for the majority of clinical scientists to provide a convenient way to interact. Keywords: retinal spatio-temporal filter static nonlinear rectifying sampling Poisson spike
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