中国神经再生研究(英文版) ›› 2016, Vol. 11 ›› Issue (4): 646-651.doi: 10.4103/1673-5374.180752

• 原著:视神经损伤修复保护与再生 • 上一篇    下一篇

一个新的双突触层级联视网膜模型的构建

  

  • 收稿日期:2015-07-22 出版日期:2016-04-30 发布日期:2016-04-30
  • 基金资助:

    国家自然科学基金(30870649);973项目(2005CB724302)

A cascade model of information processing and encoding for retinal prosthesis

Zhi-jun Pei1, Guan-xin Gao1, Bo Hao1, Qing-li Qiao2, *, Hui-jian Ai3   

  1. 1 Department of Clinical Engineering, Inner Mongolia Autonomous Region People’s Hospital, Hohhot, Inner Mongolia Autonomous Region, China
    2 School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
    3 School of Biomedical Engineering, Chongqing Medical University, Chongqing, China
  • Received:2015-07-22 Online:2016-04-30 Published:2016-04-30
  • Contact: Qing-li Qiao, Ph.D., qiaotijmu@163.com.
  • Supported by:

    This study was 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:

视网膜假体植入是视网膜感光细胞退化疾病致盲患者部分或全部恢复视觉的潜在治疗手段。建立生物视网膜模型,仿真实现其信息处理与编码功能,将入射光刺激转化为携带有效视觉信息的锋电位序列,是视网膜假体研究发展中的关键问题与重要组成部分。文章从已知的视网膜有效视觉信息提取、生物系统静态非线性调整及神经元泊松编码机制出发,整合视网膜的生物解剖连接和功能运算特征,建立一个视网膜信息处理与编码的双突触层级联模型,并在MATLAB平台上进行仿真观察,其中外网状层通过线性时空滤波实现视觉信息处理;内网状层通过静态非线性调整、径向非均匀采样及泊松锋电位发生实现视觉信息编码。结果证实,视网膜信息处理与编码的双突触层级联模型的外网状层可实现视觉信息处理,得到对比度良好的清晰边缘轮廓图像;内网状层可实现视觉信息编码,得到传递有效视觉信息的稀疏锋电位序列,可能为失明患者人工视网膜病治疗提供了参考依据。

orcid: 0000-0002-1851-0354 (Qing-li Qiao)

关键词: 视神经变性, 视网膜假体, 线性时空滤波, 静态非线性校正, 棘突列车, 泊松棘代, 突触传递, 放电率, 对比度增益控制

Abstract:

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.

Key words: 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