Abstract：
OBJECTIVE: The electroretinogram (ERG) is the summed response from all levels of the retinal processing of light, and exhibits several profound nonlinearities in the underlying processing pathways. Accurate computational models of the ERG are important, both for understanding the multifold processes of light transduction to ecologically useful signals by the retina, and for their diagnostic capabilities for the identification and characterization of retinal disease mechanisms. There are, however, very few computational models of the ERG waveform, and none that account for the full extent of its features over time.
METHODS: This study takes the neuroanalytic approach to modeling the ERG waveform, defined as a computational model based on the main features of the transmitter kinetics of the retinal neurons.
RESULTS: The present neuroanalytic model of the human rod ERG is elaborated from the same general principles as that of Hood and Birch (Vis Neurosci 8(2):107-126, 1992), but incorporates the more recent understanding of the early nonlinear stages of ERG generation by Robson and Frishman (Prog Retinal Eye Res 39:1-22, 2014). As a result, it provides a substantially better match than previous models of rod responses in six different waveform features of the ERG flash intensity series on which the Hood and Birch model was based.
CONCLUSIONS: The neuroanalytic approach extends previous models of the component waves of the ERG, and can be structured to provide an accurate characterization of the full timecourse of the ERG waveform. The approach thus holds promise for advancing the theoretical understanding of the retinal kinetics of the light response.
METHODS: This study takes the neuroanalytic approach to modeling the ERG waveform, defined as a computational model based on the main features of the transmitter kinetics of the retinal neurons.
RESULTS: The present neuroanalytic model of the human rod ERG is elaborated from the same general principles as that of Hood and Birch (Vis Neurosci 8(2):107-126, 1992), but incorporates the more recent understanding of the early nonlinear stages of ERG generation by Robson and Frishman (Prog Retinal Eye Res 39:1-22, 2014). As a result, it provides a substantially better match than previous models of rod responses in six different waveform features of the ERG flash intensity series on which the Hood and Birch model was based.
CONCLUSIONS: The neuroanalytic approach extends previous models of the component waves of the ERG, and can be structured to provide an accurate characterization of the full timecourse of the ERG waveform. The approach thus holds promise for advancing the theoretical understanding of the retinal kinetics of the light response.
摘要：
目的：视网膜电图（ERG）是所有水平的视网膜光处理的总和反应，并在基础加工途径中表现出几个深刻的非线性。ERG的准确计算模型很重要，两者都是为了理解视网膜光传导到生态有用信号的多重过程，以及它们对视网膜疾病机制的识别和表征的诊断能力。有,然而,很少有ERG波形的计算模型，也没有一个能说明它随着时间的推移的全部特征。
方法：本研究采用神经分析方法对ERG波形进行建模，定义为基于视网膜神经元发射器动力学的主要特征的计算模型。
结果：从与Hood和Birch相同的一般原理出发，阐述了人类棒ERG的当前神经分析模型（VisNeurosci8（2）：107-126，1992），但结合了Robson和Frishman对ERG产生的早期非线性阶段的最新理解（Prog视网膜眼Res39：1-22，2014）。因此,在Hood和Birch模型所基于的ERG闪光强度系列的六个不同波形特征中，它提供了比以前的杆响应模型更好的匹配。
结论：神经分析方法扩展了以前的ERG分量波模型，并且可以被构造为提供ERG波形的整个时间进程的准确表征。因此，该方法有望促进对光响应的视网膜动力学的理论理解。
方法：本研究采用神经分析方法对ERG波形进行建模，定义为基于视网膜神经元发射器动力学的主要特征的计算模型。
结果：从与Hood和Birch相同的一般原理出发，阐述了人类棒ERG的当前神经分析模型（VisNeurosci8（2）：107-126，1992），但结合了Robson和Frishman对ERG产生的早期非线性阶段的最新理解（Prog视网膜眼Res39：1-22，2014）。因此,在Hood和Birch模型所基于的ERG闪光强度系列的六个不同波形特征中，它提供了比以前的杆响应模型更好的匹配。
结论：神经分析方法扩展了以前的ERG分量波模型，并且可以被构造为提供ERG波形的整个时间进程的准确表征。因此，该方法有望促进对光响应的视网膜动力学的理论理解。
