Department of Human and Environmental Informatics, Graduate School of Science and Technology, Kumamoto University, 2-39-1 Kurokami , Kumamoto, 860-8555, Japan,
Cogn Neurodyn. 2009 Mar;3(1):25-32. doi: 10.1007/s11571-008-9059-8. Epub 2008 Sep 24.
In previous experimental studies on the visual processing in vertebrates, higher-order visual functions such as the object segregation from background were found even in the retinal stage. Previously, the "linear-nonlinear" (LN) cascade models have been applied to the retinal circuit, and succeeded to describe the input-output dynamics for certain parts of the circuit, e.g., the receptive field of the outer retinal neurons. And recently, some abstract models composed of LN cascades as the circuit elements could explain the higher-order retinal functions. However, in such a model, each class of retinal neurons is mostly omitted and thus, how those neurons play roles in the visual computations cannot be explored. Here, we present a spatio-temporal computational model of the vertebrate retina, based on the response function for each class of retinal neurons and on the anatomical inter-cellular connections. This model was capable of not only reproducing the spatio-temporal filtering properties of the outer retinal neurons, but also realizing the object segregation mechanism in the inner retinal circuit involving the "wide-field" amacrine cells. Moreover, the first-order Wiener kernels calculated for the neurons in our model showed a reasonable fit to the kernels previously measured in the real retinal neuron in situ.
在过去关于脊椎动物视觉处理的实验研究中，即使在视网膜阶段也发现了较高阶的视觉功能，如将物体从背景中分离出来。此前，“线性-非线性”（LN）级联模型已应用于视网膜电路，并成功描述了电路的某些部分的输入-输出动态，例如外视网膜神经元的感受野。最近，一些由 LN 级联作为电路元件组成的抽象模型可以解释高阶视网膜功能。然而，在这样的模型中，大多数视网膜神经元被省略，因此无法探索这些神经元在视觉计算中的作用。在这里，我们提出了一种基于脊椎动物视网膜的时空计算模型，该模型基于每个类别的视网膜神经元的响应函数以及细胞间的解剖连接。该模型不仅能够再现外视网膜神经元的时空滤波特性，还能够实现涉及“宽场”无长突细胞的内视网膜电路中的物体分离机制。此外，我们模型中神经元的一阶维纳核与之前在真实视网膜神经元原位测量的核具有合理的拟合度。
