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用于多种计算的单一视网膜回路模型。

A single retinal circuit model for multiple computations.

作者信息

Sağlam Murat, Hayashida Yuki

机构信息

Department of Advanced Analytics, Supply Chain Wizard LLC, 34870, Istanbul, Turkey.

Graduate School of Engineering, Osaka University, Suita, Osaka, 565-0871, Japan.

出版信息

Biol Cybern. 2018 Oct;112(5):427-444. doi: 10.1007/s00422-018-0767-9. Epub 2018 Jun 27.

Abstract

Vision is dependent on extracting intricate features of the visual information from the outside world, and complex visual computations begin to take place as soon as at the retinal level. In multiple studies on salamander retinas, the responses of a subtype of retinal ganglion cells, i.e., fast/biphasic-OFF ganglion cells, have been shown to be able to realize multiple functions, such as the segregation of a moving object from its background, motion anticipation, and rapid encoding of the spatial features of a new visual scene. For each of these visual functions, modeling approaches using extended linear-nonlinear cascade models suggest specific preceding retinal circuitries merging onto fast/biphasic-OFF ganglion cells. However, whether multiple visual functions can be accommodated together in a certain retinal circuitry and how specific mechanisms for each visual function interact with each other have not been investigated. Here, we propose a physiologically consistent, detailed computational model of the retinal circuit based on the spatiotemporal dynamics and connections of each class of retinal neurons to implement object motion sensitivity, motion anticipation, and rapid coding in the same circuit. Simulations suggest that multiple computations can be accommodated together, thereby implying that the fast/biphasic-OFF ganglion cell has potential to output a train of spikes carrying multiple pieces of information on distinct features of the visual stimuli.

摘要

视觉依赖于从外部世界提取视觉信息的复杂特征,并且复杂的视觉计算在视网膜水平就开始进行。在多项关于蝾螈视网膜的研究中,视网膜神经节细胞的一种亚型,即快速/双相-关闭神经节细胞的反应已被证明能够实现多种功能,例如将运动物体与其背景分离、运动预测以及对新视觉场景空间特征的快速编码。对于这些视觉功能中的每一种,使用扩展线性-非线性级联模型的建模方法表明,特定的先前视网膜回路汇聚到快速/双相-关闭神经节细胞上。然而,多种视觉功能是否能在某个视网膜回路中共同实现,以及每种视觉功能的特定机制如何相互作用,尚未得到研究。在此,我们基于每类视网膜神经元的时空动态和连接,提出了一个生理上一致的、详细的视网膜回路计算模型,以在同一回路中实现物体运动敏感性、运动预测和快速编码。模拟结果表明,多种计算可以共同实现,这意味着快速/双相-关闭神经节细胞有潜力输出一串携带关于视觉刺激不同特征的多条信息的尖峰脉冲。

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